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ABSTRACT
Birth weight is an important indicator of child survival, future physical growth and
mental development. Twenty million infants world wide representing 15.5% of all
births are born with low birth weight, 95.6% of them in developing countries like
Nigeria. This study investigates the determinants of birth weight and proposes a
statistical model that can be useful in epidemiological studies of birth weight. Data
on birth weight, maternal age, gestational age and sex of index baby, on 1023 live
births between 2000 and 2001 in a private hospital in Onitsha, Anambra State, were
extracted from the hospital’s record. The data were analyzed using multiple
regression method, Chi-square and odds ratio. Mean birth weight is 3.24 kg and
standard deviation is 0.479. Males significantly weigh more than females. Mean male
low birth weight and mean female low birth weight are not significantly different (p >
0.01). So also it is with mean male high birth weight and mean female high birth
weight. Mean male normal birth weight is significantly higher than mean female
normal birth weight (p = 0.000). This suggests that the factor responsible for the
difference in mean male and mean female birth weights must be acting only within
the level of normal birth weight. Level of Low Birth Weight is 3.91% and that of high
birth weight is 8.50%. Birth weight significantly depends on parity, gestational age
and sex of baby, p = 0.000, but not on maternal age, p > 0.01. The proposed model is
birthweight (􀝕􀷜) = 0.319 + 0.002(maternal age) + 0.045(parity) + 0.010(gestation age)
– 0.107(sex of baby). The model is adequate. F value is 31.957, p = 0.000. Mothers in
their first pregnancies and preterm labours should be handled in medical facilities
with trained personnel and adequate equipments to handle low birth weight babies.
High birth weight may be an emerging important issue and healthcare providers may
well start being aware of it.
vi
TABLE OF CONTENTS
Title page i
Approval page ii
Dedication iii
Acknowledgement iv
Abstract v
Table of Contents vi
List of Tables ix
Chapter one Introduction 1
1.0 Statement of the Problem 1
1.1 Significance of the Study 2
1.2 Scope and Limitations 2
1.3 Objectives 2
Chapter two Literature Review 3
Chapter three Research Methodology and Data Presentation 14
3.0 Type of Data 14
3.1 Source of Data 14
3.2 Method 14
3.2.1 Regression Analysis 15
3.2.1.1 Test for Significant Relationship 16
vii
3.2.1.2 Coefficient of Multiple Determination 19
3.2.2 Hypothesis Testing 19
3.2.3 Dummy Variables 21
3.2.4 Determination of number of Categories 22
3.2.5 Odds Ratio 23
3.2.6 Chi-Square 24
3.3 Data Presentation 25
Chapter four Data Analysis 26
4.0 Univariate Analysis of Birth Weight and its Determinants 26
4.1 Analysis of Birth Weight by Age and Sex 26
4.2 Analysis of Birth Weight by Parity and Sex 27
4.3 Testing for Difference Between Mean Birth Weight of
Male and Female Babies 27
4.4 Rate of Low Birth Weight 28
4.5 Testing for Difference between Mean Male Low Birth
Weight and Mean Female Low Birth Weight 29
4.6 Rate of High Birth Weight 31
4.7 Testing for Difference between Mean Male High Birth
Weight and Mean Female High Birth Weight 31
4.8 Testing for Difference between Mean Normal Birth Weight
of Male and Female Babies 33
viii
4.9 Relationship between Parity and Age of Mother 34
4.10 Relationship between Birth Weight and Parity 35
4.11 Relationship between Birth Weight and Categories of Parity
using Odds Ratio and χ􀬶 36
4.12 Relationship between Birth Weight and Gestational Age 39
4.13 Relationship between Birth Weight and Maternal Age 40
4.14 Regression Analysis 40
4.15 Regression Analysis using Dummy Variables 41
Chapter Five Summary, Conclusion and Recommendations 49
References 51
Appendix 57
ix
List of tables
1 Nomenclature according to birth weight and gestation 4
2 ANOVA Table for Multiple Regression 18
3 Frequency distribution of new born babies according to maternal
age, parity, miscarriages, gestation age, sex of baby and birth
weight. 25
4 Distribution of birth weight by maternal age and sex of baby 26
5 Distribution of birth weight by parity and sex of baby 27
6 Relationship between Parity and Age of Mother 34
7 􀟯􀬶 analysis of relationship between birth weight and parity
showing observed values and expected values in brackets 35
8 Relationship between birth weight and parity 1 showing odds
ratio and 􀟯􀬶 36
9 Relationship between birth weight and parity 2 showing odds
ratio and 􀟯􀬶 37
10 Relationship between birth weight and parity 3 – 4 showing odds
ratio and 􀟯􀬶 38
11 Relationship between birth weight and parity 5 and above showing
odds ratio and 􀟯􀬶 38
12 Relationship between birth weight and gestational age showing
odds ratio and 􀟯􀬶 39
x
13 􀟯􀬶 analysis of relationship between birth weight and categories
of maternal age with observed values not in brackets and
expected values in brackets. 40
14 Probabilities and Odds of Low Male Birth Weight Delivered
Before 37 Weeks Gestation By Selected Characteristics 118
15 Probabilities and Odds of Low Female Birth Weight delivered
Before 37 Weeks Gestation by Selected Characteristics 119
16 Odds and Odds Ratios of Low Male Birth Weight by Low Female
Birth Weight of Births before 37 Weeks of Gestation by Selected
Characteristics 120
17 Probabilities and Odds of Low Male Birth Weight Delivered
at 37 Weeks gestation and above by Selected Characteristics 121
18 Probabilities and Odds of Low Female Birth Weight Delivered
at 37 Weeks Gestation and above by Selected Characteristics 122
19 Odds and Odds Ratios of Low Male Birth Weight by Low Female
Birth Weight of Births at 37 Weeks of Gestation and above by
Selected Characteristics 123
1
A STATISTICAL MODEL OF DETERMINANTS OF BIRTH WEIGHT.
CHAPTER ONE
INTRODUCTION
1.0 STATEMENT OF THE PROBLEM
More than 20 million infants worldwide representing 15.5% of all births are born
with low birth weight, 95.6% of them in developing countries (United Nations
Children Fund, 2008). Low birth weight is of public health concern because of the
increased morbidity associated with it. The level of low birth weight in developing
countries is 16.5% and it is more than double the level in developed regions which is
7% (United Nations Children Fund and WHO, 2004).
The exact number of deliveries in Nigeria is not known. The percentage of low birth
weight may not be known but the absolute figure is probably enormous. In
developed countries such babies will be a burden on the government but in Nigeria
and other developing countries, they are likely to be a permanent burden on the
families. With the poor resource setting we have in Nigeria, such burden will worsen
the economic fortunes of the poor families.
1.1 SIGNIFICANCE OF THE STUDY
In this era when medicine is emphasizing primary treatment (preventive medicine)
epidemiology becomes a veritable tool. Epidemiology of low birth weight is the
study of the phenomenon, factors that affect it and the use of the knowledge in
managing the phenomenon. Some of the factors known in literature that affect birth
weight are modifiable like the social and environmental factors. They can easily
change. Some factors are not modifiable and may have statistical relationship with
the birth weight as a dependent variable. Gestational age, parity, age of mother and
sex of baby are non-modifiable factors. In-depth knowledge of these factors and
their relationship with birth weight is necessary for Obstetricians, Pediatricians,
Public Health Physicians and Health Policy makers to understand the epidemiology
of low birth weight and reduce its prevalence and associated public health
2
consequences. Literature is scanty in Nigeria including Anambra State. No statistical
model has been developed yet to address this issue. This study proposes to examine
these factors namely parity, maternal age, gestational age of index pregnancy and
sex of index baby and develop an exploratory model of these determinants of birth
weight that may be useful in epidemiological studies.
1.2 SCOPE AND LIMITATIONS
Method of multiple regression will be used in model specification. All the 1023 life
births obtained in a private hospital between 2000 and 2001 will be used in checking
the adequacy of the proposed model. For financial and time constraints, the scope is
limited to Nkpor, Onitsha and its environs which form the catchment area of the
hospital from which data will be collected.
1.3 OBJECTIVES
The general objective of the study is to do a statistical analysis of birth weight and of
the independent variables that affect it. The specific objectives are:
1. To determine the association, if any, between birth weight and any of the
following variables; parity, age of mother, sex of baby and gestational age.
2. To determine the relationship between parity and age of mother
3. To develop an exploratory model of birth weight with parity, maternal age,
sex of baby and gestational age as its determinants.

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