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An Assessment of Fertility Rate and Differentials in Women Within the Reproductive Age in Kaduna State

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An Assessment of Fertility Rate and Differentials in Women Within the Reproductive Age in Kaduna State


This looked at the fertility rate, fertility pattern and some of the diseases that cause fertility problems which leads to pregnancy wastage and fertility differentials in women within the reproductive age using binary Logistic and ple regression. The result shows that the average Total Fertility Rate (TFR) of sample I, sample II and sample III are approximately five (5) children per woman, seven(7) children and six (6) children respectively. The histogram and the line graph of the three samples indicate a gradual decline in TFR as the years increases. Result of logistic regression shows that Sexually Transmitted Disease (STD), Ectopic Pregnancy (ECT) and Ovarian Cyst (OVC) have a negative value which indicates decrease in Total Life Birth. ple regression result indicates a positive value in STD, FB and ECT while OVC is negative in sample I. In sample II, only STD is negative while FB, OVC and ECT are positive. Result of III shows a positive value in STD, FB, OVC and ECT which indicate increase in Total Life Birth (TLB).

Based on the result of the two methods used, binary logistic regression proved to be the best model for analyzing the data since the result is showing negative values in the variables STD, OVC and ECT which indicates decrease in fertility. While positive values in most of the variables in ple Regression result indicates increase in TLB.


TITLE PAGE – – – – – – – – – i
DEDICATION – – – – – – – – ii
CERTIFICATION – – – – – – – – iii
ACKNOWLEDGEMENTS – – – – – – – iv
TABLE OF CONTENTS – – – – – – – vi
LIST OF FIGURES – – – – – – – ix
LIST OF TABLES – – – – – – – xi
ABSTRACT – – – – – – – – – xii
1.0Introduction – – – – – – – – 1
1.1 Background of the study – – – – – – 2
1.2 of Research Problems – – – – – 3
1.3 Aim and Objectives of the Study – – – – – 4
1.4 Significance of the Study- – – – – – – 5
1.5 Scope of the Study – – – – – – – 5
1.6 Definition of s – – – – – – – 5
2.0 Introduction – – – – – – – – 8
2.1 Fertility in Nigeria – – – – – – – 8
2.2 Report on Global Fertility Rate – – – – – – – 16
3.0 Introduction – – – – – – – – 27
3.1 Materials – – – – – – – – 27
3.2 Statistical Techniques and Modeling – – – – – 27
3.2.1 variate Analysis Techniques- – – – – – 27
3.2.2 Logistic Regression – – – – – – – 28
3.2.3 ple Regression – – – – – – – 33
3.3 Tests of Statistics – – – – – – – 38
3.3.1 Normality Test – – – – – – – 38
3.3.2 Test of Independence :Chi-square test – – – – 39
4.1 Introduction – – – – – – – – 40
4.2 Normality Test – – – – – – – 40
4.3 Binary Logistic Regression – – – – – – 45
4.3.1 Binary logistic regression result of sample I – – – – 45
4.3.2 Binary logistic regression result of sample II – – – 47
4.3.3 Binary logistic regression result of sample III – – – 49
4.4 ple Regression – – – – – – – 51
4.4.1 ple Regression results of sample I- – – – – 51
4.4.2 ple Regression results of sample II- – – – – 53
4.4.3 ple Regression results of sample III- – – – – 55
4.5 Results and Discussion – – – – – – 56


1.0 Introduction

Fertility is one of the three principal components of population dynamics that determine the size and structure of the population of a country (Ramesh, ).

Differentials in fertility behavior and fertility levels in different areas and among population strata or characteristics have been among the most pervasive findings in demography (Ramesh, ).

Fertility refers to the actual production of offspring, rather than the physical capability to produce which is termed fecundity. While fertility can be measured, fecundity cannot be. Demographers measure the fertility rate in a variety of ways, which can be broadly broken into “period” measures and “cohort” measures. “Period” measures refer to a cross-section of the population in one year. “Cohort” data on the other hand, follows the same people over a period of decades. Both period and cohort measures are widely used (Wikipedia, 2013).

Infertility is defined by the American Society for Reproductive Medicine (ASRM) as a
disease of the reproductive system that impairs the body’s ability to perform the
function of reproduction. Many different factors and problems can cause infertility,
including problems in the female reproductive system, the male reproductive system,
or a combination of the two (UNTH, ).

1.1 Background of the study

It is a strange thing that in a world where one of the main problems facing humans is the population explosion, or the birth each year of too many children, a fairly large group of women are seeking desperately to become pregnant (Derek, 1998). If a couple are normally fertile, and have sexual intercourse reasonably regularly, a pregnancy will result within one year in 90 percent of cases (Derek, 1998). For this reason, a couple is considered to be infertile after this time, and may require investigations, test and treatment if they wish to have a child. With treatment about 45 percent of the infertile couples will achieve their desire, resulting in a birth of a healthy child (Derek, 1998).

The level of fertility in the world varies broadly by country and culture, social and economic conditions, as well as by individual characteristics such as age. Generally, more industrialized and economically developed societies have lower fertility than less developed societies (Frank, 2012). Also, within countries, generally, more educated groups with higher incomes have lower fertility than less educated groups with lower incomes. Historically, as groups within countries have improved their living standards, and nations have become more economically developed, health conditions have improved, morbidity and mortality have declined, and fertility has declined due to the adoption of fertility-constraining behaviors, such as the limitation of sexual relations or marriage, practice of contraception, and resort to induced abortion. This sequence of events has been observed in western industrialized societies over the last two centuries, and in developing regions in the last half century (Frank, 2012).

In the past 50 years, a reproductive revolution has swept through much of the developing world, leading to large fertility declines in Asia, Latin America and North Africa. In contrast, fertility declines in Sub-Saharan Africa have been small on average, and the continent’s total fertility has remained higher than five births per woman (Bongaarts, 2011).

Several factors contribute to the high fertility rate in Sub-Saharan Africa. Compared with populations in Asia and Latin America, the continent’s people are on average poorer, less educated and have higher child mortality. These factors contribute to a desire for large families, which in turn leads to high fertility. These demographic trends in Sub-Saharan Africa have raised concerns about their potential adverse impact on health, social and economic development and the environment (Bongaarts, 2011).

1.2 of Research Problems

Despite the high fertility rate in Nigeria, there are women that find it difficult to conceive due to some factors that made them temporary infertile and causes fertility problems such as miscarriages in some women. From the related literature, most studies looked at socio-cultural factors, socio-economic and demographical factors that affect fertility and some of these factors affect fertility positively i.e. increases fertility while others affects it negatively. The authors did not look at factors that can affect fertility and human health. However, this tends to look at disease that can cause fertility differential and also affect human health most especially in women.

The methods used for the analysis in some of the literature were logistic regression and bivariate analysis e.g. Alene, and Worku, (2008). Others used multiple regression and bivariate e.g Ramesh, (). Some used only logistic (Coste, et al. (1994)) or multiple regression only and others used other bivariate techniques. The researcher uses both logistic and multiple regression which are all multivariate technique to analyze the data. Since logistic regression is an advance technique over multiple regression (Peter, et al. (2012)), the researcher tries to assess the performance of logistic over multiple regression by comparing the two statistical method.

1.3 Aim and Objectives of the Study

The aim of this is to estimate the fertility rate and fit a model that can best determine the fertility pattern in women within the reproductive age in General Hospital Kafanchan and Dantsoho Memorial Hospital Tudun Wada, Kaduna State of Nigeria using binary logistic and multiple regression. The specific objectives are:

1. To measure the fertility rate in women within the reproductive age in the two Hospitals.

2. To determine the fertility pattern in women within the reproductive age in these two hospitals in Kaduna state of Nigeria.

3. To determine major diseases that causes fertility differentials in women within the reproductive age in these two hospitals in Kaduna state of Nigeria.

4. To compare the result of the two methods used.

1.4 Significance of the Study

The model will help in determining fertility rate and major causes of fertility problems (infertility) in the two hospitals in Kaduna state of Nigeria. Knowing the major fertility problems and the fertility rate, it will help in government policies on how to tackle such problems. It will also help for further research work.

1.5 Scope of the Study

The data for this study is from recorded cases of General Hospital Kafanchan and Yusuf Dantsoho Memorial hospital Tudun Wada Kaduna. This research will only cover the cases that were recorded in the health records of the two hospitals.

Information on total life birth and some of the diseases that causes fertility problems such as STI, ovarian cyst, ectopic pregnancy and fibroid will be used to draw conclusion and the conclusion will be based on the data collected from the two hospitals.

1.6 Definition of s

TLB (Total Life Birth): life birth is a complete expulsion or extraction from its mother of a product of conception irrespective of duration of pregnancy which after such separation, breathes or shows any other evidence of such as beating of the heart, pulsation of the umbilical cord or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. (Singha, 2002) TFR (Total Fertility Rate): is the average number of children a hypothetical cohort of women would have at the end of their reproductive period if they were subject during their whole lives to the fertility rates of a given period and if they were not subject to mortality. It is expressed as children per woman (World Population Prospect (WPP), 2012).

ASFR (Age Specific Fertility Rate): is the number of births to women in a particular age group, divided by the number of women in that age group. The age groups used are: 15-19, 20-24,.45-49. The data refer to five-year periods running from 1 July to 30 June of the initial and final years (World Population Prospect (WPP), 2012).

STD (sexually transmitted disease): are infections that can be transferred from one person to another during sexual activities. STD can lead to serious health complications and affect a woman’s future reproductive plan (Ayo, et al. 2013).

FB (Fibroid): are non-cancerous growths that originate in the muscular wall of the uterus. Fibroids can increase pregnancy complications and delivery risks (University of Maryland Medical Center (UMMC), 2014).

OVC (Ovarian Cyst): An ovarian cyst is a fluid filled sac that is found on the surface, or inside the ovary. Generally if you can become pregnant cyst will not harm a pregnancy. However cysts can interfere with fertility. Many times cysts will either halt the production of an egg or just not release it when it is developed. If you are not releasing eggs then they cannot become fertile (National Scheme (NHS Choices, 2014)).

ECT (Ectopic Pregnancy): ectopic pregnancy is when a fertilized egg implants itself outside of the womb, usually in one of the fallopian tubes. Ectopic pregnancy is a common, life-threatening condition that affects 1 in 80 pregnancies. It means “an out of place pregnancy”. It occurs when a woman’s ovum (egg), that has been fertilized, implants (gets stuck somewhere) instead of moving successfully down her fallopian tube into the womb to develop there (National Scheme (NHS Choices, 2014)).

I represents data from General hospital Kafanchan.

II represent data from Yusuf Dantsoho Memorial hospital Tudun Wada Kaduna.

III represent combined data of the two hospitals (sample 1 and sample 2).

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