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BEHAVIORAL DEVEIDPMENT OF BLACK SOUTH
AFRICAN CHILDREN: AN ECOLCBICAL APPROACH

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Ivy Naralmgelo Goduka

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Ph.D. degree in Family and Child Ecology

 

 

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Date _08-14-1987

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BEHAVIORAL DEVELOPMENT OF BLACK SOUTH AFRICAN CHILDREN:
AN ECOLOGICAL APPROACH

By

Ivy Nomalungelo Goduka

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements

for the degree of

DOCTOR OF PHILOSOPHY

Department of Family and Child Ecology

1987

ABSTRACT
BEHAVIORAL DEVELOPMENT OF BLACK SOUTH AFRICAN CHILDREN:
AN ECOLOGICAL APPROACH
BY

Ivy Nomalungelo Goduka

The major purpose of this investigation was to
determine the relationships between a multiplicity of
factors that aggravate malnutrition and the behavioral
development and physical growth of children from a family
ecosystem framework. A secondary objective was to examine
the viability of the ecosystem framework in family studies.

A myriad of ecological factors in the child’s
environment influence growth and development. Factors
included in this study were: area of residence, home
environment, the parent’s socio-economic status, the type of
family structure, and family mobility.

Three hundred black South African school children ages
5-6 years and three hundred parents/guardians were included
in the sample. The sample was drawn using a systematic
sampling technique from Herschel in the Transkei, the
resettlement of Thornhill in the Ciskei, and the farm areas
around Queenstown and Orange Free State.

The Junior South African Individual Scale was used as a
measure for cognitive development. The Brown-IDS-Self—
Concept Referents Test was used as a measure for social-

emotional development. Anthropometric measures of height,

Ivy Nomalungelo Goduka

weight, and head circumference were used for physical
growth. A parent’s questionnaire was developed and used to
gather background information about the child’s family.

The results of the chi square test indicated Va
significant relationship between the area of residence and
parent’s/guardian’s marital status, educational, and
occupational levels. Parent’s/guardian’s educational and
occupational levels also showed a significant relationship.
No significant relationship was found between marital status
and the occupational level.

The results of the correlation between self-concept,
cognitive development, and physical growth for boys and
girls separately indicated a significant relationship. Only
self-concept and head circumference were related to age for
boys, however, the correlations were low. Age showed a very
low but significant relationship with only vocabulary,
quantitative skills, weight, and height for girls.

The results of the Tukey’s HSD test indicated
significant relationships between family background
information and children’s information which included: self-
concept, cognitive development, physical growth, and the
child’s health condition. This study has demonstrated that
the family ecosystem framework is a viable means of studying
factors that influence the development and growth of black

children in South Africa.

DEDICATION

This accomplishment is dedicated
to my mother Nomantombazana
and my late father Gantolo,

who taught us not only the three
R’s at school, but also taught us
to have faith in God.

Bhele sibulele nangamso, Alale
ngoxolo no Qhudeni wagqiba.

ii

ACKNOWLEDGEMENTS

Any successful accomplishment of this magnitude results
not only from the efforts of a single individual but is a
cooperative venture among many individuals. It would have
been virtually impossible to conduct a study of this nature
without accumulating numerous debts to many people.

Specifically, I would like to give thanks to:

Dr. Lillian A. Phenice, my major professor and director
of this research, for ,your continuous support and
encouragement throughout the course work, and for your
expertise while guiding this research.

Dr. Linda Nelson, for your extensive and valuable
comments throughout this effort.

Dr. Margaret Peg Bubolz, you got me started on the
human ecosystem approach, I will see it to the end.

Dr. David Kallen, for sharing the valuable information
about starving children from different parts of the world,
and your support throughout my course work and research.

Dr. John M. Verster at the National Institute for
Personnel Research (NIPR), in South Africa, for your
interest in my academic growth, my family appreciates your
concern. Also thanks are extended to many other individuals
at the NIPR who were supportive in this research.

Dr. Verna Hildebrand for encouraging me to seek ways of

helping the black children of South Africa.

Ms. Maryna Robinson from the Human Science Research
Council in South Africa, who trained us in the use of the
Junior South African Intelligence Scale.

Mary Glass who started me on the word processor and
encouraged me to work on my own. You gave me a life-time
skill. '

Parents/guardians, children, school administrators, and
teachers from the homeland of the Transkei, the resettlement
of the Ciskei, and the farm areas in Queenstown and the
Orange Free State, who were willing to share with us their
time and valuable information. This report would not have
been possible without your cooperation.

This effort would tun: have been accomplished without
the financial support from Fulbright throughout the Master’s
program, financial assistance from the Department of Family
and Child Ecology throughout the PhD program, and a grant
from the National Science Foundation.

I also wish to convey many sincere thanks to my South
African friends, who are studying here at MSU: Nobuhle,
Seshi, and family; Yaya, Sipho, and family; Anna, Jacob, and
family; Isabella, and Kgathi for your unfailing support
throughout this mission. To my other friends who are
studying and working in the United States, and others in
South Africa, to list you all would be impossible, and to
list a few invidious. Accept my appreciation for your

encouragement and support.

iv

To my eldest sister Nomawethu, Zingisa my only brother,
Nontatu my sister in law, and my youngest sister Khosazana.
Many thanks for a vote of confidence in me. Keep up the good
spirit. Your children are mine too and they are in good
hands.

Thanks are expressed to my extended family Madlamini,
George Goduka and family; Maduna and Malume Mvuyo Msebi; my
cousins Sindiswa, Linda, and Sandla. Your powerful prayers
keep us going. Please continue to pray for all of us, this
is only the beginning.

To all my nieces and nephews in South Africa, the list
is too long, and the space limited. Suffice to say Lungie
loves you all!!!

Finally, a personal note of thanks is due to my crew
that has flown with me across the ocean and lives with me
here in East Lansing, Michigan. Luzuko and Zipo my nephews,
Akhona (Vonono) my niece, and last but not least Tando
(Lolo) my daughter. I am happy to be part of your

upbringing. You are a joy and a challenge.

TABLE OF CONTENTS

List of Tables ........................................

List of Figures .......................................

Chapter

I. INTRODUCTION .....................................
Statement of the Problem .......................
Purpose of the Study ...........................
Significance of the Study ......................
Organization of the Study ......................

11. REVIEW OF LITERATURE .............................

The Extent of Poverty and Malnutrition in
South Africa .................................
Summary ........................................
Animal Studies .................................
Human Studies ..................................
Supplementation Studies ......................
Summary ................. I ....................
Retrospective Studies ........................
Summary ......................................
Environmental Factors Aggravating
Malnutrition .................................
Summary ......................................
III. THEORETICAL FRAMEWORK ............................

Exposition of the Human Ecosystem Framework....

Source and Origin ..............................

vi

22
23
24
31
32
35

35
48
49
49
49

Definition of Ecology ..........................
The concept of Ecology .........................
Adoption of the Ecosystem Framework

in Human Ecology .............................
Focus and Scope ................................
Basic Assumptions ..............................
Central and Germane Concepts ...................
Mode of Rationality Implied or Assumed

by the Ecosystem Framework ...................
The Concept of Rationality .....................
The Need for a Critical Science Perspective

in Human Ecology .............................
Strengths and weaknesses of the

Ecosystem Framework ..........................

Strengths of the Ecosystem Framework .........

Weaknesses of the Ecosystem Framework ........
Application of the Ecosystem Framework .........
Rationale for using the Ecosystem Framework....
Assumptions Used in the Study of

Black Children in South Africa ...............
Mode of Rationality Used in the Study of

South African Children .......................

IV. RESEARCH METHODOLOGY .............................

Research Design .................................
Specific Research Objectives ....................

Research Variables ..............................

vii

50
52

55
58
61
65

66
66

68

70
70
71
72
72

75

78
79
79
80
81

Conceptual and Operational Definitions ........ 81

Research Questions .............................. 84
Research Sample ................................. 87
Description of the Three Areas ................. 88

Homeland of the Transkei ..................... 88

Resettlement of Thornhill .................... 92

White-owned Farms ............................ 96
Summary ........................................ 98
Approval and Selection of Sample ............... 98
Research Instruments ........................... 101
Data Collection Procedures ..................... 108
Methods used for Data Analysis ................. 112
Ethical Considerations ......................... 113

V. DATA ANALYSIS AND FINDINGS ON FAMILY

BACKGROUND INFORMATION .......................... 117
Findings on Parent/Guardian Information ........ 118
Area of Residence and the Marital Status ....... 119
Educational Level of Parents/Guardians ......... 123
Area of Residence by Level of Education ........ 124
Occupational Level of Parents/Guardians ........ 128

Area of Residence and the Level of Occupation.. 129
Marital Status and the Occupational Level

of the Respondents ........................... 132
Level of Education and the Occupational Level

of the Respondents ........................... 133

Other Source of Income ......................... 135

viii

Home Environment ...............................
The Structure of the House and Ownership .....
Rooms in the House ...........................
Household Size ...............................
Condition of the House .......................

Family Mobility ................................

DATA ANALYSIS AND FINDINGS ON
CHILDREN’S INFORMATION ..........................

Findings on Children’s Information .............

Correlations Between Measures/Scores
and Age for Boys .............................

Correlations Between Measures/Scores
and Age for Girls ............................

Correlations Between the Child’s
Measures/Scores and Crowdedness ..............

Gender of the Child by Children’s
Measures/Scores ..............................

Child’s Behavior and Parent-Child Interaction..

Child’s Health Condition .......................

Child’s Hospitalization ........................

Nutritional Status of the Child ................

RELATIONS BETWEEN FAMILY BACKGROUND
AND CHILDREN’S INFORMATION .......................
Child’s Measures/Scores and the

Area of Residence ............................

ix

138
138
139
141
143
144

149

150

152

154

155

156

159

160

162

165

166

Child’s Measures/Scores and the Parent’s/

Guardian’s Marital Status .................... 174
Child’s Measures/Scores and the Parent’s/

Guardian’s Educational Level ................. 178
Child’s Measures/Scores and the Parent’s/

Guardian’s Occupational Level ................ 183
Child’s Measures/Scores and Family Mobility.... 188
Child’s Measures/Scores and Health Condition... 191

VIII.SUMMARY AND CONCLUSION .......................... 195
Summary of the Study ........................... 195
Conclusions of the Study ....................... 204

Resettlement Children and Families ........... 205
Farm Children and Families ................... 207
Homeland Children and Families ............... 209
Emancipatory Mode of Rationality ............... 211
The Policy of Apartheid ........................ 213
Population Registration Act .................. 214
Land Reservation Act ......................... 215
Education Act ................................ 216

Job Reservation Act .......................... 217
Implications of the Study ...................... 220
Suggestions for the Future .................... 222
BIBLIOGRAPHY ............. . ....................... 225
APPENDICES ....................................... 245
A. Instruments ................................ 245

Methods Used to Assign Different Racial

Groups to Residential Areas .............. 254
Letters for Ministries of Education
Letters and consent forms for Parents ...... 257

Memos from school administrators ........... 26!

xi

LIST OF TABLES

Table Page

1 Respondents’ Marital Status ...................... 119
2 Contingency Table: Area of Residence.

by Marital Status ................................ 120
3 Educational Level of the Respondents ............. 1124
4 Contingency Table: Area of Residence

by Level of Education ........................... 125
5 Employment and Unemployment Rates ............... 129
6 Contingency Table: Area of Residence

by Occupational Level ............................ 131
7 Contingency Table: Marital Status

by Occupational Level ........................... 132

8 Contingency Table: Level of Education

by Occupational Level ........................... 134
9 Items Given as Pay in Kind ....................... 136
10 Number of Rooms .................................. 139

11 Analysis of Variance of the Number of People

in the Household by Residence .................... 142
12 Respondents’ Impression about their Houses ....... 143
13 Number of Moves made by Parents/Guardians

with the Child .................................. 145
14 Mean and the Standard Deviation for

Children’s Growth and Development ................ 150

xii

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

Correlation Coefficient for Boy’s Self-concept,
Cognitive, Physical Measures/Scores and Age ...... 151
Correlation Coefficient for Girl’s Self-concept,
Cognitive, Physical Measures/Scores and Age ...... 153
Correlation Coefficient for Child’s Measures/Scores
and the Level of Crowdedness ..................... 154
An Analysis of Variance of the Gender of the

Child by the Self-concept, Cognitive,

and Physical Development ......................... 156
Items the Child has at Home ...................... 157
Activities Done together with the Child .......... 158
Responses to Child’s Health Condition ............ 160
Reasons for Child’s Hospitalization .............. 161
Area of Residence by the Nutritional Status ...... 163

One-way MANOVA of the Child’s Measures/Scores
by the Area of Residence ......................... 167
One-way MANOVA of the Child’s Measures/Scores
by the Marital Status ............................ 175
One-way MANOVA of the Child’s Measures/Scores
by Parent’s/Guardian’s Educational Level ......... 179
One-way MANOVA of the Child’s Measures/Scores
by Parent’s/Guardian’s Occupational Level ........ 183
One-way MANOVA of the Child’s Measures/Scores
by Family Mobility ............................... 188
One-way MANOVA of the Child’s Measures/Scores
by Health ....................................... 191

xiii

LIST OF FIGURES

Figure Page
1 Organism and Organism Relationship ................. 56
2 Environment and Organism Interrelationship ......... 57
3 Human Ecosystem Model .............................. 62
4 A Model for Studying Black Children

in South Africa .................................. 77
A Map of South Africa .............................. 89

xiv

CHAPTER I

INTRODUCTION

Concern for the welfare of children is a priority for
many societies, which view children as the legacy of the
past, as defining the present, and as foreshadowing the
future. This is consistent with a remark made by Margaret
Mead (Hi the Year of the Child. She placed children at the
center of the world’s concern when she commented: "In a
darkened world beset by the fear of nuclear holocaust,
degradation of our soil and air, and imbalance of population
growth that threatens to strangle our human settlements, the
Year of the Child stands like a beacon of hope...." (The NFE
Exchange, 1980, p.1). However, children can only be a signal
of hope when societies make investments in them for the
future. By investing and developing children’s human
capital, society will enable children to make a contribution
to humankind.

Notwithstanding the knowledge that the future of the
human species depends on children, in developed countries
such as the United States and developing countries such as
South Africa, large segments of children live in physical
and socio-economic deprivation. Some of these children live
in dilapidated houses that are often overcrowded. Many of
these children have inadequate nutrition, insufficient

1

2
medical care, sanitation, and other essentials of life.

Their parents are likely to have obtained low levels of
education which often relate to occupations in menial jobs
and consequently earn a low income. The parent’s level of
education, occupation, and income are likely to influence
the living conditions for the family. These conditions can
in turn affect the physical growth and behavioral
development of children.

A family life style is also likely to influence how
children grow and develop. Black families in South Africa
have varying life styles. For example, while some black
children in South Africa live iri intact families, other
black children live with one parent or no parent at all for
long periods of time. These are children who are either born
to single parents or whose parents leave the homeland or the
resettlement areas to work in urban areas on a migratory
labor system. In the homelands or the resettlement areas
these children are often cared for by their siblings,
relatives, or neighbors who might be too young or too old
and frail to meet the children’s physical and psychological
needs.

The home environment, area of residence, the type of
family structure, and the parents’ socio-economic status are
but a few of the ecological factors that are likely to
influence the child’s physical growth, self-concept, and

cognitive development. These factors are also likely to

3
affect the child’s motivation to break the condition of
physical and socio-economic deprivation. Such children are
thus likely to be trapped in a vicious circle of deprivation

from the womb to the tomb.

Statement of the Problem

A myriad of factors in the child’s ecosystem can
influence the child’s development. These factors may operate
on their own <n~ in combination with other factors such as
malnutrition to influence both the physical and behavioral
development of children. A review of literature (Griesel,
1980; Levitsky, 1979; Scrimshaw and Gordon, 1968) reveals a
plethora of studies on the effects of malnutrition on the
development of children across cultures. Less well
researched are other factors embedded in the matrix of
poverty which may equally influence children’s growth and
development.

One reason for past research studies focusing on
malnutrition was that it; is readily quantifiable, whereas
other factors such as the home environment are more
difficult to measure and quantify. Another reason may be due
to the fact that malnutrition is often treated as a factor

separate from other components within the matrix of poverty.

4

However, the syndrome of malnutrition of children does

not exist 'hi isolation, rather 'Hi a contextual milieu. A
myriad of ecological factors such as the area of residence,
the type of family structure, the socio-economic status of
parents, and the home environment may contribute to 'the
growth and development of children. Thus additional
information is needed about other factors in the child’s
ecosystem which relate to physical growth and behavioral

development of children.
Purpose of the Study

This study seeks to examine physical growth and
behavioral development of black children ages 5-6 in South
Africa from an ecosystem perspective. For.the purpose of
this study a number of selected ecological factors, namely,
the area of residence, the type of family structure,
parent’s socio-economic status, and the home environment
will be examined because these may modify the nutritional
status, social-emotional, and cognitive development of
children.

Specific objectives to meet the primary goal of this
study are discussed in Chapter IV under research
methodology. A secondary objective of this study is to look

at some of the methods that could be used to further develop

5
the family ecosystem framework. A brief discussion of these

methods is included in Chapter VIII.

Significance of the Study

This study is significant at two levels: theoretical
and practical. It has theoretical significance for current
research in child development and family studies. The family
ecosystem model used in this study to examine factors in the
child’s ecosystem that could aggravate malnutrition can make
a contribution to a better understanding of growth and
development of black children in South Africa. The use of
this model could also help discover the viability of the
family ecosystem framework. Holman and Burr (1980) have
categorized the family ecosystem framework. as playing a
minor role in family studies. Its use could thus lead to
clarifying methods that could be used to develop it and help
bring it to wider use.

The realization of the need for an ecological approach
to the investigation of factors affecting growth and
behavioral development dates as far back as the late 1960’s.
For example, Canosa, 1968, Cravioto and De Licardie, 1968,
and Kallen, 1968, provided a scheme of interdependent, and
interacting factors that determine learning and behavior.
Richardson (1973, p. 101) quoting from the report of the

International Conference on Malnutrition, Learning, and

6
Behavior held in 1967 wrote "with the wide variety of
determinants already identified, the approach becomes clear,
it is ecological, the interplay between man as a biological
organism and as a human being and the many-sided
environments in which he lives."

S.A. Richardson, (1980) suggested that studies of
malnutrition address more and specific questions such as,
"What are the range of factors which influence the
intellectual development of children and to what extent is
malnutrition a contributing factor?" (p. 164). This question
suggests an emerging ecological research approach in which
many biological, social, economic, and political factors
which may contribute to the later level of functioning of
children are included.

Brozek (1980) also suggested that researchers move
beyond malnutrition per se in the study of children’s
behavioral and physical growth to the study of micro as well
as macro environments in which children live, even if the
macro-environment is, or appears to be homogenous. "It is
generally recognized that endemic malnutrition is embedded
in the matrix of poverty. Unquestionably, differences in
macro-environment co-determine the child’s mental
development" (p. 261).

This study also has practical significance for policy
making for blacks in South Africa, as well as other minority

groups faced with political, economic, and social problems

7
throughout the country. Results from this study could be
used to design programs related to children’s welfare.
These programs could identify targeted areas of concern for
parent education of different age groups, support and
establish child care centers aimed at holistic child
development, community health programs, as well as other

projects for families.
Organization of the Study

This dissertation is organized into eight chapters.
Chapter one provides the introduction, statement of the
problem, purpose of the study, and the significance of the
study. Chapter two covers the review of 'literature. The
first section of Chapter three provides an exposition of the
human ecological framework. The second section illustrates
the application of the ecosystem model to the study of
behavioral development (H: black children 'hi South Africa.
Chapter four covers the research methodology. Chapter five
summarizes major findings based on family background
variables. Chapter six summarizes major findings based on
children’s measures and scores. Chapter seven provides the
relations between family background and children’s
variables. Chapter eight gives the summary, conclusions, the
mode of rationality used in this study, implications, and

future directions in this area.

CHAPTER II

REVIEH OF LITERATURE

The review of literature is organized into four
sections. The first section looks at the extent of poverty
and malnutrition in South Africa. The second section covers
animal studies concerning malnutrition. The third section
deals with human studies. The fourth discusses environmental

factors aggravating malnutrition.

The Extent of Poverty and Malnutrition

in South Africa

South Africa has often been described as a dual
economy. On the one side exists a well developed industrial,
mining, and agricultural economy. On the other side exist
rural slums and underdeveloped, overcrowded homelands that
may well be labeled as ’Third World Countries’. The
nutritional status of South Africa parallels this dichotomy.
As noted by Disler and Oliver (1984) this country has, on
the one hand, the typical ’western’ picture of obesity,
ischaemic heart disease, and hypertension reaching almost
epidemic proportions amongst the affluent classes. On the
other hand are poverty, malnutrition, and a host of poverty-
related diseases, such as kwashiorkor, marasmus,

8

9
gastroenteritis, tuberculosis, and pneumonia.

Malnutrition is a chronic condition that affects a
large proportion of the population especially in the rural
areas of the underdeveloped countries. In South Africa it is
estimated that 2.9 million black children under the age of
15 suffer from malnutrition (South African Fact Sheet,
1984). About two thirds of these children live in the rural
areas of this country.

In children, malnutrition takes the form of deficiency
of both calories and proteins and covers a spectrum of
diseases referred in) as protein-energy-malnutrition (PEM).
Severe forms of protein-energy-malnutrition manifest
clinically as marasmus and kwashiorkor; subclinical forms
are characterized by growth and developmental retardation
(Ndaba, 1984).

Protein-energy-malnutrition can be defined in terms of
weight, and the presence or absence of edema (i.e.
pathological swelling of the body, face, and limbs due to
low protein levels in the blood). The word kwashiorkor comes
from the Ga tribe of Ghana in West Africa, and refers to a
sickness the oldest child gets when the next baby is born.
This sickness coincides with weaning from the protein-rich
breast milk diet. Children who suffer from kwashiorkor are
those who are taken from the breast milk and placed on a

starchy diet (Werner, 1979).

10

The syndrome of kwashiorkor arises from a diet
relatively high in calories and deficient in protein.
Clinically, kwashiorkor manifests itself by growth failure
and muscle wasting. The patient looks plump, however, closer
inspection shows pitting edema of the legs, arms, and the
face, which is caused by dietary protein deficiency and low
serum albumen level. The patient has a potbelly and has
ophthalmic xerosis and Bitot’s spots on the conjunctiva of
both eyes (Guthrie, 1983). There are sometimes changes in
the color, texture, strength, and pluckability of the hair.
The patient also shows mental changes such as apathy and
irritability. A lack of interest and exploratory desire are
features well known to those who treat children suffering
from kwashiorkor (Werner, 1979).

Marasmus comes from the Greek word, meaning ’to waste’.
It is caused by a continuous restriction of total food
intake, including both calories and protein. Marasmus, the
child’s equivalent of starvation in adults, usually develops
in infants younger than 1. year. “This disease is
characterized by growth retardation with wasting of
subcutaneous fat and muscle. There is almost complete lack
of subcutaneous fat, and the skin over the buttocks and
thighs often hangs loosely in folds and wrinkles. The face
is withdrawn, and the infant often looks hungry with a
’wizened monkey ’ ' face. Gastroenteritis often occurs

repeatedly. The weight of the child is often less than 60

11
percent of that considered normal for the child’s
chronological age, and height is also below average (Werner,
1979).

Another disease common to children in South Africa is
pellagra. This is caused by a diet comprised predominantly
of maize. Maize is notoriously deficient in the vitamin
nicotinamide with an imbalance of the amino acids called
leucine and isoleucine. Pellagra refers to a disease
characterized by mental disturbance, diarrhea, and a
dermatitis condition resembling flaky paint on the exposed
parts of the body like the cheeks, neck, arms, and legs.
This disease is not only common to black South African
children whose staple food is mainly maize, but also has
been reported among members of the population in one of the
Asian-Indian states whose staple food consists mainly of a
variety of millet. Millet is also deficient in vitamins
(Ndaba, 1984).

The prevalence of poverty and malnutrition in South
Africa has been well documented in recent years (Ndaba, 1984
and O’Keefe, 1984). Children and the elderly seem to be the
major victims of poverty, therefore, they are at the
greatest risk to malnutrition as is the case in other parts
of the world.

Poverty in the United States also seems to affect
mostly children and the elderly. As shown by the U.S. Bureau
of the Census, Current Population Reports (1983), children

12

and youth under 18 years and the elderly were more affected
by poverty than any other age group. For example, in 1979,
there were almost 200,000 more poor children and youth than
there were in 1969 in the United States. At the close of the
1960’s, the youth poverty rate was less than 14 percent. By
the end of the 1970’s, it was 16 percent, and it approached
22 percent by 1982. The harsh recession years from 1980
through 1982 added more than three million children to the
poverty figures.

As stated by Ogbu (1978) America’s poor children may
not resemble the emaciated skeletons of Ethiopia and the
homelands of South Africa that arouse horrified pity when
seen in newspapers or portrayed on TV. However, the plight
of these children is as apparent as that of malnourished
children from underdeveloped countries, even if less
dramatically obvious. The effects of malnutrition on these
children could have the same long and lasting consequences
that children in the Third World countries show. The effects
of malnutrition on children will be discussed later.

Poverty in the United States also seems to hit certain
states and areas, and certain racial groups more than it
affects others. For example, as stated by Harrington (1984)
if one examines the Southern states which constitute the
areas between Virginia and Louisiana, in which the black

population ranges from 30-82 percent, one finds that more

13
than 20 percent of the black population is below the poverty
line.

In South Africa, the trend seems to be the same. For
example, children, the elderly, blacks, coloreds, and people
in the homelands and resettlement areas seem to be more
affected than any other age group, race, or area of
residence.

As stated by Fincham and Thomas (1984) community
surveys of ambulant black preschool children in South Africa
show that one-third of these children is underweight.
O’Keefe (1984) using both urban and rural samples reported
that about a quarter of the rural black elderly male and
female population is more than twenty percent underweight.
He made an important link between malnutrition and
unemployment. He pointed out that a significantly higher
incidence of malnutrition was detected among unemployed
males and females who live it: the rural areas 'hi South
Africa than among factory employees who live and work in
urban areas.

Surveys as well as research studies carried out in
South Africa in the 70’s and 80’s revealed that a large
percentage of colored and black children are at risk to
malnutrition and show stunted growth. These studies also
revealed that a large number of children suffer and die from
poverty-related disease (Griesel, 1980; Ndaba, 1984; and
Vergnani, 1983).

14

Mall (1984) divided the at risk children into two broad
categories. First are children under the age of two for whom
malnutrition is often fatal. Their ill-health is closely
related to that of their mothers who frequently suffer from
malnutrition themselves. Therefore, the solution to
malnutrition among this group of children is almost
impossible without attention to pregnant and nursing mothers
as well. Second are children over the age of two for whom
the consequences of malnutrition tend to be a lack of
energy, stunted growth, susceptibility to diseases, and
perhaps brain damage.

An indication of the percentage of children at risk to
malnutrition was given by Vergnani (1983). This percentage
is based (Hi a survey conducted by the Department of Health
and Welfare in South Africa on a national sample of 20,000
school children between the ages of six and nine years from
all racial groups.

This survey revealed that in 1980 approximately 5
percent of whites, 27 percent of blacks, 36 percent of
coloreds (coloreds are people of mixed race with whites, the
Khoi-Khoi and blacks), and 44 percent of Asians (Indians,
Japanese, and Chinese) fell below the third percentile of
the Boston norms of weight for age. However, the use of
these norms may not' be appropriate for black children in

South Africa. The Boston norms were compiled on a sample of

15
white children (birth to 13 years) who came from affluent
families in Boston, Massachusetts.

Using another set of norms this survey also revealed
that 2 percent of white, 14 percent of black, 21 percent of
coloreds, and 26 percent of Asian children fell below 75
percent of the National Center for Health Statistics
Percentiles (NCHS). The data used to compile the NCHS
standards were based on a representative sample comprizing
some 20,000 American children (birth to 18 years) from all
the racial groups in the United States. As stated by
Richardson, B. D. (1980) the NCHS norms are the most
acceptable norms to many researchers and medical
practitioners in South Africa, and they are likely to
replace the Boston norms.

Kotze (1980) in a study of South African children from
all racial groups, reported that (Hi the average about one
third of the population under the age of five years suffered
from acute diseases, such as kwashiorkor and pellagra, with
the white and Asian population group least affected. In
terms of undernutrition (the failure of an individual to
take in sufficient calories and protein) the percentage of
children aged one or less at risk was found to be 8.5
percent for blacks, 12.9 percent for coloreds, 4.6 percent
for Asians and 2 percent for whites (Kibel and Moodie,
1984).

16

The disparity in the percentages of weight and
malnutrition of the Asian children suggests that, although
this group appears to be the lightest of all the groups,
these children are not at-risk to malnutrition. Their weight
could thus be attributed to their genetic make-up. Data from
this work also show that malnutrition is more prevalent
among colored and black children than Asians and whites in
South Africa.

In a survey of black children under five years of age
living in a rural Transkei village, Griesel (1980) reported
that 36 percent of these children were below the third
percentile of the Boston norms of weight for age.
Approximately 57 percent of these children were between the
ages of 18 and 32 months. Nearly 30 percent of these
children died before the age of two years.

Fincham (1982) did a study on the nutritional status of
rural black and colored preschool children in the Eastern
Cape. His study revealed that even on white-owned farms,
where there is enough food, food is not easily available for
blacks and coloreds. Height for age, which is a measurement
of long-term nutritional status, suggested that a large
number of black and colored children were short for their
ages and were likely to be at-risk to malnutrition. Data
from this study also indicated that nutrition-related
diseases, such as tuberculosis and gastroenteritis, were

common among these groups.

17

As stated by Fincham (1985) the resettlement camps
within the homelands appear to be particularly hazardous
areas in which to raise children. Severe malnutrition in the
form of kwashiorkor and marasmus is clearly a major problem
in these poverty pockets. For example, in Tsweletswele, a
resettlement close to Thornhill in the homeland of the
Ciskei, as many as 10 percent of the preschool children
surveyed had clinically definable signs of kwashiorkor (see
homelands and resettlement areas in the map of South Africa
on page 89).

A study done by Thomas (in Vergnani, 1983) in the
Postdam resettlement camp reveals that over 90 percent of
the Sub A children (Sub A is the equivalent of the first
grade in the United States) fell below the third percentile
of weight for age of the National Health Statistics
Percentiles. Approximately four percent of the seven to
eight year olds suffered from kwashiorkor. These figures can
probably be considered an underestimation of the prevalence
of malnutrition in South Africa. Vergnani (1983) gives two
possible reasons for this underestimation: many of the
malnourished children were not included in the sample as
they did not attend school or they dropped out of school.

According to Verwey (1980) approximately 17.8 percent
of black children dropped out of the school system before
completing Sub A. Also these surveys focused on children

mainly in or around the urban areas. Children in rural areas

18

were not reached because these places are not easily
accessible by cars. The number of malnourished children is
probably higher in rural areas than the percentages that are
reported. This is due to factors such as the migratory labor
system which results in one or two parents leaving children
in the homelands to seek employment in urban areas.
Conditions such as these increase the likelihood for
poverty.

Other factors which provide an indication of the
prevalence of overt malnutrition in South Africa are infant
mortality rates and deaths of children under the age of
five. As stated by Van Rensburg and Mann (1982) the
malnutrition problem is probably a major factor in bringing
about the high incidence of infectious diseases and death in
children in South ’Africa. For example, based on the
statistics from the Department of Health, infant mortality
rates per thousand were 20.1 for whites, 34.7 for Asians,
100.2 for blacks and 104.4 for coloreds (Epidemiological
Comments, 1978).

Infant mortality rates and death rates for children
under the age of five in rural and homeland areas are
significantly higher. This is due to a greater number of
children who are sent to the homeland and resettlement areas
to live with grandparents or relatives, to poorer health

services, and other factors creating a matrix of poverty.

19

Data from a study amongst Xhosa women living in the
homeland of the Transkei indicate that approximately 25
percent of all infants from this group died within the first
year of birth (Vergnani, 1983). Thomas (1981) also estimates
that the infant mortality rate for black children in the
rural homeland of the Ciskei is between 180 and 240 per
thousand. This rate is substantially higher than that
reported by the Department of Health and Welfare.

Whereas infant mortality rates only reflect deaths up
to one year, young children up to the age of five years are
the most vulnerable groups 'hi poorer populations (Moosa,
1982). Data from the Department of Statistics (in Hansen,
1984) reveal that there is considerable mortality from
diseases related to nutrition in the one to five years age
group. For example, in 1977 the infant mortality rates per
100,000 were 64 for whites, 247 for Asians, 1,781 for
coloreds, and 2,104 for blacks.

An analysis of“ the main causes of infantile deaths
reflects that the high percentages of death are due to low
birth weight and the immaturity of these infants caused by
malnutrition during pregnancy and after birth. Infectious
diseases such as gastroenteritis are another reason for
infantile deaths among blacks and coloreds (Vergnani, 1983).
Such diseases are not very common in the white and Asian

groups.

20

Fehrson (1975) basing his calculations on the 1970
census, has estimated that between 15,500 and 27,500 colored
and black children die annually from malnutrition and
malnutrition related diseases. A large proportion of these
children live in rural areas and on white-owned farms where
food is scarce or not made available to these children.

However, there is evidence to show that conditions for
blacks and coloreds living in urban areas are improving.
Hansen (1984) shows that infant mortality rates for coloreds
in Cape Town and blacks living in Soweto have dropped
dramatically. For example, in Cape Town the colored infant
mortality rate is almost at parity with that of whites,
while in Soweto the black infant mortality rate has fallen
from 233 in 1950 to 35 in 1979.

Hospital admission rates and hospital mortality rates
also give an indication of the extent of malnutrition among
the poorer groups in South Africa. For example, Ndaba (1984)
gives a total number of patients admitted to Charles Johnson
Hospital in the homeland of KwaZulu in 1981 with
malnutrition and nutrition-related diseases. According to
the hospital records, a total of 2,084 black children were
admitted to the hospital. A total of 416 children died. Of
those, 268 were malnourished. According to the hospital
records, death rate from malnutrition on the average was

about 20 percent in 1984.

21

Moosa (1982) reported that 6,649 black patients, both
children and adults, were admitted to King Edward XII
Hospital 'hi Durban, Natal ‘HT 1978. Approximately 2,775 of
these patients were malnourished and one quarter' of the
malnourished patients died that year.

Wagstaff and Geefhuysen (in Vergnani, 1983) in a
discussion of figures from Baragwanath Hospital in
Johannesburg, reported that. only! a very small number of
patients, about nine percent, reached or exceeded the 50th
percentile of the National Center for Health Statistics for
weight. This was seen as a reflection of the malnutrition

problem among some blacks living in Soweto.

Summary

These health statistics as well as research data reveal
that there is a severe nutritional problem in the preschool
and school-aged children from the black and colored
population 'hi South Africa. These statistics and research
papers also show a relationship between the geographic
location and the nutritional status of black children.

Thus, children’s area of residence and race in South
Africa seem ix) be crucial variables influencing children’s
level of nutritional status. The worst areas with severe
forms and large percentages of affected children are in the

homeland and the resettlement areas. For example, in rural

22
areas like KwaZulu, Ciskei, and the Transkei, the
nutritional conditions of children seem considerably worse.
This could be attributed to a large proportion of young
parents who leave children in the homelands and resettlement
areas to seek work in urban areas.

Children who live on white-owned farms also show levels
of nutrition which are not satisfactory, but better than the
levels of nutrition for children from the homeland and the
resettlement areas. On the other hand, children from the
urban communities, especially well-established townships
such as Soweto and Cape Town, show a drop in infant

mortality rates.

Animal Studies

Although the animal model used in controlled
experiments is limited, animal studies have yielded
important findings ("1 malnutrition, functional disorders,
and physical growth. These findings allow the researcher to
generate research questions about the possible effects of
malnutrition in humans. Therefore, while a complete review
of literature on animal studies is beyond the scope of this
study, a brief summary will be provided.

Barrett (1985) gives a listing of major studies on the

behavioral and physical effects of malnutrition in animals.

23
The investigators, species of study, type of nutritional
deprivation and the behavioral outcome are given.

Based on these studies there is evidence across a
variety of animal species and procedures that protein
calorie deprivation in animals is related to attentional
impairments, poor behavioral control, and a lack of interest
in social and physical environment. Thus, although
researchers cannot extrapolate directly from animals to
humans, the findings from the animal research link
malnutrition to important functional disorders which might
be found in humans who have experienced sub-alimentation or

have been exposed to adverse environments.

Human Studies

In addition to animal studies, prospective or
intervention as well as retrospective follow-up studies of
children who have suffered prenatal and post-natal
malnutrition in infancy or early childhood from Latin
America, South Africa, and the United States have
contributed to our knowledge of this subject. A review of
these studies (Brozek, 1985) attests to a causal
relationship between undernutrition, early mental
development, and school performance.

Based on the findings from experimental (supplemental)

studies there is evidence that prenatal undernutrition

24
results in attentional impairments, reduced social
responsiveness, poor state control, low birth weight,
dependence, passiveness, and less curiosity. Infants with a
history of undernutrition have difficulty tolerating
frustration, have low activity levels, lack initiative and
independence.

Thus, the same complex of behavioral characteristics
associated with undernutrition that were obvious in animal
research are seen in human infants as well. These
characteristics include reduced social responsiveness,
attentional impairment, diminished affect, less involvement,
and difficulty to regulate the stimuli. The researcher will
elaborate on these studies, for they provide insight into
some of the processes whereby early undernutrition may

affect the child’s later behavior.

Supplementation Studies

The studies that have been done in this area have
focused on infancy, comparing the behavioral characteristics
of infants with a history of undernutrition, including
prenatal nutritional deficit, with those of better-nourished
infants.

Four prospective investigations that have employed

nutritional and psychological supplementation have been

25
undertaken in Latin America (Colombia, Guatemala and
Mexico). One of the most extensively documented longitudinal
studies of the effects of nutritional supplementation in
pregnant mothers and young children has been conducted by
the Institute for Nutrition of Central America and Panama
(Klein et al. 1979).

Four villages from the eastern Spanish-speaking section
of Guatemala, where malnutrition is endemic, were matched on
a number of demographic, social, and economic
characteristics. Two communities were selected at random as
experimental villages. A high protein-calorie drink
(Incaparina), similar to a popular corn-based gruel (atole)
was made available for all residents twice daily at a
central dispensary. Two other villages were selected as
controls. In each village, a beverage (fresco) similar to
Kool-aid with only about one—third of the calories contained
in the Incaparina and no protein was made available to all
those who wished to participate.

Klein et al. (1977) have reported preliminary results
of the relationship that exists between supplemental foods
ingested by the mother and infants and these infants’ birth
weight, infant mortality rates, physical growth and
psychological development during the first years of life.

Lechtig et al. (1975) noted a rise in the mean birth
weight of infants with maternal caloric ingestion during

pregnancy. This association was observed whether the

26

calories were ingested early or late in pregnancy, but less
so when caloric supplementation was limited only to the
third trimester. The association between increase in birth
weight and maternal calorie supplementation during pregnancy
was maintained when the effects of maternal age, birth
order, interval since last birth, length of gestation,
illness during pregnancy, incidence of intrauterine
infection, and maternal socio-economic status (SES) were
controlled.

According to Habicht et al. (1974) a significant
interaction between maternal SES, stature, and caloric
supplementation showed a high incidence of high-birth-weight
babies. Mothers who had high caloric supplement, were short
in height, and from poor homes had roughly half the risk of
delivering low-birth weight babies compared to mothers in
the low caloric supplemented group of similar height and
SES. It appears that short-statured mothers from the low SES
group are most likely to bear the largest proportion of low-
birth-weight babies.

Data from this study also show an association between
caloric supplementation during pregnancy, stillbirths, and
infant deaths during each quarter of the first year of life.
In all comparisons made, the proportion of deaths in the
low-supplement groups was greater than in the high-
supplemented groups, especially during the first three

months after birth. According to Lechtig et al. (1975) the

27
magnitude of the difference is such that the risk of dying
during the first year of life in the high-supplemented
groups is only half of that observed in the low-
supplemented groups.

The relationship between the level of food
supplementation and physical-growth retardation was also
examined. Lechtig et al. (1975) reported a strong
relationship between food supplementation and physical
growth. They found that the risk of growth retardation is
almost three times greater in the low-supplemented group
than in the high-supplemented group. In the villages where
fresco (the low-calorie/no-protein drink) was distributed,
there was a higher rate of growth retardation than in the
villages where Incaparina (high protein-calorie drink) was
distributed. These findings raise the question of the
separate effects of protein and calorie supplementation on
physical-growth rate (Werner, 1979).

Psychological test performance and its relationship to
food supplement ingestion was also examined. For the purpose
of this analysis two measures of food supplementation were
employed. A food supplement was ingested by the mother
during pregnancy and lactation as well as by the child up
until the age of psychological assessment. The INCAP
investigators administered the psychological assessment,
Composite Infant Scale, at 15 and 24 months. Data from this
study revealed that by 15 and 24 months well-supplemented

28

children performed significantly better (Hi the mental and
motor scales of the Composite Infant Scale than poorly-
supplemented infants. The impact of the supplemental
ingestion seemed to be more closely related to perceptual-
motor and manipulative skills than to language and other
cognitive abilities (Klein et al. 1977).

Psychological test performance and its relationship to
food supplement was also examined on the same children at 36
and 48 months old. At 36 months, tests on which significant
differences in performance were noted included picture
naming and recognition, as well as in a verbal reasoning
task. In each case, the superior performance was associated
with higher levels of food supplement ingested. Two of the
tempo measures (timed tests), response time for the
discrimination-learning task and time taken to draw a line,
also varied inversely with food-supplement intake. Similar
differences were found at 48 months. For example, a
cognitive composite“ score differentiated significantly
between groups that differed in levels of food
supplementation (Klein et al. 1977). Children who received
food supplementation did better in this test than those who
did not receive any food supplementation.

By age 36 and 48 months, family socio-economic status
interacted significantly with the effects of caloric
supplementation on psychological performance. The study

revealed that the effects of nutrition supplementation on

29

test performance were more pronounced for economically
deprived children than the better off children. In the high
socio-economic groups, a poorly supplemented child was about
equally likely to fall into the highest quartile of test
scores, but in the. low socio-economic group, a poorly
supplemented child was about three times as likely to be in
the lowest quartile test performance.

The results of the INCAP intervention study reflect the
interactive effects of endemic mild to moderate protein-
calorie malnutrition and a low SES on psychological
performance of preschool children. Though the variable
range of income resources in the villages studied is
limited, the analysis revealed the differential effects of
SES on cognitive test scores as early as 36 and 48 months.
This study also revealed that children from low SES families
were positively affected by nutritional supplementation
(Klein et al. 1977).

Other studies (H: the relationship between nutritional
supplementation during pregnancy, lactation, infancy, and
early childhood were conducted in Colombia by McKay et al.
(1978), Mora et al. (1979), and in Mexico by Chaves and
Martinez (1979). Two of these studies had cognitive
stimulation programs in addition to their nutritional
intervention (McKay et al. 1978 and Mora et al. 1979). All
except McKay et al. tested their subjects during infancy and

all report that nutrition supplementation during infancy was

30
positively associated with improved development on test
scores.

However, Mora et al. (1979) reported that malnourished
children were highly irritable and had difficulty tolerating
frustration. Other characteristics shown by malnourished
children were low activity level, reduced independence, and
diminished affect (Chavez and Martinez, 1979 and Barrett
1982). In another study conducted in Guatemala (Lester and
Brazelton, 1975) reported that the behavior of malnourished
children was characterized by impaired attentional
processes. These children also showed reduced social
responsiveness. The same characteristics that were noticed
in the malnourished children were previously noted in
animals which had been exposed to malnutrition.

In addition to these behavioral and cognitive
differences between Well and poorly-nourished infants, Mora
et al. (1979) reported that babies with nutritional
supplementation showed lower levels of irritability, higher
levels of visual attention, and habituation to repeated
visual stimulus at 15 days of age.

Similarly, the studies by Als et al. (1976) in Boston
and Brazelton et al. (1977) in Guatemala compared infants
who were prenatally undernourished and had low birth weight
with infants who were well-nourished and had normal birth
weight at one month of life. Using the Brazelton neonatal

examination, the investigators found that the undernourished

31
infants showed little vigor of movement, moved slowly into
higher rates of arousal, and had difficulty orienting toward
visual stimuli. The infants were also undemanding and poor
elicitors of maternal response.

McKay et al. (1978) in a Colombian city, Cali, provided
schooling for malnourished children beginning at age three
and half years in addition to supplemental food. By age 5
these children had made some strides in catching up with the
intellectual growth of more affluent children, especially in
verbal reasoning tasks. However, a second group of formerly-
malnourished children who received only supplementary food
but no extra schooling did no better than children without
supplementation and appeared especially deficient on short-
term memory tasks. This study suggests that it is not
nutrition alone that affects children’s intellectual growth,
rather both food and the environment of schooling contribute

to intellectual growth.

Summary

All the studies discussed above are supportive of the
hypothesis that undernutrition and lack of environmental
stimulation in early life may adversely affect the child’s
physical growth, cognitive, social, and emotional
development. Children who received better caloric

supplementation during the first years of life, including

32
prenatal supplementation, were more socially involved, more
interested in their environment, had higher levels of
activity, and were more capable of affective expression than
were children who did not receive such supplementation.
These studies also suggest that at the age of 5 years
nutrition together with factors associated with schooling

made a difference.

Retro ective t d' s

Retrospective follow-up studies of children
hospitalized because of severe acute malnutrition during the
first two years of life have also made an important
contribution to our knowledge in this area. In the period
from 1955 to 1985, a large number of studies have been
carried out which have examined the effects of malnutrition
on children’s cognitive development. Reviews of these
studies (Balderson and Freire, 1981; Brozek, 1985; Griesel,
1980; Kallen, 1973; Levitsky, 1979; Scrimshaw and Gordon,
1968; Wagner and Stevenson, 1982; Warren, 1977; and Werner
1979; show that investigators have studied children around
school age with a battery of tests chosen to assess memory,
language, perceptual reasoning, learning, and abstract
skills. Most of these reviews as well as reports of
empirical work argue that the nutritional status of children

is related to mental development and physical growth.

33

Because of the difficulty of controlling for social,
economic, and other familial-environmental factors in
studies of malnutrition and mental development, sibling
pairs have been utilized. Certain variables that have
confounded most follow-up studies of children who have
suffered from early severe malnutrition have been partially
controlled by utilizing sibling pairs for these
investigations (Latham, 1974).

One example of a carefully done sibling study is a
follow-up of 71 school-age Jamaican boys who were
hospitalized for kwashiorkor or marasmus during the first
two years of their lives (Birch and Richardson, 1972;
Hertzig et al. 1972; and Richardson et al. 1973). The
investigators matched 71 previously hospitalized boys with
31 siblings as controls and other children of the same age
and gender who had not been previously malnourished.

The researchers followed children between ages 5 and 10
and evaluated them with the Wechsler Intelligence Scale for
Children (WISC), a widely used individual intelligence test
that yields a full 10, a verbal IQ, and a performance 10. In
addition, they obtained data on the children’s performance
in school, such as teachers’ evaluation of their behavior,
grades and scores on the Wide Range Achievement Test (WRAT).

These investigators found significant differences on
the full WISC IQ and the verbal WISC 10, but no significant

difference on the performance 10, between the previously

34
hospitalized children and their sibling. They also found a
significant difference between the scores from the
evaluation of teachers. For example, children who were
previously malnourished received a poorer teacher
evaluation.

Severely malnourished children had the lowest mean
scores on the WISC, their siblings had intermediate scores,
and comparison boys who had never been hospitalized had the
highest scores on the WISC. On the Wide Range Achievement
Test, formerly hospitalized children did significantly less
well than the control group. They also received poor grades
at school and poor teachers’ evaluation.

Another sibling study in Cape Town, South Africa, has
been reported by Evans, et al. (1971). Forty previously
hospitalized children who suffered from kwashiorkor during
the first three years of their lives were compared with 46
sibling controls when they were between 8 and 15 years old.
All children were given the South African Intelligence
Scale, an adaptation of the WISC,and the Goodenough-Harris
Draw-A-Person. Data were also available on their scholastic
achievement. These investigators reported IN) difference on
the intelligence scale at these ages, but did find
significant differences (Hi the Draw-A-Person Test and iri
performance on the arithmetic problems subtests on which
formerly malnourished children scored lower than the sibling

controls. The investigators suggested that lower scores on

35
the Draw-A-Person test may be due to the interference of
emotional-affective factors with the child’s cognitive
functioning. They also suggested that lower arithmetic
problem solving scores might be a reflection of attentional
defects and a reduced ability to concentrate among those who
had suffered from kwashiorkor during the first three years

of their lives.

Summary

Retrospective follow-up studies of children who had
been exposed to hospitalization for severe acute
malnutrition, either marasmus or kwashiorkor, during the
first 3 years of life, suggest an association between such
exposure and reduced intellectual functioning levels at
school age. What has been neglected by these studies is,
however, the question of why one sibling in a family
develops severe malnutrition while another or several other
siblings do not. As suggested by Werner (1979) this could be
due to the fact that one sibling is relatively neglected for
physical or emotional reasons, is less desired or less
desirabhe to the mother, or differs in some other respect
including gender.

Another reason could be that family income has varied
over time leading to fewer resources to maintain the family.

This might cause the mother to work outside the home, and

36
thus, have less time to feed and interact with young

children.

Environmental Factors Aggravating Malnutrition

Most of the studies that have been discussed above have
focused (Hi the effects of malnutrition on physical growth
and behavioral development, while overlooking other factors
in the child’s ecosystem that could aggravate malnutrition.
As stated by Monckeberg (1976) inadequate nutrition is often
associated with a host of other negative environmental
features such as low income, low educational level, low
quality houses, inadequate sanitary conditions,
overcrowding, and generally defective and poverty-related
circumstances under which the poor live in society.

The poor in South Africa also live in rural, isolated,
and remote areas which are often dry, infertile, barren, and
not suitable for raising livestock and for growing crops. As
stated by Webster (1980) the rural population in South
Africa is caught in a downward spiral of intensified
underdevelopment. This is caused by the absence of the
potentially progressive young men and women who are migrant
workers in urban areas and the decline in agricultural
productivity due to severe droughts.

Forced removals of blacks by the South African

government is another factor which seems to exacerbate

37

malnutrition. Since 1960, the government has been removing
blacks from areas deSignated for whites to the resettlement
areas which are adjacent to the homeland areas. As stated by
Disler and Oliver (1984) many of these forced removals have
involved the destruction of already-existing housing and
have often forced people into a variety of informal
settlements with very poor shelter and few or no services.
Often these people do not know their neighbors. They are
flung into a situation where they are all strangers. The
adjustment is an especially traumatic one. They have to get
used to a life with limited land, rain, houses and food
(Platzky and Walker, 1985). Such an environment could
promote risk factors that are likely to impair the
children’s physical, psychosocial, and cognitive development
from conception to maturity.

There is evidence to show that in poverty there are
associative factors that have an influence upon physical
growth and behavioral development of children. For example,
Essen, Fogelman, and Mean (1978) studied the relationship
between housing conditions and physical development in a
cohort of English, Welsh, and Scottish children. Their
morbidity (respiratory disease, headaches, and general ill-
health) and their height, used as an index of physical
development, were studied in relation to crowding and access
to amenities such as a bathroom, hot water, and indoor

toilet. Although the investigators concluded that contrary

38
to expectations the relationships were mostly weak, they
found a strong positive correlation between crowding and the
rate of growth of these children.

In another study, Graham (1972) showed that height
quotient, i.e. height as a: percentage of chronologic age,
was related to crowding. In this case the population studied
consisted of severely malnourished infants and children.
Graham’s findings suggested that in those homes with more
than four persons per room or per bed there is a drop in
height quotient. On the other hand, a control group which
consisted of malnourished children who came from less-
crowded home environments did not show a drop in height
quotient. Therefore, in this study, crowdedness was seen as
one of the factors that might have contributed to the
child’s height, rather than only the nutritional status of
the child.

Poor housing, overcrowding, loneliness, family
breakdown, personal disability, and social instability were
all shown by Jenkins, Tuthil, Tannenbaum and Kirby (1977) to
be correlates of excess mortality in a study done in
Massachusetts, United States. Multiple dwellings,
substandard housing, and overcrowding were included in the
76 significant correlations with extremely high mortality
rates found among the 39 factors which were studied.

The child’s socioeconomic background has also been

linked with both physical growth (Eichorn, 1979) and

39

cognitive development (Bogin and MacVean, 1983). For
example, in a study conducted by Griesel and Richter (1986)
in South Africa, no significant relationship was found
between physical growth as measured by height, weight, and
any of the subtest scores of the McCarthy Scales of
children’s abilities and parental education, occupation, and
income. However, lower weight and lower height of preschool
black children were both significantly related to large
household size and absences of the father from the home.

Mednick, Baker, and Hocevar (1985) investigated the
relationship between family structure variables and
children’s intellectual, psychosocial, and physical growth.
Their analyses of data indicated that when social economic
status and gender were controlled, family size showed the
most systematic relationship with physical growth. Children
from one, two, and three child families were tallest and
heaviest, whereas children from families of four or more
children were shortest and lightest. They also found a
significant correlation between family size and intellectual
development. For example, children from families of four or
more tended to have more academic problems.

The number of people in the household is also thought
to have an impact on nutritional levels of children. All
members compete for food from the communal family pot, and
often children receive what is left by adults (Newman,

1980). This is true especially in some black families in

40

South Africa. Culturally men and sometimes boys are served
first and given the best because they are breadwinners.
Women and girls are served last and often get what remains
after men have been served. In the past when food was
abundant this was run: a problem. However, at present there
is scarcity of food in the black families especially those
living in rural areas, as a result females and young
children are at risk to malnutrition.

However, Burney and Shahyar (1980) considered the
relationship between family size and the nutritional status
of family members as weak. They argued that in larger
families there may be more breadwinners to help increase the
amount of resources for the family. Another point stated by
these investigators was that the overall community
conditions, such as endemic poverty, may cut across all
community households irrespective of family size and,
therefore, affect all family members.

This study does not, however, mention the ages of
family members. It is run: clear whether this variable was
considered in their study. This could account for the weak
relationship of their findings. For example, if the majority
of family members were very young they would not be in the
labor force, therefore, such a family would be more at risk
to malnutrition.

Another factor which seems to aggravate malnutrition is

the disruption of family life. The exodus of men and women

41

to urban areas as migrant workers has a major effect on the
social system and on family life. Wilson (in Reynolds, 1984,
p.1) defines the term migrant in the context of Southern
Africa "...as meaning a: worker who oscillates between his
home and his place of work over a distance which is greater
than can be travelled on a daily commuting basis". In terms
of this definition, migrant workers iri South Africa are
black men and women who live and work in urban areas without
their children.

When introducing the Child Care Bill in the South
African Parliament in 1983, the Minister of Health, Dr. van
der Merwe, acknowledged the family as a normal, social, and
biological structure in which the child should develop
(Reynolds, 1984). However, many black children in South
Africa live without their fathers and sometimes without
their mothers for their entire childhood due to the
migratory labor system. Therefore, black children in South
Africa are denied the right to develop in their biological
family. For example, Fincham (1981) reports that in 'the
rural areas around Grahamstown, South Africa, about 54.9
percent children do not live with their parents, while in
Alicedale, 58.9 percent of children live with either one
parent, a grandparent, or with other relatives for their
entire childhood while their parents work and live in urban

areas .

42

Previous studies suggest that children raised by their
mothers are; better nourished than those reared by
grandparents, other people, or female relative (Fincham,
1982). For example, a study conducted on the white-owned
farms shows that three of the confirmed kwashiorkor cases
were children cared for by grandparents. In another study,
grandmothers who live in urban areas appeared to be
responsible for four of the ten children who were reported
to have kwashiorkor (Fincham, 1982).

Based (Hi their personal experience of malnutrition in
rural areas Clarke (1982) and Thomas (1973) both cite the
disruption of family life as a major factor in malnutrition.
Both researchers noted that very high proportions of
malnourished children were born to single parents. The
researchers also noted a strong correlation between
desertion by the father and the occurrence of malnutrition.

Factors such as influx control measures, which force
women migrant laborers to leave their children in the care
of aged parents in the rural areas, have also been cited as
important contributors to the incidence of malnutrition in
children in the rural areas (Clarke, 1984). In the urban
areas these women are required to live in hostels which are
designated for ’single’ women only. Their children and their
husbands are required by law not to live with them in these

hostels.

43

.hl a survey 'Hi the Ciskei, Thomas (1981) pinpointed
family disorganization as the major factor influencing the
development of malnutrition. The absence of either one or
both parents appeared more important than either cash
resources or the educational status of the caregiver,
although the latter had been found to be of relevance in the
urban setting. Thus the scenario is of an absent father or
often absent mother who out of necessity relegates child
care 11) an inadequate guardian. This condition appears to
increase the probability of malnutrition occurring in
children (Disler and Oliver, 1984).

Adverse effects of father absence on physical and
psychological development of children have been well
documented by a number of investigators (Biller, 1974; Lamb,
1976; and Lynn, 1974). Griesel and Richter (1986) studying
the influence of family background on the growth and
development of black preschool children in South Africa
found that lower height and lower weight were both
significantly related to the absence of the father from the
home.

Svanum, Bringle, and Maclaughlin (1982) in a study of
father-present and father-absent families could not find any
relationship with intellectual performance when
socioeconomic status was controlled. These researchers
pointed out that it is the antecedents and consequences of

father absence which may affect children’s development. For

44
example, if the absence of the father adversely affects the
SES of the family by lowering the income, that may in turn
have a detrimental effect on the intellectual development of
the child. Lack of income could force the mother to seek
work outside the home, which would keep her away from the
children, and thus decrease the amount of time to interact
with children.

Another problem associated with growing up in a one-
parent family is a child’s low self-esteem. Several earlier
studies in the United States have found that black children
have low levels of self-esteem both because of blackness and
the fact that often they grow up in a home without
appropriate role models (Staples, 1976).

However, a number of recent studies in the United
States have emerged that are in opposition to the earlier
studies of low self-esteem among black children. For
example, Staples (1976), concludes that black children today
are less likely to suffer from low self-esteem because of
countervailing influences, such as religion and positive
experiences in the extended family. Thus, it would seem from
this statement that black children, although they might not
have a present biological father, live in the extended
family network with uncles and grandfathers who serve as
role models. These role models are also available from the

church.

45

However, Staples (1981) adds that caution be taken not
to romanticize the single parent family as a totally
functional model. According to him, single parent families,
specifically female-headed families are the poorest families
and individuals from such families are overrepresented among
society’s failures in education, and mental health as well
as many societies’ criminals.

Nonetheless, as stated by Blechman (1982)
investigations on the effects of one parent on the
psychological development of children are fragmentary. The
results based on these studies are often conflicting and
inconclusive because of flawed methodology. These
methodological problems have also clouded the interpretation
of these studies. What emerges from these studies is that
father absence has been treated in an over simplistic
manner.

Forced removals are other factors which can influence
the nutritional and health status of family members. Since
1960 the South African government has removed 3,500,000
blacks from areas designated for whites to resettlement
areas. Approximately 1,700,000 blacks are under threat of
forced removals (South African Fact Sheet, 1984).

The effects of residential mobility or displacement
have been studied by several investigators (Stokols and
Shumaker 1983; Newman and Owen 1982). The latter researchers

examined the relationship between residential relocation and

46
health. They found that the impact of forced removals is not
necessarily negative. Rather, the consequences of moving
depended on how well the new location compares with
previously experienced environments in meeting important
personal needs.

Fairchild and Tucker (1982) on the other hand, found
that the most disadvantaged prior to moving were more
constrained in their ability to cope with the disruption.
For example, unskilled workers who lose their jobs, face a
much smaller set of alternative jobs than skilled workers.
Low income or minority families who are displaced from their
homes were likely in) have fewer housing options than the
richer or majority counterparts.

Stokols and Shumaker (1983) found that respondents who
reported low levels of satisfaction with the residential
setting described themselves as being in poorer spirits and
reported a larger number of visits with physicians for
medical problems than those characterized by higher levels
of residential satisfaction. Those who reported low levels
of residential choice also experienced a larger number of
illness incidents than those who reported higher levels of
residential choice. The effects of residential and job
satisfaction were additive; individuals characterized by low
levels of satisfaction in both domains reported the greatest

number of visits to physicians for health problems.

47

The above findings are consistent with the report from
Dr. Hendrick Beukes, a district surgeon in charge of the
Thornhill resettlement. He reports a high incidence of
physical and mental problems, particularly psychoses,
throughout this resettlement area (Mare, 1980). These
problems could be attributed to forced removals and to the
depressing conditions under which these people live (for a
full description of this resettlement, see page 91).

The structured inequalities in the distribution of
resources inherent in the policy of apartheid in South
Africa are seen by White (1980) as another major
contributory factor in the underdevelopment of the rural
areas, particularly the homelands and resettlement areas. He
demonstrated that the nutritional status of a sample of
children at the squatter camp at Crossroads near Cape Town
was better than that of a sample of children in the homeland
of KwaZulu. This investigation led him to believe that the
community at Crossroads, in spite of the deprived housing
conditions, enjoyed an overall better earning capacity and
more opportunities for self employment than those in a
sample drawn from the rural areas.

The findings suggest that children benefited from the
improved economic level (Hi their parents 'hi the squatter
camps near Cape Town. These children showed a better health
condition and nutritional status. On the other hand,

children in the homeland and the resettlement areas who

48
depend on cash remittance from migrant workers showed worse

health condition and nutritional status than the former.

Summary

The syndrome of malnutrition does not exist in
isolation, but rather in a contextual milieu. A host of
factors coexist with malnutrition. Thus, in examining the
physical growth and behavioral development of children, all
factors in the child’s ecosystem that may create a condition
of poverty should be included. All these factors could
reinforce each other producing synergistic effects, that

properly should be called ecological effects.

CHAPTER III
THEORETICAL FRAMEWORK

The purpose (Hi this chapter is two-fold. The first
section presents an eXposition of the human ecosystem
framework. The second section illustrates the application of
the ecosystem model to the study of behavioral development
of black children in South Africa. To accomplish the latter,
a discussion of the ecosystem framework is necessary. This
discussion will include the following: source and origin,
focus and scope, basic assumptions, central and germane

concepts, mode of rationality, strengths and weaknesses.
An Exposition of the Human Ecosystem
Source and Oriqin of the Ecosystem Framework

Clarke (1973) gives a full account of the origin of
ecology, a concept with it high level of abstraction, from
which ecosystem with a lesser level of abstraction is
derived. According to Clarke, Ernst Haekel, a world renowned
biologist, and the founder of ”new zoology", coined the
names for nearly a dozen sciences. As early as the late
18605, Haekel is credited with suggesting that a science be

developed which would study organisms in their environment.

49

50
He coined the word "Oekologie". However, he left this for
others to develop and he concentrated on other sciences.

Ellen Swallow, a chemist, aided by her fluency in
German, traced the German word "Oekologie" in) its Greek
origin. "Oik" stands for house, "Oek" stands for every man’s
house or environment, and "logie" stands for science.
According to Swallow, "Oekology" was the science (H’ the
House. Home Economics was in) her Human Ecology before it
acquired the former name.

The concept of ecology did not evolve and remain only
in biological sciences. Historically this concept has been
used in sociology also. The ecological approach was
introduced into sociology in the 1920’s by Park and Burgess.
This -concept has also gained popularity and use in
disciplines such as geography, anthropology, psychology, and
human ecology. "Hue development of this concept in human

ecology will be dealt with later.
Definition of Ecology

Webster’s New World Dictionary (1978) gives two
definitions of ecology. The first one has a biological base
and the second one has a sociological base. The first
definition is: "the branch of biology that deals with the
relations between living organisms and 'their' environment"

(p. 442). The second definition is: "the study of the

51
relationship and adjustment of human groups to their
geographical environment” (p. 442). IkHfli these definitions
emphasize the relationship between the living organisms or
human groups to their environment.

Odum (1962) deviates from this definition which he sees
as vague and too broad. According to him ecology is the
study of structure and function of an ecosystem. In a less
technical way he views this term as the study of the
structure and function of nature. By structure he means the
composition (Hi the biological community, the quantity and
distribution of the non-living materials such as nutrients,
and the physical matter. By function he means the rate of
energy, matter, and information flow through the ecosystem.

Incorporated 'hi Odum’s definition is the concept of
ecosystem. The inclusion of the concept of ecosystem serves
to narrow this definition to a more concrete level. This
ecosystem could be that of a family, child, plant, or animal
depending on the subject under study. For example, in this
study the concern is for the ecosystem of the black child in
South Africa.

Having traced the source and the origin of ecology from

which ecosystem evolved, a discussion of the concept of

ecosystem will be covered.

52

The Concept of Ecosystem

The term ecosystem was formally proposed by Tansley in
1935, as a general term for both the total complex of
interacting organisms and their habitat. According to him,
all the parts of an ecosystem, organic and inorganic,
biomass or habitat, may be regarded as interacting factors
which in a mature ecosystem are in approximate equilibrium.
It is through their interaction that the system is
maintained.

The term ecosystem as discussed by Tansley (1935)
includes the whole idea of dynamic interaction, exchange, or
interdependence between an organism (O) and the environment
(E). "Eco" which is derived from "ecology" means
"environment" 'and "system" which is derived from general
systems model indicates an interacting interdependent
complex of organisms.

As stated by Havelock (1971) a system can be
conceptualized as a set of components which act with and
upon one another to bring about a state of balance,
interdependence, or wholeness. For example, in the study of
black children in South Africa, the child’s physical,
cognitive, and social-emotional domains form a system of
individual development. These domains are interdependent and
act with and upon one another to bring about equilibrium or

a wholeness in the growth and development of the child.

53
Although these domains form a system, they do not form the
child’s ecosystem. These domains are only part of the
child’s ecosystem.

Factors selected for investigation in this study which
also comprise part of the child’s ecosystem are: the child’s
area of residence, home environment, parent’s socio-economic
status, type of family structure and family mobility. These
factors represent the components of the natural, human
constructed, and human behavioral environments. It is the
interaction of these factors with the developing child that
form an ecosystem of the child.

Systems may be characterized as either "semi-closed" or
"closed". Closed systems are isolated from their environment
in that there is no exchange of matter, energy, and
information across system boundaries. In contrast, semi-
closed systems exchange matter, energy, and information with
their environment within a limited to broader range of
possibilities.

Living entities such as the child (H‘ the family most
certainly demonstrate the complexity of semi-closed systems
i.e. they have inputs and outputs. For example, in the
child’s system the ecological factors represent what
Broderick and Smith (1979) call the environmental inputs and
the behavioral development and physical growth represent the

outputs.

54

Systems may be further described as "static" or
"dynamic". In a static system, components of a system exist
iri a more <n~ less fixed relationship with one another. In
contrast, components of a dynamic system act upon one
another; they force changes. in a pattern of action and
reaction that maintain a dynamic equilibrium or balance of
forces. Systems of the child or family contain both dynamic
and static components.

Two types of systems may be considered in the study of
growth and development of black children in South Africa,
namely the family and the individual child. The family as a
system acts as 2! processor or converter of inputs, goods,
and services from the environment to meet the needs of
individual family members, and produces an output flow of
converted products such as waste or surplus. Since resources
are scarce, South African black families establish survival
goals as high priority and manage the available resources
according to those goals in order to meet the needs of
individual family members.

A second type of system is that of the individual
child. The individual child may be viewed as a semi-closed
system which also processes matter, energy, and information
from the nearby environment. These are utilized to provide
sustenance to meet the child’s physical growth, cognitive,

and social-emotional development.

55

An ecosystem can be visualized as a grouping of
components linked by flows of energy and connected to the
surrounding environment by its system of inputs and outputs
(Bormann and Likens, 1970). All ecosystems, including the
family ecosystem, are permeable so that matter, anergy, and
information flow continually in the course of life processes
for the survival of the system of family (Evans, 1956).

The environment cH’ the ecosystem provides resources
potentially useful for the maintenance of life. Three types
of environmental factors may be distinguished: natural,
human constructed, and human behavioral (Bubolz, Eicher, and
Sontag, 1979). These environments interact with families and
provide resources (matter, energy, and information)

necessary for the survival of the families.

Adeption and Use of Ecosystem in Human Ecology

Precedence for the approach of viewing the family as an
ecosystem in Human Ecology was provided by Hook and Paolucci
(1970). These authors suggested the use of this approach
because it forces one to emphasize interdependent
relationships between people and their environment.
According to these authors, the family is a life support
system which is dependent upon the environment for the
physical sustenance and upon social organizations which are

related to humanness and give quality and meaning to life.

56

The human ecosystem approach utilizes concepts from
general system theory which have been suggested and
promulgated by some family scholars such as Parsons and
Bales (1955) and Kantor and Lehr (1975). However, their
approach restricts the study of the family to social,
psychological, and cultural aspects only. For example,
Parsons and Bales (1955) studied the socialization processes
and the personality development, of children within the
family. Their~ approach emphasizes the interaction between
family members. Part of the total environment, which
includes the physical and the biological components in which
the family is embedded, is overlooked. The relationship in a

social system is symbolized in Figure 1.

Figure l. Organism and organism relationship

57

Such a relationship from an ecosystem perspective is
insufficient because it overlooks the total environment. As
stated in! Andrews, Bubolz, and Paolucci (1980) the social
system approach to the family studies has sometimes assumed
the biological and the physical dimensions as given or when
considered has given them little attention.

An ecosystem approach, on the other hand, considers the
biological, physical, psychological, and sociophysical

dimensions of the organism and their interdependence in an

ecosystem.

 

Figure 2. Environment and organism interrelationship.

Many individuals have contributed to the development of
the ecosystem approach for studying the family in the field
of Human Ecology. However, the names of the following
scholars deserve mention (Bronfenbrenner, 1979; Bubolz et
al. 1979; Deacon and Firebaugh, 1975; and Hook and Paolucci,
1970). As discussed in a seminar by Bubolz (1985b) the

58
development of this paradigm is, however, in its infancy;
much still needs to be done in terms of building,
developing, and refining this model in order to bring it to

the level of a theoretical framework.

Focus and Scope

To understand the focus of the ecosystem approach, it
is helpful first to detail the essential elements of this
approach. An ecosystem model is based on a systems
perspective which focuses on the interrelationships, input
and output, and processes within a system. A change in any
part of the system affects the system as a whole and its
other subparts, creating a need for a system adaptation or
morphogenesis. Also, an ecosystem model denotes an
interdependence and interrelatedness of organisms in their
environment. Thus, this model focuses on the organism in its
environment composed of the natural, man-built, social, and
psychological factors.

Bronfenbrenner (1979) has described the individual’s
environment as '%i set of structures, each inside the next
like a set of Russian dolls" ( p.22). In addressing the
scope of the ecosystem framework, Bronfenbrenner posits four
general levels of environmental systems: micro-, meso-,

exo-, and macro-system. These systems are differentiated on

59
the basis of their immediacy with respect to contact with

the individual specifically the child.

Microsystem

Most immediate to the developing «child is the
microsystem. This system consists of the settings and the
behavioral interactions in which individuals experience and
create day—to-day reality. Thus the home which gives shelter
to the child and family members who feed, bathe, and cuddle

the child form the child’s microsystem.

Mesosystem

This system forms the relationship between the contexts
of microsystem in which the developing person experiences
reality. An important mesosystem for school children
includes relationships between the school and the child’s

home.

Exosystem

An exosystem is a situation which has a bearing on the
child’s development but in which the developing child does
not actually play a direct role. For example, the workplace

of parents has power over the life of the child, yet the

60
child does not participate. The exosystem enhances the
development of the child when it makes life easier for
parents; conversely, it undermines development when it makes

life harder for parents.

Macrosystem

Micro-, meso-, and exosystems are embedded in the broad
ideological and institutional patterns of a particular
culture or subculture. These patterns are the macrosystems,
the ’blueprints’ for that culture’s ecology of human
development. These blueprints reflect a people’s shared
assumptions about ’how things should be done’. Thus a
macrosystem is the norm about how development proceeds, and
the appropriate nature and structure of micro-, meso-, and
exosystem. Macrosystems are overarching institutions of a
society' which include religious, political, economic, and
educational systems. These represent not only the structural
characteristics of society, but also the carriers of
ideology and symbolic meaning that give character to life at
the micro-, meso-, and exosystem levels (Melson, 1980).

These four types of environmental systems provide the
scope for studying children and families. As shown in these
types, one can delineate boundaries that are very broad,
limited, or very limited within the range of phenomena about

children or the family.

 

 

61

Basic Assumptions of the Ecosystem Framework

Assumptions are part (Hi people’s everyday 'life. They
are those things that people perceive as ’givens’. They are
based on faith, factual knowledge, previous experience, or
ignorance. Assumptions are also part of the world of
science. "Scientific assumptions are statements taken as
given and not subject to direct empirical verification"
.(Chafetz, 1978, p.33). As stated by Klein (1979) delineation
of assumptions basic to the theoretical framework form the
foundation for the theory.

The assumptions delineated 'hi this section are drawn
from several sources (Andrews, Bubolz, and Paolucci, 1980;

Bubolz, Eicher, Evers, and Sontag, 1980; and Bubolz, Eicher,

and Sontag, 1979).

Assumptions about Human Life

A major premise underlying, an ecosystem approach is
that humans are a part of the total life system, and cannot
be considered apart from the natural, human constructed, and
human behavioral environments. This statement is consistent
with what John Donne said three centuries ago. ’No man is an
island, entire of itself; every man is a piece of the
continent, a part of the main’ (Warnke, 1963). This

statement suggests that all individuals interact in the

62
drama of human ecology, and in relation to other living
plants and animals in the environment. The model in Figure 3
serves to illustrate the interconnectedness of humans and
the environment in which they are embedded. This Figure is

adapted from (Bubolz, Eicher, and Sontag, 1979).

  

Natural Environment

  
  

 
  
 

Human Constructed
Environmnet

  

Human Behavioral
Environment

 
   

Figure 3: A Human Ecosystem Model

63

Assumptions about the Family

The family is a goal-directed system. It consists of
structures, functions, and processes. These structures form
a whole system in inrhfli the parts function in relation to
each other to reach the family’s goals.

Family systems are organizationally complex, relatively
open and in) some extent adaptive. Families also differ in
degree of complexity, openness, boundary maintenance, and
adaptability. Two critical dimensions of families which
influence their capacity to deal with change and to cope are
adaptability and cohesion. Family adaptability refers to the
ability of a family system to change its power structure,
roles, relationships, and rules in response in) change and
stress. Family cohesion refers to the degree of emotional
bonding which members have towards one another and of
individual autonomy that a person has in the family system.

Another assumption is that families must be studied in
their own natural and social contexts rather than it: an
artificial environment like the professional office or
laboratory. It is this natural milieu which provides the
richest possible context for studying the family. This
perspective also assumes that phenomena about the family
must be studied in their wholeness of interaction or

interdependedness rather than by simple, linear cause and

effect relationships.

64

Assumptions about Energy. Information. and Communication

Energy, both physical and psychic, is the basic
resource necessary for the survival of the family. Ellen
(1982) discussed another essential component to matter and
energy; this is information. According to him, an ecosystem
is a set of organic relationships in which matter, energy,
and information are in continuous circulation. Any
alteration through the family system requires adaptive
change.

Family systems are information processing systems.
Families can elaborate and/or change action patterns because
of information processing capabilities. Families differ in
degree and nature of the information processed. For example,
some families process more information than others, perhaps
because family members have higher levels of education, or
because family members have ease of access to news media.

Communication is a key process of a family system.
Families have rules about communication, i.e. meta
communication indicates unwritten, and usually unstated
rules about what can be communicated, and who can

communicate about certain things.

65

Central and Germane Concepts

As stated by Klein (1979) a theory is an architectural
creation. Basic to this architectural creation are concepts
which are the building blocks. Concepts are ideas composed

of symbols (terms, labels) and their meanings (definitions).

Organizational Concepts of the Ecosystem Framework

Major configurational concepts used 'hi the ecosystem
framework and also related to the application in this
research will be listed below. These concepts will not be
defined, since they are not the focus of this research.
However, it is necessary to list them as these concepts are
central to the ecosystem framework.

Configurational elements are those which are present in
all ecosystems. These include: boundary, energy,
environment, information, interaction, interface, organism,
system, and transaction. Included 'hi this list are also
those elements which describe the ecosystem: semi-closed or
semi-open.

The ecosystem framework also includes concepts which
define elements that describe interaction and transaction in
the ecosystem. Included are adaptation, cybernetic, entropy,

equilibrium, feedback, homeostasis, morphogenesis,

66
morphostasis, and negentropy. Concepts that are germane to

this study will be defined in Chapter IV.

Mode of Rationality Implied or Assumed by the

Ecosystem Framework

The concept of Rationality

Brown (1985) in considering the concept of rationality
states that there is :1 connection between rationality and
knowledge. Rationality, however, has less to do with having
knowledge than with how we acquire and use that knowledge. A
person is called rational when the person can exercise good
judgment and can reason logically. A rational action
connotes the absence of emotionalism.

Habermas (see Brown, 1985) holds that there are modes
of rationality or ways of examining phenomena. Each is
associated with types of knowledge. The first mode of
rationality is ’technical’ which is used when the goal is to
predict and control the environment. This mode gives rise to
the empirical-analytical sciences. This science focuses on
objective phenomena. The second mode is ’hermeneutic’ or
interpretive rationality, which is used when the goal is to
understand human actions and thought. It is the dominant
analysis used in cultural sciences such as anthropology,

history, and social sciences concerned with interpreting

67
human communication and action. The third mode of
rationality proposed in the Habermas scheme is called
’emancipatory’. This is used when the goal is to free
individuals or groups from oppression due to irrational
norms or ideas. This mode is associated with ’critical
science’.

The emancipatory rationality leads to what Habermas
calls ’political-moral action’. This is action which seeks
good for people or societies. It is based on the knowledge
gained from the careful analysis of the merits and faults of
a situation or critical self-reflection and clarification of
beliefs. The result is that people are freed from irrational
ideas or systems which ’the powers that be’ have
unconsciously or consciously adhered to because they did not
see ’better’ ways of dealing with the situation.

Brown (1984) explains that choosing one mode of
rationality rather than another is to choose the most
appropriate for the .kind of understanding desired. Such a
choice would, "not pit one against another". Rather, it
would help recognize a mode of rationality that best deals
logically with a certain problem.

Some frameworks do allow the use of all three modes of
rationality. For example, all three modes of rationality
(technical, hermeneutic, and emancipatory) are assumed under

the ecosystem framework. On a technical level, the phenomena

68
are explained as multicausal and effect relationships by
treating independent variables as outputs. The mechanism of
feedback control can In: used as contingent variables that
give the explanation of how to interpret the relationship
and interaction (Hi a hermeneutic level. With more complex
control of feedback which leads to morphogenesis of the
system or the system rules, an ecosystem framework can

assume an emancipatory mode of rationality (Bubolz, 1985b).

The Need for a Critical Science Perspective in Human Egglogy

As stated by Bubolz (1985a) a critical science
perspective is necessary to develop the knowledge and carry
out the practice of Human Ecology. Critical science starts
with an assumption which is central to the ecosystem
approach, i.e. humans are part of the total system and
cannot be considered apart from the natural, human
constructed, and human behavioral environments. The purpose
of critical science is to bring about self knowledge and
reflection to ’powers that be’ that will lead to needed
social change. By the same token, the oppressed group in
society is helped to take control over their lives.

Bubolz (1985a) has suggested ways of developing
critical thinking in students in Human Ecology. One way is

to participate in interpretive research. As shown by

69

Habermas’ scheme, the emancipatory rationality utilized in
critical science is dependent upon knowledge obtained
through technical or. empirical analytical rationality and
hermeneutic or interpretive rationality. Thus the critical
scientists begin with the empirical-analytical and
hermeneutic methodologies and end up with the emancipatory
methodology. This methodology represents an in-depth
analysis because it goes beyond the data collected,
analyzed, and interpreted to the rationale for an action.
This action could include finding means to end oppression or
inequality in society and to determine what could be done to
set the people free or give people equal opportunity.

Another way would be for students to read research and
scholarly materials and attempt to identify the ideological
assumptions underpinning the research. These could become
the basis for dialogue and plans for social action. The
critical scientist according to Habermas seeks to identify
activity and thought that are based on erroneous assumptions
and thus need rectification. Implied in the concept of
critical science is the further step of implementation, that
is, working to implement the alternative because it is
viewed as the most freeing for the people in society. As the
schema states, critical science activity ends in political

moral action.

7O

Strengths and Weaknesses of the Ecosystem Framework

One of the intentions and hopes of students and
scholars in human ecology is to make a contribution towards
the development and refinement of the ecosystem framework.
A delineation of the strengths and weaknesses of the
ecosystem framework thus serves as an indication of the
viability or lack of viability of this framework. For
example, the strengths of the ecosystem framework are an
indication of the usefulness of this framework for studying
systems such as the family and children. On the other hand,
the weaknesses show what needs to be done to save this
framework from ’demise’. Therefore, it is important to

examine the strengths and weaknesses of a framework.
Strengths of the Ecosystem Framework

The human ecosystem framework can be considered as an
overarching and all encompassing framework. Under this
framework specific frameworks and theories can be used to
examine interrelationships and interactions. For' example,
the structural-functional, interactionist, exchange, and
developmental family theoretical frameworks, as well as the
cognitive and affective theories can In: used under this

framework to study interrelationships.

71

The ecosystem framework is holistic. It. compels the
researcher or practitioner to examine the phenomena in their
entirety. Because it focuses on the interaction between the
human and the environment in which the human is embedded, it
gives a researcher something concrete and tangible to
assess. The ecosystem framework is an heuristic model. It
encourages the scholar/student in) discover and learn the

interaction and the relationship between factors.

Weaknesses of the Ecosystem Framework

The human ecosystem framework. is complex and broad,
therefore, it is difficult for the researcher to manage the
phenomena. This makes it difficult to analyze data
statistically, thus, it might be necessary in the future to
develop new methods which could be used to analyze data.

Because the ecosystem framework is so complex and
broad, it tries to explain everything and may end up
explaining nothing. Not everyone can enjoy using this
framework because of its complexity. It takes a particular
type of personality which enjoys dealing with ’wholes’ and
how things are related to each other.

The ecosystem framework contains many abstract
concepts. Such concepts need to be defined and brought to a

concrete level so they can 1H! measured and tested

empirically.

72

Application of the Ecosystem Framework

This section will illustrate the use of the ecosystem
model in the study of behavioral development of black
children 'hi South Africa. This study utilizes the human
ecosystem framework proposed by Andrews, Bubolz and Paolucci
(1980); Bubolz, Eicher and Sontag (1979); Hook and Paolucci
(1970) and Morrison (1974) for studying the family. This
study is also based on the framework proposed by
Bronfenbrenner (1979) for studying the ecology of human
development. Both these models link individual physical

growth and behavioral development to factors in one’s

ecological niche.

Rationale for Using the Ecosystem Framework

As discussed in the review of literature, a great deal
of research on the relationship of malnutrition to physical
and cognitive development has been done using animal models.
However, these models are limited because of their
simplicity. The animal models have focused only on the
nutritional aspect of the total environment. They have
overlooked the ecological factors in which the individual is
embedded. Growth and development of children is influenced

by a myriad of factors in their environment, hence the

73
rationale for utilizing the holistic approach of the human
ecosystem.

The review of literature (Griesel, 1980; Richardson,
1980) on the studies of growth and development of children
reveals that these authors decry the absence of an
ecological approach. They both suggest that studies in this
area move beyond malnutrition per se, to include all the
environmental factors that nfight. contribute to the later
level of functioning of the child. Thus, they suggest a more
ecological research approach in which physical, biological,
psychological, social, political, and economic factors are
considered.

Understanding growth and development of children is
particularly well-suited to the ecosystem model. As is
increasingly being recognized, growth and development of
children are the product of a multiplicity of factors, not
of one factor or influence acting alone.

According to the human ecosystem framework, all
children and their families live in a natural, human
constructed, and human behavioral environment. These
environments set the context for the availability of
resources to different groups in a society and within
families. The availability of these resources will influence
the level and the standard of living of groups and families.

This condition will in turn have an effect on the physical

74
growth, cognitive, and social-emotional development of
children in that society.

Bronfenbrenner (1979, p. 21) defines the ecology of
human development as:

the scientific study of the progressive mutual

accommodation between an active, growing human being,

and the changing properties of the immediate settings
in which the developing person lives, as this process
is affected by relations between these settings, and by
the larger contexts in which the settings are
embedded.

Thus, as it can be seen, the ecological or ecosystem
framework is useful not only in the biological sciences, but
also in social sciences for studying social systems such as
the family. The model in Figure 3, (HT page 62, serves to
illustrate the interaction within the family and the
environments in which it is embedded. The framework suggests
a relationship among the three environments that helps one
to keep a holistic and integrative view, rather than a
fragmented view of interaction taking place.

The ecosystem framework is used in this study because
it provides a holistic framework for the study of children.
As suggested by Sims, Paolucci, and Morris (1972) it allows
the investigator to identify contributory factors as systems
and subsystems and to focus on the transactional patterns or

exchanges that exist among the systems of the child, the

75
family, the community, and the geographic area as a whole.
The ecosystem framework is appropriate for. the study of

growth and development of black children in South Africa.

Assumptions Used in the Study (H’ Black Children iri South

Africa

Four assumptions undergird the study of black children in
South Africa.

Children develop holistically. All developmental
domains (physical, cognitive, and social-emotional) are
interrelated and interactive. Thus, when children are being
studied, these domains cannot be separated. Each affective
behavior has a physical and cognitive counterpart, and for
every cognitive outcome there are changes in affect (Goodwin
and Driscoll, 1980).

Children are part of the total environment and cannot
be considered apart from these ecological factors. These
factors provide opportunities for the development of
children. As stated by Garbarino (1977) there is no pure
context-free development.

Studies about. children’s physical and behavioral
development cannot be conducted in the professional office
or laboratory. Such studies should be done ““1 the child’s

natural and social contexts. It is these ecological factors

76
which provide the richest possible context for understanding
behavioral development and physical growth. 1

The family acts as the immediate environment
(microsystem) for the developing child. The family plays a
key linking role in providing the conditions for interaction
between the child, the meso-, exo-, and the macrosystem.

The ecosystem model will be particularly useful in
explaining factors that impinge on the ‘welfare of black
children in South Africa. This approach compels the
investigator to consider the many environmental forces and
the ecological balance among these forces that interact over
time with the family or individual child. The diagram in
Figure I! is an example of the use of the human ecosystem
framework proposed In! (Bubolz, Eicher, and Sontag, 1979).
This diagram identifies variables that will be investigated

in the ecosystem model.

77

     
   
  

Natural Environment
Area of Residence:
Farm, Homeland, and Resettlement

 
    
 
     
       
   

Child
Cognitive Development
Social Emotional Development
Physical Growth and Health Condition

Human Behavioral
Environment
Type of Family Structure
Home Environment

Human Constructed
Environment
Parent's Educational
and Occupational Levels,
Family Mobility

Figure 4. ll Model for Studying Black Children in South

Africa

78
Mode of Rationality Used in the Study of South African
Children

As stated in section 1, in the discussion of the mode
of rationality, all three modes of rationality, namely
technical, hermeneutic, and emancipatory can be assumed
under the ecosystem framework. This research starts with the
empirical analytical perspective. This helps to explain the
relationships of the ecological factors on the behavioral
development and physical growth of black children in South
Africa. Following data collection, analysis, and
interpretation, a critical science perspective which
involves the emancipatory mode of rationality will be used.
The emancipatory rationality will lead in) what Habermas
calls political-moral action. This is action which seeks
good for the people. This would be achieved by getting
members of the community involved in policy making that
would bring about social, political, and economic changes.

Also implied in the concept of critical science is
implementation, that is, working to design and implement
programs for children and families which would improve their
quality of life. One focus in this dissertation is to
uncover and discuss those data that could be later used for

community involvement in policy making.

CHAPTER IV

RESEARCH METHODOLOGY

This section provides a discussion of the research
design, objectives, variables, questions, selection, and the
description of the population. The instruments, methods for
data collection, and- data analysis used in this study are
included in this discussion as well as the ethical

principles and ethical problems.

Research Design

This is an exploratory cross-sectional study. Due to
limited data on these children and their ecological context,
it was considered appropriate to conduct an exploratory
study. The design chosen for this study is not experimental,
but rather it; is quasi-experimental. In this research the
independent variables are not under the control of the
experimenter who randomly assigned individuals to conditions
of exposure or non-exposure. In studying reactions to
naturally-occurring events such as area of residence, family
structure, and socio-economic status of the~ family, this
control is not possible. Investigations of this type are
best viewed as quasi-experimental, a term used by Campbell

and Stanley (1963). The unit of analysis investigated in

79

80

this study is a black South African child, 5-6 years of age.

Specific Research Objectives

Investigate the relations between the area of residence
and the parent’s marital status, educational, and
occupational levels.

Determine the relationship between the area of residence
and the child’s self-concept, cognitive development, and
physical growth.

Determine the relationship between the parent’s marital
status and the child’s self-concept, cognitive
development, and physical growth.

Determine the relationship between the parent’s
educational level and the child’s self-concept,
cognitive development, and physical growth.

Determine the relationship between the parent’s
occupational level and the child’s self-concept,
cognitive development, and physical growth.

Determine whether the self-concept of the child is
related to cognitive development.

Investigate the relationship between physical
development, self-concept, and cognitive development.
Determine whether the child’s health condition is

related to physical growth, self-concept, and cognitive

development.

81
9. Investigate the relationship between the home
environment and the child’s self-concept, cognitive
development, and physical growth.
10. Determine whether family mobility is related to the
child’s self-concept, cognitive development, and

physical growth.

Research Variables

Conceptual and Operational Definitions

This section gives the conceptual and operational
definition for each variable.

Area of residence: Area of residence means the place
where the child lives at the time of the interview or where
the child has lived since birth. In this study the area of
residence could either IN! the homeland, resettlement, or
farm area.

Family mobility: Family mobility is a process of moving
from one residential area to another. Family mobility will
be measured by the number of times the interviewee and the
child have moved.

Socio-economic status (SES): Involves social and
economic factors that distinguish people in society. The
term often assumes that there are distinct social classes

based on education, income, and occupation (Theordorson and

82
Theordorson, 1969). For the purpose of this study income
will not be included since information regarding income is
sensitive and difficult to obtain. The parent’s educational
and occupational levels will be considered as indicators of
SES. According to Goodwin and Driscoll (1980) occupation has
been typically the single best predictor of SES.

Family structure: The U.S. Census defines a family as:
two or more persons living together who are related to each
other by blood, marriage, or adoption. Thus by this
definition a husband and wife, two sisters living together,
mother and child, father and child, or grandparent and child
would be considered a family. Family type is based on family
structure. Seven types of families are considered in this
study, namely, married, married but not living with a
spouse, never married, divorced, widowed, separated, and
living together not married. Types of families in this study
only included those that had a child or children who were
enrolled in a primary/elementary school.

Home environment: Home enVironment includes both
physical and social factors. In this study home environment
includes the structure of the house, the number of people in
the household, the availability of books, toys, and games
for’ the child, and parent-child interaction. The parent-
child interaction includes activities such as working

together, reading books together, and telling stories.

83

Nutritional status: Sims (1971) defines nutritional
status as the state of health of an individual or group as
conditioned by choice and amounts of foods or more
specifically, nutrients eaten. In this study, the child’s
nutritional status is inferred from his/her physical growth.
Physical growth is based on standardized anthropometric
measures of height, weight, and head circumference. Height
is generally the best indicator' of extended nutritional
deficiency. Weight indicates the present nutritional status
of the individual. Head circumference is the most sensitive
to malnutrition that has occurred before the age of two
years (Yarbrough et al. 1974; Freeman et al. 1977).

Health condition: Health condition denotes the state of
well-being or the state of illness of the child. In this
study health condition refers to the child’s state of health
as perceived by the parent/guardian. This will be measured
by whether the parent/guardian reports that the child has
been hospitalized within the past year or past six months,
and what the reasons for hospitalization were.

Behavioral development: Development is a process whereby
an organism changes in complexity over time. A change in the
thought processes of young children from sensory-motor
intelligence to preoperational thought would be an example
of development. Behavioral development as used in this study

refers to cognitive and social-emotional development of the

child.

84

Cognitive development is a process by which an
individual comes to know and interprets his/her environment.
Cognition is a process of knowing and includes not only
sensation and perception, but other phenomena such as
recall, reasoning, problem solving, thinking, and an ability
to learn (Lorton and Lorton, 1984). For the purpose of this
study three areas of cognitive development will be measured.
These are verbal, quantitative, and performance.

Social—emotional development is a process by which an
individual acquires emotions, preferences, interests,
attitudes, values, mores, and a conception of him/herself
(Goodwin and [Hfiscoll, 1980). Social-emotional development
as used in this study refers only to the dimensions of self-
concept i.e. the perception(s) the child has of him/herself.
For example, does the child consider him/herself pretty or
ugly. There were also other attributes that were used to
measure the child’s self-concept (See Appendix A for a

scoring sheet for Brown-IDS-Self—Concept Referents Test).
Research Questions

Fourteen questions are formulated for this research.
These questions give specific focus to the research
activities and help ensure that the major goals of the study
are met. In exploratory research, research questions are

more appropriate than hypotheses because the directions of

85
the relationships are not known. In this study the
investigator has an interest in a topic which does not have
a substantial body of data upon which to predict
relationships among the variables. As stated by Babbie
(1979) in some cases the investigator may start out with a
concern or curiosity. This investigation explores variables
previously unresearched in regard to South African context
of ecological factors which have an: impact (H1 children’s
growth and development, therefore, research questions are
appropriate. The researcher realizes that the use of
questions rather than hypotheses makes for weaker
relationships in findings. Following the analysis of data
collected in this study, the researcher can generate

hypotheses which might be formulated for future research

studies.

Question 1:

Is area of residence related to the child’s self-concept,

cognitive development, and physical growth?

Question 2:

Is the child’s self-concept related ix) his/her cognitive

development and physical growth?

86
Question 3:
Do children from families with a low socio-economic status
differ on the self—concept measure from children whose

family SES is high?

Question 4:

Is the child’s health condition related to self-concept?

Question 5:
Is the child’s health condition related to cognitive

development?

Question 6:

Is the child’s health condition related to physical growth?

Question 7:
Is the child’s home environment related to self-concept

and cognitive development?

Question 8:
Is family mobility related to the child’s self-concept and

cognitive development?

Question 9:
Do children from single parent families differ from children

who come from two parent families in cognitive development?

87

Question 10:

Do children from single parent families differ from children

who come form two parent families in self-concept?

Question 11:

Do children from single parent families differ from children

who come from two parent families in physical growth?

Question 12:

Is the child’s home environment related to physical growth?

Question 13:

Is the socio-economic status of parents related to cognitive

development of children?

Question 14:

Is the socio-economic status of parents related to physical

growth of children?

Research Sample

The population being studied consists of 5-6 year old
black South African Xhosa speaking male and female children.
Three hundred (300) children were assessed for cognitive,
social—emotional development as well as measures of physical

growth. The parent/guardian of each child was interviewed

88
for demographic data. A group of one hundred (100) children
was selected from each of the areas in which blacks are
assigned or in some cases work. The method used by the South
African government to assign the four different racial
groups is covered in Appendix B.

The areas from which the sample was drawn were as
follows: Herschel in the homeland of the Transkei, the
resettlement of Thornhill in the hemeland of the Ciskei, the
farm areas around Queenstown and in the Orange Free State
(see map of South Africa for homeland, resettlement, and

farm areas on page 89).

Brief Description of the Three Areas from which

the Sample was drawn

This section presents salient features of the social,
economic, political, and physical environment of the

homeland, resettlement, and white-owned farm areas.

flameland of the Transkei

A key piece of apartheid legislation passed in the
1970’s was the Bantu Homelands Citizenship Act. This act
states that every black in South Africa is a citizen of one
of the ten homelands. These homelands were created to assume

responsibility for millions of blacks who according to the

89

 

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90
act would cease to be citizens of South Africa. This act
applied to all black people, even those who had always lived
in urban areas, and had no knowledge of any "homeland" and
had no relatives there.

Ten homelands have been designated according to the
U.S. Policy Toward Southern Africa, (1981). Of these ten,
four are now officially classified as independent. These
are: Transkei, Ciskei, Bophuthatswana, and Venda. Four of
these homelands, Lebowa, Gazankulu, Qwaqwa, and Kwazulu are
classified as self-governing territories. The other two,
Kangwane and Ndebele are in an early stage of self-
government. They have only begun to organize their
governments in the late 1970’s. As of 1983, 46 percent
blacks lived and worked in urban areas and on white-owned
farms and about 54 percent blacks lived in the homeland and
resettlement areas (South African Fact Sheet, 1984).

The homelands are for the most part situated in barren,
dry, and infertile areas. They are poor in resources and
lack exploitable mineral resources. The major mineral
resources are all located in the urban areas of South Africa
(U.S. Policy Toward Southern Africa, 1981).

Economically and politically homelands are inextricably
tied to the South African government despite the fact that
they have been given a form of "independence" as self-
governing states. The homelands function as reserves of

labor for South African industries. Black workers are

91
recruited from the homelands and the resettlement areas on a
migrant labor system to go and work in urban areas. They
leave their families for a period of one to two years and
return to the homelands at the end of the contract.

For the purpose of this study the homeland of the
Transkei and Ciskei will be discussed. The resettlement of
Thornhill is irl the homeland (H’ the Ciskei. These are the
homelands from which two thirds of the sample was drawn.

According to the South African Legislation the homeland
of the Transkei became fully independent on October, 1976.
The Transkei has an area of 43,798 square kilometers of
land. The population is 2,323,650 and population density is
53.1 per square kilometers (Platzky and Walker, 1985).

As stated by Muller (1984) the homeland areas contain
some of the worst victims of South African polarized
development. The following characteristics depict the
conditions of the Transkei. Sixty percent of the adult
population in this homeland is illiterate. Two thirds of
households had cash incomes below the estimated household
subsistence level of R1509 or $754 in 1982. Tuberculosis is
the greatest killer. Two thirds of the male labor force is
permanently absent working as migrant laborers in urban
areas in South Africa. The mortality rate in children up to
five years of age ranged up to 261 per thousand and averaged

190 in 1980 (Muller, 1984).

92

Another factor that adds to the problem of Transkeians
is severe drought. Drought in the homeland of the Transkei
means that few crops are sown, and even those that are sown
fail to grow because of drought. Cattle deaths in this
homeland provide the best index of the severity of drought.
Another important effect of drought has been an increase of
water borne diseases. For example, cases of cholera and
typhoid were reported during 1982-1983. Infant. and child
mortality due in) kwashiorkor, measles, and gastroenteritis
were also reported (Muller, 1984).

Because of excessive drought throughout the year in the
Transkei, food cultivation and stock raising are a futile
effort. Another reason which makes cultivation and stock
raising difficult is that a large proportion of those living
in the homelands are either very old or too young, or those
who cannot be considered undem' the migrant labor system

because of illness or some other reason.

Resettlement Area of Thornhill

The root of forced removals of blacks by the South
African government from areas designated for whites to
resettlement areas stretches as far back as the seventeenth
century. In many ways the removals of the past thirty years

in South Africa form but one phase in a long history of

93
dispossession and displacement of blacks by whites in South
Africa (Platzky and Walker, 1985).

One of the first things that Jan van Riebeeck did after
he arrived at the Cape in 1652, to establish a base for the
Dutch East India Company, was to drive out the local blacks
who were known as the Khoi-khoi from their grazing land
below Table Bay near Cape Town. Two years later Van Riebeeck
formalized the displacement of the Khoi-khoi from their
lands in the Cape Peninsula by means of an agreement.

This agreement stated that only the Khoi-khoi who were
prepared to work for the Dutch East India Company or the
first white settlers were allowed to remain on their former
grazing land. The removal of all blacks not working for
whites in the Cape to the central or eastern part of South
Africa was one of the ways by which the white settlers set
about controlling access to land and to wealth in South
Africa. The displacement of black natives of South Africa is
similar to what happened to the natives of the United States
after Columbus claimed to have "discovered” America in 1492.

The removals of blacks to their "homelands" have
resulted in several resettlement areas. Thornhill, Sada, and
Ntabethemba in the homeland of the Ciskei are but a few
examples of these resettlement areas.

The homeland of the Ciskei became fully independent in
December, 1981. The homeland of the Ciskei is comprised of

about 5,300 square kilometers of land. The population is

94

666,000 and population density is about 126 persons per
square kilometer, representing a dramatic rise of 126
percent over the period between 1975 and 1980 (Daniel,
1981). This increase can be explained by the South African
policy of forced removals of blacks to their "homelands".

The overall standard of living in the Ciskei is low.
The gross national income for 1977 was R303 or $151 per
capita, compared with R530 or $265 in South Africa as a
whole (Charton, 1982). The lack of employment opportunities
in both the homeland and the resettlement areas has forced
breadwinners especially adult lMNl and women to nfigrate to
urban areas leaving dependents such as the elderly and young
children behind.

In the Ciskei Commission report of 1980 data
illustrate high infant mortality and widespread malnutrition
in these resettlement areas. Previous studies done in the
Ciskei suggest that about 27 percent of the population under
24 months of age suffer from kwashiorkor (Gordon, 1981).

Thomas (1981) states that most Ciskeians live in
poverty and lack financial resources. Thus residents of
Thornhill have the same problems that the Ciskeians are
exposed to. These residents came from Glen Grey and Herschel
after the Transkei government took over in 1976. About
15,000 people left and were resettled in Thornhill. Some of
these people have been evicted from farm and urban areas

around this resettlement area.

95

This exodus from the Transkei seems to have been in
response to Transkeian repression of opposition groups. Also
because residents crf the Transkei had experienced severe
drought and unemployment, they had hoped that the
resettlement of 'Thornhill would offer them better 'living
conditions.

At the initial stage of the resettlement residents are
provided by the government with tin huts and basic food
rations. After a while, residents are expected to fend for
themselves and build a community as part of the Ciskei
homeland. The first and important hurdle is usually faced by
the breadwinners of these families. No consideration
whatsoever is usually given to the creation of employment
opportunities, services such as schools and clinics prior to
the resettlement of these families. The economically active
find themselves with no alternative but to become migrant
workers in urban areas.

The residents “of Thornhill, Sada, and Ntabethemba
resettlement areas comprise seven to eight percent of the
territory’s population, yet they have only one clinic which
has one doctor who visits twice a week. This clinic is run
for eight hours a day by nurses. According to Mare (1980) a
high incidence of psychosis particularly schizophrenia has
been reported in this area. This is attributed to the
depressing conditions under which residents of the

resettlement areas live.

96

White-owned Farms

An estimated 1.3 million black families live and work
on white owned farms. In 1980, the average wage for an
African farm worker was $28 to $40 per month. Farm workers
also receive pay in kind such as minimal housing facilities
and dietary staple food such as corn or mealie meal (South
African Fact Sheet, 1984).

Historically, whole families resided on the land of
white farmers who provided accommodation and some ground for
cultivation in exchange for the labor of all members of the
family as required. In many areas in the Orange Free State
and around Queenstown this system still operates and farm
children, who may or may not be provided with schooling, are
obliged to work in the fields weeding, harvesting, and
performing tasks like potato-picking.

Living conditions on the farm areas are very poor.
Workers including children are often housed in large
unfurnished sheds with no internal walls or beds. Families
live in corrugated iron huts. There may or may not be piped
water and there is in general a lack of sanitation.

In a survey conducted by the University of South Africa
on behalf of the Theron Commission in January and February
1975, Wilson et al. (1976) gave a full description of the
working and living conditions of laborers on the Karoo

farms. According to this survey, the average number of hours

97
worked by both black and colored employees is 53.8 per week.
Cash wages for blacks averaged $8.36 or $4.18 a week, cash
wages for coloreds were $9.77 or $5.36 a week. Workers also
received payments in kind. The main items supplied to
laborers were: meat, milk, clothing, medical care, grazing
rights, and rights to grow vegetables on a piece of land.

Almost all the laborers surveyed lived in farmer-built
houses of one to four rooms, built with brick, stone or
cement, with asbestos, zinc, tin, or corrugated iron roofs.
Floors were generally of cement, earth or dung. Only a few
houses had running water inside the house. Most black farm
laborers had to carry water from a distance of 30-100 meters
to the house. The average size of family was 5.02. About 75
percent of the workers who were interviewed had not been to
school at all. Reasons given for the lack of education were
that there were no schools on the farms, lack of money, or
lack of time.

In conclusion, farm life is characterized by what
Nasson (1984) labels as acute squalor, chronic poverty, and
almost total lack of alternative employment opportunities.
Farm laborers learn to be dependent on white farmers for
jobs, food, and housing. What makes this area seem worse off
than the other areas, namely the homeland and the
resettlement areas ‘Hs the isolation of farm laborers from
the mainstream culture. This is so because farms are usually

miles apart to ensure more grazing land or big acres for

98
growing crops. Thus, the world of farm laborers is
characterized by an intense and confining localism, a
crippling dependency, and encapsulation in poverty (Nasson,

1984).

511mm

These areas were included in the study because of their
homogeneity in terms of ethnicity i.e. Xhosa. They also have
common and diversified conditions imposed by the natural,
human constructed, and human behavioral environments. In the
original research proposal Soweto in Johannesburg was also
included, however, children from this area were left out due
to the political turmoil in urban areas of South Africa at

the time of this research.

Approval and Selection of Sample

An approval was obtained from the Ministries of
Education to enter the primary/elementary schools and work
with children who were included in the sample. A letter
explaining the purpose of the research and requesting an
approval to work in schools was sent by the researcher to
Ministries of Education in each area in March 1986 (see

letter in Appendix C).

99

No response was received by the researcher from the
Ministries of Education before leaving the United States.
Upon arrival in South Africa in June 1986, the researcher
visited ‘the different. inspectors’ offices in) follow-up on
the letters that were sent to the Ministries, and to request
written permission to enter the schools that were included
in the study. ‘

The researcher obtained a memo from each inspector’s
office giving permission to enter the schools and work with
the children. This permission was then taken by the
researcher to different school principals (see Memos in
Appendix D) in various areas of the homeland, resettlement,
and farm areas.

Upon arrival at each school the researcher was
introduced by the principal to the class teacher(s). A brief
description of the purpose of the study was given to both
the principal and teachers by the researcher. During this
session the time and room in which the testing was going to
take place were established. The researcher was then given
the class register from which the sample was drawn. The
drawing of the sample was done at school. The permission was
given on the condition that the class register was not to be
taken out of school premises.

A systematic sampling technique was used to select the

sample. As stated by Babbie (1979) in systematic sampling,

100

every Kth element in the total list is chosen for inclusion
in the sample. The first step was to select four schools
from the homeland area. These schools were selected from a
list of all primary/elementary schools in this area, using
the systematic sampling technique. The list in the homelands
consisted of thirty schools. Using the systematic sampling
technique, every 10th school was included in the sample.
Because of a linfited number of schools on the farm and in
the resettlement areas, the sample was drawn from all the
schools in these areas. Both these areas have four schools.

From each of these schools an enrollment register for
all the children ages 5-6 years was obtained to select the
sample. The list consisted of approximately 70-80 children
in each class. Twenty five children were selected from each
class to make up a total of one hundred children needed for
the sample from each area. Every 10th child was included in
the sample.

To ensure against any possible bias in using this
technique, the first child was chosen at random. Following
that every 10th child was included in the sample. This
technique ascertains the representativeness of the sample
and allows the investigator in) make extrapolations about
black children ages 5-6 in South Africa from this particular
ethnic group in these particular ecological areas.

After the selection procedure was completed, children

who were chosen for the sample were given a letter

101
explaining the purpose of the research and a: consent form
for the parents. This form was to be filled out and returned
the next day to school by the child. In most cases the
consent form was filled out and returned to school the next
day. However, in a few cases the researcher had to make home
visits to explain the purpose of the study to

parents/guardians and request their approval.

Research Instruments

The following are the instruments and measurement
techniques used in this research: the Junior South African
Individual Scale, Brown-IDS-Self-Concept Referents Test,
anthropometric measures for height, weight, and head
circumference, and the parent’s questionnaire.

The Junior South African Individual Scale (JSAIS) was
used as a measure of cognitive development. This scale gives
a profile of intellectual development for children between 3
and 7 years. For the purpose of this study, three areas of
cognitive development were covered. These were verbal,
numerical, and performance. The following sub-tests

correspond with these areas: vocabulary, number and quantity

concepts, and copying.

102

The following section will give a: brief statement of
the content, aim, and rationale for the use of each sub-
test.

Vocabulary: This sub-test consists of thirty four black
and white cards with four pictures on each. The testee
chooses the picture that goes best with an object, action,
quality, or characteristics named by the tester. The child
points to or marks with an "X" a picture on a card to
indicate his/her answer. This subtest. is similar in) the
traditional picture vocabulary tests for children.

The aim of this test is to measure recognition,
comprehension, identification, and interpretation of verbal
symbols. It involves specific processes and functions:
retrieval of associations or general information from
memory; the eduction of identities or similarities between a
verbal stimulus and a picture stimulus; the differentiation
of parts of a visual stimulus and the reinterpretation of a
possible ambiguous item.

This sub-test is based on the assumption that a
testee’s comprehension of a word can be determined by the
identification of pictorial representation of a word. In
thts way the child demonstrates the ability to understand
spoken language which precedes active language usage.
Considerable empirical proof exists for the validity of

using picture vocabulary tests to measure general

103

intelligence. Similar tests (for example, the Peabody
Picture Vocabulary Test PPVT) are often used to obtain a
rough indication of intelligence. According to Madge (1981)
a vocabulary test is also sensitive to neurological deficit
and psychological disturbance. Thus, such a sub-test could
be used as one measure of the adverse conditions on
cognitive development (see copy of the vocabulary test in
Appendix A).

Number and Quantity Concepts: This sub-test consists of
two parts, namely, parts A and 8. Part A comprises 31 items,
six of these items test the child’s ability to count,
sixteen items concern quantity concepts (for example,
fullness, length, mass, and quantity), and nine items deal
with simple concrete calculations such as, addition,
subtraction, division, and simple fractions. The child
points to or marks with an "X” a picture on a card to
indicate his/her answer. Part 8 consists of 15 mental
arithmetic problems which are presented and answered orally.
Part 8 is intended for 6 and 7 year old children only.
Thus, this section was not appropriate for the sample of 5
and 6 year old children included in this study, hence it was
left out.

The aim of Part l\ is to measure understanding‘ and
manipulation of quantitative material in a relatively
concrete way. The specific processes and functions involved

are: counting ability, ability to apply basic mathematical

104
processes, evaluation of quantity, size, length, fullness,
comprehension of relational items, spatial ordering, and
relatively concrete mathematical reasoning ability.

This test is based on the assumption that the
comprehension of numbers, quantity, and the ability to
manipulate number concepts constitute important facets of
the child’s ability to function adequately in school and in
other life situations. To some extent this test is based on
Piaget’s theory of cognitive development which holds that
concepts of quantity begin to develop at about five to seven
years. At this age the child begins to differentiate
quantity and fullness, size and fullness, and length and
fullness. Approximately half of the items in Part A are
based on this differentiation of the concepts of quantity.

Since mental alertness is a prerequisite for meaningful
manipulation and understanding of numbers, this subtest was
considered an appropriate measure of the impact of adverse
environmental conditions on cognitive development (see copy
of number and quantity concepts in Appendix A).

Copying: This test consists of 12 items. The testee is
presented with a booklet with geometrical figures. He/she is
required to copy figures from the example presented. The
figures to be copied comprise simple figures such as a
circle, square, or triangle, sometimes they comprise a

configuration of two adjacent figures. This sub-test

105
measures the ability to reproduce correctly a design
presented visually. The following more specific skills are
supposed to be involved: hand-eye coordination, perceptual
ability, comprehension of spatial relations, and visual-
motor organizational ability.

This sub-test is based on the assumption that smaller
children are inclined to perceive a figure globally in
contrast with older children who take details into account.
Perception of the whole is adequate for most simple tasks
involving fitting. The process of copying figures demands
perception of every detail and the organization of the parts
into the whole. According to the literature a good
performance in copying figures is significantly related to
scholastic achievement.

Wechsler (1967) points out that scores in this type of
test positively correlate (in the particular ages) with the
scores in other measures of intelligence. He is of the
opinion that correctness of a! response depends primarily
upon perceptual and visual-motor organization, the
development of which is closely 'tied to increasing
chronological age. Since copying requires some degree tof
concentration, this sub-test was considered appropriate in
this study (see copy of copying in Appendix A).

The JSAIS is standardized for 3 to 7 year old children.
It was standardized in English on a sample of 1795 white and

black children from South Africa. The sample was selected

106

based on the following criteria: age of the child, gender,
socio-economic background, and attendance at a preschool or
a primary school. The reliability is .63 for vocabulary, .60
for number and quantity skills, and .80 for copying. For the
purpose of this study a Xhosa version was used. This test
was translated by the researcher and the research assistants
at the National Institute for Personnel Research.

Brown-IDS-Self-Concept Referents Test: The self-concept
test as a measure of social-emotional development was chosen
because it is appropriate for early elementary children
(Goodwin and Driscoll, 1980). This test does not require
children to read or write, rather the descriptions and
directions are read by the interviewer to children. The
stimulus is a Polaroid picture of the child that is taken by
the researcher before the interview. The interviewer sits
with the child at the table with each child’s picture and
goes through a list of 14 items which describe what the
child thinks about him/herself as he/she sees him/herself on
the picture. These items were translated by the researcher
and the research assistants into Xhosa which is the language
spoken by these children. After the child’s response the
interviewer marks his/her answer on the answer sheet (see
Appendix A for a scoring sheet for Brown-IDS- Self-Concept
Referents Test).

This test is normed on a population of 2866 American

children from different ethnic groups. Their age ranges from

107

5-8 years. The reliability for this test is .71 for lower
class blacks, .76 for middle class white children, and .55
for K-lst grade. Although this test is not standardized for
black South African children, it might yield valuable
results as cmmparisons are done among black children from
the Xhosa ethnic group only and run: among children from
different ethnic groups.

Anthropometric Measures: The anthropometric measures of
height, weight, and head circumference were chosen for this
study because of their acceptability by researchers in
general for measuring physical growth and the ease with
which data could be collected. A bathroom scale was used to
measure weight. For height and head circumference an
anthropometer and a tape measure were used. All these
instruments are in the metric system. Measures such as
skinfold thickness which were included in the proposal were
left out because of the difficulty to use the instruments to
measure skinfolds and the unavailability' of special
equipment such as callipers. The National Center for Health
Statistics (NCHS) charts were used as a suitable reference
standard against which children’s growth was checked (see
copy of the NCHS norms for ages 5-6 in Appendix A). The
anthropometric measures of height for age, weight for age,
and head circumference were used to assess the physical

growth of children.

108

As stated by Fincham (1982) there is a consensus among
researchers and medical practitioners in South Africa that
international norms such as the NCHS are at present the only
acceptable standards against which the nutritional
conditions of children in South Africa should be evaluated.
These norms are recently compiled from 1963-1975 and are
representative samples comprising some 20,000 children from
different racial groups in the United States. These are
internationally accepted norms and are likely to replace the
Boston norms which were widely used in South Africa.

The child’s family and home environment information was
obtained by a parent’s questionnaire designed by the
investigator (see parent questionnaire in Appendix A). The
parent questionnaire was also translated by the researcher
and assistants into Xhosa a language spoken by the

respondents.
Data Collection Procedures

Data collection was begun on June 17 and ended on
August 30, 1986. The researcher and two research assistants
were trained in! a psychologist from the testing center of
the Human Science Research Council, Pretoria, South Africa
in the use (H’ the JSAIS. The training sessions took three
days at the National Institute for Personnel Research (NIPR)

in Johannesburg, South Africa.

109

The research assistants had both graduated from the
University of Fort Hare, South Africa. One of the assistants
majored in psychology and sociology, the other majored in
social work and anthropology. They were chosen because they
had previously worked with the researcher on a different
project in the homeland of the Ciskei.

After the Brown-IDS-Self—Concept Referents Test and the
parent questionnaire were translated, the questionnaire was
pilot tested with a group of parents and the self-concept
test was pilot tested with a group of children whose socio-
economic status is similar to the sample being studied. The
researcher, who received training in the use of
anthropometric techniques at Michigan State University in
Summer of 1984, trained the research assistants in the use
of this technique.

After receiving written approval regarding schools to
visit and informed consent from the parents whose children
were in the sample, the team began testing in one school at
a time. Working as a team in each school was preferred to
working individually for many reasons. For example, only one
car was rented for the research, so working in a team
eliminated the many stops that would have been costly in
terms of time and money. The investigator could help the
research assistants if there were problems; this might not

have been possible if each researcher worked in one school.

110

This method also had an advantage of distributing work
among the researchers. It also proved to be efficient in
terms of time. For example, while one researcher helped the
children undress, stand in the line, and get onto the scale,
another one took the measurements for weight, height, and
finally head circumference. The assessor would call these
measurements to the third person who recorded the
measurements. A similar team approach procedure was also
used for assessing the child’s self-concept. For example,
one person took the photographs while the other two
interviewed children. Also in a country that is politically
unstable working in a team was preferred for safety reasons.

The first area in which testing took place was Herschel
in the homeland of the Transkei. This area was chosen as the
first area because this is where the researcher was born and
raised. She also attended one oi: the primary/elementary
schools. Therefore entry Was not expected to be a problem.
The second area to be visited was Thornhill in the
resettlement of the Cfiskei. The researcher’s brother is a
principal in one of the schools in this resettlement. The
last area to be visited were the white-owned farms around
Queenstown and in the Orange Free State.

The measurements for height, weight, and head
circumference and the assessment for cognitive, and social-

emotional development were carried out at school. This took

111

place during school hours or after school in some cases in a
classroom separate from their own. Testing was done with a
group of 10-15 children at a time except for the self-
concept test. For this test interviews were done with one
child at a time after the measurements for physical growth
and assessment for cognitive development. The measurements
for height, weight, and head circumference were taken for
each child one at :3 time. Because it was winter in South
Africa at the time of this data collection, children were
weighed with their clothes on except for heavy sweaters,
coats, and shoes. Each testing session including
anthropometric measurements took 60-90 minutes.

The duration for testing did not prove too long nor too
tiring for these children because different activities were
done during the session. For example, measurements for
weight, height, and head circumference which took about 30
minutes for a group of 15 children were taken first. The
same group was then given the verbal, the quantitative
concept, and the copying tests which took about 30-40
minutes. After these tests a photograph of each child was
taken followed by an interview which took about 10 minutes
for each child. Each child was given his/her photograph as a
souvenir. Children were then thanked for their cooperation.
As a token of appreciation candy and punch were offered to

children who participated in the research. Although candy

112
does not have nutrients, it was offered to children because
it was not costly and would be appealing to young children.

To administer the parent questionnaire, parents whose
children were tested were asked to come to school. The
questionnaire was administered by all the researchers to one
parent at a time. It took about 15 minutes to administer the
questionnaire. For parents who could not come in) school
because of work or for other reasons, the researchers made
after school or evening home visits.

Parents who participated in the study were thanked for
their time, especially parents from white-owned farms who
were interviewed either during their lunch break or in the
evenings. All parents received a box of cookies and two
liters of orange juice or punch as a token of appreciation.
This was served at school or brought to the home by the

researcher in some cases.

Methods used for Data Analysis

The statistical procedures used in) test differences
between the categorical variables included the chi square
test and the multivariate analysis of variance (MANOVA) for
the categorical and the continuous variables. The MANOVA was

followed by Tukey’s test to see if the differences between

113
the categorical and the children’s measures of self-
concept, cognitive development, and physical growth were
statistically significant. The alpha level was set at .05.
To obtain the correlation between the children’s measures

Pearson Coefficient Correlation was used.

Ethical Consideration

A major consideration of this study concerned the
informed consent of the parents/guardians and their children
who were involved. A letter describing the purpose of the
study was sent to the parents/guardians and the school
administrators (see letters in Appendix C). To get an
informed consent parents/guardians filled out a form (see
informed consent form in Appendix C). These were both used
to ascertain that the purpose of the study was understood
and that the involvement of the subjects was done
voluntarily without any persuasion (H‘ any deception. This
information was considered important to both the parents and
school authorities who in a politically unstable country
view ’outsiders’ with apprehension and suspicion.

A second ethical iSsue involved the protection of
parents/guardians and the children against any physical and
psychological harm. For example, the subjects were not

harassed or intimidated if they made mistakes or if they

114
chose not to answer a question. No fear and no anxiety were
induced in the subjects for any reasons.

The third ethical consideration concerned the
protection of the subjects’ identity. In keeping with the
ethical code of confidentiality after the interviews and
testing were completed, parents’/guardians’ and children’s
names were replaced by identification numbers. Anonymity was
easily maintained especially because the study was not
focusing (Hi the child’s specific individual behavioral and
physical growth, rather (H1 black children 'hi South Africa
from the Xhosa group.

The fourth consideration for this study concerned the
maintenance of objectivity and guarding against biases.
Because of the nature of sample selection a bias was
introduced. For example, only school children were included
in the sample because of time constraints and the ease of
access to the schools. The "invisible" children who are
equally malnourished, sick, or who might be working on
white-owned farms and may not be attending school were not
included in the sample.

Only parents/guardians and children from the Xhosa
ethnic group were included in the sample. This is also the
ethnic group from which the researchers come. These
geographical areas were included because the researcher is
(familiar with the culture of the groups found in these areas

and because the language would not be a problem. On the

115
other hand if other ethnic groups were included, there would
have been a need for interpreters. This would have been a
problem in terms of ascertaining validity and would have
been also costly in terms of time and money.

Finally, the researcher had to make sure that promises
were not made that could not be fulfilled. For example, in
all the areas which were visited the researcher was viewed
as a "Messiah who was coming to redeem sinners". After the
introduction was made all parents were ‘willing to .share
information with the researcher, even neighbors who were not
involved in the study were willing to give information as
long as this would help change "the plight of black families
in our country", one woman added.

The willingness to share information with the
researchers showed how desperate these families were to
discuss their living conditions and that they would do
anything, even talk with ’strangers’. This also may be an
indication that some of the black families in the rural
areas have become more aware of the policy of apartheid and
are prepared to make a contribution towards change. In spite
of the willingness to share information with the researcher,
only those who were included in the study were interviewed.

A brief explanation of the purpose of the study was
made to those who were not included in the study. They were

also told that the researcher might on her return to South

116
Africa work with families in the rural areas on different
projects. No promises were made to anyone whether or not

involved in the study.

CHAPTER V

DATA ANALYSIS AND FINDINGS ON FAMILY
BACKGROUND INFORMATION

This chapter summarizes the family background
information findings which include: area of residence,
socio-economic status, type of family structure, home
environment, and family mobility.

Demographic characteristics of families were obtained
by a parent questionnaire which was administered to the
parents/guardians whose children were in the sample. The
first step was to obtain a percentage of respondents for
each category of variables. The second step was to obtain a
breakdown of the following variables: area of residence by
marital status, educational and occupational levels of the
parent/guardian; marital status by the occupational levels;
as well as the level of education by the occupational level
of the respondents. A chi square test was used to see
whether ~the relationships between these categorical

variables were significant.

117

118

Findings on Parent/Guardian Information

The total number of parents/guardians who were
interviewed was three hundred. One hundred of these were
from each of the three areas from ‘which the sample was
drawn. These were the homeland, resettlement, and the farm
areas. Thirty two percent of the respondents were males and
68% were females. Their mean age was 42.20 and the standard
deviation was 8.32. The range of their age was 24-62.

A breakdown of the respondent’s age by area of
residence shows that the sample from the homeland represents
a mean age of 39.83, the sample from the resettlement area
represents a mean age of 42.77, and the sample from the farm
areas represents a mean age of 43.99.

This finding suggests that parents in the homeland were
younger than parents in the resettlement or farm areas. A
few of the respondents in the resettlement and farm areas
were grandparents who were taking care of children while
parents were working in urban or on white-owned farms.

The majority (65%) of the respondents were married or
married but not living with a spouse at the time of this
research. Less than one third of the parents/guardians (32%)

were never married and a small percentage (3.3%) was widowed

or divorced (Table 1).

119
Table 1

Resoondents’ Marital Status

 

 

 

Marital Status Number Percentage
Married 103 34.3
Never Married 95 31.7
Married no spouse present 92 30.7
Widowed 6 2.0
Divorced 4 1.3
Total 300 100.0

 

Area of Residence and the Marital Status

A breakdown of the area of residence by marital status
shows a relationship between the area of residence and
marital status. The chi square was found indicating a
significant relationship at p< .05 level between the area of
residence and marital status.

As shown in Table 2 the homeland had the highest
percentage (78%) of marriages both with the spouse living at
home and with no spouse living at home. The farm area had a

higher percentage (37%) of marriages with a spouse living at

120
home than the resettlement areas. However, the resettlement
area compared with the farm area had a higher percentage
(33%) of marriages with no spouse living at home. The
resettlement area also shows a higher percentage (40%) of
unmarried respondents than the homeland and the farm areas.
The divorced and widowed categories show a higher percentage
(7%) in the farm areas than in the homeland and in the

resettlement area.

Table 2

Contingency Table: Area of Residence by Marital Status

 

 

Residence Marital Status
M. M. no spouse N. M. D&W Total
% % % %
Farm 37 22 34 7 100
Homeland 41 37 21 1 100
Resettlement 25 , 33 4O 2 100

 

Chi Square . 20.13 with df=6

* p<.05 level

These findings suggest that the pattern of marital

status differs from residence to residence. All the three

' 121

areas show a different pattern of marital status. The high
rate of marriages with or without a spouse living at home in
the homeland could be attributed to the fact that the
homeland communities are more stable than the resettlement
and the farm areas. Data from this study indicate that more
than half (63%) of residents in the homeland had never
moved. More than a third (37%) of residents in the farm area
had never moved, and only a small percentage (8%) of
residents in the resettlement areas had never moved. These
findings suggest the highest rate of family mobility in the
resettlement area and the lowest rate of family mobility in
the homeland.

Because of a feeling of stability and a sense of
belongingness the homeland communities might have
established values and mores that are cherished by the group
as a whole. Thus marriage could be viewed in these
communities: as one of the societal institutions that is
valued. However, the high percentage of marriages with no
spouse at home in the homeland and the resettlement areas
suggests that residents from these areas leave the homelands
and the resettlement areas to seek jobs in urban areas or on
white-owned farms in other cases.

The resettlement area showed the lowest percentage of
marriages with the spouse living at home and the highest
percentage of unwed mothers. Some of the residents of this

area have been forcibly removed by the government of South

122
Africa from areas designated for whites, others have been
forcibly removed from other homelands when a different
homeland government took over. Families are usually
.separated when men or women remain working in urban or farm
areas, or when other members of the family decide to remain
in the homeland.

Residents in the resettlement area are flung into
situations where they are all strangers. They have to start
building a new community. These areas also lack
opportunities for employment, the land is dry and infertile
for farming and for carrying out agricultural activities.
Families thus suffer material deprivation, as well as
pyschological deprivation. As one woman stated during the
visit to the resettlement of Thornhill, "it would be better
to live in hell rather than live in the resettlement areas".

Because residents in the resettlement area are highly
mobile and reflect little stability they may not have
established values that are cherished by the community as a
whole. Marriage might thus not be valued by the residents in
this area hence there exists a higher percentage of
repondents who had children out of wedlock. Evidence from
this study shows that these are some of the children who are
often malnourished, and who suffer from other preventable
diseases.

In the farm areas it is usually a requirement that the

husband, wife, and children live and work on white-owned

123
farms. This arrangement is reinforced by farmers. This is
encouraged to ensure family stability which presumably
increases job morale and high productivity and lowers the
rate of hiring and firing. As stated by Ndaba (1984) white
farmers will go to extremes to retain a stable work force.
For example, farmers may even encourage single male workers
to form relationships with women who work on the farms.
These relationships often end up in marriages. However, in
the farm area the divorced and widowed category has more
cases reported than in the resettlement or homeland areas.

But this is a very small percentage (7%) of respondents.

Educational Level of Parents/Guardians

Data in Table 3 indicate that 66.6% of the respondents
had six or less years of education. Twenty nine percent of
the respondents had a: junior secondary school certificate
and high school diploma. The lowest percentage (4%) of the
respondents had a bachelor’s degree.

This finding indicates that about two-thirds of the
adult respondents in this study had six or less years of
education. Approximately one third of the respondents had a
junior secondary school certificate, a high school diploma,

or a bachelor’s degree.

124

Table 3
Educational Levelaof-the Resoondents

 

 

 

Level of Education Number Percentage
<6 years 94 31.3
6 years 106 35.3
Jr. Sec. Sch. 45 15.1
High School 43 14.3
Bachelor’s 12 4.0
Total N 300 100.0

 

Area of Residence by Level of Education

The relationship between the area of residence and the
level of education is indicated by a significant
relationship at p< .05 level. Data in Table 4 indicate that
the farm areas had the highest percentage (82%) of
respondents with six or less years of education. The
resettlement had 65% of residents with six or less years of
education. The homeland had 53% of residents with six or

less years of education. All the three areas had about

125
equal respondents with a junior secondary school
certificate. All the areas had respondents with a high
school diploma. The homeland had 20%, the resettlement area
had 19%, and the farm areas had the lowest percentage (4%).

Only the homeland had respondents with a bachelor’s degree.

Table 4

Contingency Table: Area of Residence by Level of Education

 

 

Residence Level of Education
<6yrs 6yrs JSS HS BA Total
% % % % %
Farm 51 31 14 4 0 100
Homeland 23 30 15 20 12 100
Resettl. 20 45 16 19 0 100

 

Chi Square . 57.98 with df=8

* p<.05 level

Data from this study indicate that all of the
respondents with a bachelor’s degree lived in the homeland
and 20% of the homeland respondents had a high school
diploma. This finding suggests that education in the

homeland might be viewed by parents as a means to improving

126
the quality of life. Education in the homeland is thus
viewed as important for adults. For example, two of the
respondents who had' a bachelor’s degree 'hi the homeland
reported that they were enrolled in a master’s program at
the time of this research.

In the resettlement area 19% of the respondents had a
high school diploma. Residents of the resettlement areas, as
was mentioned earlier, were removed either from an urban
area, a different homeland, or farm areas during the late
705 and the early 805. The process of eviction and forced
removals still continues in the late 80$. Residents in the
resettlement area showed levels of education that were more
or less equal to the levels found in the homeland, however,
no one from this area had a bachelor’s degree. Thus
residents in the resettlement area might have acquired this
level of education prior to being resettled. According to
personal communication with respondents a few of the
respondents from this area were also studying by
correspondence at the time of this research.

Data from farm laborers show that they have the least
amount of formal education. One reason could be attributed
to a: lack of schools for blacks in the farm areas. White
farm owners make a decision as to the number of schools that
are required for their employees as well as the number of

teachers that are employed by the school, the type and size

127
of the building, and the kinds and amounts of school
equipment necessary for the education of blacks.

For example, in one of the farm areas that was visited
by the research team, the building that was used as a school
was a dilapidated house that formally belonged to the
farmer. The classrooms in this school were unusually small
as these were living space rooms for the farmer’s family.
Four schools for black children in the farm areas were
included in the study. Each classroom in these schools had
about 50-70 children. The school equipment, such as tables
and desks, was broken and in poor condition; the windows
were broken and unattended to.

The highest level of education that the farm residents
can usually achieve is standard four (the equivalent of the
sixth grade in the United States). Many are required to work
on the farm after completing standard four. One parent
mentioned that sometimes parents send their children to live
with friends or relatives in the homelands in order for
their children to get a higher level of education. Such an
arrangement is sometimes made with daughters whose services
are not as important on the farms. Young men have little
opportunity for this type of arrangement.

Nasson (1984) writing on the farm schooling for black
South Africans has explored several reasons for the lack of
schools on the farm areas. He states that formal schooling

is not considered relevant by most farmers when hiring farm

128
workers. White farm owners are in general indifferent
towards schooling and 'very .suspicious of schooling. They
think that the possession of too much education is dangerous
and would lead in) capricious behavior that would threaten
the farmer’s future labor. The type of education that white
farm owners consider appropriate for their laborers is that
which enables farm laborers to understand instructions from
the master and from the master’s wife. One could conclude
from Nasson’s (1984) statements that the type of education
that farm owners promote for their farm laborers is one

which makes farm laborers subservient and obedient servants.

Occupational Level of Parents/Guardians

Slightly more than half (53%) of the
parents/guardians who answered the questionnaire for this
study had no jobs at the time of this research. Of those who
were employed, 27% were in menial and unskilled jobs.-About
20% of the respondents were employed in semi-skilled,

skilled, or semi-professional positions.

129
Table 5

Employment and Unemployment Rates

 

 

 

Employment Number Percentage
None - 158 52.7
Menial 51 17.0
Unskilled 30 10.0
Semi-skilled 17 5.7
Skilled 16 5.3
Semi-professional 28 9.3
Total N 300 100.0

 

Area of Residence and the Level of Occapation

A breakdown of the area of residence by the level of
occupation shows a significant relationship at p< .05 level.
Data in Table 6 indicate that the resettlement area had the
highest percentage (62%) (H’ residents without employment.
The homeland had 50% of residents without employment, and
the farm areas had the lowest percentage (46%) of residents
who were unemployed at the time of this research.

A higher percentage (51%) of farm laborers were

employed in menial and unskilled jobs than were the

130
residents from the homeland and the resettlement areas. A
small percentage (3%) of farm ‘laborers were employed in
semi-skilled jobs. No one from the farm area was employed in
skilled or semi-professional positions.

The results suggest that farm laborers in": had the
least level of education were more likely to be employed in
menial and unskilled jobs. On the other hand although the
homeland and resettlement residents showed the highest
levels of education, the residents of these areas had a
higher rate of unemployment than the farm areas, with the
resettlement area showing the highest rates.

In the homeland and the resettlement areas respondents
were distributed from menial to semi-professional positions.
Only residents from the homeland and the resettlement areas
were employed in skilled and semi-professional positions.
However, a higher percentage (18%) of workers in semi-
professional positions were in the homeland. In the
resettlement area there were only 10% of residents working
in semi-professional positions.

The high rate of unemployment in both these areas
suggests that education is not a factor in determining
whether residents in these areas will be employed or not,
rather the area of residence in which one lives is a related
factor. For example, farm areas have the highest rates of

employment, yet farm laborers are the least educated.

131

These results also suggest that the homelands and the
resettlement areas lack opportunities for employment. The
resettlement area seems worse off compared to the homeland
in terms of job opportunities. Previous data indicate that
in the homeland and the resettlement areas there were higher
percentages of respondents who were married, but not living
with a spouse than in the farm areas. A hypothesis is that
these individuals might be some of the men or women who

leave these areas to seek work in urban areas.

Table 6

Contingency Table: Area of Residence by OCCUpational Level

 

Residence Occupational Level

 

None Menial Unskill S.S. Skilled Semi-Prof

% % % % % %
Farm 46 35 16 3 0 0
Homeland 50 13 4 7 8 18
Resettl. 62 3 10 7 8 10

 

Chi Square a 69.44 with df=8
* p<.05 level

132

Marital Status and the Occupational Level of the

Respondents

Although the findings of the relations between marital

status and the occupational level of the respondents do not

show a significant relationship,

individuals in the category of married and married but not

a look at the numbers of

living with the spouse have more people who work in semi-

skilled, skilled,

who are not married and who are divorced or widowed

(Table 7).

Table 7

Contingency Table: Marital Status by Occupational Level

or semi-professional positions than those

 

Marital Status

Occupational Level

 

None Menial

n % n %
M . 44 28 14 28
M.S. 53 34 19 37
N.M. 54 34 15 29
D&W 7 4 3 6

Unskill
n %
10 33
8 27
12 40
0

O‘Nto

S.S
%
52
ll
35
0

Skilled
n %
8 50
4 25
4 25

0

S.Prof.
n %
18 70
6 20
4 10

0

 

Chi Square a 26.35 with df=12

not significant

133
Level of Education and the Occupational Level of

Resoondents

A significant relationship at the p< .05 level exists
between the level of education and the occupational level of
parents/guardians (Table 8). For example, 83% of those with
less than six years of education were unemployed and 17%
were in menial jobs. No one with less than six years of
education reported that he/she was employed in any other
occupational level. Of those with six years of education 61%
were unemployed, 18% were in menial jobs, 15% were in
unskilled jobs, and 6% were in semi-skilled positions. No
one ‘Hl this category was 'hi skilled (H‘ semi-professional
occupations. 0f the respondents with a junior secondary
school certificate there was a distribution in all job
levels. Twenty nine of the respondents with a junior
secondary certificate were unemployed. Thirty one percent
were in menial jobs and the rest were in unskilled, semi—
skilled, skilled, and semi-professional levels. Those with a
high school diploma only 5% were unemployed and 5% were in
menial jobs. Twelve percent were in unskilled jobs and 14%
were in semi-skilled jobs. Twenty one percent were in
skilled positions, and 43% were in semi-professional
positions. Of those with a bachelor’s degree all were
employed in semi-skilled, skilled, and semi-professional

positions. A higher percentage (58%) was employed in semi-

134
professional positions and a lower percentage (42%) was in
semi-skilled and skilled positions. No one in this
educational category was unemployed or employed in menial or

unskilled jobs.

Table 8

Contingency Table: Level of Education by OCCUDational Level

 

 

Education Occupation

 

None Menial Unskill S.S. Skilled S. Prof

n % n % n % n % n % n %
<6 yrs 78 83 16 17 0 0 0 O
6 yrs 65 61 19 18 16 15 6 6 O 0
J85 13 29 14 31 9 20 3 7 4 9 2 4
HS 2 5 2 5 5 12 6 14 9 21 19 43
BA 0 O 0 2 17 3 25 7 58

 

Chi Square - 241.93 with df-16
* p<.05 level

The data indicate that higher education in the homeland
and in the resettlement areas is related to employment in
semi-skilled, skilled, and semi-professional positions.
Residents 'hi these areas were distributed throughout ‘the

categories from menial to semi-professional. However, most

135
respondents were working in semi-skilled, skilled, and semi-
professional positions. The farm residents were ‘mostly
employed in menial and unskilled occupations, here there was
no need for a higher education. Thus it would seem from this
finding that the level of education is not the only factor
that determines whether residents are employed or not,
rather the area of residence seems to be another important

factor determining one’s employment.
Other Source of Income

In an effort to verify whether parents/guardians had
other sources of family income, they were asked whether they
had only their wage, were supplemented with the wage of
others, or were paid in kind. Forty eight percent of all the
respondents who were interviewed had only their own wages as
the major source of family income whereas 52% did not have
only their own wage as a source of income. Of this group 36%
of the respondents were paid in kind and 64% were not paid
in kind. For further clarification respondents who reported
that they were paid in kind were asked what they received as
pay in kind.

Items that were considered in the questionnaire as
payment in kind included: food supplies, blankets and other
material supplies, cattle, and sheep. Of those who were paid

in kind only a small percentage (10%) were given food

136
supplies, about one fourth (27%) cattle, and (27%) sheep.

No one received blankets and material supplies (Table 9).

Table 9

Items Given as Pay in Kind

 

 

Pay in kind Yes No

n % n %
Cattle 82 27.3 218 72.7
Sheep 82 27.3 218 72.7
Food 30 10.0 270 90.0

 

Data indicate that more than half (52%) of the
respondents in this study depended on the wages of others
for added source of nmdor income. These were some of the
homeland and resettlement residents who may have had family
members who worked in urban areas. Farm laborers were those
who reported that they depended on the wage of others as
well as pay in kind which included food, cattle, and sheep.
They also reported that they were offered housing as a
fringe benefit.

A breakdown of pay in kind by the area of residence
shows that in the homeland and the resettlement areas no one

was given food, cattle, and sheep as pay in kind. Only farm

137
laborers reported that they were offered these items by

their employers.

These are some of the methods which white farm owners
use to make life on the farm areas more attractive to farm
laborers, so as to deter farm laborers from looking for
alternative jobs 'hi urban (n: other areas. Offering meager
wages, food supplies, and shelter to hungry persons
increases the farm laborers’ dependency on the farmer and
instills in these black families who work on white-owned
farms a sense of security, thereby, limiting the
possibilities of searching for alternative opportunities.

This idea is ‘consistent with Maslow’s theory of
motivation (Crain 1980). According to this theory, there are
six kinds (Hi needs: physiological, safety, belongingness,
love, self-esteem, and at the highest level are the self-
actualization needs. These needs are arranged in a
hierarchical order, such that the fulfillment of lower needs
propels the individual to the next highest level. For
example, a person who has a strong physiological need such
as hunger and a need for shelter will not be easily
motivated by other needs because his/her mind revolves
around the need for food and shelter. However, when this
need is satisfied he/she will move on to the next levels.
Farm laborers as well as most blacks in South Africa are at
the lowest level of Maslow’s hierarchy because. of

inequalities in the distribution of resources.

138

Home Environment

Included under this category were the following: the
structure of the house, house ownership, the number of
bedrooms in the house, household size, and the general
condition of the house as perceived and reported by the

parent/guardian.

TI 5! l E II N I Q I'

All of the respondents’ houses were built with either
bricks, mud, or corrugated tin. Thirteen percent of 'the
respondents lived in houses built with bricks, 72% had
houses built with mud, and 15% had houses built with tin.
Most of the houses built with bricks were in the homeland.
Most of the houses built with tin were in the resettlement
area, the rest of the houses in this area were built with
mud. In the farm areas most of the houses were built with
mud.

Based (Hi the findings, the resettlement area had the
worst quality of building material for tin is a poor
insulator in areas of changing temperatures. As one of the
respondents from the resettlement area stated, "these houses
are not only small, but they are also not meant for people
to live in. These houses are very cold to live in during the

winter months and very hot in summer".

139
Seventy two percent oir all the respondents reported
that they owned their houses and 28% rented or did not own
their houses. Ownership of the house was reported by
residents of the homeland and the resettlement areas. Those
who did not own their houses lived in houses provided by

white farm owners as a fringe benefit.
Rooms in the House

Data as shown in Table 10 indicate that more than half
of the respondents lived in a one room house. Less than half
of the respondents had two rooms, and a smaller percentage

(11%) had three or four rooms.

Table 10

Number of Room;

 

 

Rooms Number Percentage
One 157 52.3
Two 110 36.7
Three 28 9.3
Four 5 1.7

 

Total 300 100.0

 

140

A breakdown of the number of rooms by area of residence
shows that the homeland had a wider range of accessibility
to rooms than the other areas. Most families in the
resettlement and the farm areas had only one room in their
houses. In one room houses within the resettlement and farm
areas the room was used for sleeping, cooking, and for
dining. These were also the areas with the highest number of
people living in a household. Thus, the results of this
study suggest that children from the resettlement and the
farm areas often live in overcrowded homes with only one
room.

The shortage of houses and the problem of overcrowding
among blacks in South Africa has been investigated in recent
years. For example, Disler and Oliver (1984) gave an
estimation of the shortage of houses in both the urban and
the rural areas. According to these authors, in 1981 there
was a shortage of 160,000 housing units in urban areas and
260,000 housing units in the rural areas of South Africa.

This shortage inevitably results in overcrowding. For
example, up to 17 people were found living in a four room
house in Soweto, Johannesburg (Disler and Oliver, 1984).

These rooms include two bedrooms, a kitchen, and a living

TOOTH.

141

Household Size

To assess the level of crowdedness that might be found
in households parents/guardians were asked the question; how
many people lived in the household? The mean number of
people found living in the household was 7.55, the standard
deviation was 2.68. The range 'hi households was from 2
persons up to 12 individuals.

A breakdown of the area of residence by the number of
people living in the household indicates that the mean
number of pe0ple living in the household in the resettlement
area is 8.35, in the homeland is 7.31, and in the farm areas
is 6.98. Table 11 show the one-way ANOVA used to obtain the
difference between the three areas. If the one-way ANOVA was
significant it was followed by a Tukey’s test to find where
these differences occurred .

The Tukey’s test indicates a significant difference
between the number of people living in the household in the
resettlement, homeland, and the farm areas. There is no
significant difference between the homeland and the 'farm
areas. These findings suggest that more people live in the

household in the resettlement areas than in the homeland and

in the farm areas.

142
.Table 11
Analysis of Variance of the Number of People in the

Household by Residence

 

 

Variable Source OF SS MS F

People Between' 2 102.25 51.12. 7
Within 297 2038.10 6.86
Total 299 2140.35

 

*p< .05 level

Tukey’s Test of Significance

 

Mean Group F. H.
6.98 . Farm (F)

7.31 Homeland (H)

8.35 Resettlement (R) * *

 

*p<. 05 level

143

Condition of the House

To obtain data on the overall condition of the house,
the parent/guardian was asked to give his/her general
impression about their house. Less than a quarter of the
respondents reported that their house was in good condition.
More than three-fourths of the respondents said the house
needed renovation or was dilapidated and falling apart

(Table 12).

Table 12

Respondents’ Impressions about their Houses

 

 

 

Impression Number Percentage
Good 66 22.0
Needs Renovation 118 39.3
Dilapidated 116 38.7
Total 300 100.0

 

Most of the respondents who reported that their houses
were in good condition came from the homeland area. Those
who reported that their houses needed renovation or were

dilapidated lived in the resettlement area and on white-

144
owned farms. Houses in the resettlement area were built by
the government for those who are removed. However, as a
respondent from the resettlement area stated, "the
government dumps us here, and never looks back to see how we
are doing." These uprooted people are expected to stand on
their feet and fight to survive in a foreign and hostile
environment. Most of the houses for farm laborers are
provided by farmers as a fringe benefit. These houses too
needed renovation. A few of the houses that were visited by
the research team in the resettlement and the farm areas had
leaks in the roof, the walls were cracked, and the windows

were broken.

'Family Mobility

In an attempt to ascertain the mobility of families in
the sample, parents were asked how long they had resided
with the child at the present address. If the parent and the
child had lived at the address fewer years than the child’s
age, the parent/guardian was asked the number of times
he/she and the child had moved. The mean number of months
lived with the child at the present address was 67.90 or 5
years and 7 months, the standard deviation was 9.75, and the
range was 12-78 months.

Forty five percent of the parents who were interviewed

reported that they had never moved with the child, 11% had

145
moved once, 8% had moved twice, and 36% had moved several

times with the child (Table 13).

Table 13

Number of Moves made by Parents/Guardians with the Child

 

 

 

Moves Number Percentage
Never 134 44.7
Once 34 11.3
Twice 24 8.0
Several 108 36.0
Total 300 100.0

 

Parents/guardians were also asked questions related to
the reasons for moving. Fifty percent of those who had moved
said they were looking for better living conditions, 40%
reported that they were forced by the government because the
areas in which they previously lived were designated as
white areas, 9.7% were forced to move from urban areas by
the police, and less than one percent was too old to work in
urban areas and were forced to move to the homeland or

resettlement areas.

146

A breakdown of family mobility by area of residence
shows a significant chi square at p< .05 level. The
resettlement area shows the highest percentage» of 'family
mobility. All the respondents from this area had moved at
least once during the child’s life time. About 92% of
residents had moved twice, and about 41% had moved several
times. About 63% of the residents in the homeland had never
moved and the rest had either moved twice or several times.
About one third (37%) of the residents on white-owned farms
had never moved, 63% reported that they had moved either
twice or several times.

In order to clarify the problems associated with the
mobility issue of residents in the resettlement area, a
follow up question was asked as to whether residents in this
area had moved within the area. Data based on this question
suggest that residents in the resettlement areas might not
have moved only once when they were resettled, these people
reported that they had moved within the resettlement areas

in search of land for farming or for the livestock to graze.

CHAPTER VI

DATA ANALYSIS AND FINDINGS
ON CHILDREN’S INFORMATION

To obtain information about the children, standardized
tests were used. The Brown-IDS-Self-Concept Test was used to
assess the child’s social-emotional development. The Junior
South African Individual Scale (JSAIS) was used to assess
the child’s cognitive development. The sub-tests used were
vocabulary, quantitative skills, and copying skills. The
child’s weight, height, and head circumference were used as
measures of physical growth. Information regarding the
child’s behavior at home and health condition were obtained
by the parent’s questionnaire.

This section gives the mean, the standard deviation,
and correlations of the child’s measures of self-concept,
cognitive development, and physical growth. Percentages
based on the child’s behavior at home and health condition
are also reported in this section.

The total number of children tested was three hundred.
One hundred of these children were from each of the
residence areas: the homeland, resettlement, and farm areas.
Forty two percent were boys and 57.7% were girls. The mean

age in months was 70.03 or five years 8 months and the

standard deviation was 3.85.

147

148

A breakdown by gender of children and by the area of
residence shows that in the homeland and in the resettlement
areas an equal number of boys and girls were tested.
However, in the farm areas more girls than boys were tested.
The difference is significant at p< .05 level.

These findings suggest that boys ages 5-6 are not
equally enrolled in school on the farm areas. Data indicated
that the enrollment showed 42% boys and 58% girls in schools
at the time of this research in the farm areas. As was
mentioned earlier, children on white-owned farms are
expected to work along side their parents. Thus boys join
the labor force at an early age either as herders of
livestock or work in the field to grow crops. On the other
hand, girls do not play a major role in the labor force in
the farm areas, thus they may attend school if their parents
so choose and can afford to pay for their books and school
fees.

A breakdown of the children’s age by the area of
residence indicates that boys from the farm areas were
significantly different at the p<.05 level from boys from
the resettlement area, but not boys from the homeland. Boys
from the farm areas had the mean age of 72.24, boys from the
homeland had the mean age of 70.90, and boys from the
resettlement area had the mean age of 69.56. The mean age
difference between boys from the farm areas and boys from

the resettlement areas was three months.

149
Girls from the homeland were significantly different at
the p<.05 level from girls from the farm areas, but not
girls from the resettlement area. Girls from the homeland
had the mean age of 70.78, girls from the farm area had the
mean age of 69.00, and girls from the resettlement area had
the mean age of 69.63. The mean age difference between girls

from the homeland and the farm area was one month.

Findings on Children’s Information

The mean and the standard deviation of the total group
for self-concept, vocabulary, quantitative skills, copying
skills, weight, height, and head circumference are reported

in Table 14.

150
Table 14

Maanajyui the Standard Deviation for Children’s Growth and

Devel0pment

 

 

 

Growth and Development Mean S.D.
Self— concept 6.67 2.77
Vocabulary 12.37 4.79
Quantitative Skills 11.76 4.61
Copying Skills 11.53 6.48
Weight 17.41 2.67
Height 98.66 8.17
Head Circumference 47.37 3.79
N=3OO

Correlations Between Measures/Scores

and Age for Boys

The results (Hi the correlation coefficient of self-
concept, cognitive development, physical growth, and age for
boys show a significant relationship at p< .001 levels. Only
the self-concept and head circumference showed a significant

relationship at p< .05 level with age (Table 15).

151
Table 15

Correlation Coefficient ikn‘ Boy’s Self-concepta Coonitive.

Physical Measures/Scores and Age

 

 

Self-Con. 1.00

Vocab. (V) .69 1.00

Ouant. (Q) .68 .78 1.00

Copy (C) .65 .71. .78 1.00

Weight (W) .58 .66 .59 .53 1.00

Height (H) .50 .57 .50 .43 .62 1.00

Head Cir. .60 .58 .54 .41 .65 .72 1.00

Age .20 .09 .14 .06 .13 .10 .18 1.00

 

* * p< .001 level (Self-concept, cognitive, and physical
development).

* p< .05 level (Age, self-concept, and head circumference).

N=3OO

This finding suggests a relationship between self-
concept, cognitive development (vocabulary, quantitative,
and copying skills) and physical growth (weight, height, and
head circumference) and cognitive development and physical
growth for boys. Only self-concept and head circumference

were related to age at p< .05 level, however, the

152
correlations were very low (.20 and .18). This finding
suggests that age is not related to cognitive development,

weight, and height of boys in this study.

Correlations Between Measures/Scores

and Age for Girls

The results of the correlation coefficient of self-
concept, cognitive develOpment, physical growth, and age for
girls indicate a significant relationship at p< .001 level.
Age showed a low but significant relationship at p< .05
level with only vocabulary, quantitative skills, weight, and
height. No relationship was found between age, self-concept,

copying, and head circumference (Table 16).

153
Table 16

Correlation Coefficient for Girl’s Self-concept. Cognitive.

Physical Measures/Scores and Age

 

 

Self-Con. 1.00

Vocab. (V) .70 1.00

Quant. (O) .57 .74 1.00

Copy (C) .57 .66 .71 1.00

Weight (W) .58 .56 .47 .49 1.00

Height (H) .64 .51 .40 .35 .49 1.00

Head Cir. .53 .50 .42 .43 .65 .60 1.00

Age .10 .15 .15 -.O5 .13 .13 .07 1.00

 

* ‘* p< .001 level (Self-concept, cognitive, and physical
development). _

* p< .05 level (Vocabulary, quantitative skills, weight, and
height).

N-300

This finding suggests a relationship between self-
concept, cognitive development, and physical growth for
girls. Age showed a very low but significant relationship at
p< .05 level between vocabulary, quantitative skills,

weight, and height (.15, .15, .13, and .13).

154
Correlations Between the Child’s MeasuresLScores

and Crowdedness

The child’s measures/scores for self-concept, cognitive
development, and physical growth are inversely correlated
with the number of people in the household. Although the
correlations for all the measures/scores are not high, they

are significant at p< .001 level (Table 17).

Table 17

Correlation Coefficient for the Child’s Measures/Scores

and the Level of CroWdedness

 

Measures Number of People

in Households

 

 

 

Number of People 1.00
Self-concept -.3O * *
Vocab. -.37 * *
Quant. -.37 * *
Conying -.4o * *
Weight — -.4o * *
Height -.26 * *
Head Cir. -.31* *
* *

D< .001 level N=300

155
Findings suggest that the more people living in a
house the lower arethe scores on the measures for self-
concept, cognitive development, and physical growth. In the
resettlement area the mean number of people per household

was 8.35, in the homeland it was 7.31, and in the farm areas

it was 6.98.
Gender of the Child by Children’s Measures/Scores

The analysis of variance shows a significant difference
at p< .05 level between the gender of the child and the
self-concept. Boys had a higher mean of 7.06 on the scores
for self-concept, girls had a lower mean of 6.40. There was
no significant difference on the scores for cognitive
development and measures for physical growth (Table 18).

The findings of this study suggest that boys and girls
ages 5-6 years do not differ significantly on cognitive
development (vocabulary, quantitative, and copying skills),
and physical growth as measured by weight, height, and head

circumference.

156

Table 18
An Anajysis of Variance of the Gender of the Child by

the Self-concept. Cognitive. and Physical Development

 

Boys Girls

 

 

Self-concept 7.06 6.40 .05*
Vocabulary 12.18 12.62
Quantitative 12.33 11.39

Copy 11.63 11.45

Weight 17.69 17.49

Height 100.94 98.12

Head Cir. 48.01 46.93

*p< .05 level N=300

Child’s Behavior and Parent-Child Interaction

This section provides information regarding the child’s
behavior at home. This includes how the child interacts with
other siblings and with the parent/guardian as perceived by
the parent/guardian.

Of the parents/guardians who were interviewed 35%
reported that their children were easy to work with. Another
52% said their children were difficult to handle and

sometimes fought with their siblings. Thirteen percent

157
reported that their children mixed freely with other
siblings. These findings suggest that about half of the
parents/guardians had children whom they felt were difficult
to bring up.

The parent/guardian was also asked to respond to a
question on how many books, games, and toys the child had at
home. Regarding the items that the child had at home, more
than half of the parents/guardians reported that their
children did not have books, games, or toys. Less than 25%
of the parents/guardians said that their children had books,
games, or toys at home (Table 19). Parents/guardians who
reported that their children had books could possibly be the
same parents/guardians who reported the purchase of games

and toys for their children.

Table 19
Items the Child has at Home

 

 

Items Yes No

n % n %
Books 66 22.0 234 78.0
Games 69 23.0 231 77.0

Toys 73 24.3 227 75.7

 

158

Parents/guardians were also asked questions on the kind
of activities that they participated in with the child at
home. These activities included: working and playing
together, reading, telling stories, and watching T.V. with
the child.

Regarding activities that the parent/guardian and the
child did together at home, almost all the parents reported
that they worked together with their children at home. More
than three fourths of the parents/guardians said that they
told stories and less than one fourth of the
parents/guardians said that they read books to their
children. A smaller percentage of the parents/guardians said

that they watched T.V. with their children (Table 20).

Table 20
Activities Done together with the Child

 

 

Activities Yes No

n % n %
Work together 296 98.7 4 1.3
Tell stories 231 77.0 69 33.0
Read books 62 20.7 238 79.3
Watch T.V. 23 7.7 277 92.3

 

159
A breakdown of respondents who reported that they
read stories to their children by area of residence
indicates that in the homeland about (35%) of the
respondents reported that they read stories with their
children. In the resettlement areas (27%) reported to have
read stories. None of the respondents on white-owned farms
reported that they read stories to their children.
These findings may suggest that parents in the homeland
and in the resettlement areas regard the importance of
reading to their children more so than parents in the farm
areas. Another factor which must be considered is that many
families who work on white-owned farms had less than six
years of education and therefore, reading may pose a
problem. Also since these families work on the farms they
might not have the time to read or tell stories to their

children.

Child’s Health Condition

This section gives information about the child’s health
condition. This includes the health condition of the child
as perceived by the parent/guardian, whether the child has
been hospitalized, reasons for hospitalization, and how
recently the child has been hospitalized.

More than half of the parents/guardians reported that

their children were either healthy or somewhat healthy.

160
About one third of the parents/guardians reported that their

children were sickly (Table 21).

Table 21

Responses to Child’s Health Condition

 

 

 

Health condition n %

Very Healthy 134 44.7
Somewhat Healthy 61 20.3
Sickly 105 35.0
Total 300 100.0

 

Child’s Hospitalization

Thirty seven percent of all the parents/guardians
reported that their children had been hospitalized. Of those
who reported that their children had been hospitalized, 33%
said the children were hospitalized within the past six
months and approximately four percent were hospitalized
within the past year.

Reasons for hospitalization were either kwashiorkor,
pneumonia, or diarrhea. Table 22 shows that there were more

cases of kwashiorkor than cases of pneumonia and diarrhea.

161
Table 22

Reasons for Child’s Hospitalization

 

 

 

Reasons n %

Kwashiorkor 68 61.0
Diarrhea 26 23.2
Pneumonia 18 16.1
Total 112 100.0

 

A breakdown of the reasons for hospitalization by the
area of residence shows that 31% of the children in the
homeland were hospitalized. Of those 23% were hospitalized
for kwashiorkor; 5% had diarrhea; and 3% had pneumonia.

In the resettlement area 32% of the children were
hospitalized. Of those hospitalized 25% had kwashiorkor, and
7% had diarrhea. No case of pneumonia was reported.

0n the farm areas 49%. of the children were
hospitalized. Twenty percent were hospitalized for
kwashiorkor; 15% for pneumonia. and 14% for diarrhea.

The percentage of kwashiorkor cases ranged from 20%-25%
in all these areas. The farm and resettlement areas show
more cases of kwashiorkor. However, more cases of pneumonia

and diarrhea were reported in the farm areas. Pneumonia and

162
diarrhea seem to In: a problem in the farm areas, however,
this does not seem to be a problem in the homeland and the
resettlement areas. Pneumonia in the farm areas could be
attributed in) the mud houses and the size of the house or
climatic conditions.

Results for the resettlement area are contrary to
expectation for this area has a high percentage of houses
built with tin which were reported as very cold in winter
and very hot in summer. The parents of children in the
resettlement area did not report any cases of pneumonia as
one might have expected. This could be attributed to the dry
climate within the resettlement area as opposed to the moist
climate within the farm areas. However, the researcher did
not collect data about the climate «no humidity factors,
therefore, is unable to make conclusions about the possible

effect of climatic conditions on children’s health.
Nutritional Status of the Child

The nutritional status of the child was inferred from
the physical growth measurements of weight for age. Eighty
seven percent of children who were in the sample fell below
the 5th percentile of the National Center for Health
Statistics growth curves (Hamill et. al 1977) on the
measures of height and head circumference. These unexpected

data forced the researcher to use other means of inferring

163

the nutritional status of the child. Therefore, the
differences between the malnourished and well nourished
children were based on the measures of weight for age only.

Using weight for age, a breakdown of the nutritional
status of children by gender shows that 45% of all the boys
who were tested fell below the 5th percentile weight for age
and 55% fell above the 5th percentile. Fifty five percent of
the girls fell below the 5th percentile of weight for age
and 45% fell above the 5th percentile.

Table 23

AVEQAOf Residence by the Nutritional Status

 

 

Residence Nutritional Status
Malnourished Well Nourished
n % n %
Farm 36 66.7 18 33.3
Homeland 32 59.3 22 40.7
Resettlement 44 86.3 R 7 13.7

 

Chi Square . 9.75
* p< .05 level

Also using weight for age as a measure, a breakdown of

the nutritional status of children by area of residence

164
shows that 59% of the children in the homeland were
malnourished and 41% were well nourished. Eighty six percent
of the children in the resettlement area were malnourished
and 14%. were well nourished. Sixty seven percent «rf the
children in the farm areas were malnourished and 33% were
well nourished (Table 23).

These findings suggest that all the three areas had
more malnourished than well nourished children, however, the
resettlement area inui more malnourished children than the
homeland and the farm areas. These data are consistent with
the previous findings on hospitalization for kwashiorkor an
indicator (H’ malnutrition. In the resettlement areas the
problem of malnutrition of children can be attributed to
lack of resources such as jobs, drought, and the fact that
young men and women leave these areas to seek employment in
urban areas leaving the dependents behind often to be cared

for by the elderly or their siblings.

CHAPTER V11

RELATIONS BETWEEN FAMILY BACKGROUND
AND CHILDREN’S INFORMATION

This chapter will provide information about
relationships that may or may not be significant between
parents’/guardians’ and children’s information. A number of
one-way multivariate analyses of variance of the independent
and the dependent variables are reported. The independent
variables were the area of residence, the parent/guardian
marital status, level of education, level of occupation, and
family mobility. The dependent variables were the child’s
self-concept, vocabulary, quantitative skills, copying
skills, weight, height, head circumference, and the child’s
health condition.

The Manova test was used to find differences between
the levels of the independent variables and the dependent
variables. 11’ the overall Manova test (Wilk’s Lambda) was
significant, the F test of the Anova for each dependent
variable was checked for significance. If this F test was
significant the Tukey’s HSD was used to find differences
between the levels (H’ the- independent variables (N1 that

particular dependent variable.

165

166

The following Manova Tables will contain four sections.
The first section shows the overall multivariate statistic,
Wilk’s Lambda. The second section shows the univariate F
test 1%”: each dependent variable. The third section shows
Tukey’s HSD for self-concept and cognitive development
scores with significant univariate F tests, and the last
section shows the Tukey’s HSD for physical growth measures

with significant univariate F tests.

Child’s Measures/Scores and the Area of Residence

A one-way MANOVA was obtained for the area of
residence and the children’s measures and scores. The
results of the MANOVA show an overall significance at
p< .001 and p< .05 levels. All of the individual univariate
tests of the children’s measures and scores are also
significant at the p< .05 or p< .001 levels (Table 24).

Data in Table 24 section 3 indicate that there is a
significant difference at p< .05 level between the self-
concept, vocabulary, quantitative skills, and copying of
children between the homeland, the resettlement, and the
farm areas. Children from the homeland showed higher mean
scores on the self-concept and the cognitive» development
tests. There was I”) significant difference between these

scores for children from the resettlement and farm areas.

167

Table 24
One-way MANOVA of the Child’s Measures/Scores by the Area of

Residence

Section 1: Multivariate Test

 

Wilk’s Lambda Value DF F P

 

0.675 14/58 9.02

 

*p< .05 level

Section 2: Univariate F test

 

Dependent variables F (2,297) D.F P

 

Self-concept 12.13 .001 * *
Vocabulary 10.37 .001 * *
Quantitative Skills 18.79 .001 * *
Copying 3.56 .029 *

Weight 5.02 .007 *

Height ' 31.21 .001 * *
Head Circumference 8.77 .001 * *

 

* *p< .001 level
*p< .05 level

168

Section 3: Tukey’s Test of significant univariate F test

Self-concept. Vocabulary. Quantitative skills. Cooying. by

the Area of Residence

 

 

Mean Group F. R. H.
SC. V. O. C.
6.08 11.68 10.81 11.79 Farm (F)

6.18 11.35 10.53 10.19 Resettl. (R)
7.74 14.09 13.93 12.57 Homeland (H) * *

 

*p<. 05 level

Section 4: Tukey’ Test of significant univariate F test

Weight. Height. and Head Circumference by Area of Residence

 

Mean Group F. 'R. H.

 

Weight Height Head Cir.

17.44 94.67 43.83 Farm (F)
16.80 98.33 46.65 Resettl.(R) *
17.98 102.98 48.63 Homeland (H) * *

 

*p< .05 level

169

Data in Table 2 in Chapter V indicated a higher
percentage of families with both spouses at home or with no
spouse at home in the homeland than on the farm and in the
resettlement areas. The higher level of self-concept in
children from the homeland could thus be attributed to a
more stable home life, intact families, or extended family
in other cases, and a sense of a community. The homeland had
also a higher percentage of respondents with a high school
diploma and was the only area with respondents who had a
bachelor’s degree.

Findings on books, games, and toys indicated that 22%
of the respondents from the homeland and the resettlement
areas reported that they had these available for their
children. In the homeland 35% of the parents reported that
they read stories to their children. All these factors could
help children find a more meaningful sense of self.

Children from the resettlement and the farm areas show
lower levels of selfjconcept. The finding suggests that the
overall ecological context in the areas of residence as well
as other factors may be influencing how children feel about
themselves.

As viewed by most blacks in South Africa, the
resettlement areas are the "dumping grounds" for marginal
black people who neither belong to urban areas nor the

homelands. Thus, residents of the resettlement areas are

170

viewed by residents of the homeland as "amalose". The
equivalence of this concept is aliens. They are often
treated with suspicion, anger, and are ostracized by the
residents of the homelands. One reason for the hostile
treatment is that families in the resettlement areas are
viewed as coming to take away the limited land from the
homeland residents.

Families that are forcibly removed are often "dumped"
in these resettlement areas with little or no resources.
Lack of resources creates an undesirable social milieu for
survival which could influence residents from the
resettlement areas to engage in less desirable means for
their survival. Such acts could serve to intensify feelings
of animosity against this group.

From previous data reported, children in the
resettlement areas live with parents who are more poverty
stricken than those from the homeland, or farm areas. It is
thus possible that parents/guardians of these children also
have lower levels of self-esteem. Such negative feelings
might be transmitted to the children. However, the
conclusions regarding parents’/guardians’ self-esteem cannot
be made because data regarding parents’ feelings were not
collected.

The possible explanation for a lower self-concept and

cognitive development for black children who live and work

171

on white-owned farms may be attributed to their daily
interactions with the members of the white farm families.
These children learn from their parents to address their
employer as ’baas’ the Afrikaans/Dutch term for master. The
sons of the employer are addressed as ’klein baas’ or young
master. Black children learn early in life to defer and to
pay due respect to the white master who provides the whole
family' with £1 salary, food, accommodation, and clothing.
This all helps the white farm owners to portray a feeling of
the "Omnipotent Figure" which serves to perpetuate the black
child’s respect for these white farm owners.

These black children thus know that their fate is in
the hands of the white master. This sense of dependency on
white farmers can lead to a lack of confidence in what their
own parents can do for them and in what they can do for
themselves.

Children in the homelands had higher scores in
cognitive development than children in the resettlement and
farm areas. Although these children appear to be ’smarter’
than their counterparts, this could also be a reflection of
how poorly children from the resettlement and farm areas
performed in the cognitive development tests.

Children from the resettlement and farm areas showed
lower scores in cognitive development. The lower scores on

these measures can be a reflection of the depressed

172

social conditions (see Table 2) under which these children
and their families live in these areas. Although both the
homeland and the resettlement area had higher percentages of
unemployment than farm areas, residents in the homeland were
less mobile, had intact families, higher levels of
education, and better houses all of which may have
contributed to the children’s cognitive development.

The deficit in cognitive development in children from
the resettlement and farm areas could also be attributed to
family mobility. The resettlement and farm areas showed a
high percentage of family mobility with the resettlement
showing the highest. For example, about 92% of residents in
the resettlement area had moved once or twice, 63% of
residents on white—owned farms had moved once, and 37% in
the homeland had moved once.

Moving from one place to the other might hinder
adaptation of children to their environment. It might thus
be the failure to adapt or the lack of the necessary time to
adjust to the environment that influences children’s
cognitive development. The high scores iri cognitive
development of children in the homeland might be due to the
fact that children in this area have not moved as much as
children from the other areas, thus children from the
homeland might have had a more stable influence to adapt to

their environment.

173

Children’s physical growth it: the homeland was
significantly different from children 'Hi the resettlement
and farm areas. The mean scores on the measures for weight,
height, and head circumference for children in the homeland
were higher than the mean scores for children in the
resettlement and farm areas.

This finding suggests that children in the homeland may
be provided with better nutrition, despite the parents’
limited access to employment. Better educational levels of
parents in the homeland might be helping parents to buy a
variety of foods and prepare these types of food in such
ways that can enhance children’s physical growth.

Children in the resettlement area differed from
children in the farm areas. The mean scores for weight were
higher for children in farm areas than for children in the
resettlement. However, scores for height and head
circumference were higher for children in the resettlement
area.

Children from the resettlement area show lower levels
of physical growth as compared to the homeland children.
However, resettlement children show higher levels of growth
in height and head circumference than farm children. This
may be due to the fact that these children are mainly raised
by unemployed single parents who have higher levels of

education than residents from farm areas, but lack access to

174

employment and other important resources to support their
children. I

The results for the farm children are contrary to
expectation. These are some of the children whose
parents/guardians (H‘ siblings are ‘Hl most cases employed.
Therefore, one would suspect that the data should show a
better nutritional status of children from farm areas
because food is more likely to be available to them.
However, the findings suggest that children 'Hi the farm
areas are heavier but shorter and have a smaller head
circumference than children from the resettlement area. This
could suggest that children in the farm area may be getting
an imbalanced diet that consists mainly of starchy foods
such as maize and little or no protein. As stated by Ndaba

(1984) maize is notoriously deficient in amino acids.

Child’s Measures/Scores and the Parent’s/Guardian’s

Marital Status

A one-way Manova was obtained for marital status and
the child’s measures and scores. The results of the Manova
show an overall significance at p< .001 and p< .05 levels

(Table 25).

175

Table 25
One-way MANOVA of the Child’s Measures/Scores by the Maaital

Status

Section 1: Multivariate Test

 

Wilk’s Lambda Value DF F P

 

.798 21/83 .324

 

*p< .05 level

Section 2: Univariate F test

 

Dependent variables F (3,296) D.F. P

 

Self-concept 8.80 .001 * *
Vocabulary 6.37 .001 * *
Quantitative Skill 3.89 .009 *
Copying 7.0 .001 * *
Weight 3.33 .020 *
Height 6.52 .001.* *
Head Circumference 2.63 .050 *

 

* * p< .001 level
* p< .05 level

Section 3: Tukey’s Test of Significant Univariate F test

Self—concept.

Vocab..

1

76

Quant.L Copy by Marital Status

 

 

 

 

 

 

 

 

Mean Group D&W N.M M no 5. M.
SC. V. C.
4.20 9.70 10.80 12.60 D&W
6.13 11.79 12.20 11.30 N.M.
6.42 11.53 11.05. 9.39 M.no s.
7.62 13.92 12.99 12.99 M. * * *
*p< .05 level
Section 4: Tukey’s Test of Significant Univariate F test
Weight. Height. and Head Circumference by Parent’s
Marital Status
Mean Group D&W N.M. M no S. M.
Weight Height Head Cir.
16.80 89.30 44.50 D&W
17.04 97.53 47.22 N.M. *
17.19 99.26 47.27 M. no 5. *
18.07 100.08 47.87 M. *
*p< .05 level

177

Children who come from married families with the spouse
present were significantly different at the p< .05 level on
the mean scores for self-concept, vocabulary, quantitative
skills, and copying from children who come from families
which were divorced, and widowed, never married, and married
but not living with the spouse. Children from intact
families show higher mean scores, on all 'these dependent
variables. The mean scores of children from the divorced and
widowed, never married, and married but not living with a
spouse show the lowest for self-concept, vocabulary, and
quantitative skills but not copying skills. The finding
suggests that intact families have an advantage in the
homeland as reflected by children’s high self-concept scores
and as well as better scores on the cognitive development
tests. Also more families iri the homeland than iri other
areas interacted with their children. This might contribute
to higher levels of self-concept and higher levels of
cognitive development.

On the other hand, larger numbers of children who come
from single-parent homes live in the resettlement area.
Children who come from divorced and widowed families come
mostly from farm areas.

These results show that children from married, married
but not living with a spouse, and never married differed
significantly on the physical growth from children whose

parents were either divorced or widowed families. This

178

finding adds to the suggestion that children on farm areas
might not be getting the right kind of nutrition that
enhances their physical growth or that other factors such as
crowding are having an effect on height. As suggested by
Graham (1972) crowdedness can be seen as one of the factors
that might contribute in) the child’s height, rather than
only the nutritional status of the child.

Child’s Measures/Scores and the Parent’s/Guardian’s

Educational Level

A one-way Manova was conducted for the analysis of data
concerning the parent’s/guardian’s level of education and
the child’s measures. The results (H: the Manova show an
overall significance at p< .001 and p< .05 levels (Table
26).

The results show that children who come from families
in which the parental level of education was sixth grade or
less were significantly different on the scores for self-
concept, vocabulary, quantitative skills, and copying from
children whose parents had junior secondary school
certificate, high school diploma, and a bachelor’s degree.
Children whose parents had a bachelor’s and a high school
diploma were also different on the measures for self-
concept, cognitive development, and physical growth from

those whose parents did not have a high level of education.

179

Table 26
ne- y MANOVA of the Child’s Measmmaaz§§ama§___by

fiarent’s/Guardian’s Educational Level

Section 1: Multivariate Test

 

Wilk’s Lambda Value Of F P

 

.485 28/1043 2.43

 

*p< .05 level

Section 2: Univariate F test

 

 

Dependent variables F (4,295) D.F. P

Self-concept 33.18 .001 * *
Vocabulary 38.05 .001 * *
Quantitative Skills 35.11 .001 * *
Copying 36.39 .001 * *
Weight 16.15 .001 * *
Height 23.34 .001 * *
Head Circumference 18.59 .001 * *

 

* * p< .001 level

180

Section 3: Tukey’s test of significant univariate F test

 

 

 

 

 

Self-concept. Vocab.. Quantitativea, Capying by
Parent’slGuardian’s Educational Level
Mean Group <6yrs 6yrs JSS HS BA

SC. Voc. Quant. Copy
5.09 9.78 9.29 9.52 <6yrs
6.19 11.46 10.89 9.52 6yrs
7.73 13.44 13.13 13.89 JSS * *
9.34 17.53 16.00 18.23 HS * * *
9.50 18.25 18.42 19.25 BA * * *
*p< . 05 level

Parents/guardians who showed higher levels of

education were from the homeland and the resettlement areas.
This finding thus suggests that families with a better level
of education might have had time, other support systems and
information that helped them to

child’s

access to resources’ and

children thus

interact with their promoting the

self-concept and cognitive development.

181

Section 4: Tukey’s Test of Significant Univariate test

Weight. Height. and Head Circumference by

Parent’sLGuaLdian’s Educational Level

 

 

Mean ‘ Group <6yrs 6yrs JSS HS BA
Weight Height Head Cir.

16.33 93.35 42.28 <6yrs

16.95 99.26 47.26 6yrs

18.44 101.71 49.02 JSS * *

19.02 104.72 49.95 HS * * *

20.17 101.75 49.25 BA * * *

 

*p< .05 level

This finding supports earlier studies which show the
importance of parent-child interaction in promoting
intellectual and social development. This has been clarified
in a study by the Harvard Preschool Project (White, Kaban,
and Attanucci, 1979). The. major finding of their study
concludes that the most favourable experience promoting
intellectual and social competence in children is listening
to live language being directed towards them.

Inspite of their parents/guardians higher levels of

education children from the resettlement areas did not show

182
high mean scores in self-concept and cognitive development.
The findings for these children suggest that the level of
education alone may not be the only influence in black South
African children’s self-concept and cognitive development.
Other factors such as being a single-parent without a job
can influence the development of children.

Farm laborers showed lower levels of education and were
mostly employed in menial and unskilled jobs which might
have required them to work long hours. Their children
showed lower mean scores on self-concept and cognitive
development than children from the homeland or the
resettlement areas. The data concerning children’s measures
and scores on white-owned farms suggest a relationship
between the area of residence, parent’s/guardian’s level of
education, the child’s health condition, self-concept, and
cognitive development.

Physical growth of children whose parents/guardians had
a junior secondary school certificate, high school diploma,
and a: bachelor’s degree was significantly different from
children whose parents/guardians had six or less years of
education. These findings suggest that parents/guardians who
had higher levels of education probably had more access to
resources and information such as knowledge of the types and

kinds of food necessary for healthy physical growth.

183
Child’s Measures/Scores and the Parent’s/Guardian’s

Occupational Level

A one-way Manova was obtained for the
parent’s/guardian’s level of occupation and the child’s
measures and scores. The results of the Manova indicate an

overall significance at p< .05 and p< .001 levels (Table

27).

Table 27
One-way MANOVA of the Child’s Measures/Scores by

Parent’s/Guardian’s Occupational Level

Section 1: Multivariate Test

 

Wilk’s Lambda Value Of F P

 

.373 42/1712 7.51

 

*p< .05 level

184

Section 2: Univariate F test

 

 

Dependent variables F (6,293) D.F. P

Self-concept 25.05 .001 * *
Vocabulary 30.13 .001 * *
Quantitative Skills 31.19 .001 * *
Copying 29.59 .001 * *
Weight 19.17 .001 * *
Height 13.41 , .001 * *
Head Circumference 19.96 .001 * *

 

* * p< .001 level

The data indicate that children whose parents were not
employed were significantly different on the mean scores for
self-concept, vocabulary, quantitative skills, and copying
from children whose parents were employed either in menial,
semi-skilled, skilled, (H‘ semi-professional positions.
Children whose parents were employed in menial, semi-
skilled, skilled, and semi-professional positions had mean
scores which were higher than children whose parents were
not employed at all. Children whose parents were working in
semi-skilled, skilled, and semi-professional positions were
significantly different from children whose parents were in

menial jobs or not employed.

185

Section 3: Tukey’s test of significant univariate F test

Self-concept. Vocabulary. Quantitative Skills. Copying. by

Earent’s/Guardian’s Occupational,Level

 

Mean Grp None Menial S.S. S. S.Prof

 

SC. Voc. Quant. Copy
5.31 9.99 9.47 8.20 None

N-

7.01 12.13 11.39 11.92 Menial
7.64 14.71 15.76 16.00 S.S. * *

X'
X-

9.18 16.44 15.93 16.43 Skilled
10.38 18.38 17.13 19.45 S.Prof. * *

 

*p< .05 level

Sixty two percent of parents in the resettlement area
were not employed. Therefore more of the children from the
resettlement area had parents/guardians who were not
employed. These low mean scores on the self-concept,
cognitive development, and physical growth could be scores
for children whose parents/guardians were not employed.
However, this hypothesis cannot be verified at this time,
since data collected on parents/guardians and the child were

not coded as matched pairs.

186

Section 4: Tukey’s Test of Significant Univariate Test

Weight. Height. Head Circumference tn! Parent’s/Guardian’s

Occupational Level

 

Mean Group None Menial S.S. S. S.Prof

 

Weight Height Head Cir.

16.13 95.70 45.49 None

18.24 102.64 48.13 Menial

18.80 104.25 49.69 S.S. *
19.25 104.24 49.80 Skilled *
20.25 108.13 50.25 Semi.Prof. * *

 

*p< . 05 level

Fifty percent of parents in the homeland were without
jobs. However, children from the homeland showed higher mean
scores on self-concept, cognitive development, and physical
growth. The findings for children in the homeland thus
suggest that there might be other factors in the environment
of children in the homeland that might contribute to their
development.

Eighty one percent of farm laborers worked in menial
and unskilled jobs, EHHI children on white-owned farms had

lower mean scores on the self-concept, cognitive

187

development, height and head circumference. A possible
speculation is that parents/guardians who work on the farms
usually work long hours, thus may have had only limited time
to carry out activities that might have helped to enhance
their children’s development. However, data (Hi the total
number of hours worked by farm laborers were not collected.
It is thus not possible to draw conclusions about whether
time was an important factor or not in determining the low
mean scores on self-concept, cognitive development, height,
and head circumference. However, data reveal that the level
of education for farm laborers was lower than the level of
education for residents from the other areas. Thus the area
of residence, the parent’s level of education, and
occupation have a significant relationship to children’s
development on white-owned farms.

These results indicate that children of parents who
were employed in semi-professional, skilled, and semi-
skilled jobs differed significantly at p<. 05 level from
children whose parents were in menial jobs or unemployed on
all the measures for height, weight, and head circumference.
Children whose parents were working in semi-professional
positions also showed higher mean scores on the measures of
physical growth than mean scores for children whose parents
were working in skilled or semi-skilled jobs. There were no

significant differences between children whose parents were

188
working “hi semi-professional positions EHKI children whose

parents were working in skilled positions.

Child’s Measures/Scores and Family Mobility

A one-way Manova was obtained for the number of times
the family moved with the child and the child’s
measures/scores. The results of the Manova show an overall

significance at p< .001 and p< .05 levels (Table 28).

Table 28
One-way MANOVA of the Child’s Measures/Scores by Family

Mobility

Section 1: Multivariate Test

 

Wilk’s Lambda Value Of F P

 

.633 21/833 1.54

 

*p< .05 level

Section 2:

1

Univariate F test

89

 

 

Dependent variables F (3, 296) D.F. P

Self-concept 19.38 .001
Vocabulary 16.24 .001
Quantitative Skills 25.14 .001
Copying 17.89 .001
Weight 23.78 .001
Height 17.38 .001
Head Circumference 32.32 .001

 

 

 

 

 

* * p< .001 level

Section 3: Tukey’s Test of significant univariate F test

Self;concept. Vocab.. Quant.. Copying by Family Mobility
Mean Number Several 2

SC. Voc. Quant. Copy

5.40 10.57 9.75 8.90 Several

5.66 9.54 8.16 7.66 Twice

6.7 13.29 13.20 13.94 Once * *

7.8 14.09 13.64 13.69 None * *

*p< .05 level

191
Data from this study indicate that family mobility was
higher in the resettlement and in the farm areas than in the
homeland. Thus low mean scores on self-concept, cognitive
development, and physical growth might be due to family
mobility as well as other factors in the resettlement and

farm areas that were cited as unfavourable for children’s

development.

Child’s Measures/Scores and Health Condition

A one-way Manova was obtained for the child’s health
condition and measures of self-concept, cognitive, and
physical growth. The results of the Manova indicate an
overall significance at p< .001 and p< .05 levels (Table

29).

Table 29
One-way MANOVA of the Child’s Measures/Scores by Health

Section 1: Multivariate Test

 

Wilk’s Lambda Value Of F P

 

.476 14/582 18.67

 

*p< .05 level

191
Data from this study indicate that family mobility was
higher in the resettlement and in the farm areas than in the
homeland. Thus ‘an mean scores on self-concept, cognitive
development, and physical growth might be due to family
mobility as well as other factors in the resettlement and

farm areas that were cited as unfavourable for children’s

development.

Child’s Measures/Scores and Health Condition

A one-way Manova was obtained for the child’s health
condition and measures of self-concept, cognitive, and
physical growth. The results of the Manova indicate an
overall significance at p< .001 and p< .05 levels (Table
29).

Table 29
One-way MANOVA of the Child’s MeasuresLScores by Health

Section 1: Multivariate Test

 

Wilk’s Lambda Value DF F P

 

.476 14/582 18.67

 

*p< .05 level

192

Section 2: Univariate F test

 

 

Dependent variables F (2,297) D.F. P

Self-concept 76.28 .001 * *
Vocabulary 62.18 .001 * *
Quantitative Skills 57.01 .001 * *
Copying 66.45 .001 * *
Weight . 74.57 .001 * *
Height 60.09 .001 * *
Head Circumference 77.35 .001 * *

 

* *p< .001 level

Section 3: Tukey’s test of significant univariance F test

Self-concept. Vocab.. Quanti.. Cooy by Health Condition

 

Mean Health Sick Somewhat Healthy

 

SC. Voc. Quant. Copy

4.70 9.39 8.86 15.52 Sick

6.39 11.40 11.16 17.16 Somewhat *

8.32 15.14 14.29 18.99 Healthy * *

 

*p< .05 level

193

Section 4: Tukey’s Test of Significant Univariate Test

Weight. Height. Head Circumference by Health Condition

 

Mean . Health Sick Somewhat Healthy

 

Weight Height Head Cir.

16.10 94.81 45.10 Sick
17.58 101.21 47.71 Somewhat *
18.62 102.62 49.27 Healthy * *

 

*p< .05 level

The results show that healthy or somewhat healthy
children were significantly different on the mean scores for
self-concept, vocabulary, quantitative skills, copying,
weight, height, and head circumference from children ‘who
were sickly. Children who were healthy or somewhat healthy
as perceived by the parent/guardian showed mean scores that
were higher than for children who were reported by their
parents as sick. Healthy children were also significantly
different on the mean scores for self concept, cognitive
development, and physical growth from children who were
somewhat healthy. Healthy children had higher mean scores on

these measures.

194

All residential areas had children who had been sick
and had been hospitalized within the past six months or
year. However, the farm areas. had the higher percentage
(49%) of children who were hospitalized than the other two
areas. Children on white-owned farms showed lower mean
scores on self-concept, cognitive development, and physical
growth than children from the homeland. However, when
compared with children from the resettlement area, children
from the farm area weighed more, but were shorter and had a
small head circumference. The lower mean scores on these
tests may be due to all the factors in the child’s
environment already mentioned as well as the child’s health

condition.

CHAPTER VIII
SUMMARY AND CONCLUSIONS

This chapter gives a summary of the study, conclusions,
the mode of rationality used in this study, implications, as

well as suggestions for the future.
Summary of the Study

The major purpose of this investigation was to
determine the relationships between a multiplicity of
ecological factors that aggravate malnutrition and the
behavioral development and physical growth of black South
African children from a family ecosystem framework. A
secondary objective was to examine the viability of the
ecosystem framework in family studies and to arrive at
suggestions that could help develop this framework.

Three hundred black South African school children ages
5-6 years were assessed for cognitive, social-emotional
development, and physical growth. Three hundred
parents/guardians were interviewed for background
information .regarding the child and the family. The
residential areas from which the sample was drawn were:
Herschel in the homeland of the Transkei,. Thornhill a
resettlement area in the homeland of the Ciskei, the farm

areas around Queenstown, and in the Orange Free State. One

195

196
hundred children and their parents/guardians were selected
from each of these areas using a systematic sampling
technique.

The Junior South African Individual Scale (JSAIS) was
used as a measure of cognitive development. Three areas of
cognitive development were tested. These included: verbal,
numerical, and performance» ‘The Brown-IDS—Self-Concept
Referents Test was used as a measure of social-emotional
development. Anthropometric measures of height, weight, and
head circumference were used for physical growth. A parent’s
questionnaire was developed and used to obtain the child’s
family demographic information, home environment, and the
child’s health condition.

A chi square test was used to determine whether the
relationships between the’ demographic variables were
significant. Variables included were, area of residence,
home environment, the socio-economic status of parents, the
type of family structure, and family mobility. The results
of the chi square tests indicated a significant relationship
between the area of residence and parent’s/guardian’s
marital status, educational, and occupational levels. A
significant relationship was also found between the
parent’s/guardian’s educational and occupational levels
(Tables 2-8). No significant relationship was found between
marital status and parent’s/guardian’s occupational level

(Table 7).

197

A Pearson Coefficient correlation was used to examine
relationships between gender, self-concept, cognitive
development, physical growth, and age. The results indicated
a significant relationship between self-concept, cognitive
development, and physical growth for boys. Only self-concept
and head circumference were related to age, however, the
correlations were very low (Table 15).

The results (rf the correlation between self-concept,
cognitive development, physical growth, and age for girls
indicated a significant relationship. Age showed a low but
significant relationship with only vocabulary, quantitative
skills, weight, and height. No relationship was found
between age, self-concept, copying, and head circumference
(Table 16). These findings suggest that age may not be
related to the child’s self-concept, cognitive development,
and physical growth.

The results (rf the correlation between self-concept,
cognitive development, physical growth, and the home
environment as measured by crowdedness indicated an inverse
relationship. Although the correlations for all these
scores/measures were not high, they were significant (Table
17). This finding suggests that the more people living in a
house, the lower the scores on the measures for self-
concept, cognitive development, and physical growth.

The results of the analysis of variance between the

gender of the child and the child’s measures/scores on self-

198

concept, cognitive development, and physical growth
indicated a significant difference between only the gender
of the child and self-concept. No significant difference was
found between the gender of the child, cognitive
development, and physical growth (Table 18). This fflnding
suggests that boys and girls ages 5-6 years old do not
differ significantly on cognitive development and physical
growth.

Results on the child’s behavior and parent-interaction
indicated that more than half of the parents/guardians
reported that their children were difficult to handle and
fought with their siblings. This finding suggests that some
of the children in the study showed behavioral problems at
home.

Parents/guardians were also asked to respond to a
question on how many books, games, and toys the child had at
home. More than half of the parents/guardians reported that
their children did run: have books, games, and toys. Less
than one-fourth of the parents/guardians said that their
children had books, games, and toys. These findings suggest
that most children in the farm, homeland, and resettlement
areas do not have books, games, and toys.

Regarding activities that the parent/guardian and the
child did together at home, almost all the parents reported
that they worked with their children at home. More than
three fourths of the parents/guardians said that they told

199
stories and less than one fourth of the parents/guardians
said that they read books to their children. A smaller
percentage of the parents/guardians said that they watched
T.V. with their children (Table 20).

Most parents/guardians who reported that they read and
told stories to their children were from the homeland area,
a few parents/guardians were from the resettlement area.
None of the respondents from white-owned farms reported that
they read stories to their children. These findings may
suggest that parents/guardians in the homeland and the
resettlement area regard the importance of reading and
telling stories to their children more so than
parents/guardians in the farm areas.

Regarding the child’s health condition more than half
of the parents/guardians reported that their children were
either healthy or somewhat healthy. About one third of the
parents/guardians reported that their children were sickly
(Table 21). Of the children who were sickly, about one third
had been hospitalized within the past six months. Reasons
for hospitalization were either kwashiorkor, pneumonia, or
diarrhea. The farm and the resettlement areas showed more
children who were hospitalized for kwashiorkor than the
homeland. More cases of pneumonia and diarrhea were also
reported in the farm areas.

These findings suggest that kwashiorkor which is a

syndrome of malnutrition is a problem in all three areas.

200
However, the resettlement and the farm areas had higher
percentages of malnourished children than the homeland. Also
suggested by the findings is that diseases such as pneumonia
and diarrhea that are related to malnutrition are prevalent
in the farm areas.

One way multivariate analyses of variance were obtained
for the family background information and the child’s self-
concept, cognitive development, and physical growth. If the
overall MANOVA test was significant, the F test of the Anova
for each dependent variable was checked for significance. If
the F: test was significant a Tukey’s HSD was used to find
differences between the levels of the independent variables
on that particular dependent variable.

The results of the MANOVA test and the Tukey’s test HSD
indicated a significant difference between the family
background information and the children’s measures/scores on
the self-concept, cognitive development, and physical
growth.

The following section discusses the research questions that

were addressed in this study.

Question 1: (Research question 1)
Is the area of residence related to the child’s self-

concept, cognitive development, and physical growth?

201

The results indicated a significant relationship at the
p<.05 level between the area of residence and the child’s
self-concept (Table 24).
Homeland: Children in this area showed the highest mean
scores on self-concept, cognitive development, and physical
growth compared to children from the resettlement and the
farm areas.
Resettlement area: Children in this area showed a higher
mean score for height and head circumference than children
from farm areas.
Farm areae: Children in this area had the lowest mean scores
on self-concept, height, and head circumference. However,
farm children had higher mean scores on cognitive
development and weight than children from the resettlement

area only.

Question 2: (Research questions 9, 10, and 11)
Is the parent’s/guardian’s marital status related to the
child’s self-concept, cognitive development, and physical

growth?

The results indicate a significant relationship at the
p<.05 level between the parent’s marital status and the
child’s self-concept, cognitive development, and physical

growth. Children from married families showed higher mean

202
scores on self-concept, cognitive development, and physical
growth than children from parents who were married but not
living with a spouse, those who were never married, or those

who were divorced or widowed (Table 25).

Question 3: (Research questions 3, 13, and 14)
Is the parent’s/guardian’s socio-economic status as measured
by the level of education related to the child’s self-

concept, cognitive development, and physical growth?

The results indicated a significant relationship at the
p<.05 level between the parent’s/guardian’s level of
education and the child’s self-concept, cognitive
development, and physical growth. Children who came from
families in which a parent/guardian had a bachelor’s degree,
a high school diploma, or a junior secondary school
certificate had higher mean scores on the self-concept,
cognitive development, and physical growth than children
whose parents/guardians had six years of education or less.
Children who came from families where parents/guardians had
a bachelor’s degree (H‘ a high school diploma also showed
higher mean scores on physical growth than children whose
parents/guardians had a junior secondary school education or

six years of education or less (Table 26).

203
Question 4: (Research questions 3, 13, and 15)
Is the parent’s/guardian’s socio-economic status as measured
by the level of occupation related to the child’s self-

concept, cognitive development, and physical growth?

The results indicate a significant relationship at the
p<.05 level between the parent’s/guardian’s level of
occupation and the child’s mean scores on self-concept,
cognitive development and physical growth. Children whose
parents/guardians were employed in semi-professional,
skilled, semi-skilled, or menial jobs had mean scores for
self-concept, cognitive development, and physical growth
which were higher than scores for children whose parents
were not employed. Children whose parents/guardians had
semi-skilled, skilled, and semi-professional positions had
higher mean scores than children whose parents/guardians had

menial jobs (Table 27).

Question 5: (Research question 8)
Is family mobility related to the child’s self-concept,

cognitive development, and physical growth?

The results. indicated a. significant relationship
between family mobility and the child’s mean scores on self-
concept, cognitive development, and physical growth.

Children from families who had never moved or those who had

204
moved only once showed mean scores for self-concept,
cognitive development, and physical growth that were higher
than for children who had moved twice or several times

(Table 28).

Question 6: (Research question 4, 5, and 6)
Is the child’s health condition related to his/her self-

concept, cognitive development, and physical growth?

The results indicated a significant relationship
between the child’s health condition, self-concept,
cognitive development, and physical growth. Children who
were healthy or who were somewhat healthy as perceived by
the parent/guardian had higher mean scores (”1 the self-
concept, cognitive development, and physical growth than
children who were sick. Children who were perceived as
healthy by their parents were also significantly different
from children who were somewhat healthy (Table 29).

Conclusions of the study

The findings of this study have demonstrated that
behavioral development and physical growth of children are
related to factors in the ecosystem of children. For

example, the area of residence, home environment, type

205
of family structure, parent’s socio-economic status, family
mobility, and the child’s health condition as well as gender
show a relationship with the child’s self-concept, cognitive
development, and physical growth. The following section

presents the findings according to residential areas.

Resettlement Children and Families

Children in the resettlement of Thornhill and the farm
areas around Queenstown and the Orange Free State showed
lower mean scores (H1 self-concept, cognitive development,
and physical growth than children from the homeland area.

Both these areas lack the necessary resources and the
opportunities for upward mobility. The resettlement area had
the highest rate of unemployment and the highest rate of
unwed mothers. The home environment as measured by
crowdedness was reported as poor and the land as dry and not
arable. Most houses in the resettlement area had only one
room and were reported by the residents as dilapidated and
in need of renovation. The mean number of people found
living in the household in the resettlement area was 8.35,
this was higher than the mean number of people found in the
homeland 7.31 or the farm areas 6.98 .

Physical growth for children in the resettlement area

is significantly different from children 'hi the homeland.

206

These children showed a mean score for height , weight, and
head circumference that were less than for children in the
homeland. These low mean scores could be attributed to
crowdedness in the household of the resettlement areas. This
finding is consistent with the findings reported by Essen,
Fogel, and Mean (1978). These authors reported a strong
positive correlation between crowding and the rate of growth
of children. For example, children who were growing up in
crowded homes were smaller in stature than children who were
growing up in families with one or two children.

The resettlement showed a high percentage of
parents/guardians who were married but not living with a
spouse. These are some of the young men and women who leave
the resettlement areas to seek jobs in urban areas. As
stated by Fincham (1985) the resettlement area appears to be
a particularly hazardous area in which to raise children. As
indicated by data on hospitalization of children for
kwashiorkor which is a syndrome of malnutrition, this area
has a higher percentage of cases reported than the homeland,
but fewer cases than the farm area. Malnutrition of children
in this area is aggravated by the absence of young men and
women who often leave children in the care of grandparents
to seek jobs in urban areas. This area is also plagued by a
high rate of unemployment. For example, the resettlement

area has the highest rate (62%) of unemployment.

207

Another factor that seems to influence children’s
growth and development is family mobility. The resettlement
area shows that 92% of the families had moved at least twice
and that 41% had moved several times. Data indicated that
families in the resettlement area. moved more often than
families in other areas. Moving from one place to the other
with young children might affect their growth and

development.

Earm Children and Eamiljee

Data from this study indicated that laborers on white-
owned farms showed the lowest levels. of“ education, were
mostly employed in menial jobs and unskilled jobs, and thus
earning a low income. Data also indicated a lack of books,
toys, and games for children in these areas. Therefore farm
children live (H1 limited resources such as food, shelter,
and other resources necessary' for’ developing their’ human
capital. As stated by Fincham (1982) even on white-owned
farms, where there is food, food is not easily available for
blacks and coloreds.

Data from this study indicated that height for age,
which is a measurement of long-term nutritional status,
suggested that farm children who were included in this study

were short for their age and, therefore, likely to be at

208
risk to malnutrition. The highest percentage of
hospitalization was reported in the farm areas. Reasons for
hospitalization were kwashiorkor, pneumonia, and diarrhea.

Data also indicated that most of the houses for black
farm laborers were built with mud. The houses had only one
room and were offered to farm laborers by the white farm
owners as a fringe benefit.

What might be influencing ‘the self-concept and
cognitive development of children who live (Hi white-owned
farms is their dependency on white farmers for resources.
Another factor could be their every day contact with white
children who live in houses that are luxurious by anyone’s
standard.

Another factor that may influence children’s self-
concept and cognitive development on white-owned farms is
the environment of schooling in farm areas. As stated
earlier, white farm owners make decisions as to the number
of schools, teachers, curriculum, the type and condition of
equipment for the schools. More girls than boys were
enrolled in school in the farm areas. Boys are usually
required to work along side their parents. Boys may be
enrolled in school Idepending on the labor supply on a
particular farm.

Black children who live and work on white-owned farms

are socialized ix) treat their white counterparts the same

209
way they treat their white masters. For example, when riding
a van black laborers know that their place is on the back of
the van, much as blacks in the United States before the
civil rights movement in the 60’s knew their place on the
bus. This rule cannot be violated at any time even when
there is room for two people in the front seat. Thus, black
children learn early in life that the color black is

associated with an inferior status and little power.
Homeland Children and Families

Children in the homeland showed higher mean scores on
measures of self-concept, cognitive development, and
physical growth than children from the resettlement and
farm areas. However, the findings indicate that families in
the homeland experience the same kinds of deprivations as
those experienced by the other areas. For example, half of
the families in this area were unemployed. A small
percentage (7%) of children from this area suffered from
kwashiorkor. Thus data in this study indicate that
malnutrition might be a problem in the homeland as well,
however, not as severe as in the other residential areas.
Although the problem is not as severe, it is known that 87%
of children in this study fell below the 5th percentile of

210
the National Center for Health Statistics growth curves on
the measures for height and head circumference.

However, the high mean scores of children from the
homeland (Hi the measures of self-concept, cognitive
development, and physical growth raise many questions as to
possible reasons. These could be attributed to social
factors available - in the homeland area such as
parent’s/guardian’s higher levels of education, the intact
families that are not as prevalent in the other areas, the
availability of high status jobs for the residents such as
teaching in the schools, as well as many other factors that
could lead to a sense of belonging to a community. Parents
from the homeland also reported that their houses were in
better condition than other areas. About one third of the
parents/guardians reported that they read books and told
stories together with their children. These parents have the
highest percentage of interaction with their children.

The homeland also showed the lowest percentage of
family mobility as opposed to the resettlement and farm
areas. Moving from one place to the other might hinder
adaptation of children to their environment. Because
children in the homeland had not moved as much as children
from other areas, these children might have more easily
adapted to their environments even though this area is also

characterized by limited resources.

211
Emancipatory Mode of Rationality

As stated in Chapter three, this research started with
the empirical analytical perspective. Following data
analysis and the interpretation, critical science
perspective which involves the emancipatory rationality is
used.

As stated by Bubolz (1985a) critical science starts
with the assumption that is central to the family ecosystem
framework, that is, families are social products and have
mutually interdependent relationships with the natural,
human constructed, and human behavioral environments. Thus
families cannot be considered apart from these environments.
The aim of critical science is to enlighten and educate; to
emancipate from false consciousness by uncovering factors in
the environment that make people define reality in
particular ways. Thus, this perspective might lead to the
exploration of the historical social structures that led to
the ideology of apartheid in South Africa. Also implied in
the concept of critical science is implementation, that is,
working to design and implement programs for children and
families which would improve their quality of life.

According to Brown (1984) critical theorists hold that
the fact that certain social practices exist does not

justify them, and the fact that certain conceptions of

212
social reality exist does not justify them. Thus, where
repressive social practices exist and lead in) systematic
distortions of moral systems of interaction, and of the
conceptual meaning of language, emancipation becomes the
interest of moving beyond the structures of distorted
communication. The use of the emancipatory rationality leads
to what Habermas calls political-moral action. This is
action which seeks to promote a free and just society.

According to Habermas the social structures and
processes which are dominating and repressive need to be
changed through political action of citizens. Social
evolution, in Habermas’ critical theory of society, comes
about through the development of individual learning
capacities. In this study, learning vfill be achieved by
making community members in and outside of South Africa
become aware of the effects of the policy of apartheid on
black families and make a contribution towards changing this
policy.

This section provides a brief discussion of the roots
and the structure of the policy of apartheid. This
discussion will benefit readers outside South Africa who
might not be familiar with this policy. This might also
explain the reasons for the failure~ of the majority of
blacks in South Africa to acquire higher levels of

education, the failure to be employed in higher occupational

213
levels, and the reasons for black families to be
concentrated in residential areas which lack resources

necessary for the development and growth of children.

The Policy of Apartheid

Apartheid is a form of government that has been in
existence in South Africa since 1948. Many laws and acts
have been passed by the South African government which serve
to entrench and legalize apartheid. The author will
elaborate on some of these laws/acts because the findings of
this study suggest that it is these laws/acts which
influence growth and development. Some of these acts
include: the population registration, land reservation,
education, and employment acts.

Dr. Hendrik Verwoerd who became Minister of South
Africa in 1958 played a leading role as an architect of
apartheid. He studied psychology in South Africa and studied
philosophy in the late 20’s at various German universities.
This is where he had close contact with Hitler’s system of
nazism. When he joined the South African parliament in the
early 40’s he transplanted the fundamental ideologies that
were basic in the system of nazism in the South African
parliament. For example, in Germany the Jews were singled
out as a race unfit to be citizens, because they did not

have ’pure blood’.

214

In South Africa a justification given for racial
discrimination is the preservation of racial purity. In
essence racial discrimination in South Africa has been
maintained in order to preserve white superiority. The
native blacks of South Africa are regarded as inferior and,
therefore, as requiring the guidance of whites who are a
superior race.

A brief discussion of some of the laws/acts which
undergird the policy of apartheid and which were included in

the study is provided in this section.

Population_Registration Act

This act provides for a rigid system of racial
classification. Based on this act everyone in South Africa
is classified as either black, colored, Asian, or white.
According to this act blacks are required to carry
identification documents (passes) which state that they are
classified as ’Bantus’, a label that is greatly abhorred by
blacks of South Africa, because it has the same negative
connotation that the label ’Negro’ has in the United States.
This term has as a result fallen into disuse in South
Africa. However, for consistency the term ’Bantu’ will be
used in this discussion as it was used to name the acts.

These documents are used to monitor and control

the movement of blacks in South Africa. For example, the

215
pass laws are enforced in urban areas more than they are
enforced in rural areas to check on blacks who might be in

the urban areas ’illegally’.

Land Reservation Act

In 1936, the limited franchise that a few blacks
enjoyed was abolished. This disenfranchisement was
formalized legally through the Bantu Self-Government Act
which stripped blacks their South African citizenship and
declared them foreigners in their: own country. This act
declared a territorial and political segregation of blacks
and whites and a separation in residential areas, education,
and jobs.

According to this act blacks are relegated to the
homelands and the resettlement areas. The conditions under
which blacks live in these areas have been already
discussed. Blacks cannot buy land in urban areas. Only
whites, Asians, and coloreds can buy land in urban areas.

Following the Group Area’s Act, the Urban Area’s
Amendment Act was passed in parliament. This act empowers
the Minister of Native Affairs to order the demolition of a
black residential area in the urban areas, and to move all
blacks in that area to another site without consulting them.
This has led to the forced removals from the areas

designated for whites to the resettlement areas.

216
E u ati n A t

In 1953, the white South African government enacted
legislation that created for the first time in the history
of South Africa a government office to deal exclusively with
the education of blacks. The Bantu Education Act gave the
government jurisdiction over all aspects of black education.
The readers must be reminded that in all these acts blacks
were neither consulted nor included at any time when these
decisions which concerned them were made.

When the Prime Minister of Education introduced this
bill in parliament in 1953, he gave the following reason for
the segregated education. "For a white minority to face a
large majority of civilized and educated non-Whites, wishing
to share our way of life, and striving for equality in all
respects would make the fight for a White South Africa
immeasurably more difficult" (Mzimela, 1980 p. 177).

This act has 'led to segregated schools for the
different racial groups. In the schools for blacks the
curriculum is inferior, is monitored, and censored by the
government. Teachers are under qualified and the equipment
is inadequate because of a great disparity in the allocation
of resources to different racial groups. For example, the
expenditure per student during the ,years 1978-1979 shows
$940.00 for a white student and $90.00 for a black student
(South African Institute of Race Relation’s Report, 1980).

217

Job Reservation Act

The job reservation act gives the Minister of Labour
authority to determine which jobs should be reserved for
whites only. For example, in mining blacks may not be
employed in the sampling, surveying, and ventilation
departments. They also may not by law hold senior positions
in industries or supervise whites. Needless to say that even
if blacks had a choice in the matter, the type and the level
of education that a few blacks manage to receive would not
allow them to qualify for these jobs. The South African
government has many laws/acts that are used to enforce
apartheid. However, for the purpose of this study the acts
that have been discussed above will suffice.

Under the policy of apartheid black parents are both
rightless and powerless. Consequently, their children are
denied all the rights of children as declared by the United
Nations General Assembly Act of 1959.

As stated by Kunene (1979) these children are made to
suffer not only from malnutrition and from poverty related
diseases, they are also made to suffer from a ’victim
syndrome’. All these factors interact to influence the
social-emotional, cognitive development, and physical growth
of children. Some of these children grow up not knowing

their own potential talents which are stunted by the laws

218
that have been created by the South African government. Many
of these children do run: even live long enough for their

parents to enjoy and help them realize the talents in them.

"Full many a gem of purest ray serene

The dark unfathomed caves of ocean bear:
Full many a flower is born to blush unseen
And waste its sweetness on the desert air."
Elegy Written in a Country Church Yard by
Thomas Gray (Starr, 1968).

This passage encapsulates the rich human potential
which is available in black children in the homeland,
resettlement, and the farm areas, which under the policy of
apartheid is ignored, wasted, and rarely developed or
utilized.

From this study it can be concluded that black families
in the rural areas of South Africa live in a condition of
unequal access to resources and knowledge that are found in
the natural, human constructed, and behavioral environments
in which these families are embedded. Black families are
thus trapped in conditions of political, social, and
economic deprivation and their children are also likely to
be trapped in the same condition. It is these environments
that contribute to the culture of deprivation which hinders

these families from getting better levels of education,

219
occupation, and ix) earn a better income that would enable
them to improve their quality of life.

However, despite the conditions of deprivation in the
rural areas of South Africa in which black families live,
these families show a powerful intrinsic survival mechanism.
This mechanism is termed by Davis (1984) a survival dynamic.
It is in fact a cultural mechanism used by the poor to
counteract the difficulties imposed upon them by the
political, economic, and social factors.

This survival dynamic operates on both the individual
and the community levels. On the individual level it is
evident in how black families especially those from the farm
and the resettlement areas survive with the barest minimum
resources available to them. These include the lack of
political power, land, housing, food, and other essentials
of life. It is also evident in how blacks in South Africa
have persisted to find ways to restore their identity and
selfworth.

At the family and community levels it is shown by the
persistence to maintain stable family forms despite the
government’s efforts to recruit and separate black family
members through the migratory labor system. Black families
have also persisted to find ways to start building new
communities to meet the psychological and physical needs of

residents despite the government’s efforts to break

220
communities by demolishing houses and forcing residents to
move to ’unknown places’.

The high mean scores of self-concept, cognitive
development, and physical growth for children in the
homeland also show this survival mechanism which has helped
these children to adapt to the impoverished environment of
the homeland.

The researcher is not in support of the kind of
adaptation that children in the homelands of South Africa
and other areas are forced to make in order to survive.
Children should be treated equally' and be provided with
enough food and decent accommodation, and be able to live
with their parents, and be provided with educational and
health services that will enhance physical growth,
cognitive, and social-emotional development. The ability of
the poor to adapt to the most hostile environments of the
homeland, resettlement, and the farm areas leads the
government of South Africa to be convinced that the policy
of apartheid is working, and thus there is no need to change

it.
Implications of the Study
This study demonstrates two implications: theoretical

and practical. This study has shown the viability of the

ecosystem framework' in studies designed to examine

221
behavioral development and physical growth of black children
in South Africa.

This study suggests that the syndrome of malnutrition
is embedded in a multiplicity of factors in the children’s
ecosystem. Thus any effort to improve the development and
growth of black children in South Africa should take into
consideration all levels of the child’s ecosystem from the
micro to the macro level.

The effort to improve growth and the development of
these children can be achieved at two levels. The first and
a more pressing effort involves the institution of cost-
effective strategies within the present social, economic,
and political climate, so that the immediate needs of the
vulnerable groups can be met. These might include community
health care, nutrition, and food information programs, adult
education programs, job training skills, community
development skills, and preschools which aim at the holistic
development of children.

However, for intervention projects in black communities
in South Africa to be successful and to have long lasting
effects, factors at the macro level should be addressed.
Thus the second effort must be a restructuring in the
distribution of resources so that there is equal access to
political power among different racial groups, allocation of

land, educational and ;hfl> opportunities, health care, and

222
social welfare services. This action will lead to what
Habermas calls political-moral action. This is action which

seeks good for the people.
Suggestions for the Future

A secondary objective of this study is to examine ways
to further develop and refine the ecosystem framework. The
following section gives some of the methods that might be
used to improve the ecosystem framework. Some of the most
important ways to develop and refine theoretical frameworks
were suggested by Nye (1978) and Holman and Burr (1980).

For example, Nye (1978) has suggested a "Causal
Analysis Model”. This is a very refined system of analysis
because the researcher is forced to state the direction of
causality between each interrelated variable it: the
analysis. The findings of this study indicate significant
relationships between the variables that were selected for
this study. Therefore, a multi-causal model might be the
best method for organizing the findings for this study.
Causal models that could be used include: a path analysis
model, time-series design which is recommended by Schucts
and Hicks (1981), and the linear estimation of structural
relationships (LISREL) which is recommended by Joreskog and
Sorbom (1978). All these models might be suitable methods of

data analysis for describing the ecosystem framework.

223

Cross-cultural studies might also contribute to
building new concepts and for testing already existing
concepts. This suggests that family scholars in the United
States need ix» look beyond their borders to expand their
pool of concepts.

Another way to, foster creativity and efficiency in
developing the ecosystem framework would be to encourage a
network of scholars from different disciplines such as
biology, sociology, anthropology, and geography for they can
help to clarify the complexities cH’ the human ecosystem
framework.

In conclusion then, the ecosystem framework has a place
and future in family theory. What needs to be done is to
achieve what Christensen (1964) has called theoretically
oriented research and empirically oriented theory. Thus,
there is a need to focus on building on already existing
theoretical frameworks such as the ecosystem framework. This
process includes the discoveny of new concepts and
propositions relevant to this framework. The next step would
be the application of this theoretical framework in
research.

There is also a need for students and scholars in human
ecology to become engaged in critical science. As stated by
Bubolz (1985a) in critical science, theory and practice are
not separate. She also adds that in critical science the

role of a scientist becomes that of political actor.

224
Therefore, a critical scientist engages in research that has
social policy as its implication, in order to influence the

political-social milieu and bring about changes in society.

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APPENDICES

APPENDIX A

Instruments

245

Junior South African Individual Scale (JSAIS)
Vocabulary

Quantitative skills

Copying

._——.r. _—

 

....-.— _—‘

245A

VOCABULARY (3 T0 7 YEARS)

Cards a and b are presented to three- to five-year-olds only. Irrespective of the
score 6n these cards, the picture booklet is then presented. Where necessary, help
three- to five-year-olds with Items 1, ii, v and 1-3 of the picture booklet.

Six- and seven-year-olds start with Item 5 of the picture booklet after they have
done the two practice examples. If Example 3 is done correctly without a551stance,
ive 1 point. If necessary, children in this age group may be helped with Item 5.

(See Manual for full details.)
Discontinue after 4 consecutive failures on the items of the picture booklet.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Item 5:6nse chreo Item Egense lCEFEO
card a
Ex. Key 11. friendly b
i lock (help) 12. swan c
ii lamp (help) 13.. calendar d
iii drum 14. wool b
iv cradle 15. sad c
curd b 16. temperature c
v going up u (help) 17. fear a
vi pulling something 18. weapon b
Picture booklet 19. freckles b
Ex. a tree b 20. swarm a
b boiling b - 21. flame a
1. tortoise (help) c 22. abyss a
2. gate (help) c ' 23. funny a
3. dreaming (help) d 24. vehicle c
4. tricycle ‘ b 25. insect c
5. sieve (help 6/7y.)d 26. reptile d
6. turkey . ' d 27. fastest b
7. fence 6 28. pair a
8. teasing, a 29. astonishment b
9. straight c 30. reflection b
10. hurrying b 31. aquarium a
32. motionless a
Max. = 39
Total
raw score
Scaled
score

 

 

 

NUMBER AND QUANTITY CONCEPTS:

is answered correctly.

Six- and seven-year-olds start with Item 8.
Discontinue after 3 consecutive failures.

2458

PART A (3 TO 7 YEARS)
Three- to five-year-olds start with the example for which 1 point is given if it

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Item Score Item Score
1 or O 1 or 0
Ex. balls 15. stars
1. sticks 16. glasses
2. stars 17. apples
3 birds 18. dots
4. fish 19. pigs -
5. poles 20. bird cages
6. buttons 21. birds
7. hearts 22. 7} of a tart
8. ropes (help 6/7 yrs) 23. scales
9. ducks 24. birds sitting on fence
10. buttons 25. cups/saucers
11. buttons 26. socks
12. dots 27. small bags
13. ink 28. marbles
14. I of a tart 29. walking-sticks
30. watohes
Max.=31
A: Total
raw score
Use the A scaled score for calculating A: Scaled
score

GIQ for three- to five-year-olds.

 

 

COPYING (4 TO 7 YEARS)

All testees start with Item 1.
vvil I not copy any further designs.

24

Discontinue when the child obviously cannot or

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Item .Score
1. 0-2
2. _L— 0-2
3. 0-2
4. C::j 0-2
5. 0-2
6. l1: \\ 0-2
7. 5 0-2
9. O<l 0-3
10. {:::) 0-3
11. ~ 0-3
Max. = 29
Total raw
score
Scaled

 

score

 

 

 

 

 

 

- ‘~-—- -——

.-.—— -.-— .—--——-.—.

246

Self Concept

' 246A

....

 

Scoring sheet for Brown ~- IDS Self Concept Referents Test

Example of question format: 1.

10.

ll.

13.

14.

2.
Item

Happy-sad

Clean-dirty

Good looking-ugly

Likes to play with other
kids-doesn't like to play

with other kids

Likes to have own things-
likes to have other kids
things '

,Good-bed

Likes to talk a lot-
doesn't like to talk
a lot _

Smart-stupid

Scared of a lot of things- -

not scared of a lot of
things

Scared of a lot of people-
not scared of a lot of
people

Likes the way clothes look-
doesn't like the way
clothes look

Strong-weak
Healthy-sick
Likes the way (my) face

looks- doesn't like the way
(my) face looks

*Kote: Score values 3

Now tell me, is Johnny Callager happy
or is he sad? ’

Does Johnny Callager's mother think
Johnny Callager is happy or sad?

Est.

Score*

1,0
1,0
1,0

1,0

1,0

1,0

1,0

1,9

1,0
1,0

1,0

L.)

U!

“other
Score

1,0
1,0
1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0
1,0

1,0

Teacher
Score

1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0

1,0

Peer
Score

1,0

‘1,0

1,0

1,0

1,0

1,0

1,0

p rrllel order in which adjectives are presented.

247

National Center for Health Statistics Norms

Table 4. Obsuvcd pucenmcs 01 head civcum'mence (in cemimetcnl, by so: and age: Fol! fluemch Immune, him»? you.

247A

 

Observed pevcemile

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sex and .90 n
5m 1 10m 1 25114 1 50m I 75m I 9041: L95m
My: Head civcumlevence in centimeters

Birth ........... 155 32.2 32.6 33.6 34.6 35.5 36.4 37.2
1 month ..................................... 276 35.2 35.7 36.4 37.3 38.2 39.2 39.6
3 months ................. 436 38.2 38.7 39.6 40.6 41.6 42.5 43.1
6 months ................... 421 41.6 42.0 42.8 43.7 44.7 45.6 46.2
9 months ............................... 362 43.6 44.1 44.9 45.8 46.7 47.4 48.0
1 year .. 366 44.7 45.2 46.1 47.1 47.8 48.8 49.3
1 '5 years 459 46.2 46.7 47.4 48.3 49.3 50.2 50.6
2 yew: .- 415 47.2 47.7 48.3 49.2 50.2 50.9 51.3
2‘}: years ...................................................... 332 48.1 48.5 49.2 50.0 51.1 51.8 52.3

3 vents . 240 48.5 48.8 49.6 50.4 51.4 52.2 52.71
3% years ............................................ 202 48.9 49.2 50.0 50.9 51.9 52.7 53.3
4 you! . ............................................ 185 49.3 49.6 50.1 51.0 52.1 53.0 53.2
4% you: ..................................... 181 49.5 50.0 50.4 51.4 52.5 53.4 54.1
5 years .-.. 158 49.7 50.0 50.6 51.7 52.6 53.8 54.1
5‘!» years ........................................ 134 50.0 50.4 51.2 52.0 53.0 53.9 54.5
6 years ........ 138 50.2 50.5 51.2 52.2 53.2 54.0 55.3
6% your: ..................... 48 50.5 50.6 51.5 52.5 53.3 54.0 54.2
7 years .. . 130 50.6 50.7 51.6 52.5 53.4 54.2 54.6

Female

Biuh ........................................... 145 31.5 32.4 33.2 34.1 34.7 35.6 35.9
1 month ~ 243 34.6 35.1 35.8 36.5 37.2 37.8 38.3
3 months ............................................. 405 37.1 37.7 36.6 39.5 40.4 41.2 41.7
6 months ................................................... 398 40.4 40.8 41.6 42.4 43.3 44.2 44.6
9 montfi! .. 341 42.3 43.0 43.6 44.4 45.2 46.0 46.3
. 1 year 320 43.5 44.: 44.3 45.6 45.4 41.2 47.7
1% Vents ..................................... 439 45.0 45.5 46.2 47.1 47.8 48.2 49.1
2 years ................ 395 46.1 46.6 47.3 48.1 48.8 49.6 50.2
2% years ............................................... 332 47.0 47.3 47.9 48.7 49.5 50.3 50.8
3 ye." ............................... 226 47.6 47.9 48.6 49.3 49.9 50.8 51.4
3‘/. years ............. 177 4 7.9 48.4 48.8 49.6 50.5 51.2 51.8
4 years ................................ 178 48.0 48.5 49.0 50.0 50.8 51.6 52.2
472 yen: .................................................................................... 157 48.4 48.9 49.5 50.3 51.0 51.9 52.5
5 Vents ............................................... 148 48.6 49.0 49.6 50.5 51.4 52.0 52.6
5% yean ..... . .............................................................................. 129 48.8 49.4 50.0 50.9 51.8 52.4 53.2
6 V2.7! 130 49.0 49.5 50.1 51.2 52.0 52.8 53.5
6% veers .................................... 51 48.9 49.5 50.1 51.4 51.8 52.8 53.2
7 years .................................................. 123 49.4 49.7 50.5 51.6 52.3 53.4 54.2

 

 

 

 

 

 

 

 

 

NOTE: n ' sample size.

26

 

Teble 6. Observed percentiles 01 stature (in centlmetersl, by sex and age: Nllionel Center lor Harm Stetistlcs. 2-24 veers

PO
4:
\J

[75

 

Observed percentile

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sex end ege N'
5m I 10m I 251» I son. 1 75m I 90th I 9541.
M Steture in centimeters
2.00-2.25 veers 419 82.6 83.5 86.1 87.8 90.3 91.9 97.3
2.25-2.75 veers ............................................................ 945 86.1 87.0 89.0 91.2 93.8 97.3 98.3
2.75-3.25 veers .......................................................... 785 88.9 90.5 92.4 95.1 97.2 100.1 101.2
3.25-3.75 veers . .. .................. 857 92.1 93.3 95.7 98.2 101.1 102.8 104.4
3.75-4.25 veers ........ .............................................. 856 96.2 97.3 100.0 102.6 105.3 107.5 110.8
4.25-4.75 veers . ..................... 937 98.0 100.2 103.4 105.8 108.6 111.8 113.2
4.75-5.25 veers .................... 874 100.7 103.2 105.5 108.8 112.4 115.4 116.5
5.25-5.75 veers ............................... 878 106.2 107.7 110.1 113.5 116.1 118.2 119.5
5.75-6.25 veers . . ......................................... 908 108.5 110.1 112.8 117.0 119.4 122.2 123.1
6.25-6.75 veers .................................................................. 1,033 108.9 110.0 114.8 118.2 121.9 125.0 127.1
6.75-7.25 veers ....................................................................... 988 114.1 115.6 118.5 122.3 125.9 128.3 129.8
7.25-7.75 veers ...... . ................................................................ 1,120 115.6 118.3 120.8 124.5 127.9 131.4 133.4
7.75-8.25 veers ................................... 1.014 119.3 121.0 123.8 127.9 131.7 134.9 138.0
8.25-8.75 veers 902 121.2 123.4 126.2 129.6 133.2 136.4 138.8
8.75-9.25 veers ....................................................................... 943 121.1 124.5 127.5 132.8 136.3 139.4 141.9
9.25-9.75 veers 958 125.2 127.7 131.2 135.0 138.7 142.7 144.7
9.75-10.25 veers ................................................................. 1,030 127.3 130.0 133.7 138.8 142.1 145.9 149.0
10.25-10.75 veers ................................................................... 1.070 130.5 132.5 135.8 139.4 144.1 148.4 151.4
10.751 1.25 veers ................................................................... 1,052 132.5 135.3 138.7 143.5 147.9 151.4 154.0
11.25-11.75 veers ................................................................... 952 135.1 138.0 141.4 145.8 150.8 154.5 156.1
11.75-12.25 veers ................................................................... 1.010 138.5 140.1 144.1 148.6 153.7 159.4 162.8
12.25-12.75 veers ...... . ............................................................ 1,092 139.3 141.8 146.4 152.1 157.2 162.6 165.5
12.75-13.25 veers ................................................................... 1.155 142.2 144.8 149.7 154.8 159.6 165.3 167.8
13.25-13.75 veers .. ..... . ......... . ................................................. 1.056 145.6 148.6 153.6 160.0 166.5 172.2 175.5
13.75-14.25 veers ................................... 954 149.2 153.0 157.7 164.4 169.9 175.1 177.6
14.25-14.75 veers ........................... 1.019 152.9 156.4 161.1 167.8 173.1 177.8 179.4
14.75-15.25 veers ............................ 1,112 155 0 157.6 163.0 169.4 173.8 178.2 181.8
15.25-15.75 veers ..... . ............................................................. 914 158.8 161.4 166.6 171.6 175.4 180.4 183.4
15.75-16.25 veers ............................................................ 1,051 160.5 164.3 169.0 173.5 177.8 181.5 185.8
16.25-16.75 veers ................................................................... 876 163.8 165.5 170.6 174.9 179.5 183.3 186.4
16.75-17.25 veers ..................... 1,054 164.4 166.2 170.7 176.8 181.8 184.6 187.3
17.25-17.75 veers ................................................................... 935 163.3 167.7 172.1 176.4 181.0 185.0 187.8
17.75-18.25 veers ................................................................... 866 166.5 170.1 173.1 176.0 180.2 186.1 187.3
18.25-19.00 veers . .................................................................. 1.067 166.8 169.3 172.0 175.8 180.1 185.9 186.8
19.00-20.00 veers ................................................................... 1,770 162.8 166.9 171.6 177.2 180.8 185.0 186.2
20.00-21.00 veers ................................................................... 1.668 159.4 168.4 172.2 177.4 181.2 183.6 185.8
21.00-22.00 veers . .. .............................. 1,703 166.2 168.3 172.5 177.3 181.1 184.8 190.0
22.00-23.00 veers ................................................................... 1.662 167.2 167.7 171.3 177.1 180.6 187.1 192.0
23.00-24.00 veers ................................................................... 1,589 161.3 165.3 172.3 176.8 183.0 188.5 189.2
24.002500 veers ................................................................... 1,595 165.4 168.5 172.9 178.1 183.0 186.7 189.5

 

 

 

 

lSemple sire expressed in tlmusemls. 'l'lrc N's 01 tlsuse cells containing: suhjects lrom 1mm llANl-IS 1 end Ill-l8 II or 11158 111 heve

been cut in hell to meintein representstlveness.

28

247C

Tebte 6. Observed percentiles ol stature (in centimetersl, by sex end age: National Center lor Health Statistics, 2-24 veers—Con.

 

Observed percentile

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sex and age N|
51h 10m 25m 50m 75m 90m 9511»
Female Stature in centimeters
2.00-2.25 veers - .. ........................................... 440 81.3 82.5 84.6 86.8 89.9 93.6 94.6
2.25-2.75 veers ....................................................................... 972 84.2 85.3 87.1 90.3 93.4 94.8 96.4
2.75-3.25 veers .. ........................................... 622 90.2 90.7 92.7 95.3 96.7 99.1 100.6
3.25-3.75 veers ....................................................................... 887 91.8 92.8 95.0 97.4 99.8 102.1 103.6
3.75-4.25 veers _ ............ 775 94.8 96.2 97.9 100.5 103.8 106.0 108.2
4.25-4.75 veers ................................................................... 848 96.8 97.6 100.5 103.8 106.2 109.4 112.0
4.75-5.25 veers ....................................................................... 876 99.1 101.1 105.2 108.1 111.6 113.7 114.7
5.25-5.75 veers ....... . .............................. . ......................... . 890 103.8 106.1 108.4 111.8 115.5 118.7 121.3
5.75-6.25 veers ............... . ....................... . ............... 866 107.1 109.0 111.9 115.4 118.8 122.1 124.6
6.25-6.75 veers .................................................................... 1,025 109.3 111.6 114.3 117.7 121.7 125.2 126.9
6.75-7.25 veers ....................................................................... 945 111.7 113.2 117.4 120.8 124.3 126.8 128.6
7.25-7.75 veers ................................................................... 952 115.8 117.2 120.0 123.7 127.9 131.7 134.2
7.75-8.25 veers 1.004 117.8 119.5 122.8 127.5 130.6 132.9 134.6
8.25-8.75 veers ....................................................................... 968 118.9 121.4 124.4 129.2 133.4 135.8 138.0
8.75-9.25 veers ....................................................................... 988 122.2 124.8 128.4 132.7 137.7 141.0 142.3
9.25-9. 75 veers ....................................................................... 885 126.6 127.6 131.1 135.1 139.8 144.4 147.6
9.75-10.25 veers ..................................................................... 1,092 129.0 130.3 134.4 138.5 143.0 147.0 149.8
10.25-10.75 veers ................................................................... 1,086 129.4 131.1 135.2 140.6 144.7 149.8 152.4
10.75-11.25 veers ................................................................... 870 132.1 134.8 139.5 143.9 148.8 153.7 157.0
11.25-11.75 veers ................................................................... 862 134.5 135.8 141.7 147.3 152.6 157.1 158.8
11.75-12.25 veers ................................................................... 1,082 139.4 142.2 146.7 151.8 156.4 161.4 165.9
12.25-12.75 veers ................................................................... 1,019 141.7 145.9 150.8 154.8 159.7 164.0 165.7
12.75-13.25 veers ................................................................... 1,058 143.7 147.7 153.0 157.5 161.4 165.5 167.4
13.251175 veers ................................................................... 1,120 149.4 151.6 155.4 159.6 163.8 165.9 169.2
13.75-14.25 veers ................................................................... 1,080 149.8 151.6 155.7 160.0 163.4 167.1 168.7
14.25-14.75 veers ................................................................... 951 150.3 153.2 157.4 161.6 165.4 169.5 171.1
14.75-15.25 veers 1.012 151.5 153.3 157.2 161.2 166.3 171.2 174.9
152545.75 veers ................................................................... 980 152.6 154.8 157.9 162.9 167.6 172.1 176.2
15.75-16.25 veers ................................................................... 959 152.5 154.8 158.2 163.6 167.7 170.7 172.3
16.25-16.75 veers ...... ............................................................. 836 150.7 153.3 157.6 162.1 166.5 171.5 172.6
16.75-17.25 veers ............ . ............... . ....................... 1.108 151.8 154.6 158.0 161.8 166.5 171.6 173.8
17.25-17.75 veers - ........................... 810 150.7 154.3 158.0 162.6 166.6 170.0 172.5
17.75-18.25 veers ................................................................... 826 152.2 155.5 159.8 163.9 168.0 171.0 171.8
18.25-19.00 veers ................................................................... 1,420 154.9 157.8 161.2 165.3 167.2 172.4 174.2
19.00-20.00 veers ................................................................... 1,384 155.0 155.9 159.9 163.0 166.8 170.6 173.1
20.00-21.00 veers ................................................................... 1.771 152.3 155.1 159.0 163.2 168.8 172.4 175.3
21.00-22.00 veers ................................................................... 1,818 152.0 154.6 158.5 162.5 167.0 170.8 173.0
22.00-23.00 veers ................................................................... 1,734 150.4 153.0 156.9 162.8 167.2 171.2 174.5
23.00-24.00 veers ................................................................... 1,800 154.2 156.0 158.6 163.1 166.8 170.5 172.6
24.00-25.00 veers ................................................................... 1,796 152.3 155.4 158.3 162.3 167.4 170.4 171.6

 

 

 

 

'Sample size expressed 1n tlinusenrls. Tln: N's nl' tlmse cells crmtalnlng subjects from lmth llANl-ZS I and 111-28 11 or 111-ZS Ill heve

been cut in lrelf tn nmintein representativeness.

1

Teble 7. Observed percentiles 01 might (in kilnrjrernsl, by sex and ego: Netirmel Center lor Health Statistics. 22" veers

247D

 

Observed percentile

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sex and age N.
5m tom 25m 50m 75m 90m 95m
1125 Weight in kilograms
2.00-2.25 veers ....................................................................... 419 9.97 11.10 11.63 12.67 14.05 14.85 1547
2.25-2.75 veers ....................................................................... 945 11.31 11.89 12.63 13.53 14.57 15.69 16.80
2.75-3.25 veers ..................................... 785 12.28 12.84 13.55 14.43 15.34 16.39 17.37
3.25-3.75 veers 857 12.70 13.34 14.33 15.39 16.46 17.77 18.63
3.75-4.25 veers . ...................................................................... 856 13.83 14.70 15.46 16.64 17.85 18.87 20.62
4.25-4.75 veers 93 7 14.42 15.09 16.02 17.71 19.17 20.45 21.51
4.75-5.25 veers ....................................................................... 874 14.99 15.52 16.91 18.47 20.22 21.02 22.59
5.25-5.75 veers ....................................................................... 878 17.01 17.31 18.33 19.88 21.39 23.21 25.32
5.75-6.25 veers - .......................................... 908 16.87 17.80 19.53 21.21 22.85 24.98 26.40
6.256. 75 veers .. 1.033 17.21 17.82 19.70 21.59 23.41 26.21 28.18
6.75-7.25 veers 992 18.59 19.39 21.37 22.93 25.22 28.74 30. 72
7.25-7.75 veers ....................................................................... 1.120 18.76 20.07 22.04 24.33 26.48 29.08 3231
7.75-8.25 veers ....................................................................... 1.014 20.20 21.47 23.47 25.65 28.70 31.36 35.15
8.25-8.75 veers ....................................................................... 902 21.71 22.63 24.35 26.31 29.27 33.08 34.96
8. 75-9.25 veers 943 22.01 22.98 25.13 27.89 31.75 36.82 4023
9.25-9.75 veers ....................................................................... 958 23.11 24.30 26.40 29.65 33.63 38.58 45.67
9.75-10.25 veers 1,030 24.40 25.63 27.98 31.83 36.09 41.08 43.69
10.25-10.75 veers . 1,070 26.09 27.73 29.49 32.57 36.39 40.75 45.66
10.75-11.25 veers .. 1.052 27.98 28.79 31.23 35.86 39.68 44.71 51.83
11.25-11.75 veers 952 28.17 30.14 34.07 37.48 41.94 47.16 52.45
11.75-12.25 veers ................................................................... 1,010 30.10 31.18 34.21 38.75 46.43 55.24 62.43
12.25-12.75 veers ................................................................... 1,092 31.72 32.98 36.18 41.98 47.30 54.05 58.45
12.75-13.25 veers ................................................................... 1.155 32.17 34.61 38.43 43.62 50 17 59.22 64.29
13.25-13.75 veers ................................................................... 1.056 36.24 37.80 42.92 49.23 58.38 63.44 68.39
13.75—14.25 veers ................................................................... 954 38.25 41.47 46.98 51.65 60.77 67.04 76.61
14.25-14.75 veers 1.019 40.52 43.64 49.70 55.32 62.62 72.69 77.03
14.75-15.25 veers 1,112 42.14 44.93 50.35 56.35 63.63 71.27 76.91
15.25-15. 75 veers ................................................................... 914 46.26 49.12 54.29 58.92 66.68 75.40 81.81
15.75-16.25 veers ................................................................... 1.051 46.83 51.29 55.79 61.74 69.33 76.78 86.07
16.25-16.75 veers ................................................................... 876 50.46 53.22 56. 77 64.71 72.28 81.62 87.57
16.75—17.25 veers ................................................................... 1.054 52.15 55.42 60.65 65.90 73.76 81.72 91.23
1 7.25-17.75 veers .. 935 51.80 55.53 60.81 66.64 75.36 83.35 92.16
17.75-18.25 veers ................................................................... 866 54.76 58.18 62.04 68.96 75.49 88.36 94.71
18.25-19.00 veers 1,067 54.96 60.35 63.62 69.88 78.67 92.66 99.60
19.00-20.00 veers ................................................................... 1.770 55.40 57.38 65.91 70.66 76.43 87.01 96.48
20.00-21.00 veers ................................................................... 1.668 55.86 57.71 65.04 71.89 78.44 88.86 94.84
21.00-22.00 veers ................................................................... 1.703 52.66 58.17 65.29 72.12 80.96 89.04 96.13
22.00-23.00 veers ................................................................... 1.662 55.02 59.14 65.09 71.77 79.66 90.57 96.93
moo-24.00 veers ................................................................... 1.589 59.16 60.69 65.54 74.71 82.44 94.05 105.35
24.00-25.00 veers ............................ 1.595 60.87 63.96 67.96 79.37 85.69 97.60 103.19

 

1Sample the expressed in tlnnrsenils. l'lre N's n1 those cells wntelnlne subjects lrnrn lrotlr IIANLS l and ill-ZS 11 or 111.8 111 have

been cut in ltell tn meintein representativeness.

30

247E

Teble 7. Observed percentiles 01 weight lin kilogrernsl, by sex and age: National Center lor Health Statistics, 2-24 years—Con.

 

 

Observed percentile

 

 

 

 

 

 

 

 

 

Sex end age N|
5m 1 10th I 25th 1 50m l 75th I 90th I 95111
Female Weight in kilograms
ZOO-2.25 veers ....................................................................... 440 10.06 10.66 11.41 12.21 12.86 13.84 14.57
2.25-2.75 veers ....................................................................... 972 10.77 11.20 11.98 12.76 13.94 14.74 15.09
2.75-3.25 veers ....................................................................... 622 12.14 12.40 13.12 13.93 15.61 16.84 17.74
3.25-3.75 veers 887 12.29 13.03 13.58 14.60 15.93 17.54 18.28
3.75-4.25 veers ....................................................................... 775 13. 13 13.63 14.51 15.68 17.15 18.22 18.94
4.25-4.75 veers ....................................................................... 848 13.45 14.05 15.04 16.57 17.78 19.35 20.26
4.75-5.25 veers ....................................................................... 876 14.33 15.21 16.48 17.73 19.66 21.23 22.10
5.25-5.75 veers ....................................................................... 890 15.18 16.20 17.47 18.92 20.96 23.44 25.01
5.75-6.25 veers ....................................................................... 866 15.99 17.09 18.21 20.19 22.39 24.88 28.71
6256.75 veers ....................................................................... 1,025 17.02 17.71 19.24 21.06 23.55 26.17 27.89
6.75-7.25 veers 945 17.86 18.74 20.20 22.13 23.98 26.91 29.58
7.25-7.75 veers ....................................................................... 952 18.84 19.60 21.33 23.72 26.54 29.61 31.55
7.75-8.25 veers 1.004 20.11 20.79 22.49 24.89 27.73 32.63 35.20
8.25-8.75 veers 968 20.47 21.50 23.30 26.39 29.69 33.65 36.45
8.75-9.25 veers ....................................................................... 988 22.20 23.17 25.27 28.79 33.40 39.66 42.69
9.25-9.75 veers ....................................................................... 885 23.29 24.72 26.92 30.26 34.54 39.87 43.62
9.75-10.25 veers ..................................................................... 1,092 24.34 25.25 28.03 31.68 36.38 43.16 45.92
10.25-10.75 veers ................................................................... 1,086 25.28 26.69 29.42 33.00 37.63 45.90 48.37
10.75-11.25 veers ................................................................... 870 26.73 28.32 32.09 36.13 42.27 47.72 54.49
11.25-11.75 veers ................................................................... 862 27.44 29.45 32.88 37.97 44.38 50.77 58.09
11.75-12.25 veers ................................................................... 1,082 29.72 32.74 36.42 41.70 48.78 57.77 64.79
12.25-12.75 veers - .. ..................................... 1.019 32.59 34.97 39.46 45.37 51.40 58.10 63.21
12.75-13.25 veers ................................................................... 1,058 34.21 37.17 41.44 47.06 54.79 62.20 66.61
13.25-13.75 veers ................................................................... 1,120 37.72 39.45 45.00 50.30 56.81 67.05 75.78
13.75-14.25 veers . .................................................................. 1.080 37.74 39.86 44.86 50.22 56.44 66.44 74.70
14.25-14.75 veers ................................................................... 951 40.77 42.96 47.21 53.03 60.95 68.88 78.43
14.75-15.25 veers ................................................................... 1,012 41.14 43.65 47.48 53.29 59.72 71.57 75.36
15.25-15.75 veers ................................................................... 980 42.99 46.11 48.98 55.25 60.80 71.45 77.78
15.75-16.25 veers ................................................................... 959 43.64 45.74 49.22 54.92 61.58 67.70 78.03
16.25-16.75 veers ................................................................... 836 43.86 45.69 49.46 54.97 62.64 72.37 83.10
16.75-17.25 veers ................................................................... 1,108 43.87 45.57. 50.76 56.49 62.22 72.45 84.19
17.25 17.75 veers 810 42.90 45.36 50.56 55.23 61.59 70.62 84.82
17.75-18.25 veers ................................................................... 826 45.05 47.89 52.68 57.68 62.32 69.62 75.86
18.25-19.00 veers 1,420 44.83 45.89 51.03 56.97 63.16 72.62 78.70
19.00-20.00 veers ................................................................... 1,384 48.65 48.83 51.62 57.24 63.48 76.33 83.48
20.00-21.00 veers ................................................................... 1,771 44.40 47.23 51.70 57.22 63.94 72.15 75.89
21.00-22.00 veers 1,818 46.08 48.54 52.15 58.36 64.64 72.88 81.76
22.00-23.00 veers ................................................................... 1.734 42.86 46.18 51.35 58.82 67.38 75.54 85.35
210024.00 years ................................................................... 1,800 45.59 47.77 52.16 59.87 64.64 72.80 84.62
24.00-25.00 years ................................................................... 1,796 46.65 48.13 52.06 58.88 66.33 77.17 86.04

 

 

 

'Semple she expressed in tlumsentls. The N's of those cells crmteining subjects frnrn lmlh llANl-L'S l and 111-25 11 or Ill-SS lll heve

been cut in 11311 to rrminteirr representativeness.

1

31

248

Parent Questionnaire

249
PARENT INTERVIEW QUESTIONNAIRE
Background Information

1. Name of Parent/Guardian

2. Sex: M F
3. Date of Birth: Month ______ Day ______ Year ______ Age
4. What is your religion: ___ Methodist
____ Catholic
Anglican

Apostolic Church
Other, what is it?

____ None
5. Which of the following best fits you?
____ Married, living with spouse
Married, but not living

with spouse
Never married

Divorced
Widowed
Separated

Living together, not

married

6. People living in the household besides yourself.

Number Sex/Age Relationship Education Job Part-time

NHOOCDNO'tm-ths—r

1—45—41—0

7 How long have you and child lived at this address?

How long have you lived in this area?

 

250

If family has lived at current address fewer years than
age of child, ask:

7.1 How many times have you and child moved?
_ Several times

Twice

Once

Never

7.2 Where have you and child lived before?

_ Same place, different
location

Different place

Rural area

___ Urban
___ Other
7.3 What were the reasons for moving?
I.
2.
3.
4.

7.4 If you had a choice, where would you rather live?

Socio Economic Status
Level of Education

8. What is the highest level of formal school that you
have completed?

no schooling

less than standard 6 of primary schools
six years of primary school

completed Junior secondary school
completed high school

Bachelor’s degree

Master’s degree

____ Ph.D.
Other (please specify)

251

8.1 Have you had any other training other than one
mentioned above?
____ Yes
No

8.2 If yes, please specify your field of training
1.
2.

Occupation

9. Are you presently employed: ____ yes
no

9.1 If yes, are you working: full-time or half-time?

__ full-time
_ half-time

9.2 What is your job?

1. No job (if 1 go to next line).

2. Menial service work (janitor, private household
worker, farm laborer)

3. Unskilled worker (bartender, gas station
attendants).

4. Semi-skilled worker (barber, dressmaker, except
factory workers).

5. Skilled manual worker (blacksmiths, bakers).

6. Clerical and sales worker (bank tellers, billing
clerks).

7. Semi-professionals (advertising agents, teacher
aides).

8. Professionals (teachers, administrators).

10. What is your source of income: _ _ my own wages

wage of another

pay in kind

10.1 If pay in kind, what is it?

Structure of House

11. What is the house you live in built of?

1. Brick, concrete wall, cement floor, zinc/asbestos
roof

2. Mud and thatch

3. Tin/zinc

252

4. Other
House Ownership

11.1 Do you own/rent the place you live in?
Own

11.1.1 Do you have this house as a fringe benefit?
Yes

11.2 How many bedrooms in the house?
one room
two rooms
three rooms
four rooms
Over

11.3 Where does child X sleep?

In a room with other siblings
In a room with parents

In a room by him/herself

11.4 What is your general impression about the house?
Good condition

Needs to be renovated

Dilapidated/falling apart

Child X’s general behavior at home

11.5 How would you describe X’s behavior

1. Easy going
2. Difficult
3. Mixes freely with siblings
4. Fights with siblings
5. Other
11.6 Does child X have books to read at home?
____ Yes
____ No
11.7 Does child X have toys to play with?
____ Yes
____ No
11.8 Does child X have games to play with?
____ Yes
No

11.9 What things do you and child X do together?
Work together
Read stories

12.

253

Tell stories
____ Watch television
___ Other

Approximately how often do you do things together?
_ 1 hour/day
Twice a week
_ Once a week
_ Never

Child’s health condition

13.

13.1

13.2
13.3

How would you describe the condition of X’s health?
_ Very healthy
____ Somewhat healthy

_ Sickly

Has X been hospitalized?
Yes

What was the reason for hospitalization?

How recently has X been hospitalized?
Within last 6 months

_____ Within the last year
Within the past 3 years

254

APPENDIX B

Methods Used by the South African Government to

Assign Different Racial Groups to Different
Residential Areas

255

Population

The population of South Africa is 31.3 million. Twenty
two million or 72% are blacks, 4.8 million or 16% are
whites, 2.8 million or 9% are colored, and .8 million or 3%
are Asians (Africa South of the Sahara, 1986).

In order to get a better understanding of how land is
divided among the four racial groups of South Africa, a
brief discussion of the elements of the policy of apartheid
is necessary.

Under the policy' of apartheid, a rigid racial
segregation is enforced. This segregation is in all aspects
of life. For example, segregation in South Africa among the
four racial groups is in the residential areas, education,
and occupation. To achieve this segregation yet at the same
time to maintain the policy of apartheid, land and other
resources have been distributed unequally among the four
racial groups. Eighty seven percent of the country’s
territory has been reserved for whites, coloreds, and
Asiatics who make up 25 percent of the total population.
These groups may buy land in the urban areas. Blacks who
make in) 75 percent have been separated based on ethnicity
and assigned to the 13 percent of the country’s territory.

The fragmented areas designated for blacks are called
homelands/bantustans (See Map (”1 page 98). Thus, based on

the land reservation act, a person’s racial classification

256
or color of his/her skin determines to a large degree
his/her area of residence. Black families are relegated to
the homelands. These homelands are similar to the Indian
reservations in the United States, which are isolated,
remote, and less productive in terms of farming and
agriculture.

Other black families have been forcibly removed by the
South African government from areas designated for whites
and "dumped" in the resettlement areas which are adjacent to
the homelands. Other blacks live and work on the white-owned
farms, and in urban areas. Blacks are prohibited by law to
buy land in white areas. They may also remain in the white
areas for as long as they serve the interests of whites as

miners, domestic servants, or farm laborers.

257

APPENDIX C

Letters to Ministries of Education

Letters and Consent forms to Parents

258
Dear Sir/Madame:

I am Nomalungelo Ivy Goduka. I was born in Herschel in
South Africa. I graduated in Psychology from the University
of Fort Hare in April 1979. Since then, I worked as a
research assistant at the National Institute for Personnel
Research (N.I.P.R.) in Johannesburg, South Africa.

In 1981, I came to study for a Master’s degree in the United
States at Michigan State University in the Department of
Family and Child Ecology. Presently, I am enrolled in a
Ph.D. program in the same department.

As part of the Ph.D. requirements, I have chosen to study
factors that influence children’s physical growth and
behavioral development. This study is being conducted among
children in South Africa from thefollowing areas: Herschel,
Thornhill, the farm areas around Queenstown, and in ‘the
Orange Free State.

Children of ages 5-6 years will be selected from different
schools in your district.

To gather the information, I will need to test children, who
have been selected for the sample in their school. The
tests are for social, emotional, and mental ability and
physical growth.

In order to do this, I am requesting your approval to enter
the schools and work with children during school hours or
after school.

I see this type of research as valuable for your own
information as an educator. This information could be used
by teachers to better understand the children’s development.

I will be more than willing to share with you the findings
of the study, if you so desire.

Dr. J. M. Verster, Deputy Director of the N.I.P.R. will
supervise my work while I am in South Africa collecting
data. If you have further questions about this project,
please feel free to call him at 339-4451 at the Institute.

Thank you.

Nomalungelo Ivy Goduka

259
Dear Mr. and Mrs.

I am Nomalungelo Ivy Goduka. I was born in Herschel in the
homeland of the Transkei. I graduated in Psychology from
the University of Fort Hare in April 1979. Since then, I
worked as a research assistant at the National Institute for
Personnel Research (N.I.P.R.) in Johannesburg.

In 1981, I went to study for a Master’s degree in teh United
States at Michigan State University, in the Department of
Family and Child Ecology. Presently, I am enrolled in a
Ph.D. program in the same department.

As part (H’ the Ph.D. requirements, I have chosen to study
factors that influence children’s physical growth and
behavioral development. This study is being conducted among
Xhosa speaking families from the following areas: Herschel,
Thornhill, the farm areas around Queenstown, and in the
Orange Free State.

To gather the information, I will need to give your child

tests for social-emotional, mental ability, and physical

growth at school. I will also need to visit your family for

less than an hour on a day and time that is most convenient

tolyou. I will bring a questionnaire which I will help you
1 out.

This letter is to request your cooperation in providing
information about you, your spouse, and your child.

The information gathered from you and your child will be
kept confidential and anonymous. Information specific to a
family is not an important issue, rather the overall results
of family differences are important in this study.

I will be more than willing to share with you the findings
of the study.

Dr. J. M. Verster, Deputy Director of the N.I.P.R., will
supervise my work while I am in South Africa collecting
data. If you have further questions about this project,
please feel free to call him at 339-4451 at the Institute.

Thank you.

Nomalungelo Ivy Goduka

260
Consent Form

Child’s Name:

 

As the legal parent/guardian of the above named child, I
hereby give my permission for her/his participation in a
study conducted by Nomalungelo Ivy Goduka, a Ph.D.
candidate, under the supervision of Dr. J. M. Verster of the
N.I.P.R. and Dr. L. Phenice of the Department of Family and
Child Ecology, Michigan State University.

Parent/Guardian’s Name:

 

In addition, I freely give consent for my child and I to
take part in this study.

I understand that my child and I are free to discontinue our
participation in the study at any time.

I understand that my participation and my child’s
participation in the study does not guarantee any beneficial
results to me or to my child.

I understand that at my request, I can receive additional
explanation (H’ the study after my participation is
completed.

I understand that the results of the study will be treated
in strict confidence and that I will remain anonymous.
Within these restrictions, results of the study will be made
available to me at my request.

Signed

 

Date

 

261

APPENDIX D

Memos from School Administrators

\ w _\— ' _ s

261A

-.. ivvymlq
ini‘R-zcuu {3‘71ij 1‘ ’117. (1111(1'3'1 117;-..C'ICI?
112.? .1'1' I.'J1.T C?" :11117(' ,‘j‘LI O1}
' 3'11‘..-”'..'l‘-3 ..vJG 215096
1 13'1"“? .LI‘H 1'13"
1 5560

111.:P'1I‘11/1 1: $-
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8 JUIY 19$ 6
TC: i‘J-l 3"1111‘3LI3‘.‘.I.’I CI" JUILIC'H I'I.'II'.‘..'2‘{ 1303311113

This is to notify you that 1719.: I‘JT 1!. HE‘S-villi. 1m:- lJecn {given
approval by the Circuit Office to do res,nrch in your school.

For the 1:1.1r'."0'.te of this resezu' ch 1 is.: Goduka '.-v:i..l.] ".'.'C'I'I~. with
children in Dub. A. The tests will take 30 - 45 minutes.
Children wi11 also be measured to obtain their weight and height.

This letter is to request you to give kiss Goduka pernis:icn to

do this res arch at your school.

We see this type of a study as very helpful for the cduestion

and development of the child.

Your co-operation is highly rcques ed in this regard for the

eifective su.cccs.s of this exercise.

:jCA—\]J e . -

GILL: C111,]: 111-211.11C'1C‘11
9 cavLa:-:

hm.J..ii$F--.Oh'. I .1:u4

1 ..... ....

2618

3". C12
l\-.- 2 IRII'IIAIILJKI YECISKEI
11,133. RLPUDLIC or ClSKlzl

\vt
Ire/(emf: V
Rel. N0 ............................ 101131.11. - Ollice ol the
I/oni- . I 1.1,”. .14-1115121! r.
Telephone: ...... 1. 311.111.111.11 11.0.0: ...... l I ' "NJ {213131)} 3' /

1 1 ..l' :1 3'1 1

Imibwo: , q . r ’ a... v ' '~. , . .~ '
Enquiries: ..... 1‘13". .1991111911‘19. .'.' v1. .0. . 1 1" "LE'TPVW :.'--mi. I

I1}

T0 ' M.I.- I'1111!(’Ifll‘?-I..J CI" 15113-15111" -‘.'r".}11(‘:(.11.3

This is to notify you that V153.l!¥.1; QQQHLfi has

been given approval by the Circuit Ufffee tofldo research
in your school.

For the purpose of this research Kiss Goduka will work with
children in Sub. A. The tests will tale 30-45 minutes.
Children will also be measured to obtain their weight and
luiiffiit.

This letter is to request you to give Miss Goduka permission
to do reseurch at your school.

We see this type of a study as very helpful for the nducstinr
and develOpment of the child.

highly requested in this regsrd for the

Your co-opcration is
7f this exercise.

effective success r

      
  

(,IVW .

0.00.0.0...

KS ZCTOH

/{///;1,

CJHUU

261C

G.P.-S. 33-0140

Verw. NLIRQI. No.

NAVRAEIINQUIRIES:
7 1 O7

1’ . G . ST. .1 'l‘EIi

101. No.

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so “01 for excurnfi ruryerex

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ac 110 cl

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Prospvvt Farm
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REPUBLIC OF SOUTH AFRICA

KANTOOR VAN DIE—OFFICE OF THE
Circuit Jiihyeotes.‘ Cf
HM‘. "3113' 21:1 r;

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you. scan

General 1to visit there

2610

"[1723”

CPS. 300140 (1 H)

REPUBLIEK VAN SUlD-AVRIKA REPUBLIC OF SOUIH AFRICA

 

 

Verw. NL/Re‘. No. 9/1/7
NAVRAE/INQUIRIES: 311/11;-

Ye" No. 8421:

_ _..- KANTOOR VAN DIE—OFFICE OF THE
[.h's. Ivy N. Goduka K1‘i11,-:711‘11,1)th0ur
C o Manxeba Junior Secondary School Slgeml‘on ”19’093311'1'18
.. ... ... ... .............. .. 1‘1:1.v:1.1l;:)r11'..1£\)513
Privu te 3.1;; X16 BLOBILFOLITB -.'
unusaunL 9J°0

"542 J 1986 — 08 - 12

L“ ........

BLJD'JJI '..\'..' SIZOLS I 3LCLZT'X‘231'JI 3430.31111le

mcv. Ivy II. Goduka. 23:15 tron Opanbure Slcool

1. 'I‘oestmnming and vorlvon 13.-1t .. ..................................
19139-143 in die ‘lloemfontein—‘fo 1333111,; 1113;; bonock.

2. Desoeke is onderhcwig mm «1.10. m1,-;en(lv:

2.1 Die goalkeurixg van die ukoolhnol‘ 1.10131: verkr] word.

2.2 Gee!) inbx-euk 11:13 0;» die normule sizonlprohjrzun genumk word 115.0.

2.3 Desoeke moot 11111 to skaolure pl'muvind.

2.4 Die Departmnont v3.11 Outierzzys on Owleidinc mag 0p green wysu benadoel

of be trek innl .1'19.

3. U sa'newcrkizxg 31.1. Opreg; urnnlcer uonl.

Die 111:0

G. 'I'iIOI'i
K2113") {3.51'.‘.'311'l':2U1l : WLOEITOIf'PuIII—CULSKRTIU}

 

261E

Raad vir Geesleswelenslaplike Navorsing
Human Sciences Research Council

1111111
111.11

i

l

HON ”an

 

Nasionale lnsliluul vir Personeelnavorsing (NIPN) fi'j‘:\\
Nalional lnslilule lor Personnel Research (NIPR) ’ V)
.__a’

Navree \

Enquiries
Teleloon Byiyn
Telephone (011)339-4451 Extension

Verwysino
Relerence verSter/fm

U vervvyslng
Your tolerance

 

. --__—_--._.

———.—. -.—. - _.._.--...

 

21 July 1986

The Director General
Education and Training
Private Bag X212
PRETORIA

0001

For Attention : Mr J H Bester

Dear Sir,

HS IVY GOOUKA

As discussed with you telephonically this morning,

Goduka, a PhD student at Michigan State University,

Posbus 3200
Braamionlcin

2017 Republic-k van Suld-Alnka
Teleks: 4-25-459 SA
Telegramme NAVORSPERS

P 0 Box 32410

Braamlonlem

2017 Reoubhc 01 South Alnca
Telex: 425459 SA

Telegrams NAVORSPERS

Ivy
EJSt

Lansing, USA, has requested permission from your department to
undertake fieldwork for her thesis at farm schools in the DFS

and Cape Province. Her university has appointed me

05

supervisor. of her fieldwork in South Africa. I would be
grateful if you could give her the assistance she seeks with a

view to completing fieldwork of her PhD research.

Yours sincerely,

 

1

J M VERSTER
for EXECUTIVE DIRECTOR
NATIONAL INSTITUTE FOR PERSONNEL RESEARCH

261F

Raad vir Geesleswetenskaplike Navorsing

Human Sciences Research Council

-—..-—-—--.-— ..--._—..——_.__....-— _m __

 

Nasionale lnsliluul viiPersoneelmvorsihg (NIPN)
Nalional lnslilule ior Personnel Research (NIPR)

Newee
Enqulrles

1:13:33)?“ (011)339-4‘51 Bylyn

Verwyelng
Reierence

U vervvyslng
Your relerence

 

on...”
0"

Extension

TO WHOM IT MAY CONCERN

 

 

Posbus 32410

Braamionlein

2017 Republlek van Suld-Alrlke
Teleks: 4-25459 SA
Telegremme NAVORSPERS

P 0 Box 32410

Braarnlonieln

2017 Republic 01 South Alrlca
Telex: 4-25459 SA

Telegrams NAVORSPERS

Miss Ivy Goduka is a PhD student at Michigan State University, East
She is conducting research for her PhD thesis on

Lansing, U.S.A.

"Behavioural deveTOpment of black children in South Africa :
I have been asked by her university to supervise

Any assistance you are able to give her
in the course of her fieldwork would be greatly appreciated.

ecological approach“.

her fieldwork in

Yours sincerely

  

for txscui
NATIONAL INSTITUT

(O.Li t et PhiT
E DIR CTOR

South Africa.

FOR PERSONNEL RESEARCH

an

Raad vir Geecteswetenslaplike Navorsing
Human Sciences Research Council

 

Nasionale lnsliluul vir Personeelr-iavorsing (NIPN) [’1
Nalional lnslilule lor Personnel Research (NIPR) "

Navree
Enqulrles

13:11:12.. (01113394451 Bvlyn

Venvyslng
Reierence

U verwyslng
Your relerence

_..~__.-..___.__..._..._..__ ___—-_——__ _. . .---

Extension

 

 

5:?- “ «5:.
E? ‘-
“£— 1 E
:1... :q:
11' 1N 113.1116

Posbus 32410

Braamionlein

2017 Republlek van Suld-Alrlka
Teleks: 4-25459 SA
Telegrarnrne NAVORSPERS

P O Box 32410

Braamlonlein

2017 Republlc of South Airlca
Telex: 4-25459 SA

Telegrams NAVORSPERS

...—.._——-— .- .. - _-s.

AAN HIE DIT MAG AANGAAN

Mej Ivy Goduka is 'n Ph.D.-student aan die Universiteit van die staat
van Michigan, East Lansing, V.S.A. Sy doen navorsing vir haar
Ph.D.-proefskrif oor "Gedragsontwikkeling van swart kinders in
Suid-Afrika : 'n ekoiogiese benadering". Ek is deur haar universiteit
gevra om toesig te hou oor haar veldwerk in Suid-Afrika. Enige huip wat
u aan haar kan verieen tydens haar veldwerk sal hoog waardeer word.

Die uwe

. 1 ..

I .\ V

-‘\.'

f i“, ,1 1"

/// [7 '1. \

_/,/I./11 1 1
(

J M VERSTER O.Lit. et PhiT.
vir UITVOERENOE DIREKTEUR
NASIONALE INSTITUUT VIR PERSONEEL NAVORSING

"111111111111111is