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THE EFFECT OF THE MOTHER'S CHOICE AND TIMING OF
COMPLEMENTARY FOODS ON THE GROWTH OF CHILDREN IN
GABAN E , BOTSWANA

presented by

Maria 8. Nnyepi

has been accepted towards fulfillment
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11m CBIRCMN.N5-p.14

THE EFFECT OF THE MOTHER’S CHOICE AND TIMING OF
COMPLEMENTARY FOODS ON THE GROWTH OF CHILDREN IN
GABANE, BOTSWANA

By

Maria S. Nnyepi

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

Department of Food Science and Human Nutrition

2000

ABSTRACT
THE EFFECT OF THE MOTHERS CHOICE AND TIMING OF
COMPLEMENTARY FOODS ON THE GROWTH OF CHILDREN IN
GABANE, BOTSWANA.
By

Maria S. Nnyepi

The choice and timing of complementary foods are pivotal to the sustained
growth of a breastfeeding child. In developing countries, 3-36 months old
children are at risk of malnutrition due to unfavorable environments that
surround complementary feeding. Efforts to address malnutrition require an
understanding of the relationship between the mother’s feeding practices, the
household’s demographic characteristics and the child’s growth. This study
investigates the effect of the mother’s choice and timing of complementary foods
on the child’s growth parameters. Using an interview schedule data on the
child’s diet, anthropometrics, feeding practices and demographic factors were
collected from respondents and clinic records. Respondents were mothers, aunts
or grandparents accompanying the child to the clinic. Complementary diets in
Gabane are predominately sorghum-based and do not meet requirements for
adequate growth. Both the choice and the timing of complementary foods were
associated with the child’s growth. Sorghum-use was associated with low
weight-for-age and weight-for-height z-scores. Children in households with

more than two Children and / or resident were at greater risk for malnutrition.

Copyright by
Maria S. Nnyepi
2000

ACKNOWLEDGEMENTS

I am thankful to God, through his grace and wisdom this work has been
accomplished. I am also very indebted to my academic and research advisor
Dr. Jenny Bond for her never-ending support. She has been a model advisor,
whose desire has been to bring out the best in my role as a mother, wife and
student. I am very fortunate to have been her advisee.

My gratitude also goes to my committee members, Dr. Nan Johnson and
Dr. Lorraine Weatherspoon. Dr. Johnson was tremendously helpful in the
analysis and interpretation of the data. Those many office visits proved to be
worth it. Dr. Weatherspoon’s proximity to my office made her an easy target
for my questions, which she readily addressed. Her experience with South-
African social environments and related nutrition issues was helpful.

Many thanks go to Marcia Scott for her support, and Margaret Negilski
for helping with the data editing. My special appreciation goes to my mother
and grandmother for their love and intercessory prayers, and Martha for her
kindness, love and help with the children. I hope that the completion of this
work will inspire her to continue with her program of study. I also want to
thank my three very special children Mbano, Tatenda and Bubuya who
brighten up my soul with their jokes and smiles daily. My final and special
appreciation goes to Mbako, my husband, for love, support and respect.
Thank you for sharing our parenting responsibilities so that I could also find

time for schoolwork. You’ve been a great study partner too!

iv

TABLE OF CONTENTS

 

 

 

 

 

TABLE OF CONTENTS ......... - ...... ............. . .............. . .......... - V
LIST OF TABLES: .................... - -- - -- - _ _ ...... -IX
LIST OF FIGURES - - - -- -- -- - - --.X
CHAPTER I INTRODUCTION - - - - - - - -1
Nutritional Needs of Children and Breastfeeding ............................................. 1
Problems Associated with Complementary Feeding ......................................... 2
Nutritional Status of the Under-five’s in Botswana ........................................... 5
Complementary Feeding in Botswana ................................................................. 6
Problem Statement .................................................................................................. 7
JUSTIFICATION OF THE STUDY ...................................................................................... 8
OBJECTIVES ................................................................................................................. 10
CONCEPTUAL FRAMEWORK ....................................................................................... 11
WORKING DEFINITIONS .................................................................................... 14
CHAPTER II LITERATURE REVIEW _ - 17
CORRELATES OF CHILD HEALTH IN DEVELOPING COUNTRIES ................................ 17
Mother’s Income and Employment Outside the Home ................................... 18
Mother’s Formal Education Level ....................................................................... 19
Household Hygiene .............................................................................................. 21

' Intra-Household Food Allocation Rules ............................................................ 21

Child Feeding Practices ........................................................................................ 2
METHODS ................................................................................................................ 24
Approval to Conduct the Study .......................................................................... 24
Subjects and Sample Size ...................................................................................... 24
Subject Recruitment .............................................................................................. 25
Interview Schedule ................................................................................................ 26
Anthropometrics ...................................................... . ............................................. 27
Review of Records ................................................................................................. 27
Dietary Data ........................................................................................................... 28
RESEARCH QUESTIONS, HYPOTHESIS AND VARIABLES ............................................. 29
Research Questions ............................................................................................... 29
Null Hypotheses .................................................................................................... 29
Independent Variables .......................................................................................... 30
Dependent Variables ............................................................................................. 31
STATISTICAL ANALYSIS .............................................................................................. 31
CHAPTER IV RESULTS ................................................................................... 33
SAMPLE CHARACTERISTICS ............................................................................. 33
Household’s Demographic Profiles .................................................................... 33
Child’s Demographic Characteristics ................................................................. 34
Child Feeding Practices ........................................................................................ 38
Child Anthropometric Measurements ............................................................... 39

vi

RESEARCH FINDINGS .......................................................................................... 45

Nutrient Qualities of Complementary Diets ..................................................... 45
Prevalence of Malnutrition in Gabane ............................................................... 46
Household Factors and Child Malnutrition. ..................................................... 49
Choice and Timing of Complementary Foods .................................................. 51
Nutritional Quality of Complementary Foods ................................................. 55

PREDICTION MODELS FOR HEIGHT -FOR-AGE, WEIGHT-FOR-HEIGHT

 

AND WEIGHT-FOR-HEIGHT. ............................................................................. 58
Height-for-Age ....................................................................................................... 58
Weight-for-Age ...................................................................................................... 62
Weight-for-Height ................................................................................................. 65

CHAPTER V DISCUSSION AND CONCLUSIONS 67
The Predominant Role of Sorghum in Complementary Diets ........................ 67
Association of Sorghum Porridges with Low Nutritional Status .................. 68

The Relationship between the Mother’s Choice of Complementary Food,

Culture, and Food Availability ............................................................................ 70
Nutritional Quality of Complementary Foods in Gabane .............................. 72
Height-for-Age ....................................................................................................... 74
Weight-for-Age ...................................................................................................... 78
Weight-for-Height ................................................................................................. 81
SUMMARY AND CONCLUSIONS .................................................................................. 86
STUDY LIMITATIONS AND STRENGTHS ...................................................................... 88

vii

STUDY IMPLICATIONS AND RECOMMENDATIONS. .................................................... 9O

 

 

 

 

RECOMMENDATIONS FOR FUTURE RESEARCH .......................................................... 93
APPENDIX A ........ 96
CONSENT FORM .................................................................................................... 96
APPENDIX B- ................. 99
UCRIHS LETTER ..................................................................................................... 99
REQUEST LETTER TO KDC ................................................................................. 99
APPENDIX C .................... - _- _ -102
QUESTIONAIRE ................................................................................................. 102
APPENDIX D 111
OTHER DATA TABLES ....................................................................................... 111

REFERENCES- - 117

viii

LIST OF TABLES

TABLE 4. 1 SAMPLE CHARACTERISTICS ............................................................ 35

TABLE 4. 2 PREVALENCE OF LOW HEIGHT-FOR-AGE, WEIGHT -FOR-AGE
AND WEIGHT-FOR-HEIGHT. ......................................................... 40

TABLE 4. 3: HEIGHT -FOR-AGE AND WEIGHT -FOR-AGE DISTRIBUTION .. 40

TABLE 4. 4: Z-SCORE COMPARISON OF GABANE CHILDREN WITH

CDC / NCHS REFERENCE POPULATION. .................................... 46
TABLE 4.5 A COMPARISON OF MALNUTRITION IN GABANE (CURRENT
STUDY) WITH BOTSWANA DATA ................................................ 48
TABLE 4.6 ANOVA RESULTS FOR HAZ, WAZ, AND WHZ BY CHILD’S
AGE. ......................................................................................................... 50
TABLE 4. 7 TUKEY’S TEST RESULTS COMPARING MEAN HAZ,WAZ AND
WHZ BY CHILD’S AGE ...................................................................... 51
TABLE 4.8 RELATIONSHIP BETWEEN THE CHOICE OF FOOD AND HAZ,
WAZ AND WHZ-SCORES ................................................................. 53
TABLE 4.9 TIMING OF MASHED FOOD AND HAZ, WAZ AND WHZ ..... 55
TABLE 4.10 SUMMARY OF THE NULL HYPOTHESES TESTED ...................... 57
TABLE 4.11 LOGISTIC REGRESSION MODEL 1: PREDICTION OF STUNTING
(1 = Yes 0 = No) .................................................................................... 60
TABLE 4.12 LOGISTIC REGRESSION MODEL 2: PREDICT ING STUNTING
(1 = Yes; 0 = No) ..................................................................................... 62
TABLE 4.13 LOGISTIC MODEL 3: PREDICT ING UN DERWEIGHT ................. 64

TABLE 4.14 LOGISTIC REGRESSION MODEL 4: PREDICT ING WASTING
(Yes=1,No=O) ...................................................................................... 66

TABLE 5.1 PREDICTORS OF HEIGHT -FOR-AGE, WEIGHT-FOR-AGE AND
WEIGHT -FOR-HEIGHT . .................................................................... 83

ix

 

 

LIST OF FIGURES

FIGURE 1.1 CONCEPTUAL FRAMEWORK OF THE DETERMINANTS OF

CHILD GROWTH, SURVIVAL AND DEVELOPMENT .............. 13
FIGURE 4. 1 MEAN Z-SCORE DISTRIBUTION BY CHILD’S AGE .................. 41
FIGURE 4. 2 HEIGHT FOR-AGE Z-SCORE DISTRIBUTION .............................. 42
FIGURE 4. 3 WEIGHT -FOR-AGE Z-SCORE DISTRIBUTION ............................. 43

FIGURE 4. 4 WEIGHT -FOR-HEIGHT Z-SCORE DISTRIBUTION ...................... 44

CHAPTER I

INTRODUCTION

Nutritional Needs of Children and Breastfeeding

Nutrition is integral to optimum child growth especially between birth and
five years. Between birth and six months, for example, the caloric needs of a
child are estimated at 108 Kcal/ kg body weight (National Academy of Sciences,
1989). When the child is exclusively breastfed, these very high nutritional needs
are often easy to meet, even in poor households. Breastfeeding has been shown
to meet the nutritional, health and developmental needs of infants and young
children.

In the first 6 months of life, breastfeeding meets the three determinants of
child growth and development defined in the United Nation’s Children’ Fund
(UNICEF) conceptual frame work of nutrition as Care, Food Security and
Health (UNICEF, 1996; Butte et al., 1992; Cohen et al., 1995).

Additionally, during the first 4 to 6 months of life, the exclusively breastfed
child’s access to breast milk is not adversely influenced by factors that normally
influence household food distribution. Consequently, socio-economic factors
such as the size of the family, head of family, household income level, quality of
family housing, and mother’s education level have minimal influence on the
exclusively breast fed child’s growth and development during this period

(Harrison et al., 1993; Millard, 1994; Zumrawi, 1991). Therefore, the

exclusively breast-fed infant tends to be relatively more food secure and

healthy during this period than other members of the household.

Problems Associated with Complementary Feeding

Beyond 4-6 months however, when breastfeeding alone cannot adequately
meet the nutritional needs of the child, nutritionally dense and hygienic
complementary foods are essential for continued growth and development.
Even though the caloric needs of the child drop from 108 Kcal / kg to 98Kcal / kg
body weight after 6 months, these needs are often difficult to meet in
developing countries as a result of unfavorable circumstantial child rearing
environments, health and socioeconomic factors (Harrison et al., 1993; Howard,
1994;Wa1ia et al., 1985). When complementary foods are inadequate and
unhygienic, as is often the case in poor families in developing countries, growth
faltering and increased incidences of diarrhea and other gastrointestinal
infections become prevalent. All these can precipitate malnutrition and become
the major components of the vicious cycle of malnutrition and infection.

Comparative studies on child growth in poor communities (Peru) and
affluent communities (US) found similar growth patterns in Children under 12
months between the two populations as long as both groups of children were
exclusively breastfed (Dewey et al., 1992). However, when complementary
foods were introduced, children in poor communities in developing countries

fared worse than those in affluent communities (Dewey et al., 1992). Analysis

of the diet in this comparative study indicated that children from poor
communities had lower calorie and protein complementary foods and higher
incidences of gastrointestinal infections. This finding, corroborated by others,
suggests that the low nutritive quality of complementary foods, among other
things, in developing countries significantly contributes to growth faltering in
children of weaning age (Harrison et al., 1993; Sirnango, 1997; Sirnondon and
Simondon, 1995; Zumrawi, 1991).

The child’s age at the onset of complementary food can differ greatly. The
most common reasons mothers give for introducing complementary foods are:
perceived insufficient breastrnilk, slow weight gain, child’s reaching a suitable
age and pregnancy (Cosminsky et al., 1993; Harrison et al., 1993; Al-Mazrou et
al., 1994; Ubomba-Jaswa and Belbase, 1996). In some studies the introduction of
complementary foods was most likely when the mother perceived the child as
being too small or not getting enough breast milk regardless of the child’s age
(Simondon and Simondon, 1995; 1997). However, introduction of
complementary foods earlier than the 4-6 months World Health Organization
(WHO) recommendation is detrimental to child growth. Early introduction of
complementary foods may increase the risk of gastrointestinal and other
infections or promote the replacement of breast milk with less nutrient dense
complementary foods (Cohen et al., 1985; 1995; Al-Mazrou et al., 1994;

Zumrawi, 1991). More recently, the introduction of complementary food earlier

than 4-6 months was found to have no added growth benefit even in children
born small for their gestation age (Dewey et al., 1999).

Similarly, as the timing of complementary food differs, so does the onset of
growth faltering. In some studies growth faltering was observed in children
from 2 to 3 months through 6 months, while in others, growth faltering was not
observed until at least 9 months (Butte et al., 1992; Cohen et al., 1995;
Cosminsky et al., 1993; Dewey eta1.,1 992; Simondon and Simondon, 1995, 1997;
Zumrawi, 1991). In several of these studies, growth faltering was found
associated with the timing of complementary foods. However, the complexity
of weaning environments in developing countries or study limitations often
make the temporal delineation of growth faltering and the onset of
complementary foods difficult to define. In some studies, for example, growth
faltering was observed following the introduction of complementary foods
(Dewey 1992), while in other studies mothers reported introducing
complementary foods in response to the child’s slowed growth (Claufeild et al.,
1995)

Besides the nutritional and hygienic quality of weaning diets and the
tinting of complementary foods, several correlates of malnutrition in
developing countries have also been identified. Factors such as the mother's
beliefs related to child feeding, household socio-economic factors, intra-
household food allocation rules, urbanicity, and mother's education level are

strongly related to malnutrition (Armstrong, 1995; Barret and Browne, 1996;

Doan and Bisharat, 1990; Harrison et al., 1993; Millard, 1994; Rahmanifar et al.,
1996; Zumrawi, 1991). In attempting to investigate the role of complementary

diets on child growth, these factors will be controlled.

Nutritional Status of the Under-five’s in Botswana

Recent reports show that although 95 % of mothers in Botswana initiate
breast-feeding, and a large number of them continue breastfeeding for an
average of 14.9 months, child health parameters in Botswana are still below
desired levels (Aplogan et al, 1996; Ubomba-Jaswa and Belbase, 1996). Diseases
known to be minimal in exclusively breast fed children, such as pneumonia,
intestinal infections and other acute upper respiratory infections are among the
leading causes of childhood mortality and morbidity in Botswana (Central
Statistics Office, 1995; Feachem and Koblinsky, 1994). In addition, malnutrition
remains high in Botswana with 27.6%, 16.9% and 6.6% of children under five
years stunted, underweight, and wasted respectively (Ubomba-Jaswa and
Belbase, 1996). Ubomba-Jaswa and Belbase (1996) also found a significant
decline in all growth parameters (height- for-age, weight-for- age and weight-
for-height) from 9 months of age to 6 years across sexes. The worst levels of
these parameters coincided with the 6 months to 3-year growth window. In
addition, chronic malnutrition (stunting) appeared to be more severe (range of
20.5% -37%) than acute malnutrition or wasting (44-84%). All these forms of

malnutrition also coincided with the cessation of breastfeeding by most

mothers. Given that this period of low nutritional status starts two months
after the introduction of complementary food by most mothers, it is possible
that the timing of complementary foods is also associated with the decline in

nutritional parameters.

Complementary Feeding in Botswana

Complementary feeding in Botswana is started early, with 11.5% of infants
on complementary foods by 3 months and nearly 80% by four months
(Ubomba-Jaswa and Belbase, 1996). Only about 22% of infants are exclusively
breast fed from birth to about 4 months (Omondi et al., 1990). In congruence
with the cultural belief that infants thirst, but contrary to the WHO/ UNICEF
Baby and Mother Friendly Hospital Initiative (BMFHI) adopted by the
Botswana Government, a large number of infants are given water shortly after
birth (Aplogan et al., 1996). Other milks and sorghum porridges are also
introduced before 4- 6 months old. This high prevalence of introduction of
complementary foods by 4 months might be closely associated with the free
provision of tsabana (a sorghum/ soy bean porridge mix) to Children from 4 to
36 months through the Botswana Supplementary Feeding Program.

According to Ubomba-Jaswa and Belbase (1996) water, juicesl, porridges,
cow’s milk, and infant formula are the main complementary foods given to

infants. On average 47%, 33%, and 10% of mothers complemented their infant’s

 

1 Locally the word juice may also be used to include dairy-juice mixes-

diets with porridge, commercial infant formula, cow/ goat milk respectively.
Women with no formal education tended to use porridge (60%) more than
infant formula (26%). Among educated women, 46% of mothers used
porridges and 33% used infant formula.

The mother’s choice of complementary food also varies by geographical
location in Botswana. Infant formula use was more common in small towns
(55%), big villages (35%) and big towns (44%) compared to small villages (11 %)
and settlements (24%). The use of porridge was higher in small villages (53%)
and settlements (72%) compared to small towns (26%), big towns (35%), and big

villages (39%) (Ubomba-Jaswa and Belbase, 1996).

Problem Statement

Recent studies (Aplogan et al., 1995; Lesetedi et al., 1988; Ubomba- aswa
and Belbase, 1996) have provided general and descriptive background
information on child health in Botswana. Although such information is
valuable, in that it provides the bases for research, it lacks the specificity
required for planning effective nutrition intervention for children under five
years old. The high prevalence of malnutrition in children of ages 6—36 months,
despite the presence of the Supplementary Feeding Programs, may in part be a
reflection of the inadequate information on the nutritional needs available for
this age group.

Since no dietary quantitative assessment was done in any of these studies,

we are unable to fully characterize complementary diets in Botswana or
describe their association (if any) with child growth or nutritional status.
Additionally, the relationship between household demographic profiles,
prevalence of porridge use for complementary feeding, and the nutritional
quality of porridges is still not well understood. In Botswana, cereal-based
meals are collectively known as porridges. However, the consistency and
constituents of these porridges may differ greatly by households and regions in
the country. Hence the observation that 46% versus 60% formally educated or
non-formally educated mothers in Botswana respectively, use porridge in
complementary feeding as reported by Ubomba-Jaswa and Belbase (1996) is not
very revealing. It is likely that socio-economically more advantaged
households prepare nutritionally dense porridges more than poorer
households who lack the financial means required to procure adequate

quantities of meat, milk, butter / margarine or mayonnaise on a regular basis.

Justification of the Study

An in-depth, understanding of complementary diets especially porridge
use in Botswana is essential for several reasons. 1) Porridges are culturally
accepted as weaning foods and are relatively inexpensive. 2) They are versatile
and their nutritive value can be enhanced by adding fats and oils (margarine,

mayonnaise, cooking oil), rich sources of proteins (milk, sour milk, peanuts

(ground or butter), or served with meat or beans. 3) Other ways of improving
the nutritional quality of porridges include replacing cooking water with
melons and / or use of fermented or malted flours. Nutritionally enhanced
porridges therefore have the potential to improve the diet quality of
complementary foods and thus help reduce child malnutrition in Botswana.
The village of Gabane was Chosen as the study site for several reasons.
Gabane’s proximity (15 km) to the Capital City of Botswana (Gaborone), makes
it susceptible to Changes that take place in the cities. Therefore, some villagers
have similar characteristics to people living in the city. Consequently, Gabane
people are a mixture of people with village-like and urban-like life styles.
Additionally people originating from other regions of the country, with jobs in
Gaborone have settled in Gabane to avoid the high housing rental costs in the
city. Thus, Gabane embodies a variety of subcultures found in the country and
this was considered an advantage in this study. Gabane Clinic, like other
clinics in Botswana, provides both preventive and curative services.
Information generated by this study, such as the characterization of
mothers who use porridge consistently in complementary feeding, might help
the Supplementary Feeding Program target households with the most need for
these resources. Such households are those with children below the cut off
point for malnutrition. Such a move would also improve the efficacy of the
program by providing food to households with a higher likelihood of using the

food as recommended. Additionally, the characterization of food items that

study households serve with their porridges may assist the program in
increasing the variety of supplementary food as well as provide more culturally
acceptable foods. It is also conceivable that the savings brought about by
improved targeting might help the program increase their rations from the
current 30% of the child’s nutritional needs per month to a slightly higher
proportion.

Nutrition programs with education and communication prerogatives in the
country, particularly the Supplementary Feeding Program and the Breast
Feeding Program, will also benefit from the study findings because they may
flag areas where program evaluation or target-specific nutrition education
messages are needed. More specifically, the Supplementary Feeding Program,
which provides mothers with cooking oil in addition to tsabana (sorghum-soy
bean meal), would benefit from the study findings by ascertaining whether
mothers use tsabana for children or add cooking oil to tsabana porridge as
recommended. This information has not been available, although health
workers have suspected that the cooking oil might be used for other purposes,

such as in preparing relishes for the whole family.

Objectives
The overall objective of this proposed study therefore, is to build on the recent
studies on child nutrition in Botswana, by studying the influence of the

mother’s choice and timing of complementary food on the growth of children

10

between 3 months and 3 years in Gabane. The specific objectives of this study

are to:

1. Characterize complementary diets for children between 3 months and 3
years in Gabane, Botswana

2. Evaluate growth indicators (weight for age, height for age, and weight for
height) for children in Gabane, Botswana

3. Characterize households with children at risk for malnutrition as
determined by low height-for-age, weight-for-age and weight-for-height Z-
scores.

4. Describe the relationship between the mother’s choice and timing of
complementary foods, household, and child demographic characteristics

and child’s anthropometrics.

S“

Identify predictors for children with inadequate growth.

Conceptual Framework

In studying the effects of the choice of complementary feeding in children of
ages 3-36 months, this study will help expand our understating in the first two
levels of UNICEF's conceptual framework (Figure 1. 1) on the determinants of
child survival and development (UNICEF, 1996). In this framework, the causes
of malnutrition are classified as immediate, underlying, or basic causes. The

immediate causes, which include inadequate dietary intake and diseases,

11

directly influence nutritional status. At this level, the model underscores the
importance of ” Access to food” and ”access to basic health services” in the
survival and development of children. The framework describes the underlying
determinants of malnutrition as factors that influence ”household food security,
maternal and child care, health services, and the health environment”. These
factors have been shown to influence nutritional status by modifying the
immediate factors (dietary intake and diseases). Though outside the scope of
this study, the framework also defines the basic determinants of malnutrition as
global factors that include the economic resources and political system of a
given country.

In this study, the choice and timing of complementary foods and the
household hygiene level represent the immediate determinants of malnutrition.
These are considered appropriate for this level because the lack of nutritionally
adequate complementary food Choices and unhygienic feeding environments
such as lack of proper waste disposal and toilet facilities can ultimately
compromise the child’s nutritional status. Additionally, the increased rate of
infection in household with poorer hygiene level compared to those with
adequate hygiene level may also increase the nutritional needs of the child.
Thus, the resulting imbalance between the child’s nutritional needs and actual
dietary intake may precipitate malnutrition.

The underlying determinants of malnutrition are represented by factors

that influence the household’s food security, childcare and the overall

12

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

g Child Survival, Growth 53
:5 and Development '3
B B
’3 A ’i
2 2
3
U
"r'c’ g Adequate 4;
'§ g Dietary §——p Health 43 g
E U Intake '5 E
E '35 o
, f E .5 a
a v - r--;
m in
Eng Household Maternal Health 2° 5
E, 5 Food ......... y and Child ‘ ....... u Serv1ces and E. g
B E Security Care Health 3 E
"6: % Environment r: '3‘”,
Resources and Control
Human, Economic, and Organizational
: m_ . T 3
'5 Political and Ideological Superstructure g
I: .—
g Economic Structure g
F '5‘
.3 I a
3 Potential :3
Resources

 

 

 

 

 

 

 

Figure 1 CONCEPTUAL FRAMEWORK OF THE DETERMINANTS OF
CHILD GROWTH, SURVIVAL AND DEVELOPMENT. (UNICEF, 1996)

13

JU

I)

I:

St-

11

environment within which the child is reared. These are factors such as
maternal income, maternal education, household headship, type of primary
childcare giver, number of children in the households, presence of residing
relatives and the quality of household housing. These factors fall in this
classification level because they influence child growth indirectly by modifying
the child’s dietary intake or illness rate.

In this study, the growth indices, height-for-age, weight-for-age, and
weight-for-height are used to assess the effects of the outlined determinants of
malnutrition on the child's nutritional status. Malnutrition results when the
immediate or the underlying factors promote the decline of the growth indices
to levels below two standard deviations of the reference mean. The model
refers to these indicators as the ”manifestations of child survival, growth and

development”.

WORKING DEFINITIONS

Terms, variables and concepts used in this study are defined in this section.
Several of these definitions were taken from the Food and Agriculture
Organization (FAO)/ WHO Codex Alimentarius publications (F AO / WHO,
1992).

1. Complementary food: Any food or beverage regardless of nutritive value

given to supplement breast milk. In this study, complementary feeding is

14

'5‘ ‘ '3‘
‘ .

synonymous to supplementary feeding.

. Weaning: A process characterized by the gradual replacement of breast-
feeding/ infant formula by other foods or beverages. The process ends when
the child completely depends on family food to meet his / her hunger and
nutritive needs.

. Infant: A person from birth to not more than 12 months.

. Young child: A person between 12 months and 36 months.

. Child feeding practices: The child’s caregiver characteristics centered on the
preparation of the child’s food and feeding. These practices may include the
duration of breast feeding / formula feeding, timing of complementary
foods and the cultural beliefs or circumstantial behaviors regarding child
feeding.

. Household: A unit of people living together and sharing the same
resources.

. Moderately wasted: 2 score at two standard deviations below the mean
weight for height of the CDC / NHCS references.

. Severely wasted: Z score at three standard deviations below the mean
weight for height of the CDC / NHCS references.

. Moderately Stunted: Z score at two standard deviations below the mean

height for age of the CDC / NHCS references.

10. Severely stunted: Z score at three standard deviations below the mean

height for age of the CDC / NHCS references.

15

11. Moderately underweight: Z-scores at two standard deviations below the
mean weight-for-age of the CDC / NCHS references.

12. Severely underweight: Z-scores at three standard deviations below the
mean weight for age of the CDC / N HCS references.

13. Growth faltering: A decline of anthropometric measurements, particularly
in reference to weight or height.

14. Pula: Local currency in Botswana. Current conversion rates can be
obtained from commercial institutions. At the time of the study, one Pula
was about 25 cents.

15. UHT milk: Ultra high temperature pasteurized milk.

16. Surrogate parent: Any adult who accompanied the child to the clinic.
Surrogate mothers in this study were either the child’s aunt or

grandmother.

l6

CI

CHAPTER II

LITERATURE REVIEW

Correlates of Child Health in Developing Countries

Child health in general is influenced by global socio-economic and health
care systems that surround and influence the household; the unit within which
each individual child is reared (Berman et al., 1994; Millard 1994). Since
decisions made within the household and the child rearing practices are subject
to the environment defined by these global systems, it is assumed that studying
the household can reveal the impact of these factors on child health. It is also
anticipated that complementary feeding and weaning practices within each
household, like other components of Child health, will likewise be influenced by
these global systems.

In this section, the correlates of Child health will be discussed at the
household level because; 1) Decisions made within the household affect the
child directly. 2) The household may adapt within the constraints of the global
systems to make its environment more favorable to child’s health as reported
by Schumann and Mosley, 1994. 3) The household is the main target for social
and health services within each state. In fact, the household is said to be well
suited for processing resources from social and health programs to ”produce

healt ” for its members (Schumann and Mosley 1994).

17

The discussion in this section will focus only on those factors that have
been strongly associated with child health in developing countries such as:
maternal education, maternal employment outside the home, family headship,
intra-household food allocation, child’s gender and the nutritional and hygienic

quality of weaning diets.

Mother’s Income and Employment Outside the Home

Within the household, several studies over many coimtries have shown
that the mother’s income, and / or employment outside the home correlate well
with child health indicators (Bicego and Boerma, 1993; Dargent-Molino et al.,
1994; Tekce, 1990; Zumrawi, 1991). In several of these studies, children born to
employed mothers were found to fare much better than those whose mothers
were not employed. The benefits of maternal employment were greater when
the mother had secured a suitable childcare alternative for her child. However,
children who were cared for by older siblings or who accompanied their
mothers to work, as is often the case among street vendors, fared much worse
than those cared for by adult relatives (Lamontagne et al., 1998). In some
studies however, maternal income / employment appeared to offer more
protection for infants and young children who were already on partial or full
complementary foods. In some studies, maternal employment/ income did not
appear to have a differential impact on child health in the pre—weaning stage

presumably because both groups of children had equal access to breast milk

18

despite their mothers employment status (Lamontagne et al., 1998; Tekce, 1990;

Zumrawi, 1991).

Mother’ s Formal Education Level

Maternal education has also been shown to have positive effects on child
health (Barret and Browne, 1996; Doan and Bisharat, 1990; Tekce, 1990). Several
studies have shown that maternal education remains a significant determinant
of child health even after other socioeconomic status variables like household
assets were controlled (Bicego and Boerma, 1993;Ubomba-Jasha, 1996;
Lamontagne et al., 1998). It should, however, be noted that some researchers
suggest that maternal education alone is not a significant determinant for child
survival (Millard, 1990), especially with the understanding that the protective
effect of maternal education may, to some extent, be dependent on the
prevailing socioeconomic environment (Dargent-Molino et. al., 1994). Dargent-
Molino et al., found that the protective effect of maternal education against
diarrhea in Cebu (Philippines) was contingent upon the availability of
community resources. In this study, maternal education was also more
protective in the more socio-economically advantaged communities. This
finding is not surprising given that educated mothers were more likely to use
community resources (health facilities) than mothers with low or no education.
Additionally, mothers with higher education level were shown to have better

comprehension and implementation of health education messages (Barret and

19

 

On

(0‘.

Browne, 1996).

Dargent- Molino et a1. (1994) also found that the protective effect of
education was less significant in the wealthiest families. These researchers
attributed this observation to the suggestion that the protective effect of
maternal education against diarrhea in wealthy families was comparable to the
effects of other socio-economic resources that wealthy families have available to
them.

In yet another study on the impact of maternal education on child
survival in 17 developing countries, maternal education had a varying impact
on child survival depending on the socio-economic status of each individual
country (Bicego and Boerma, 1993). In some countries, maternal education was
strongly protective while in others the protection was low or non-existent. In a
recent work in Malaysia, no association was observed between the mother’s
education level and decision making regarding intra-household food allocation
(Shariff, 1998).

The impact of maternal education on child health in some situations may
also be influenced by the mother’s position in the household’s decision-making
structure (Doan and Bisharat, 1990). In highly patriarchal societies where the
new (and usually younger) mother resides with her in-laws, maternal
education has been shown to have no effect on the well being of the children. In
these situations, the daughter-in-law (child’s mother) only follows and

implements decisions made by her mother-in-law and occasionally, her

20

husband. Thus, the influence of the mother’s education on the child’s growth

parameters would differ depending on the culture.

Household Hygiene

Household hygiene / sanitation has also been identified as one of the strong
correlates of child health (Barret and Browne, 1996; Rahmanifar et al., 1996).
Some indicators of sanitation/ hygiene whose impact on child health has been
explored include: room occupancy ratio, type and use of latrines, source of
household water (Zumrawi, 1991), type of housing material (Ubomba-Jaswa
and Belbase, 1996), hand washing after using latrines/ toilets, and care and
storage of cooking and eating utensils (Rahmanifar et al., 1996). Generally,
children in more hygienic households had better growth indicators than those
in less hygienic households. The more hygienic households were more likely
to be built with more permanent housing material, have running water in the
household whereas the less hygienic household were built with less durable

housing material and had pit latrines.

Intra-Household Food Allocation Rules

Rules and practices regarding intra-household food distribution have also
been shown to influence child health indicators. However, the degree to which
intra-household food distributions impact child health appears to be highly

influenced by cultural / ethnic beliefs regarding the ”worth” of one household

21

member over the other (Engle and Nieves, 1993;). In some communities food
allocation is biased in favor of income earners (Engle and Nieves, 1993), while
in other communities the member’s gender may determine his / her proportion
of the household’s food. Such biased food distribution tends to discriminate
against young children and in some specific situations girls more than boys
(Engel and Nieves, 1993; Miller, 1984). In some Asian countries, for example,
girls are more disadvantaged than boys. At marriage, girls are culturally
required to take their family's wealth to the husband’s household and so girls’
parents consider them irnpoverishing. Consequently, girl children may be
discriminated against very early in life because they are considered to be less of
an investment than are boys (Miller, 1984; Winkvist and Akhtar, 2000). There
are however, other communities such as those in Peru and Botswana where
food allocation does not appear to be biased based on gender (Graham, 1997

and Ubomba-Jaswa and Belbase, 1996).

Child Feeding Practices

With respect to child feeding practices, breastfeeding and the nutritional
and hygienic quality of complementary food have been associated with child
health in developing countries (Brutte et al.,1992; Cohen et al., 1995; Dewey,
1992, 1998; Tekce, 1990; Walia et al.,1985). Comparative studies on child
growth in poor communities and affluent communities found similar growth

patterns between the two populations as long as both groups of children were

22

exclusively breastfed (Dewey et al., 1992). However as complementary foods
were introduced, children in poor communities in developing countries fared
worse than those in affluent communities (Dewey et al., 1992). Analysis of the
diet in this comparative study indicated that children from poor communities
had diets low in calories and protein and higher incidences of gastrointestinal
infections. This finding, corroborated by others, suggests that the low nutritive
quality of complementary foods, among other things in developing countries
significantly contributes to growth faltering in children of weaning age
(Harrison et al., 1993; Sirnango, 1997; Simondon and Simondon, 1995; Zumrawi,
1991)

The correlates of child health in developing countries are many and at
times have a synergistic impact. The magnitude of their impact on child health
may also vary between communities depending on the culture / ethnic beliefs
and the prevailing conditions at the time of the study. Nonetheless, this review
provides some general concepts that may be explored further when studying
the determinants of child health in developing countries in general, or as in the
case in this thesis, the choice of complementary food and / or weaning practices

on child health in Botswana.

23

CHAPTER III

METHODS

Approval to Conduct the Study

Approval to conduct the study was sought from the University Committee
on Research Involving Human Subjects (UCRIHS) and from the Kweneng
District Health Team, Molepolole, Botswana. The request letter to Kweneng
District Health Team and the UCHRIS approval letter are appended in
appendix A. Kweneng District did not send an approval letter. However upon
a follow-up telephone call, it became apparent that the District Medical Officer
was outside the country on job related trip. Permission was granted over the
telephone by Matron Boiteto, who also called Gabane Clinic Sister-in-Charge
and notified her. A blank questionnaire was left with the clinic, upon request

by the Sister-in-Charge of the clinic.

Subjects and Sample Size

Data were collected on a convenience sample of respondents attending the
Child Welfare Clinic at Gabane Clinic funded by the government of Botswana.
The data collection was started on June 10 and completed on July 10, 1999.
Eligible respondents were those with children of ages 3 months to 3 years.
Although complementary feeding is recommended for children who are at least

4 months old, a significant number of children in Botswana are complemented

24

a\
th

UN

Sui

before 4 months. Hence, for this study, data collection also included 3-month-
old infants. A sample size of about 30 is considered reasonable for a
descriptive survey (Fraenkel and Wallen, 1996). However, data would be
collected from a larger sample because it is anticipated that this study will also
serve as a pilot project for a Ph.D. dissertation. Additionally, Gabane CWC
Register indicates that the clinic provides services to about 700 children under
five years of age every month, so a sample size of at least 30 children of ages 3-
36 months old children would be possible to obtain.

In this study, a convenience sample was used despite its limitations
because it was the most feasible. Child Welfare Clinic attendance in Botswana
averages between 60 and 80 percent of children under five years depending on
the season. The attendance rate was also expected to be higher for children
under- three years because of their intense immunizations schedule, whereas
older children have a more spread out immunization schedule. Thus, even
with our convenience sample we still would be capturing a large proportion of

children between 3 months and three years.

Subject Recruitment

Mothers / surrogate parents of children between 3 months and 3 years were
approached individually by the investigator and asked to participate in the
study. A consent statement, explaining the purpose of the study, the kind of

information requested and known risks and benefits to the child and the

25

 

 

 

 

 

 

 

 

anI
Mot
COTS
wen
or r:

“'6?

Inte

Prefc
SUITC
(Om?
hi813

the n:

 

COnam

 

mother were read to all potential respondents in Setswana (local language).
Mothers or surrogates willing to participate in the study were asked to sign the
consent form. Consenting mothers or surrogate parents with no writing skills
were asked to put a mark (X or +) in place of their name or have a close friend
or relative Sign their name for them. Mothers opting to verbalize their consent
were allowed to do so, because insisting that they sign the consent form might
have been very embarrassing when the mothers did not have writing skills.

In this study, only children seeking preventive services (growth monitoring
and / or immunizations) between June 10th and July 10th, 2000 were included.
As illness negatively influences growth, inclusion of ill children could bias the

findings.

Interview Schedule

A questionnaire, similar to the one previously used in Botswana (Ubomba—
Jaswa and Belbase, 1996) was adapted and used to collect household socio-
demographic characteristics and information on the mothers’ child feeding
preferences and practices. The investigator interviewed consenting parents and
surrogate parents. Although it would be cost effective to have parents
complete the questionnaires, this option seemed inappropriate given the low
literacy levels in Botswana (69%). The interviews were conducted in Setswana-
the national language for Botswana, to ensure that respondents who could not

communicate in English would not be omitted.

26

Si

It

 

III

 

 

Anthropometrics

The weight and height (length if age < 2 years) of children were measured
by the investigator using a Salter Scale2 and a Harpenden portable stadiometer3,
respectively. The length of children younger than 2 years was taken by
mounting the portable stadiometer on a measuring bench previously used in
the Ubomba-Jaswa study (1996). The length measurements could have been
read from the bench directly, but the portable stadiometer was preferred
because it was also used to measure heights children over 2 years. Weight was
measured in kilograms and recorded to the nearest 0.1kg (allowed by the
instrument). The scale was re-calibrated every morning with a known weight.
Children were weighed once and this measurement was used both for the
study and the child’s record for the month. The height (length for age< 2
years) was measured to the nearest centimeter. Since clinics in Botswana do
not have the capacity to measure height/ length, the investigator provided the
equipment. Since this was the first time the children had their height/ length
measured, care was taken to ensure that the procedure elicited as little stress as

possible.

Review of Records

Information on the child’s age, birth weight, Apgar score, and sometimes

 

2 Salter Scales. CMS Weighing Equipment Limited. London, England.

3 Harpenden portable stadiometer. Model VF2M. Holtain LTD. England

27

the mother’s age and the child’s birth order was taken from the Child Welfare
Clinic card (CWC card). Information on the mother’s age and the child’s birth
order were further verified by the respondent. The information contained in
the CWC card is generally accurate and reliable because the CW C card is
completed by nurses (midwives) at the hospital when the child is born and is
given to the mother to keep. Cards are kept by the mothers and are brought to
the clinic each time the child visits the hospital / Clinic for services. Mothers
protect CWC cards because they are required to produce them when the child
begins primary school or when the mother completes application forms for the
child’s birth certificate or passports. Thus, all respondents had their CWC

cards.

Dietary Data

The dietary data were collected by a 24-hour recall conducted by the
investigator. Local utensils for serving children were made available during
the interview to help mothers describe the portions of food served to the child.
The capacity of each of the utensils was estimated using a 250-milliliter
measuring cup prior to the interview. Furthermore, mothers were asked to use
a 250-milliliter teacup as the reference measure when estimating amount of
food served to the child. Kilocalories, total protein, animal protein,
carbohydrates and fat were estimated from the 24-hour recall using Dietary

Manager (1998), a nutritional analysis software program bought from Program

28

Re

RI

9)

H

.w

Management, Bromhof, and South Africa.

Research questions, Hypothesis and Variables

Research Questions
1. What are the nutrient compositions and diet qualities of complementary

foods in Gabane, Botswana?
2. What is the prevalence of malnutrition in Gabane, Botswana?
3. What are the characteristics of households with malnourished children?
4. What is the relationship between the mother’s choice and timing of
complementary foods and
a) mother’s education level, b) household size, c) head of household,
(1) household’s income, e) child’s birth order, f) child’s growth,
g) child’s father’s presence in the home, and h) child’s gender?
5. What are the predictors of low weight-for-age, low height-for-age and low

weight-for-height in 3-36months old children?

Null Hypotheses
1. The nutrient qualities of complementary diets for children between 3 months

and 3 years in Gabane, are not different compared to those required for
adequate growth.

2. The prevalence of malnutrition for children of ages 3-36 months in Gabane
village is different compared to malnutrition rates in the entire country
(Botswana)

3. Households with malnourished Children of ages 3-36 months are not

29

IVE

 

 

Inc

 

different from households with well nourished children in these

demographic factors:

a) mother’s income, b) mother’s education level, c) household’s income
level, (1) child’s gender, e) child’s birth order, f) child’s age, g)

household Size, and h) headship (head of household).

4. There is no relationship between a) the mother’s choice and b) the timing
of complementary foods and the child's weight for age, height for age, and
height for weight Z-scores.

There is no relationship between the nutritional quality of the mother’s choice

of complementary foods and the child ’s weight-for-age, height-for-age and

weight-for-height Z-Scores in children of ages 3-36 months.

Independent Variables

1. Child’s demographic characteristics:

a) age, b) gender, c) birth order, and d) birth weight.
2. Household demographic Characteristics:

a) mother’s income, b) mother’s education level, c) household's income
level, d) total number of children, e) number of children under five
years, f) presence of father in the home, g) household size, h) headship
(head of household), i) type of household housing, and j) type of toilet

used.

30

IO

st.“

Sit

Wa

nut

3. Child feeding practices:
a) duration of breastfeeding, b) duration of exclusive breastfeeding,
c) infant formula use, d) store-bought cow milk, e) home-milked
goat/ cow’s milk, f) timing of complementary foods, g) proportion of
protein (animal) in the diet, i) caloric content of complementary food, j)
types of primary complementary food items, and k) types of food items

added to or served with the main complementary food item.

Dependent Variables
Child’s growth parameters:

The child’s growth indicators used in this study are weight-for- age, height-
for age and weight-for-height z-scores. These are based on the Center for

Disease Control / National Center for Health Statistics (CDC / NCHS) reference

standards.

Statistical Analysis

Three data analysis programs were employed in this study. SPSS 7.5 / PC
was the primary statistical analysis program used. The Dietary Manager
nutritional analysis program was used to analyze dietary data and Epi. Info.
6.04 was used to calculate Z-scores and analyze anthropometric data.

Statistical tests allowing group comparisons were employed in this study. T-

31

tests for two independent groups, chi square test and AN OVA when more than
two group means were compared.

Since associations of weaning diets and child growth indicators are difficult
to make because of confounding factors, children were assigned to two groups
based on their weight-for- age, height-for-age and weight for height Z-scores.
The two groups; adequately nourished (above —2 Z scores of HAZ or WAZ
WHZ), and malnourished (-2 Z scores) were compared relevant to their diet
and household and child socio-demographic characteristics. This approach
highlights the differences between Children with adequate and poor growth
during weaning and enables us to investigate the differences in weaning diets
amongst the groups.

The Pearson Product Moment correlation coefficient was used to assess the
relationship between continuous variables such as the relationship between the
proportion of kilocalories in diet from porridge, Z- scores, household’s income
and others. Logistic regression models for predicting Z-scores for the
dependent variables were generated for this study. In all statistical tests, a

significant level (alpha) was set at 0.05.

32

 

 

Ill
ct

lit

to

in

he

the

CHAPTER IV

RESULTS

SAMPLE CHARACTERISTICS

In this section, the characteristics of the 132 children and the households
sampled for this study are presented. The household’s and the index Child's
demographic characteristics, child feeding practices, and anthropometric

measurements are described.

Household’s Demographic Profiles

Table 4.1 summarizes the sample characteristics. On average, the study
households had 2.89 :t 1.9 children born within the household and 2.48 i 2.33
Child-relatives. Sixty-eight (68), 49, and 11 of the 132 households sampled were
headed by the child’s father, the grandparent and mother respectively. A
higher proportion of men (98 / 109) was employed outside the home compared
to women (45/ 132). Additionally, employed men earned more money than
women. Ninety one percent (91 %) of employed women had incomes below 699
pula per month compared to 37.2% of men. However, fewer men (43/ 111) had
secondary and tertiary education than women (78/ 132).

Household housing was predominantly modern, with (101 / 132)
households living in corrugated iron -roofed houses compared to (27/132) with

thatch roofing. Over sixty percent (80/132) of the households owned their

33

‘P I:

houses. The remaining households either stayed in the child’s grandparents’
(40/ 132) or rented (10/132) houses. Most households (80/132) had public
standpipes as their water source. Forty-seven (47) households had private
standpipes within their yard and three households had in-door plumbing. The
types of toilet used in this population paralleled the household’s source of
water. Most households (123/ 132) had pit latrines compared to flush toilets

(3/132)

Child’s Demographic Characteristics

The average age for the 132 Children sampled in this study was 17.8 i100
months. The youngest child was 3 months and the oldest was 40 months.
Fifteen percent (15.2%), 38.6% and 74.3% of children were under 6, under 12,
and under 24 months respectively. Fifty-two percent (n=69) of the subjects
were males and 48% (n= 63) were females. In this sample, 56.8%, 78.8% and
21.2% of children had birth orders under 2, under 4 and over 4 respectively.

As reflected in Table 4.1, the children were well nourished at birth, with an
average birth weight of 3.09 i .44 kg. Only 7.1 % (9) of the children had birth
weights below the cut off point for low birth weight (2.5kg). The average (1, 5,
and 10 minutes) Apgar score for children in this sample ranged from 8 to 10

with a mean of 9. 2 :t .6.

34

TABLE 4. 1 SAMPLE CHARACTERISTICS

 

 

 

 

 

 

 

Household N % Index N %
profiles Child’s profile

Headship Sex
Father 68 51.5 Male 69 52.3
Grandparent 49 37.1 Female 63 47.7
Mother 11 8.3
Other 4 3.0
Mother’s Child’s birth order
education level
None 21 15.9 1 and 2 75 56.8
Primary 33 25 3 and4 29 22.0
Secondary 76 57.6 over 4 28 21.2
Tertiary 2 1.5
Maternal Child’s birth weight
employment
Yes 45 34.1 s 2.5kg 9 7.1
No 85 64.4 2.5- 3.25kg 75 59.5
In School 2 1.5 Over 3.25 kg 42 33.3
Maternal age(yrs) Average Apgar Score
15-19 8 6.2
20-29 61 46.9 Less than 9 27 20.5
30-40 51 39.2 Greater than 9 47 35.6
41- 50 7 5.4 Unknown 58 43.9
51-59 3 2.3
Father’s Child’s breastfeeding
employment status
Yes 98 74.2 Yes 65 49.2
No 9 6.8 N o 67 50.7
School 2 1.5 Ever breastfed 63 47.7
Unknown 23 17.4 Never breastfed 4 3.0

 

 

 

 

 

 

35

 

Table 4.1 (Cont’d).

 

Father’s

Duration of breastfeeding

 

 

 

 

 

 

 

 

 

education level
None 41 31.1 S 6 months 15 23.1
Primary 27 20.5 7-12 months 15 23.1
Secondary 40 30.3 13-18 months 22 33.8
Tertiary 3 2.3 19-24 months 12 18.5
Unknown 21 15.9 Over 24 months) 1 1.5
Number of Child Intended duration
relatives of breastfeeding
1-3 42 59.2 S 6 months 0 0
4-6 20 28.2 7-12 months 14 21.5
7-8 9 12.7 13-24 months 44 67.7
over 24 months 7 10.8
Home ownership Primary complementary
food
Parent 80 60.6 Fermented sorghum 91 68.9
Grandparent 40 30.3 Unfermented sorghum 12 9.1
Rented 10 7.6 Commercial baby foods 11 8.3
Other 2 1.6 Other 13 9.8
None 5 3.8
Main house Primary food served with
roofing
Milk 51 41.5
Corrugated iron 101 76.5 Milk and sugar 31 25.2 .
Thatch 27 20.5 Bean/ vegetable soup 12 9.8
Tile 4 3.0 Variety of foods 17 13.8
Nothing 12 9.8

 

36

 

Table 4.14Cont’d).

 

 

 

 

 

Main house Complementary foods or

lighting fluids before 6 months (0-
5 months)

Paraffin lantern 125 94.7 Water (129)4 122 94.6

Candle stick 3 2.3 Infant formula (64) 57 89.1

Electric lamp 4 4.0 Mashed food (126) 111 84.1
Cows / goat’s milk (32) 14 43.8
UHT milk(29) 29 36.7
Tea (70) 10 14.3

Household’s Protein adequacy ratio5

source of water

Public stand pipe 80 60.6 Less than 66% 25 51

Stand pipe in the Greater than 67% 24 49

yard 47 35.6

Indoor plumbing 3 2.3

Other 2 1.5

Maternal Income Calorie adequacy ratio6

(Pula)

Under 400 20 15.2

Over 400 22 16.7 Less than 66 2 4.1

Unemployed 90 68.2 Greater than 67% 47 95.9

Type of toilet Primary person who feeds
the child

Pit latrine 123 93.2

Flush toilet 3 2.3 Mother 80 60.6

None 6 4.5 Grandmother 32 24.2
Other relative 10 7.6
Other 10 7.6

 

 

 

 

 

 

 

 

4 The number in parenthesis indicates the total number of children introduced
to the indicated food / fluid. It includes children introduced to the indicated
food at ages outside the (0-5) months age bracket.

5 This is the proportion of protein provided by the child’s diet. This ratio is calculated
using the Dietary Manager. It is based on the 1989 age and sex specific RDA.

6 The proportion of calories provided by the child’s diet. It was calculated by the
Dietary Manager.

37

Child Feeding Practices

Breastfeeding was very common in this population. Sixty-five (65)
mothers were breastfeeding at the time of the study. Sixty-three (63) of 67
mothers who were not breastfeeding at the time of the study reported they had
breastfed their children an average of 13.4 months in the past. Mothers who
were still breastfeeding during the study intended to breastfeed their children
for an average of 20 months. However, exclusive breastfeeding from birth to 6
months was rare. A high proportion of infants was given water (94.6%), infant
formula (89.1 %), ultra high temperature pasteurized milk (36.7%) and / or
mashed food (88.1) before 6 months of age.

Children were generally fed by their mothers (80 / 132), grandparents
(32/132) or other adult relatives (10 / 132). Of the 127 children who were
already on mashed or regular food at the time of the study, 71.6% (n=91) and
9.4% (n=12) were predominately fed fermented sorghum porridge and
unfermented sorghum (or maize meal porridge) respectively. Besides
sorghum/ maize porridges, a few children were predominately fed
commercially prepared baby food (11/127) while others (13 / 127) had no
predominant complementary food. The child’s primary food was served with
either milk (51 / 123), milk and sugar (31 / 123), vegetable/ bean soup (12/123)
or a combination of varied food (17/123). Twelve (12) children were served
their primary food only.

Based on the analysis of the 24-hour dietary intakes, complementary diets

38

in Gabane had lower calorie content compared to protein relative to the 1989
age and sex specific United State Recommended Dietary allowances (RDA).
Nearly fifty percent (49%), and 51 of diets had protein adequacy ratio of below
66% and above 67% respectively. With respect to calories, 89.8 and 10.2% diets
had calorie adequacy ratio of below 66% and above 67% respectively. These
nutrient adequacy ratios were based on the 1989 United States Recommended
Dietary Allowance (RDA). The mean nutrient adequacy ratios for protein and

calories in this study were 82% and 35.1 % respectively.

Child Anthropometric Measurements

The prevalence of stunting, underweight and wasting defined as -2
standard deviations of height—for-age, weight-for-age or weight-for-height in
this sample was 9.1 %, 12.1 %, 5.3% respectively. The prevalence of wasting,
stunting and underweight was comparable across the sexes. In both sexes, no
children under 6 months were stunted, wasted or underweight. Furthermore,
only one child was both stunted and wasted. Although the prevalence of low
height-for-age, weight-for-age and weight-for-height appears to be more
common in males than in girls, the difference is not statistically significant.
Tables 4.2 and 4.3 and Figure 4.1 provide summaries of the nutritional status of

children in this population.

39

TABLE 4. 2 PREVALENCE OF LOW HEIGHT-FOR-AGE, WEIGHT-FOR-

AGE AND WEIGHT-FOR-HEIGHT.

 

Nutrition Indices Prevalence Prevalence in Prevalence in Boys
in boys Girls and Girls

Low height-for-age 11.6% 6.3% 9.1 %

Low weight-for-age 13.0% 11.1 % 12.1 %

Low weight-for-height 5.8% 4.8% 5.3%

 

 

TABLE 4. 3: HEIGHT -FOR-AGE AND WEIGHT-FOR-AGE DISTRIBUTION

 

 

 

 

 

 

 

Low Height-for-Age
Yes No Total
Q
in Yes N 1 6 7
‘5 % 0.8 4.5 5.3
5.3
350 No N 11 114 125
'8 % 8.3 86.9 94.7
3
3
3 Total 12 120 132
N 9.1 90.9 100

 

 

 

4o

 

 

 

 

 

 

2

1

o

t
. r I1
l

e
o -2
8
A. WAZ
C —
CU
g -3 WHZ

 

 

3.00 7.00 11.00 15.00 19.00 23.00 28.00 32.00 37.00
5.00 9.00 13.00 17.00 21.00 25.00 30.00 34.00 40.00

AGE in months

FIGURE 4. I MEAN Z-SCORE DISTRIBUTION BY CHILD’S AGE

41

 

 

 

 

 

 

 

 

 

 

 

Mea n Height-for-Age Z-scores

 

child sex

.2 _
boys
'3 girls

3.00 7.00 11.00 15.00 19.00 23.00 28.00 32.00 37.00
5.00 9.00 13.00 17.00 21.00 25.00 30.00 34.00 40.00

Child age in months
Figure 4. 2 HEIGHT FOR-AGE Z-SCORE DISTRIBUTION

42

 

 

 

 

 

 

 

  

child sex

Mean Weight -for -Age

boys

 

 

gins

3.00 7.00 11.00 15.00 19.00 23.0) 28.00 32.00 37.00
5.00 9.00 13.00 17.00 21.00 25.0) 300) 34.00 40.00

Agein months

FIGURE 4. 3 WEIGHT-FOR-AGE Z-SCORE DISTRIBUTION

43

 

 

 

 

 

9
[/

I
A
l

1. A .
till i, ,

-3 —Tj

 

 

Mean Weight—for-Height S-score

I
N
(

 

child sex

boys

 

 

3.00 ' 7:00 ' 11:00' 151061900 23.00'28ioo' 3500'37ioo

giris

5.00 9.00 13.00 17.00 21.00 25.00 30.00 34.00 40.00

Child age in months

FIGURE 4. 4 WEIGHT-FOR-HEIGHT Z-SCORE DISTRIBUTION

RESEARCH FINDINGS
In this section, the study findings pertaining to the specific hypotheses stated
in Chapter 1 are presented. For ease of reference, the study hypotheses are

restated as headings of the relevant discussion sections.

Nutrient Qualities of Complementary Diets

Null Hypothesis 1: The nutrient qualities of complementary diets for children
between 3 months and 3 years in Gabane are different from those required for
adequate growth.

The assessment of the nutritional adequacy of breastfeeding children’s diet
is often complicated by problems in estimating the amount of breast milk
consumed by the Child (Dewey et al., 1996). Furthermore, it is not adequate to
rely on the volume of breast milk consumed by the infant because the
nutritional quality of breast milk has been shown to reflect the mother’s
nutritional status (Fomon, 1993). Given these challenges, the child’s physical
growth performance is considered the most objective measure of the overall
nutritional quality of the child’s diet. Thus, in this study, the nutritional quality
of Gabane Children ’5 diet was assessed by comparing their growth parameters
to the CDC / NCHS growth standards.

This comparison reflects that the prevalence of stunting, wasting and
underweight observed in 3-36 months old children in Gabane (see Tables 4.2
and 4.4) is high compared to the CDC / NCHS reference population (2.3%). T-

tests evaluating whether the sample mean weight-for-age, height-for-age and

45

weight-for-height differs from zeros (the mean of the CDC / NCHS the reference
population) yielded large and highly significant t- statistics. Thus, the HAZ,
WAZ and WHZ-scores of children in Gabane are Significantly lower than those
observed in the reference population as shown in Table 4.4. Based on this

observation the null hypothesis 1 is rejected.

TABLE 4. 4: Z-SCORE COMPARISON OF GABAN E CHILDREN WITH
CDC/NCHS REFERENCE POPULATION.

 

 

Index SUM Mean Standard T-statistic P-Value
dev.

HAZ -100 -O.754 1.182 7.303 0.000

WAZ -89 -0.677 1.234 6.304 0.000

WHZ -31 -0.232 1.186 2.246 0.026

 

Prevalence of Malnutrition in Gabane

Null hypothesis 2: The prevalence of malnutrition in Children of ages 3-36
months in Gabane village is not different compared to malnutrition prevalence
rates in the entire country (Botswana).

A comparison of the prevalence of malnutrition in Gabane and the entire
country is presented in Table 4.5. The cutoff point used to define malnutrition
is set at -2 z scores of the mean for all three indices. The prevalence of low
weight-for-age, weight-for-height and height-for-age in Gabane followed the
same trend as was observed in a 1996 nationally representative survey in

Botswana (Ubomba-Jaswa and Belbase, 1996). Children below six months of

age had a lower risk of malnutrition in both samples than children over 6

46

months of age. The prevalence of malnutrition in both samples was highest in
children between 12 and 36 months. Additionally, a t-test comparing the
national prevalence of malnutrition with that of Gabane was not significant for
weight-for-age and weight-for-height, suggesting that underweight and
wasting rates for 3—36 month old children in Gabane compared well with the
country’s rates. The difference in the prevalence of stunting in Gabane and the
nationally representative sample was approaching P = .06. Though this
difference did not reach a P-value of .05 set a priori, it may be important. Thus,
this possible difference in the prevalence of stunting in Gabane and the entire
country may need to be clarified through a larger sample size follow-up survey.
Based on these findings, the null hypothesis of no difference in the prevalence
of malnutrition in Gabane and the rest of the country is definitely retained for
WAZ and WHZ, but tentatively retained with respect to HAZ. Nevertheless,
these results need to be evaluated with caution because the comparison relied
on grouped data from Ubomba-Jaswa and Belbase’s study instead of raw data.
The researcher was not able to gain access to Ubomba-Jaswa and Belbase’s raw

data in spite of several requests for it.

47

TABLE 4. 5 A COMPARISON OF MALNUTRITION IN GABANE

(CURRENT STUDY) WITH BOTSWANA7 DATA

 

 

 

 

 

 

 

 

 

 

 

 

Nutrition Index
and child age in Gabane Botswana (1996)
months

% <-2 SD % < -2 SD
WAZ
3-5.99 0 0 11 0 0 51
6-11.99 5.9 2 34 7.4 7 94
12-23.99 15.7 8 51 17.0 30 176
24-35.99 16.1 5 31 17.3 29 168
36- 47.99 20.0* 1 5 16.1 22 137
All ages 11.5 15 132 11.5 66 489
3-36 9.4 14 127 10.4 44 352
HAZ
3-5.99 0 0 11 7.1 3 42
6-11.99 5.9 2 34 19.5 17 87
12-23.99 7.8 4 51 29.3 44 150
24-35.99 16.1 5 31 27.4 44 161
36- 47.99 20.0' 1 5 23.7 28 118
All ages 9.1 12 132 21.4 136 468
Ages 3-36 8.6 11 127 20.8 108 440
WHZ
3-5.99 0 0 11 4.9 2 41
6-11.99 0.0 0 34 5.9 3 85
12-23.99 11.8 6 51 6.8 10 147
24-35.99 0.0 0 31 6.2 10 161
36- 47.99 20.0' 1 5 4.4 5 113
All ages 5.3 7 132 5.1 30 547
Ages 3—36 3.0 6 127 5.4 25 434

 

 

 

7 Ubomba-Jaswa and Belbase, 1996
* Cell size very small. In the Gabane sample only children from 36 months up to

40 months are included in this cell.

48

 

 

 

”'1

r9-

 

 

I“.

(i.

 

Household Factors and Child Malnutrition.

Null hypothesis 3: Households with malnourished children of ages 3-36
months are not different from households with well nourished children in these
demographic factors: a) mother’s income, b) mother’s education level, c)
household’s income level, (1) child’s gender, e) child’s birth order, f) child’s age,
g) household size, and h) headship (head of household).

In this population, no association (at P =. 05) was observed between height-
for-age, weight-for-age, or weight-for-height and the mother’s income,
mother’s education level, the index child’s birth order, child’s sex and the
number of children in the household. The F-test, one-way analysis of variance,
comparing the means of weight-for-age, weight-for-height or height-for-age z-
scores and these variables was not significant (Tables for non-significant tests
are in Appendix D). Similarly, Chi-square tests, between these variables and
levels of stunting, underweight and wasting were not significant.

However, children below the age of six months had a different (lower) risk
of stunting, wasting and underweight than children above six months. An F-
test comparing means of weight-for-height, height -for-age and weight-for-age
Z-scores for children aged, 3-6, 7—12, 13-24 and 25-36 months yielded a large
and significant F-statistic. Table 4.6 summarizes these findings. Follow- up
analysis with Tukey’s post hoc test reflects that the mean weight-for-age and
weight-for-height Z-scores for children of ages 3 and 6 months is significantly

different (larger) from that of the other 3 age groups. Thus, children under 6

months were less likely to be underweight or wasted than children over 6

49

months old. However, the mean height-for-age Z- scores for the 3-6 months
old is only significantly different from that of children 25-40 months.
Additionally, at P-value of 0.05, Tukey's post hoc test has the mean subsets
outlined in Table 4.7.

Additionally, stunted children were significantly older than children
with normal linear growth. The average age of stunted children was 23.5
months compared to 17.2 months for children with normal linear growth. This
difference in age was significant at P =. 03. However, there was no significant
difference in the ages of children with normal and below normal weight-for-age

and weight-for-height in this population.

TABLE 4. 6 ANOVA RESULTS FOR HAZ, WAZ, AND

 

 

WHZ BY CHILD’S AGE.
Nutrition DF F-Statistic P-Value
indices
Height for Age 3,128 3.087 .030
Weight for Age 3, 128 9.304 .000
Weight for 3,128 7.754 .000
Height

 

50

TABLE 4. 7 TUKEY’S TEST RESULTS COMPARING MEAN HAZ,
WAZ AND WHZ BY CHILD’S AGE

 

 

 

 

 

 

 

 

Malnutrition Index Cell Sides Mean Subsets at alpha = .05
Subset 1 Subset 2

HAZ

i) 25-40 months 34 —1.1362

ii) 13-24 months 47 -.8789 -.8789
iii) 7-12 months 31 -.5077 -.5077
iv) 3-6 months 20 -.2445
WAZ

i) 25-40 months 34 -1.0265

ii) 13-24 months 47 -1.0028

iii) 7-12 months 31 -.5848

iv) 3-6 months 20 .4840
WHZ

i) 25-40 months 34 -.6115

ii) 13-24 months 47 -.3565

iii) 7-12 months 31 -.1771

iv) 3-6 months 20 .7905

 

 

 

Based on the preceding tests, hypotheses 3 a-e, g and h are retained
while hypotheses f is rejected. These observations suggest that households

with malnourished children were more likely to have older children.

Choice and Timing of Complementary Foods
Null hypothesis 4: There is no relationship between a) the mother’s choice and

b) the timing of complementary foods and the child’s weight-for-age, height-
for-age, and weight-for-height z-scores.

The Choice of Complementary Foods
Table 4.8 summarizes t-test results comparing the mean WAZ, WHZ, and
HAZ-scores for children fed different primary complementary foods. Children

primarily complemented with sorghum porridges had significantly different

51

(lower) WAZ and WHZ-scores at p-values .011 and .008 respectively from those
complemented with commercially prepared baby foods and UHT milk.
However, the mean HAZ-scores did not differ depending on the child’s
primary complementary food. Furthermore, children whose primary
complementary food was served with milk (i.e. sorghum and milk) had
significantly different (lower) WHZ-scores and WAZ-scores from those whose
complementary food was served with other foods.

However, 84% (n=69/ 82) of children whose primary food was served with
milk, had sorghum as the primary complementary food whereas 68% (34/ 50)
had a non-sorghum complementary food. A chi-square test of independence
between sorghum porridge and milk was highly significant (Chi-square; df 1, P
value = .03). Thus, a t-test Showing lower mean WAZ and WHZ-score for
children whose complementary food was served with milk, as is the case in this
study, does not necessarily suggest that milk has a lower nutritive quality but
rather reflects the strong correlation between porridge consumption and milk
use.

Height-for-Age Z-scores were not influenced by whether or not the child’s
primary complementary food was served with milk. Thus, the null hypothesis
stating no association between the HAZ-score and the mother’s Choice of
complementary food is retained while those stating no association between

WAZ and WHZ and the mother’s choice of complementary food are rejected.

52

TABLE 4. 8. RELATIONSHIP BETWEEN THE CHOICE OF FOOD AND
HAZ, WAZ AND WHZ-SCORES

 

 

Nutrition Indexflype 0f N Mean T-statistic P- Value
complemen tary food
HAZ -1.104 .272
1. Sorghum 103 -.8231
2. Other foods 29 -.5445
-1.105 .271
3. Served with milk 82 -.8521
4. Served with non milk 50 -.6140
based food/ relishes
WAZ -2.596 .011
5. Sorghum 103 -.8316
6. N on-sorghum based 29 -.1666
-2.408 .017
7. Served with milk 82 -.8856
8. Served with non milk- 50 -.3572
based food / relishes
WHZ -2.679 .008
9. Sorghum 103 -.3747
10. N on-sorghum based 29 .2776
food
-2.628 .010
11. Served with milk 82 -.4384
12. Served with non milk- 50 -.1082
based foods / relishes

 

 

The Timing of Complementary Foods

The child’s nutritional status measured in z-scores (HAZ, WAZ and WHZ)
did not differ depending on the child’s age at the introduction of ultra high

temperature pasteurized milk, tea, infant formula, water and milk from a home

53

reared animal in this population. None of the t-tests comparing mean HAZ,
WAZ and WHZ-scores for children introduced to these complementary foods
and drinks at different ages was Significant (data tables for non-significant tests
are in appendix D). However, there was a significant difference (t-test: df =1, p
value = 022) in mean WAZ-scores between infants introduced to mashed food
between 0-3 months and those complemented from 4 months. Consequently,
the null hypothesis of no association between the timing of complementary
foods and HAZ-scores, WAZ-scores and WHZ-scores is retained for all fluids
(water, tea, animal milk, infant formula and UHT milk) assessed in this study.
However, early (0—3 months) introduction of mashed food in this population
was associated with better WAZ—scores than introduction of mashed food at 4
months. Hence the null hypothesis of no association between the age at
introduction of mashed food and weight-for—age is rejected. However, this
observation was based on a small number of children (14) because of the small
sample size in this study.

When carrying out these analyses, the nutritional status of children
introduced to infant formula, or mashed food between 0-3 months was
compared to that of children complemented at four months or later. With
respect to cows/ goat’s milk, water, or tea, the nutritional status of children
complemented between 0-6 months was compared to that of children

complemented at 7 months or greater (Appendix D).

54

TABLE 4. 9 TIMING OF MASHED FOOD AND HAZ, WAZ AND WHZ

 

 

Nutrition Index / Age of N Mean Z-score (SE) T-statistic P
child at introduction of (df 119)

mashed food

HAZ 1.115 .267
1. 0-3 months 14 —. 4286 (.3327)

2. 4-6 months 107 -.7991 (.1155)

WAZ 2.335 .021
1. 0-3 months 14 6.07E-2 (.3830)

2. 4-6 months 107 -.8479 (.4060)

WHZ 2.360 .37
1. 0-3 months 14 .3357 (.4601)

2. 4-6 months 107 -.4061 (.7E-2)

 

Nutritional Quality of Complementary Foods
Null hypothesis 5: There is no relationship between the nutritional quality of
the mother’s choice of complementary foods and the child’s weight-for-age,
height-for-age, and weight-for-height z-scores in children of ages 3-36 months.
The T-test comparing the mean height-for-age, weight-for-age and weight-
for-height Z-scores for children in the groups with nutrient adequacy ratio
(NARS) for protein and calories below 66% or above 67% was not significant
(data tables for non significant tests are in Appendix D). Additionally, the
results of chi-square testing the null of independence between stunting, wasting
or underweight and NARS of protein calories were not significant. Therefore,
the null hypothesis 5 is retained. This hypothesis testing should be evaluated

carefully because the dietary analysis only reflects the child’s complementary

diet. The contribution of breast milk could not be assessed. Furthermore, this

55

hypothesis testing was based on a sub-sample of 49 cases.

Summary Hypothesis Testing
Table 4.10 presents a summary of the null hypotheses tested in this study. The
findings suggest that the nutrient qualities of complementary diets for Gabane
Children are different from the requirements for adequate growth, but they are
not different from that of children in the entire country. Also, households with
malnourished children were similar in maternal income, maternal education,
household’s income, child’s gender, child’s birth order, household's size, and
headship when compared with adequately growing children. However,
malnourished children were significantly older than adequately grong
children.

Regarding complementary feeding there was an association between the
choice and the timing of the introduction of complementary foods and WAZ
and WHZ. However, there was no relationship between the nutritional quality

of the choice of complementary foods and WAZ, WHZ and HAZ.

56

 

 

TABLE 4. 10 SUMMARY OF THE NULL HYPOTHESES TESTED
Null Hypotheses Statistical Decision Reached
Tests
1. The nutrient qualities of T-test Reject

complementary diets for children Table 4.4

between 3 months and 3 years in

Gabane, are not different compared to

those required for adequate growth.
2. The prevalence of malnutrition for T-test Retain
children of ages 3-36 months in Gabane Table 4.5
village is not different compared to
malnutrition rates in the entire country
(Botswana)
3. Households with malnourished ANOVA, Retain a-e, g and h
children of ages 3-36 months are not Tukey's 8:
different from households with well T-test Reject f
nourished children in these
demographic factors: Tables 4.6 & 4.7
a) mother’s income, b) mother’s
education level, c) household’s income
level, (:1) child’s gender, e) child’s birth
order, f) child’s age, g) household size,
and h) headship (head of household).

4. There is no relationship between T-test Retain 4a with
a) the mother’s choice and b) the Tables 4.8 8: 4.9 respect to HAZ,
timing of complementary foods and reject with respect
child’s weight for age, height for age, to WAZ and WHZ
and height for age Z-scores in children
of ages 3—36 months. Retain 4b with
respect to fluids,
reject with respect

5. There is no relationship between T-test

the nutritional quality of the mother’s
choice of complementary foods and
the child’s weight-for-age, height-for-
age, and weight-for-height z-scores in
children of ages 3-36 months.

57

to mashed food
Retain

PREDICTION MODELS FOR HEIGHT-FOR-AGE, WEI GHT -F OR-HEI GHT
AND WEI GHT -FOR-HEI GHT .

Logistic regression models were built to distinguish households with
children at greater risk for low height-for-age, low weight-for-age, and low

weight-for-height from those with adequately growing Children.

Height-for-Age

A highly significant (P value .0016) logistic regression model estimating the
likelihood that a given child’s height-for-age Z score would be above or below
the cut off point for stunting was built. The variables entered included the
child’s birth weight, number of meals a day, age, birth order, current
breastfeeding status, the number of children at home, the presence of relatives
at home, and household headship. The magnitudes of the influence of these
variables on height-for-age are reported in odds ratios in Table 4.11. This
model accurately predicted 45.45% and 98.48% of stunted and non-stunted
children respectively. ~

The Homer and Lemeshow Goodness-of—Fit test (N orusis, 1990), which
tests the null hypothesis that the model fits, was used to evaluate the goodness
of the model. This test was not significant (chi-square 2.3047, df 8, p-value
.9702), so the null hypothesis was retained. In this model, the child’s

probability of stunting was higher for Children with low birth weight (p-value

.0085), birth order less than 2 (p-value .0286), and who had the father as the

58

head of the household (p-value .0238). Children with low birth weights (less
than 2.5kg), were 52 times, more likely to be stunted than children with birth
weights greater than 2.5kg. Also, first and second born children were 51 times
more likely to be stunted than children with birth orders greater than 2.
Regarding household headship, children in households headed by the child’s
father were 16 times more likely to be stunted than those in households headed
by the child’s grandparent. Nevertheless, the probability of stunting for
Children in households headed by the mother was not significantly different
from that of children in households headed by the child’s grandparent. The
presence of relatives in the household increased the likelihood of stunting by
about 10 times. This odds ratio was approaching significance.

Conversely, the likelihood of stunting was lower for children in households
with 2 or less children compared to households with more than 2 children.
More specifically, households with fewer than 2 children were only 1 % as likely
to have stunted children as households with more than 2 children.

In this model, the influence of the child breastfeeding status, the child’s
age, and the number of meals the child had a day did not reach significance.
However, when the child age and number of meals variables were removed
from the model, the significance of the breastfeeding variable improved from
.5882 to .0625. This might be a reflection of the high correlation between the
variables child’s age and the child’s breastfeeding status. In addition, the

model significance improved from .0016 to .0006. However, the reduced

59

model was only able to accurately predict 27.17% of stunted children compared
to 45.15 % reported earlier. The new reduced model is summarized in Table
4.12.

TABLE 4.11 LOGISTIC REGRESSION MODEL 1: PREDICTION OF
STUNTING (1 = Yes 0 = No)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Model chi-square 29.960 df 11 sig .0016
Homer and Lemeshow chi-square 2.3047 df 8 Sig .9058
Variables R B Odds 95% CI Odds P-value
Ratio Ratio

Child age (months)

1-12 -.0786 -2.250 .105 .006 - 1.758 .29

13-24 .332 .033 - 3.304 .12

25-40 ref8

Birth Order

5 2 .1947 3.934 51.10 1.511 -728.40 .029

2 3 ref

Number of children

5 2 -.2408 -4.3731 .0102 .0003 - .369 .012

z 3 ref

Household Headship

Father .2055 2.812 16.637 1.454 - 190.328 .024
' Mother 1.570 4.805 .158 - 145.800 .367

Grand parent ref

Child’s breastfeeding

Yes -.678 .5078 .0437-5.896 .5880

No ref

Meals/ day

2-3 .6868 .5851 .0114 -29.952 .6990

4-6 ref 1.987 .0612 -64.570

Residing Relatives?

Yes .146 10 .918 -125.485 .0586

No ref

Birth weight

5 2.50kg .259 3.96 52.901 2760-1015972 .0085

2 2.51kg ref

 

 

8 Ref denotes the reference variable in the logistic regression model.

60

 

In congruence with the current understating as reflected in the literature
review, the reduced model (model 2) suggests that breastfeeding is protective
against stunting. More specifically, children who were breastfeeding at the time
of the study were only 16% as likely to be stunted compared to those who were
weaned. However, this association was only approaching significance with a p-
value of .0624. Also, the variables; birth weight, number of children in the home,
birth order, and household headship remained significant predictors of stunting
while the variable, presence of relatives at home, was approaching significant.

Other variables often associated with child nutrition such as; the mother’s
employment outside the home, child’s gender, mother’s education level, the
mother’s choice of complementary foods, and the duration of breastfeeding were

not significantly associated with stunting in this population.

61

TABLE 4. 12 LOGISTIC REGRESSION MODEL 2: PREDICT ING
STUNTING (1 = Yes; 0 = No)

 

 

 

 

 

 

 

Model Chi-square 25.639 df. 7 Sig. .0006
Homer Lemeshow Chi-s uare 3.4138 df. 8 Sig. .9058
Variable B R P-value Odds 95% CI
Ratio Odds Ratio
Birth weight
5 2.50kg 3.700 .309 .0026 40.456 3.629 - 451.07
2 2.51 ref
Birth order
5 2 3.382 .159 .0492 29.432 1.01 - 855. 839
2 3 ref
Breastfeeding
Yes -1.829 -.149 .063 .161 .023 - 1.100
No ref
Residing relatives
Yes 2.258 .141 .062 9.560 .890 - 7059
No ref
Children born in
the household
5 2 -3.749 -.196 .028 .0235 .0008 - .667
_>_ 3 ref
Headship
Father 2.782 .222 .015 6.155 1.709 - 152.71
Mother 1.548 .336 4.704 .201- 110.706
Grandparent ref

 

 

 

 

 

 

 

Weight-for-Age

Table 4.13 summarizes the logistic regression model built to estimate the

child’s likelihood of being under weight or normal weight from the entered

variables. In this model, low weight-for age was more likely in Children who

were currently breastfeeding (p-value .008), had other relatives in the home

62

 

(.0239), or had mother’s with incomes over 400 Pula (.0499). More specifically,
children in households with residing relatives were 26 times more likely to be
underweight than children without residing relatives. Children of mothers with
formal incomes of above 400 Pula were 5 times more likely to be underweight
compared to those whose mothers had no formal incomes. Additionally, the
likelihood of being underweight for children whose mothers earned less than
400 Pula was not significantly different from that of mothers without formal
employment.

Regarding infant feeding, the likelihood of low weight-for—age was not
significantly influenced by breastfeeding or lack thereof. However, among
children who were breast fed, low weight-for-age was 2% as likely in weaned
children compared to those currently breastfeeding. In addition, children who
were introduced to complementary food before 4 months of age were 13% as
likely to be underweight compared to those introduced to mashed after 4
months of age.

The child’s birth order, birth weight, sex, and the number of meals the child
received per day did not significantly influence the likelihood of low weight-for-
age. Other variables often associated with child growth performance, such as
the household headship, the mother’s education level and the household size

were not significantly associated with the child’s weight-for-age.

63

TABLE 4. 13 LOGISTIC MODEL 3: PREDICT ING UNDERWEIGHT

 

 

 

 

 

 

 

 

 

 

Yes = 1, N0 = 2
Model chi-square 34.972 cif. 13 Sig. .0011
Hosmer and Lemeshow chi-square 2.7113 (If. 8 Sig. .9512
Variables B R P- Odds 95% CI for
Value Ratio Odds Ratio
Mother’s formal
income level
S 400 -1.022 .4819 .360 .0211- 6.20
z 400 1.714 -.141 .0499 5.552 1.00 - 30.80
None ref
Child’s age (months) .0249
1-12 -4.412 -22.57 .0105 .0121 .0004 - .356
13-24 -1.197 .2664 .3022 .0366 -2.49
25-40 ref
Child’s age at
introduction of
mashed food
5 4 months -1.989 -.1885 0229 .1368 .0246 - .759
2 4 months I‘Cf
Residing relatives
Yes 3.274 .1864 .0239 26.404 1543-5191
No ref
Sex
Boys .2278 .7866 1.256 .241 - 6. 534
Girls ref
Number of meals / day
2-3 -.4851 .6027 .6156 .0991 - 3.825
4-6 ref
Child’s breastfeeding
status
Ever breastfed 10.204 .794 27005 .000- 4.6E+37
Never breastfed ref
Current breastfeeding
status
Weaned -3.53 -.237 .0080 .0292 .0021 - .398
Breastfeeding ref

 

 

 

 

 

 

 

 

Table 4.13 (Cont’d).

 

 

 

 

 

 

 

 

 

 

 

Birth Order
5 2 .714 .394 2.043 .396 - 10.548
2 3 ref
Toilet facility
Yes -3.422 -.154 .0422 .0326 .0012 - .886
No ref
Birth weight
S 2.5kg 1.171 .307 3.225 .3420 - 3.404
2 2.5kg ref

Weight-for-Height

The logistic regression model summarized in table 4.14 accurately classifies
66% and 99.1 % of wasted and normal weight-for-height children. This model is
significant at p-value .0111. The goodness-of-fit test is not significant, thus the
null hypothesis that the model fits is retained. According to this model, the
probability of wasting might be higher for children with younger mothers (P-
value .0995 and.0764) and those in household whose source of cooking energy
was wood (.0757). These relationships should be evaluated carefully because the
p-values are only approaching significance.

The introduction of mashed food earlier than 4 months (P-value = .0131),
first and second birth orders (P-value = .0257) and the child’s good appetite (P-
value = .0391) were very protective against wasting. In this model children
introduced to mashed food earlier than four months were 0.6% as likely to be
wasted compared to those introduced to food at 4 months or later. In addition,

children whose mother’s perceived as eating enough food were only 1.3% as

65

likely to be wasted compared to those who were perceived to be eating too

much. Furthermore, first and second born children were 1.5% as likely to be

wasted compared to children with birth order of three and greater.

TABLE 4. 14 LOGISTIC REGRESSION MODEL 4: PREDICTING WASTING
(Yes =1, N0 = 0)

 

 

 

 

 

 

 

 

 

 

Model Chi-square 24.424 df. 11 Sig. .0111

Hosmer and Lemeshow Chi-square 1.9152 df. 8 Sig. .9644
Variables B R P- Odds 95% CI for

Value ratio Odds Ratio

Residing relatives

Yes 4.055 .168 .068 57.669 .745- 4465

N 0 ref

Mother’s age (years)

5 21 6.053 .123 .0995 425.183 .317- 570825

22-30 5.493 .155 .0760 242.980 .558- 105794

2 31 ref

Child current breastfeeding

status

Weaned -1.645 .317 .193 .0077 - 4.853

Breastfeeding ref

Child’s age at introduction

of mashed food

5 4 months -4.984 -.296 .0131 .0068 .0001 - .352

2 4 months IEf

Birth order

s 2 -4.172 -.250 .0257 .0154 .0004 - .6032

_>_ 3 ref

Child’s eating pattern

Eats enough -4.314 -.218 .0391 .0134 .0002 - .8053

Eats too little -2.380 .2765 .0925 .0013 - 6.732

Eats too much ref

Birth weight

5 2.50kg -10.28 .8707 0000 .000-1.95E49

2 2.51kg ref

Household cooking energy

Wood 3.2875 .0797 26.776 .712-1007.59

Gas ref

 

 

 

 

 

 

66

 

 

CHAPTER V

DISCUSSION AND CONCLUSIONS

In this chapter, the observations made in the previous chapter are discussed.
Each of the following sections attempts to address each of the five study
objectives. Evidence is drawn from the findings of the relevant research
hypotheses tested in Chapter 4. Furthermore, the similarities and / or differences
between the study findings and the current understanding of the issues as
reflected in the reviewed literature are highlighted.

Objective 1: To characterize complementary diets for children aged between 3
months and 3 years in Gabane.

The Predominant Role of Sorghum in Complementary Diets

Complementary diets in Gabane are primarily sorghum-based. Eighty-one
percent (81%) of children on complementary food were served sorghum-based
porridges. The majority (88%) of these children had fermented sorghum. Soft
' porridge (motogo) was served for breakfast, mid-morning snack and supper.
Thicker consistency of porridge was prepared for the mid-day (main) meal.
Adults were more likely to have meat or vegetable relishes accompanying their
thicker porridges whereas Children’s were served with milk. In fact in this
study, sorghum porridges for Children were mostly (69 / 103) served with milk or
milk and sugar (chi—square; 4.7 df 2 p .030). Among those children whose

primary food was served with milk, 84% had sorghum as the primary

67

complementary food.
Association of Sorghum Porridges with Low Nutritional Status

The observed association between the use of sorghum porridges in
complementary feeding and lower mean WAZ and WHZ but not HAZ scores in
this study is not surprising. First, porridges are bulky and children can tolerate
only very thin consistencies. Yet, these thin porridges, locally referred to as
motogo, are less nutrient dense than thicker porridges and may not meet the
high caloric needs of the growing child. Furthermore, other studies have also
found an association between the use of porridges (sorghum or maize) in
complementary feeding and lower nutritional status (Simondon and Simondon,
1995)

Secondly, it is expected that a child’s inadequate intake will be reflected by
decreased weight-for-age Z— scores. This is because weight-for-age is a very
sensitive measure of the current nutritional status (Gibson, 1990). It responds
quickly to the child’s current inadequate dietary intake and / or acute illnesses.
Hence, weight-for-age has become the nutritional index of choice in less-
developed countries, where resources do not permit regular measurement of
height. Weight-for- height on the other hand is an indicator of the child’s
overall nutritional status. It is influenced by changes in either the child’s weight
or height over time (Gibson, 1990). For children between 1 and 10 years, the
accuracy of weight-for-age’s in assessing nutritional status is stable. It is

therefore considered a more reliable indicator of nutritional status over time.

68

fiM’.

The observed association between the use of sorghum porridges in
complementary foods and lower weight-for-height, validates observations made
earlier with regard to weight-for-age. Thus, decreased weight-for-age and
weight-for-height in this situation may be indicative of the inability of these
porridges to meet the current nutritional needs of growing children.

The observed association between serving complementary food with milk and
lower weight-for-age and weight-for-height was rather surprising (Table 4.8)
because it is expected that the higher nutritive value of milk over sorghum
would be beneficial to the child. Also, nutritionally milk and sorghum are
regarded as complementary proteins because milk provides lysine, the limiting
amino acid in sorghum. This unexpected observation might be explained by the
fact that 84% of children whose primary complementary food was served with
milk had sorghum porridge as their primary complementary food. Thus, the
beneficial effects of milk proteins may have been negated by the low calorie
levels of the overall diets.

Observations that calories and not proteins are often the limiting nutrients
in protein energy malnutrition may also help explain this observation.
Particularly because the efficiency with which the body uses dietary proteins
may be influenced by the adequacy of other nutrients, including calories, in the
diet. In one high protein supplementation study, caloric intake and not protein
was well correlated with both linear growth and weight gain (Martorrell and

Habicht, 1986). This study suggested that the derived benefits of

69

supplementation with high protein supplement might not be explained solely on
the amount of protein in the diet. Similarly, a Collaborative Research Study
Project (CRSP) study, observed that the prevalence of malnutrition in Mexican,
Kenyan and Egyptian preschool children, remained high even though their diet

was high in protein and essential amino acids (Beaton et al., 1992)

The Relationship between the Mother’ 8 Choice of Complementary Food,
Culture, and Food Availability

The use of sorghum porridges and UHT milk in complementary foods may
also be indicative of both cultural preferences and availability. Sorghum is a
drought resistant crop and performs much better than maize in Botswana,
because of the country’s semi-arid climate (Hiebsch and O’Hair, 1986). A
nationally representative survey also found sorghum and UHT milk among the
common complementary foods (and fluids) used in Botswana (Ubomba-Jaswa
and Belbase, 1996). However, the proportion of mothers choosing porridge, as
the primary complementary food compared to other foods in Gabane (88%), was
higher than the national average (47%) reported in 1996 However, it was more
comparable to that seen in settlements (72%).

The use of porridges in complementary food is not unique to Gabane,
Botswana. Porridge (maize, sorghum or millet) use in complementary diets has
been reported in several other studies in less developed countries (Cosminsky et

al., 1993; Simango, 1997; Simondon and Simondon, 1995). In some of these

70

studies, porridge was preferentially given to children perceived to be young for
their age or perceived as unsatisfied by their mother’s milk (Simondon and
Simondon, 1995). Tea, water, home reared animal’s milk and commercially
prepared baby foods are the other food used in complementary feeding.
Interestingly, these fluids were not correlated with the child’s growth
parameters.
The use of tsabana, a soy/ sorghum complementary food provided by the

Government, was rarely reported as a primary complementary food by mothers.

Only one parent out of the 127 whose children were already on complementary
foods considered tsabana as the child’s primary complementary food. This was
rather surprising because tsabana is made available to all children between the
ages of ages 4 and 36 months at a cost to the government and not to the family.
In addition, tsabana is nutritionally superior to sorghum porridges because it is
made from a combination of sorghum and soybeans. Furthermore, tsabana is
fortified with vitamins and minerals. Surprisingly, eligible mothers were seen
receiving tsabana and cooking oil at the time of the study. Additionally, the
clinic supplementary food log indicated that the supply of tsabana had been
uninterrupted for at least 3 months prior to the study. It is likely that tsabana is
not prepared for the index child only but is shared by all children in the
households and / or the whole family. Thus, the allotment is used up sooner
than expected because the program only provides 5-10 kg of tsabana meal

depending on the age of the child. Further investigation into the intra-

71

household distribution and use of tsabana is recommended.

Nutritional Quality of Complementary Foods in Gabane

There is a consensus that nutrient dense complementary foods are required
to sustain a child’s growth and development when breast milk no longer meets a
child’s nutrition needs. The adequacy of the contribution of complementary
diets’ towards a child’s overall nutritional need is estimated based on the
difference between the child’s breastfeeding intake and the requirements for
sustaining the growth trajectory, as defined by a given growth standard (Brute,
1996; Dewey, 1996). This approach requires accurate assessment of the volume
and the nutritional quality of breast milk and measurements of complementary
food consumed by the child. Given the problems inherent in this approach, it is
recommended that these estimates not be used to replace the child’s physical
growth performance (Institute of Medicine, 1992). In keeping with this
recommendation, growth parameters were used in evaluating the nutritional
quality of the child’s intake.

As reflected in the analyses (Table 4.4), Gabane children had lower height-
for-age, weight-for-age and weight-for-height than the CDC / NCHDS reference
population. The prevalence of both chronic and current malnutrition increased
with age. The higher prevalence of undemutrition in older children may be an
indication of the inadequacy of complementary foods. Similar observations in

some studies were associated with low calorie and protein complementary diets

72

 

or increased gastrointestinal infection (Dewey etal., 1992). In this study,

morbidity may also have played a role because of the mildly significant

relationship between Children’s curative clinic visit in the past two weeks and

weight-for-age (x2 = 3.657, P-value =.053).

Objective 2: To evaluate growth indicators (height-for-age, weight-for-age
and weight-for-height) for children in Gabane.

Height-for-age, weight-for-age, and weight-for-height z-scores were used to
assess the growth of children in Gabane. These measures were chosen over
percentiles because they have been shown to more accurately assess nutritional
status of children in developing countries (Gorstein et al., 1994; WHO, 1986).
Percentiles have been shown inadequate in estimating malnutrition prevalence
in populations where a large proportion of anthropometric measurements falls
below the fifth and the third percentile.

The prevalence of low height-for- age, weight-for-age and weight-for-height
in Gabane is high compared to the CDC/ NCHS reference population. As
reflected in Figures 4.1- 4.4 the growth indicators of sample children are within
normal limits from birth to about 3 months. However, all three indices begin to
decline at about 6-7months of age reaching the lowest levels between 12-18
months. These gradually declining growth patterns might be a reflection of
nutritional insults associated with the introduction of complementary foods at
about 4-6 months and the cessation of breastfeeding by most mothers at about 13

months. The increasing prevalence of undernutrition with age, especially

73

 

height-for-age, may also be a reflection of the extended period of time during
which the children were exposed to inadequate diets. Similar observations were
made by Ubomba-Jaswa and Belbase (1996) in a nationally representative
survey.

When compared to other African countries, malnutrition rates in Gabane
may be considered moderate to low. On a three point scale where 5-10%, >20%
and >40% are considered usual, high and severe respectively, the prevalence of
low weight-for-height (5.3%) in Gabane is typical for African countries (UN-
ACC/ SCN, 1998).

Objective 3: Characterize households with children at risk for
malnutrition as determined by low height-for-age, weight-for-age and
weight-for-height. Objective 5: Identify predictors of children with
inadequate growth.

In this section, the findings of the logistic regression models described in the

previous chapter are discussed in an attempt to address objective 3. Objective 5

is also addressed here because it is a logical transition from objective 3.

Height-for-Age.

The increased odds of stunting in children with low birth orders seen in this
study are difficult to explain (Tables 4.12 and 4.13). This difficulty comes about
because birth orders may be used to reflect the relationship between the child’s
growth parameters and the household’s size or assess the possibility of

differential treatment of children based on their birth orders. Given the former

74

understanding, higher birth orders reflect larger nuclear families and may be
associated with increased socio-economic strains. However, it is possible that
this variable is capturing other maternal demographic factors, particularly
because there is a strong (66%) and significant (p-value = .01) positive
correlation (Pearson’s r) between maternal age and birth order. It may be that
younger and inexperienced mothers have difficulty raising their first and second
born children or that the child’s nuclear family is not economically established.
In fact, the inclusion of the maternal age variable in the logistic regression model
causes the birth order variable to loose significance but the maternal age variable
does not reach significance.

The possibility of differential treatment of children based on the child’s birth
order in this study is remote. None of the bivariate analyses completed earlier
suggests any differences in the child’s growth parameters related to the child sex
or birth order. Furthermore, none of the research completed in Botswana and
reviewed in this study supports this possibility (Aplogan et al., 1996; Ubomba-
Jaswa and Belbase 1996).

However in both scenarios, the findings should be evaluated with caution
because the helpfulness of the child’s birth order in assessing the impact of the
household on the child growth performance may vary depending of the
structure of the household. Some households may be made up of multiple
nuclear families while others may have one nuclear family. Thus, a child with a

birth order of two from a given nuclear family may not characterize the growth

75

performance of children from other nuclear families within the same household.

The presence of relatives in the home also appeared to be a disadvantage to
the grong child, in that stunting was 10 times more common in households
with residing relatives. However, this relationship was approaching significance
(P-value = .0586). This variable might also be a reflection of the economic
burden of maintaining a large family. In this study, 70 / 83 households with
adult relatives reported that the relatives helped purchase food. However, each
household also had a mean of 2.48 child relatives with no ability to purchase
food. The suggested association between the presence of residing relatives and
'socio-economic constraints is plausible because this study also found that the
likelihood of stunting was higher in households with fewer than two children
compared to those with more than two children (P-value .0123). Furthermore, a
recent study in Letlhakeng village (Botswana) found that 96% of households
depend on store bought food (Holmboe-Ottesen, 1991). However, 67%, 47% and
13% depended on remittance from household’s member, other relatives and
social welfare respectively.

The increased odds of stunting for children in male-headed households
relative to those headed by the child’s grandparent was also very surprising. If
this variable captured income, as was intended, we would expect better growth
performance for children in male-headed households, because fathers earned
more than mothers regardless of education level in this study. Additionally,

male-headed households were more likely to have older mothers than younger

76

mothers (previously associated with better height-for -age). In this study, a high
proportion (20/ 26) of young mothers (up to 21 years) remained in a households
headed by their mothers (child’s grandparent) compared to 22/ 68 and 6 / 32 of
mothers of ages 22-30 and at least 31 years respectively. Furthermore, an even
higher proportion 23 / 32 of older mothers (at least 31 years old) were in homes
headed by the child’s father compared to 39 / 68 and 5 / 26 for mothers of ages 22-
30 and under 21 years respectively. A Chi-square assessing independence of
mother’s age and household headship was significant at p-value less than .0005.

The suggested association between the male headship and increased
stunting in this sample is difficult to explain. However, further assessment of
the data indicates that in 20 and 21 of the 68 male-headed households’ the
father’s monetary support could not purchase adequate food for the family
and / or the father was also working and resident in a different town/ country
from the rest of the family. The impact of male headship on the child’s stature
may need to be investigated further using a larger sample size.

In congruence with the current understanding on the relationship between
birth weight and the child’s stature, low birth weight strongly increased the
odds of stunting in this population. Low birth weight is thought to result from
intrauterine growth retardation. Other studies have also shown that low birth
weight is a strong predictor for stunting (Adair and Guilkey, 1997).

The likelihood of stunting in this study was minimal in households with

currently breastfeeding children and fewer than two children (Table 4.11 & 4.12).

77

“TI-

Lower birth orders, presence of relatives in the home and low birth weight
increased the odds of being stunted. Among all these variables, the number of
children in the household, birth order, and household headship were highly
Significant predictors of height-for-age, whereas the presence of relatives in the
home and current breastfeeding status were less significant predictors.

Other variables often associated with Child’s growth such as mother’s
income, child’s gender and primary complementary food were not significant
predictors of height-for-age. In the model, the child’s age appeared not to be a
significant predictor of height-for-age, but this needs to be evaluated carefully
because of the high (68 %) and significant (p= .01) correlation (Spearman’s rho)

between current breastfeeding status and child’s age.

Weight-for-Age

With respect to weight-for-age, the odds of being underweight were higher
for currently breastfeeding children, children of mothers who earned more than
' 400 Pula ($100.00/ month) and who had residing relatives. Studies have shown 7
that maternal income is generally protective if suitable child-care alternatives are
available. However, in such studies a clear distinction was made between low
and high-income households. In this study however, the majority of employed
mother could be easily classified as low-income. Twenty (20) of the 45 mothers
with formal employment earned less than 400 Pula, thirteen earned between 400

and 699, eight earned less than 1,000.00 while only 4 earned over 1,000 Pula.

78

Thus, the higher likelihood of low weight-for-age in households with maternal
income of at least 400 Pula does not necessarily suggest that a higher income is
worse than no income but rather reflects the unfavorable trade off between
childcare and formal employment for low-income employed mothers compared
to mothers with no formal income. It is therefore plausible that the income
earned by mothers with incomes greater than 400 Pula did not off set the
disadvantages of leaving the index child with an alternative Childcare giver.
Additionally, since most Gabane residents are employed in the nearby city, it is
likely that such mothers were more likely to spend the whole day away from the
index child. On the other hand, mothers with incomes below 400 Pula and
unemployed mothers were more likely to take care of or possibly supervise the
index child’s care during the day.

However, given the small sample size in this study and the tendency for
respondents to under report incomes, these observations may need validation.
Furthermore, no associations were observed between measures of household’s
wealth such as the type of housing, roofing material and household source of
water with any of the child’s growth parameters.

The higher odds of underweight in currently breastfeeding Children
compared to weaned children may appear puzzling, particularly because of the
well established benefits of breastfeeding across cultures. However, it has also
been shown that the introduction of teas and water to breastfeeding children

may be detrimental to their growth. The introduction of these fluids has been

79

associated with increased exposure to gastrointestinal pathogens and decreased
suckling of the child at the breast. The World Health Organization (WHO)
estimated that 70% of 1, 400 million episodes of diarrhea in children under five
years worldwide are caused by pathogens in contaminated food (WHO, 1993).
Twenty-five percent (25%) of these episodes are caused by E. coli. In turn,
diarrhea] and other gastrointestinal diseases predispose children to malnutrition
as described in the vicious cycle of malnutrition.

The introduction of teas, water and other fluids to breastfeeding children
promotes the replacement of breast milk with these fluids. In addition, the
amount of breast milk produced by the mother falls, as demand diminishes.
Given that almost 95 %, 44%, 37% and 14% of breastfeeding children in this study
were introduced to water, cow’s or goat’s milk, UHT milk and tea before 6
months respectively (Table 4.1), their growth potential may have been
compromised by both increased exposure to gastrointestinal pathogens and
reduced breast milk intake.

Although the current breastfeeding variable collectively looks at Children
who are currently breastfeeding, it is also likely that older breastfeeding children
fared worse compared to younger Children because breastfeeding contributes
only a small portion of their nutritional requirements. Hence in this model,
younger children ( p = .0238) and children introduced to mashed food before
four months (p = .0129) were less likely to be stunted compared to older

children.

80

The presence of relatives in the home also increased the likelihood of
underweight. This variable might undermine the child’s weight-for-age as
previously suggested for stunting.

Conversely low weight-for-age was less likely in younger children (1-12
months) and children introduced to mashed food before 4 months.
Additionally, older children were disadvantaged relative to younger children
because they were exposed to the poor complementary diets for an extended
period.

In the Gabane population therefore, weight-for-age can be accurately
predicted by the variables: the mother’s formal income level, the timing of
introduction of mashed food, the presence of relatives in the home, and the
child’s current breastfeeding status. With these variables, 53% and 94% of

wasted and normally growing children respectively was accurately predicted.

Weight-for-Height

The built logistic regression model for weight -for -height accurately
predicts 66% and 99% of wasted and normally growing children respectively.
Households with mothers of ages 22-30, residing relatives and those who used
wood as source of cooking energy were more likely to have wasted children.
However, these associations did not quite reach significance. The source of
cooking energy is a proxy indicator for household’s income. Households with

higher incomes tend to use propane gas and gas stoves compared to poorer

81

households. Thus, this relationship suggests that children in poorer households
(cook with wood) may have slightly higher probabilities of being wasted. Along
the same line, residing relatives may increase the cost of maintaining the family i
and thus make it harder for families to provide for their children. The presence
of residing relatives has consistently been associated with increased odds of
malnutrition in all growth indices in this study.

The association between mothers of ages 22-30 years with higher
probabilities of stunting was puzzling at first. However, further analyses
revealed that 22-30 year old mothers were more likely to be in a household
headed by the Child’s father. Previously, households headed by the father were
more likely to have stunted children compared to those headed by the child’s
grandparent. In a chi-square test, 39/ 68 mothers of ages 22-30 were in
households headed by the child’s father, whereas 13 / 68, and 22/ 68 were headed
by the child’s mother and grandparent respectively. Furthermore, 22-30 year
old women constituted a larger proportion (39/ 67) of mothers in households
headed by the child’s father. Women under 21 and over 31 years constituted
only 5/ 67 and 23 / 67 respectively. A Chi-square test of independence between
the variables mother’s age and head of household was significant at p-value less
than .0005. Given the relatively small sample size in this study, all these findings
may need further validation.

The variables, introduction of mashed food earlier than four months, birth

orders less than 2 and the child’s good appetite, were protective against wasting.

82

The protective effect of introducing mashed food earlier than four months was
seen earlier, with respect to the child’s weight-for age. The recurrence of this
variable and its consistency in protecting child growth across different models
and indices may be an indication of its importance in child growth in Gabane.
The variables birth order and the child’s appetite were also protective against
wasting. However, they were not consistent across the models. Table 5.1
summarizes the relationship between the predictor variables and height-for-age,

weight-for-age and weight-for-height.

TABLE 5. 1 PREDICTORS OF HEIGHT-FOR—AGE, WEIGHT -FOR-AGE AND
WEIGHT-FOR-HEIGHT.

 

 

 

 

 

 

 

 

 

 

Variable Relationship of the variable with the growth
index (P-Value)
Height-for- Weight-for-Age Weight-for-
Age Height
Headship NA9 NA
Father
Mother Lowers (.0238)
Grandparent
Residing relatives
Yes Lowers (.0586) Lowers (.0239) Lowers ( .0677)
No
Children born in the NA NA
household
5 2 Protects (.0123)
2 2
Birth weight N510 NS
3 2.50kg Lowers (.0085)
2 2.5 kj

 

 

 

9 Predictor variables that were not significant and could not be retained in the
model are designated as ”not applicable” (NA).
10 Predictor variables that were entered into the model but were not significant
predictors (NS) are designated as NS.

83

 

Table 5.1 (Cont’d).

 

Sex
Boys
Girls

NS

NS

NA

 

Child’s age (months)
1-12

13-24

2 25

NS

Protects .0105)

NA

 

Birth order
S 2
2 2

Lowers (.0286)

NS

Protects (.0257)

 

Breastfeeding status
Weaned
Breastfeeding

NS

Protects (.0080)

NS

 

Breastfeeding
Ever breastfeed
Never breastfeed

NA

NS

NS

 

Child’s age at
Introduction of
mashed food

S 4 months

2 4 months

NA

Protects (.0229)

Protects (.0131)

 

Number of meals/ day
2-3
46

NS

NS

NA

 

Child eating pattern
Enough

Too little

Too much

NA

NA

Protects (.0391)

 

Mother’s formal
income

S 400

2 400

None

NA

Lowers (.0499)

NA

 

Mother’s age (years)
< 21

22-30

> 31

NA

NA

Lowers( .0995)
Lowers ( .0764)

 

 

Cooking fuel
Wood

Propane
Gas

 

NA

 

NA

 

NA

 

 

Objective 4: Describe the relationship between the mother’ s choice and
timing of complementary foods, the household’s demographics and the
child’s anthropometrics.

In the bivariate analysis, the mother’s choice of complementary foods
appeared to influence the child’s growth parameters (t-tests, Table 4.8).
However, this influence did not persist when other variables were factored into
the analyses. In the logistic regression models built earlier, the child’s primary
complementary food was not a significant predictor for any of the three growth
parameters measured in this study. This finding is not surprising because a
large proportion of children is given the same food item (sorghum porridge). In
essence, the predictive power of the mother’s choice of complementary food is
weakened by its commonality compared to other predictors. In short, there
appears to be one primary complementary food item —sorghum porridge and
children exposed this Choice (holding all other variables constant) will inevitably
have comparable growth parameters.

Similarly, a higher proportion of children in the sample was breastfed.
Thus, breastfeeding was not a significant predictor of any of the three growth
parameters measured. However, since the children were breastfeed at different
times relative to the data collection time, some growth parameters could be
predicted based on whether the child was weaned or currently breastfeeding at
the time of the study.

In contrast to the choice of complementary food, the influence of the

85

timing of the introduction of mashed food on weight-for-age was consistent in
both the bivariate (Table 4.9) and the multivariate (Tables 4.13 & 4.14) analysis.
This variable was highly significant in protecting against low weight-for-age and
low weight-for-height.

Among the household demographic variables, the presence of residing
relatives consistently increased the probability of malnutrition. Younger
children were less likely to be malnourished than older children (Table 4.5), but
the influence of the child’s birth order was variable across the growth
parameters. Regarding household headship, children in households headed by
relatives other than the child’s father, mother, or grandparent were more likely
to be malnourished. In addition, the odds of stunting were higher for children

in households headed by the child’s father compared to the Child’s grandparent.

Summary and Conclusions

Understanding the child’s feeding practices, the relationships between the
household profiles, and the prevailing types of child malnutrition are essential
for the proper management and prevention of malnutrition. Such information is
also crucial in the formulation of sound and effective public health policies. The
purpose of this study was to fully describe the relationship between the choice
and timing of complementary food, household demographic factors and the

outcome variables (height-for-age, weight-for-age and weight-for-height z-

86

scores).

The key variables in describing the child feeding practices included the
child’s primary complementary food, the age of the child at introduction of the
different complementary foods and fluids, breastfeeding and the relationship
between the child’s primary caregiver. The variables household headship,
mother’s income, father’s income, the presence of residing relatives, number of
children in the household, type of toilet facilities, nature of household housing,
and the sources of water, cooking and lighting energy were used to describe the
household demographic characteristics. The variables sex, birth weight, and
birth order were used to describe the child’s characteristics.

The study findings suggest that low height-for-age, weight-for-age and
weight-for-height are significant problems in children of ages 3- 36 months in
Botswana. The risk of all forms of malnutrition is lowest in children under 6
months and highest in children of ages 25-36 months.

In general, complementary diets in this study did not adequately meet the
nutritional requirements for children of ages 3-36 months. In addition,
complementary diets are largely constituted of unfortified fermented sorghum
porridge. Tsabana, a high energy, high protein government formulated
weaning food is not considered a major complementary food by mothers. In
addition, complementary fluids and foods are introduced earlier than the
recommended age of introduction. Water and mashed food are introduced

earlier than 4-6 months while cow's milk is introduced earlier than 1 year.

87

Using prediction models built in this study, at least a third of children were
accurately predicted as malnourished. Significant predictors of low height-for-
age in order of increasing partial correlations were, residing relatives (15%),
birth order (19%) number of children in the home (- 24%) birth weight (26%).
Significant predictors of low-weight-for-age were; mother’s income over 400
pula (14%), presence of a toilet facility (-15%), age at introduction-of mashed
food (-19%), residing relatives (19%), the child’s age (-23%), and weaned from
breastfeeding (-24%). With regard to weight-for-height the significant predictors
were the mother’s age under 21 (12%), and between 22 and 30 (16%) years,
residing relatives (17%), source of cooking energy (17%, child’s eating behavior

(-22%), birth order (-25%) and age at introduction of mashed food (-30%).

Study Limitations and Strengths

This study had several limitations. A convenience sample was used instead
of a random sample. Homes in Gabane, like other villages in Botswana, do not
have numerical physical addresses. Thus, although the clinic register had all
names of children under-five years, it was not possible within the time available
for this study to track these households and number all children of ages 3-36
months. Our inability to identify and number these children made random
sampling impossible. Additionally, time and monetary constraints restricted the

sample size in this study.

88

Furthermore, only children who regularly attended Child Welfare
Clinic (CWC) had a chance of being in the study. Children who did not attend
the Child Welfare Clinic for any reason may have different growth parameters
from those who attend. It is expected that the welfare of children whose lack of
government CWC attendance is not replaced by a comparable service would be
worse compared to those who attend.

In addition, the study respondent could be any adult who accompanied the
child to the clinic. In an attempt not to exclude children who were not
accompanied by their mothers, an aunt or a grandparent was allowed to stand in
the place of the child’s mother. This decision was based on the assumption that
adults who are prepared to seek clinic services for the child should be
accountable enough to serve as study respondents. Thus, in this study the
respondents included the child’s aunt, mother, or grandparent. However, it is
not known how the variability in the respondent’s relationship with the study
child might have influenced the accuracy of the information provided.

In analyzing the dietary data, it was not possible to estimate the amount of
breast milk consumed by the child, thus the contribution of breast milk and
complementary diets to the child’s overall intake could not be estimated.
Consequently, the adequacy of either could not be evaluated.

The 24-hour dietary recall method used in this study has inherent
limitations. The method relies on recall and requires correct estimation of

serving sizes of the food consumed. Even with the use of interview aids, the

89

latter requirement may particularly be difficult to meet in a culture that does not
use measurements regularly. Furthermore, only a sub-sample of dietary data
was selected to evaluate the child’s dietary intake in this study.

The study also had several strengths. The investigator’s familiarity with the
culture and language of the study population was especially helpful during the
data collection stage. The other strength in this study was her professional
training and work experience in the area of maternal and child nutrition.
Additionally, the data were checked for possible data coding and entering errors
by another student.

This study comprehensively assesses child growth parameters in Gabane.
The collected data includes the child’s anthropometrics, child feeding practices,
the household’s and Child’s demographic characteristic and dietary intake. This
is probably the first study that has attempted to quantitatively assess dietary
intakes in Botswana. Consequently it is the only study that has attempted to
describe the relationship between the child growth parameters, dietary intake

and household’s demographic characteristics.

Study Implications and Recommendations.

The government sponsored Baby and Mother Friendly Initiative and the
Vulnerable Group Feeding programs are designed to curtail the prevailing rates
of malnutrition in children under five years old in Botswana. The former aims at

strengthening and protecting breastfeeding for the benefit of all Children except

in situations where breast milk is contraindicated. The latter has different target
groups. Of interest to this study are children from 4-36 months. Through the
program, qualifying children are provided with a vitamin and mineral fortified
soy / sorghum mix (T sabana) and cooking oil. The vitamin and mineral
fortification of tsabana is done in accordance with the Codex Alimentarious
guidelines. Thus, the amount of tsabana provided when used as recommended
could potentially meet at least 1 / 3 of the nutritional requirements for children of
ages 4-36 months.

The Baby and Mother Friendly Hospital Initiative (BMFHI) and the
Vulnerable Group Feeding (V GF) programs are therefore complementary.
Exclusive breastfeeding from birth up to 4-6 months as advocated by BMFHI
program, followed by complementation with nutrient dense foods (including
tsabana) and continued breastfeeding until 2 years, as advocated by the latter
(V GF) would eventually meet the needs of the growing child.

However, given the observed child feeding practices in Gabane and the
prevailing malnutrition rates as reported in this study, the effectiveness and
efficiency of these two programs, among other Government programs, need
improvement. It is thus recommended that these programs be evaluated and
possibly be restructured to address the problems such as those seen in Gabane.
Furthermore, this recommendation needs to be given immediate attention
because the country anticipates higher malnutrition prevalence rates due to high

HIV / AIDS prevalence in childbearing mothers. Currently it is estimated that

91

7000-9000 children are infected yearly (Family Heath Division, 2000). Gabane
villagers will definitely have their share of the problem, particularly because
Gabane village has a high prevalence of HIV / AIDS compared to other villages
in the country (AIDS/ STD Unit, Ministry of Health, 1998).

A sizable number of study children also came from households headed by
grandparents. The evolution of this family type may need further investigation.
Such investigation may shed more light into circumstances surrounding this
family type. Does this family type arise due to orphaned children or lack of
family planning by younger mothers? If the former is true then, what
proportion of these orphans are due to AIDS? Further investigation may clarify
these questions and consequently signal the relevant agencies for intervention.
Additionally, health and nutrition education messages may need to target
grandmothers in addition to the Child’s mother.

Extended families are very common in Botswana. The composition of such
families and their impact on the child’s growth may need to be elucidated. This
recommendation is based on the observed relationship between the presence of
relatives in the home and increased odds of stunting, underweight and wasting.
The partial correlation for this variable was 15%, 22%, and 17% for height-for-
age, weight-for-age and weight-for height respectively. In the past, extended
families were believed to be helpful in that all adults shared in the raising

children. However, the current observation reflects an opposite effect.

92

Recommendations for Future Research
This study has highlighted areas that may need further research. First, the

prevalence of malnutrition observed in Gabane compares well with malnutrition
trends reported in 1996 (Ubomba-Jaswa and Belbase, 1996). Malnutrition
persists despite the continuation of the BMFHI and VGF programs. This lack of
improvement suggests that the disparity between the child’s dietary intake and
the nutritional needs of the growing children still exist. This disparity might be
a direct consequence of poor access to food by households and / or unfavorable
changes in any of the underlying causes of malnutrition {also known as
ecological variables}( Jelliffe and Jelliffe, 1989, UNICEF, 1996)

It is also likely that the program inputs (e. g. tsabana) do not reach the
targeted children. Such a leakage in the flow of services might erroneously give
the impression that the nutritional needs of 3-36 months Gabane children exceed
the inputs of the nutrition intervention programs.

In either Situation, a thorough needs assessment of the determinants of
malnutrition in Gabane is essential. In studying these determinants, much
emphasis should be put on the mother's perceived needs and on how the
identified needs can be met. Furthermore, the BMFHI and VGF program
objectives need to be evaluated against the findings of the needs assessment and
appropriate adjustments be taken as needed.

The Vulnerable Group Feeding Program supplies tsabana through its clinic-

based Supplementary Feeding Program to children between the ages of 4 and 36

93

months. However, in this study only one mother considered tsabana as the
child’s primary complementary food. It is unclear why tsabana was not
considered as the child’s primary food and thus was not reported in the 24-hour
dietary interviews. However, if the tsabana was not mentioned in the interview
because it was used up days before the interviews, then our observation is
understandable. Nonetheless, the program may need to investigate the intra-
household distribution of tsabana and its perception by mothers.

One major observation of this study is that over 80% of mothers used and
considered sorghum porridge as the child’s primary complementary food.
However, unfortified sorghum porridges do not meet the nutritional needs of a
child. Most mothers fed their children fermented sorghum porridge which has
higher caloric density per given volume than unfermented sorghum.
Fermentation has been shown to improve both the protein and energy
digestibility of some sorghum varieties (Dendy, 1995). However, even with
fermentation, the caloric content of complementary diets was lower than the age
and sex specific recommended dietary allowances. It is thus recommended that
sustainable household-level technologies for improving the nutrient densities of
complementary sorghum porridges in Gabane be explored.

Extended families are very common in Botswana. Culturally these have
been valued because they promote sharing of resources by members and
transmission of information and skills from older to younger members of the

household. However, in the study the presence of residing relatives was

94

associated with increased odds for underweight, stunting, and wasting. It is
likely that the impact of residing relatives on the household has changed with
the increasing reliance of households on formal income to procure food as
opposed to subsistence agricultural production. In the latter, all members of the
household contributed to the production of food whereas in the former only a
few members of the family may be employed at given time. It is recommended
that the impact of residing relatives on the household and on growth parameters

of 3-36 months old Children be investigated.

95

APPENDIX A

CONSENT FORM

96

11CON SENT FORM (English version)
The investigator is interested in studying the relationship between the

mother’s choice and tinting of weaning/ complementary foods and child
growth in Gabane. The objective of this study is to describe the main weaning
foods that mothers in Gabane feed their children regularly, identify factors
which influence the type of foods the mothers choose, and the age of the child
when these foods are introduced.

As part of this study, I am requesting information from you and other
mothers attending Gabane Clinic today. The information I am requesting
include, your household’s size, income level, type of housing, source of drinking
water, how you normally feed your Child, your formal education level, the
weight and height measurements of your Child and other factors related to how
you care for your child.

Although young children are generally not bothered by weight
measurements, their weights will be taken using Gabane Clinic equipment
because the children are accustomed to them. However, some children appear
not to like height/ length measurements because this procedure requires that
they be helped to stand or lie down as straight as possible. This being the first
time the children ’5 height / length will be taken in the clinic, we intend to make

the measurements less stressful as much as is possible. Length measurements

 

11 Respondents were read a Setswana version of the consent form (directly translated
from this one).

97

will therefore not be taken from any child who appears particularly fearful of the

procedure.

The whole data collection process is expected to take about 15 minutes of
your time. However you are free to Choose not to continue with the data
collection process at any time without any penalty (i.e. you will continue to
receive child welfare Clinic services as usual even if you choose not to

participate in the study).
Please complete the following information

I understand the objectives of this study and the information required as
read to me by the investigator or self. I understand the known risks or
concerns and believe that care has been taken to minimize the risks to my

child and me.

I understand that even after signing the consent form, I can still decide not to
proceed with the entire interview or Choose not to answer certain parts of

the questionnaire.

 

 

Mother’s signature Date

Research Investigator: Maria S. N nyepi
University of Botswana
Private Bag 0022.

Gaborone, Botswana
Tel. 267-355 3469

98

APPENDIX B

UCRIHS LETTER

REQUEST LETTER TO KDC

99

 

OFFICE or
RESEARCH

AND
GRADUATE

niversiiy CommitIee on
Research Involving
Human Subjects
(UCRIHS)

Michigan State University
'46 Administration Building
East Lansing. Michigan
48824—1046

517/355-2180
FAX: 517/353-2976

The Michigan State University
IDEA rs institutional Diversny:
Excellence in Action

MSU is an aflr’nnalive-aclion,
equal—opportunity institution

MICHIGAN STATE

 

UNIVERSITY

June 10, 1999

TO: Dr.Jenny BOND
2100 South Anthony Hall

RE: IRB# 99344 CATEGORY: 1-C, E
APPROVAL DATEzJune 10, 1999

TITLEITHE MOTHER'S CHOICE AND TIMING OF COMPLIMENTARY FOODS ON
GROWTH OF CHILDREN IN BOTSWANA

The University Committee on Research involving Human Subjects' (UCRIHS) review of this
project is complete and I am pleased to advise that the rights and welfare of the human
subjects appear to be adequately protected and methods to obtain informed consent are -
appropriate. Therefore, the UCRIHS approved this project.

RENEWALS: UCRIHS approval is valid ~for one calendar year, beginning with the approval
date shown above. Projects continuing beyond one year must be renewed with the green
renewal form. A maximum of four such expedited renewals possible. Investigators wishing to
continue a project beyond that time need to submit it again for a complete review.

REVISIONS: UCRIHS must review any changes in procedures involving human subjects, prior
to initiation of the change. If this is done at the time of renewal, please use the green renewal
form. To revise an approved protocol at any other time during the year. send your written
request to the UCRIHS Chair, requesting revised approval and referencing the project's IRB#
and title. Include in your request a description of the change and any revised instruments.
consent forms or advertisements that are applicable.

PROBLEMS/CHANGES: Should either of the following arise during the course of the work,
notify UCRIHS promptly: 1) problems (unexpected side effects, complaints, etc.) involving
human subjects or 2) changes in the research environment or new information indicating
greater risk to the human subjects than existed when the protocol was previously reviewed and
approved.

If we can be of further assistance. please contact us at 517 355-2180 or via email:

UCRIHS@piiot.msu.edu. Please note that all UCRIHS forms are located on the web:
http://wwwmsu.edu/unil/vprgs/UCRIHS/

David E. Wright. Ph. D. R‘}

UCRIHS Chair

    
 

DEW:
cc: Maria Nnyepi

100

 

University of Botswana

 

Private Bag 0022 Gabo rone Botswana
Telephone 351151 . Fax 356591 . Telex 2429 SD

 

 

May 10, 1999

Regional Medical oflicer
Kweneng Regional Health Team
Private bag 5

Molepolole

Dear Regional Medical officer,
Subject: The role of weaning porridges on the child's growth indicators: A Survey

I am interested in investigating the relationship between the mother’s choice of
complementary food and the child’s growth indicators. My interest was sparked by the
findings of the Determinants of Malnutrition Survey carried out in 1995 by the Family Health
Division, UNICEF and the University of Botswana. A UNICEF Consultant, Ms. Ubomba-
Jaswa and Mr. Krishna Belbase put the initial report for this survey together in 1996.
Ubomba-Jaswa and Belbase reported differential use of porridges, infant formula and UHT
milks by mothers of different demographic characteristics. However, the survey never
attempted to correlate the child’s complementary diet with the child’s growth indicators. A
step that might shed more light on the reported slowed growth (growth faltering) in children
of weaning age.

As an attempt to shed more light on the relationship between weaning diets and growth
faltering, I have proposed to investigate this issue further in one of the villages that was
surveyed in the Ubomba-Jaswa and Belbase’s survey. Therefore, the purpose of this letter is
to request permission to interview consenting mothers of children attending the Child
Welfare Clinic at Gabane Clinic. The interviews will not disrupt your regular Child Welfare
Clinic services or require your employee’s time, as I will be interviewing consenting parents
as they await regular services or finish receiving their services.

Your assistance in this matter will be greatly appreciated.

 

Maria S. Nnyepi

Department of Home Economics Education

101

APPENDIX C

QUES TIONAIRE

102

Respondent Number

 

HOUSEHOLD DEMOGRAPHIC DATA

1.0 Are you this Child’s mother?

1.1 YES 1.2. NO. If NO, how long have you known the child?

2.0 If NO, is this child an orphan?
2.1 YES
2.2 NO

3.0 How many children do you have? Refers to mother or surrogate mother.

3.1 Boys
3.2 Girls
4.0 What is the total number of children less than five years.
5.0 Is this child’s father staying with you?
5.1 YES. (Skip to 11)
5.2 NO
6.0 If NO, is this child’s father working in another town / country?
6.1 YES
6.2 NO (skip to 9)
7.0 If YES, how often does this child’s father come home?

 

 

 

 

7.1 per week

7.2 per month

7.3 per 3 months
7.4 per 6 months
7.5 per year

 

8.0 How long does the father stay with the family whenever he visits?
9.0 If NO, Are you the head of the family?
9.1 YES (skip to 11)
9.2 NO
10.0 If NO, who is the head of the family?
11.0 Does this child’s father help support the children?
11.1 YES
11.2 NO (skip to 13)
12.0 IF YES, is the support enough to buy food?

 

 

 

12.1 YES
12.2 NO
13.0 Are there any close relatives staying with you? YES
13.1 NO. (skip to 18) If YES, how many adults? And
Children?
14.0 Are some of these relatives this child’s grand parents?
14.1 YES 14.2 NO

103

15.0

16.0

17.0

18.0

Do all people in the household share meals?

15.1

YES

15.2 NO
If YES, do the adults staying with you help buy food?

16.1

YES

16.2 NO

EDUCATION AND EMPLOWENT DATA.

What is your education level?

17.1
17.2
17.3
17.4

None.
Primary.
Secondary
Tertiary

Are you employed outside the home?

18.1
18.2

YES
NO. (skip to 23)

19.0 If employed outside the home, who takes care of this child while you are
at work?Grand parent(s)

20.0 What is your occupation?

19.1
19.2
19.3
19.4
19.5
19.6

Employed helper

Relative other than grand parent
Neighbor

Day care center / preschool

I take the child with me to work
Other

 

21.0 How much are you (refers to the mother/ surrogate mother) paid per

month?

22.0

21.1
21.2
21.3
21.4
21.5
21.6
21.7
21.8

under 400 Pula
401 to 699 Pula
700 to 999 Pula
1000 to 1399 Pula
1400 to 1899 Pula
1900 to 2399 Pula
2400 to 2999 Pula
over 3000 Pula

What (other) sources of income do you (mother / surrogate mother) have?

2.1
22.2
22.3
22.4
22.5

Source of income Amount per month
Rentals
Sales of produce from your garden
Sales of Handicrafts
Support from Child’s father
Proceeds from a kiosk in the home

 

 

 

 

 

104

23.0

24.0

25.0
26.0

22.6 Other

 

What is the education level of the child’s father?N one
23.1 Primary

23.2 Secondary

23.3 Tertiary

Is this child’s father employed outside the home?
24.1.1 YES
24.1.2 NO (skip to 28)
If YES, what is his occupation?
How much do think this child’s fathers is paid per month?
26.1 under 400 Pula
26.2 401 to 699 Pula
26.3 700 to 999 Pula
26.4 1000 to 1399 Pula
26.5 1400 to 1899 Pula
26.6 1900 to 2399 Pula
26.7 2400 to 2999 Pula
26.8 over 3000 Pula

 

27.0 What (other) sources of income do you think the child’s father has?

Source of income Amount per month
27.1 Rentals
27.2 Sales of agricultural produce
27.3 Sales of Handicrafts
27.4 Proceeds from a kiosk in the home
27.5 Other

 

 

 

 

 

CHILD FEEDING PRACTICES.

28.0 Is this child breastfeeding?

28.1 YES (skip to 32)
28.2 NO

29.0 If NO, was the child ever breastfed?

 

29.1 Yes -) how long was the child breastfed?
29.2 NO.

30.0 If NO, what was this child fed? ( answer this question and then Skip to 34)

30.1 Infant formula
30.2 UHT pasteurized milk
30.3 Store-bought fresh milk

105

30.4 Milk from an animal at home
30.5 Other
31.0 How long do you intend to breastfeed?
32.0 How long was the child exclusively breastfed?
33.0 If employed outside the home, what was this child fed in place of breast
milk while you were at work?
33.1 Expressed breast milk
33.2 Infant formula
33.3 UHT pasteurized milk
33.4 Store-bought fresh milk
33.5 milk from an animal at home
33.6 Other
34.0 If the following fluids have been introduced, when were they first given to
the child regularly? ‘
34.1 Infant formula
34.2 UHT milk
34.3 Store-bought fresh milk
34.4 milk from an animal at home
34.5 Tea
34.6 Water
34.7 Juice
34.8 Other
35.0 If this child has been introduced to mashed or semi-solid food, when they
first given regularly?
36.0 How many meals does the family eat per day?
36.1 One
36.2 Two to three
36.3 More than 3

 

 

 

 

 

 

37.0 How many times is this child fed
38.0 per day?
38.1 Two to three
38.2 Four to Six
38.3 Other
38.4 If this child is still breast feeding, give number of breastfeeds per
day

39.0 Who feeds this child most often?
39.1 Mother
39.2 Surrogate mother
39.3 Older Sibling
39.4 Grand parent(s)
39.5 Other Adult relative

 

106

39.6 Helper

39.7 Child feeds self
40.0 If the child is already on semi-solids foods, What is the major food item

fed to the child( i.e. the most frequently fed food item per day)

40.1 Porridge, Type

40.2 Tsabana

40.3 Commercially prepared

40.4 baby food (bottled food)

40.5 Commercially prepared Instant baby cereals

40.6 Mashed potatoes / pumpkin

40.7 Other mashed vegetables

 

 

 

 

 

40.8 Mix of and
40.9 Other
41.0 How do you usually prepare and serve (the major food item

 

identified in 38 above). Check all that apply.
41.1 Type of cereal meal
41.2 Prepared / served with a source of animal protein(milk/ meat)

 

times per day
41.3 Served with beans times per day.
41.4 Served with sugar times per day
41.5 Served with a rich source of fat/ oil( nuts, mayonnaise,
butter / margarine per day
41.6 Other

 

42.0 How do you describe this child’s eating behavior?
42.1 Child eats enough food
42.2 Child does not eat enough food
42.3 Child eats too much food
43.0 Does this child have his / her own plate or shares the plate with other
children
43.1 Child eats by herself/ himself
43.2 Child eats with others
44.0 Is there usually enough for this child to eat?
45.0 Is there usually enough food for this child to eat?
44.1YES
44.2 NO

107

DIETARY DATA SPECIFICALLY FOR THE STUDY CHILD
45 24 hour- dietary recall

 

Time Food item Portion Description of food
Size

 

 

 

 

 

 

46 Is this recall typical of this child’s intake?
46.1 YES
46.2 NO--- How is it different?

 

47 Does this child take other meals away from home? e.g. at preschool? Or
Day Care Center?

47.1 YES
47.2 NO

108

 

CHILD ANTHROPOMETRIC AND HEALTH DATA
48.0. Complete the table

 

 

 

 

 

48.1 Birth Date 48.5 Birth weight

48.2 Apgar score 48.6 Today’s weight

48.3 Birth order 48.7 Today’s height/ length
48.4 Sex

 

 

 

 

49.0 Was this child ill within the last two weeks?

49.1 YES
49.2 No
50.0 YES, was this child taken to the clinic?
50.1 YES
50.2 NO

51.0 How would you describe this child’s general health?
51.1 Very healthy
51.2 Fairly healthy
51.3 Child is ill most of the time

52.0 How many times was this child hospitalized in the past year
53.0 Why was this child hospitalized?

 

 

 

 

HOUSING CONDITIONS.

54.0 What type of housing does the family live in?
54.1 Traditional houses/ roundavels

54.2 Modem house
54.3 Other

55.0 Is the dwelling place rented or owned by the family?
55.1 Rented

55.2 Owned
55.3 Grand parent’s home

109

 

55.4 Allowed use without charge by other relative
55.5 Other

 

56.0 What type of roofing is on the main house / roundavel

56.1 Thatch

56.2 Tiles

56.3 Metal sheets
56.4 Other

57.0 What is the household’s source of drinking water?

57.1 Public standpipe

57.2 Stand pipe in the yard
57.3 In-door plumbing
57.40ther

58.0 What type of toilet does the household use?

58.1 Pit latrine
58.2 Flush toilet

59.0 How do you light your house?

59.1Paraffin lamp
59.2 Candle

59.3 Electricity
59.40ther

60.0 What type of energy is used for cooking?

60.1 Wood
60.2 Gas

60.3 Electricity
60.4 Other

110

APPENDIX D

OTHER DA TA TABLES

111

TABLE D]: THE RELATIONSHIP BETWEEN AGE OF INTRODUCTION

OF COMPLEMENTARY FOODS/FLUIDS AND THE CHILD’S

 

 

 

 

GROWTH PARAMETERS
Nutrition Index/proportion of N Mean Z-score T-statistics P-value
calories or protein in diet
HAZ
Tea
0-6 16 -1.2256 -.461 .678
7-12 11 -.9789
UHT milk
0-6 42 -.7907 .442 .660
7-12 20 -.9845
Infant Formula
0-3 48 -.6215 .254 .801
4-12 11 -.7255
Cow / goat’s milk
0-6 17 -.8794 .737 .533
7-12 3 -1.9500
Water
0-3 96 -.8002 -.464 .644
4-12 31 -.6839
WAZ
Tea .
0-6 16 -.9094 .059 .954
7-12 11 -.9373
UHT milk
0-6 42 -.7740 .853 .397
7-12 20 -1.0480
Infant Formula
0-3 48 -.6215 .254 .801
4-12 11 -.7255
Cow/ goat’s milk
0-6 17 -.6018 1.190 .348
7-12 3 -2.0167
Water
0-3 96 -.6427 .796 .2090
4-12 31 -.8487

 

 

 

 

 

112

 

TABLE 01 (Cont’d.)

 

WHZ
Tea
0-6
7-12
UHT milk
0-6
7-12
Infant Formula
0-3
4-12
Cow/ goat’s milk
0-6
7-12
Water
0-3
4-12

 

 

16
11

42
20

48
11

96
31

 

-.9172
-.4109

-.3350
-.5105

6.667E-02
1.388E-17

-.453E-02
-.9400

-.1300
-.5326

 

.638

.638

.165

1.765

1.640

 

.529

.526

.869

.095

.103

 

113

 

TABLE D2: THE RELATIONSHIP BETWEEN THE PROPORTION OF
CALORIES AND PROTEIN IN THE DIET12 AND THE CHILD

 

 

 

 

GROWTH PARAMETERS.
Nutrition Index/proportion of N Mean Z-score T-statistics P-value
calories or protein in diet
HAZ
% Protein
S. 66% 25 -.5824 .483 .633
2 67% 24 -.7346
% Calories
_<_ 66% 47 1.500E-2 .885 .380
2 67% 2 -.6855
WAZ
% Protein
5 66% 25 -.3904 .735 .466
2 67% 24 -.6821
°/o Calories
g 66% 47 .9050 1.54 .134
2 67% 2 -.5945
WHZ
% Protein
5 66% 25 -3.12E-2 .652 .517
2 67% 24 -.2888
% Calories
g 66% 47 1.2150 1.460 .151
2 67% 2 -.215

 

 

 

 

 

 

 

12 Dietary analysis excludes the contribution of breast milk

114

 

TABLE D3: THE RELATIONSHIP BETWEEN HOUSEHOLD'S
DEMOGRAHIC FACTORS AND THE CHILD’S HAZ, WAZ,

 

 

 

AND WHZ
Nutrition Index / Demographic N Mean Z-score T-statistics P-value
factors
HAZ
Sex
Boy 69 -.8303 -.683 .496
Girl 63 -.6870
Maternal education
None 21 -.5914 .827 .410
Secondary 78 -.8355
Maternal income
5 400 Pula 20 -.8140 .382 .704
.>. 400 Pula 22 -.9664
Maternal employment
Yes 45 -.7836 -.148 .882
No 87 -.7507
Birth order
s 2 75 -.8141 -.571 .699
2 3 57 -.6932
Headship
Parent 79 -.6623 1.076 .284
Grandparent 52 -~8933
WAZ
Sex
Boy 69 -.7399 -.524 .601
Girl 63 -.6259
Maternal education
None 21 -.6619 .120 .905
Secondary 78 -.6996
Maternal income
5 400 Pula 20 -.7990 .360 .726
2 400 Pula 22 -.9400
Maternal employment
Yes 45 -.7451 -.395 .694
No 87 -.6546
Birth order
g 2 75 -.7221 -.387 .699
2 3 57 -.6372
Headship
Parent 75 -.6768 .062 .946
Grandparent 52 '-6921

 

 

 

 

 

 

115

 

TABLE D3 (Cont’di

 

 

‘WHIZ

Sex

Boy

(Sirl
Maternal education

None

Secondary
Maternal income

5 400 Pula

2 400 Pula
Maternal employment

'Yes

190
Birth order

5:2

225
Headship

Parent

Grandparent

 

69
63

21
78

20

45

87

75
57

79
52

 

-.2712
-.1878

-.3910
-.8355

-.3035
-.4050

-.2927
-.1997

-.2435
-.2154

-.2925
-.1435

 

-.402

-.703

.269

-.428

-.134

-.700

 

.688

.484

.791

.671

.894

.485

 

116

 

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117

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