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TABLE OF CONTENTS

ABSTRACT

CHAPTER ONE

INTRODUCTION

1.1 THE BACKGROUND OF THE STUDY:

1.2 RESEARCH QUESTION

1.3 PROFESSIONAL SIGNIFICANCE OF THE STUDY

CHAPTER TWO

LITERATURE REVIEW

2.1 BACKGROUND

2.2 THEORETICAL FRAMEWORK

2.3 HYPOTHESIS

CHAPTER THREE

METHODOLOGY

3.1 DATA SOURCE

3.2 SAMPLE DESIGN

3.3 DATA DESCRIPTION

3.3.1 Selected Variable

3.3.2 Description of Variables

3.3.3 Analytical Strategy

3.4 DESCRIPTIVE STATISTICS

CHAPTER FOUR

RESULT

4.1 DATA VISUALIZATION

4.2 THE GEO-POLITICAL ZONES

4.2.1 Fertility in the North-Central Geo-Political Zone in Nigeria.

4.2.2 Fertility in the North-East Geo-Political Zone in Nigeria.

4.2.3 Fertility in the North-West Geo-Political Zone in Nigeria.

4.2.4 Fertility in the South-East Geo-Political Zone in Nigeria.

4.2.5 Fertility in the South-South Geo-Political Zone in Nigeria.

4.2.6 Fertility in the South-West Geo-Political Zone in Nigeria.

4.3 NATIONAL VIEW

CHAPTER FIVE

DISCUSSION

5.1 NIGERIA

5.2 NORTH-CENTRAL GEO-POLITICAL ZONE

5.3 NORTH-EAST GEO-POLITICAL ZONE

5.4 NORTH-WEST GEO-POLITICAL ZONE

5.5 SOUTH-EAST GEO-POLITICAL ZONE

5.6 SOUTH-SOUTH GEO-POLITICAL ZONE

5.7 SOUTH-WEST GEO-POLITICAL ZONE

CHAPTER SIX

CONCLUSION AND POLICY RECOMMENDATIONS

6.1 SUMMARY

6.2 RESEARCH QUESTION

6.3 HYPOTHESIS

6.4 RECOMMENDATIONS

6.5 LIMITATIONS OF THE STUDY

REFERENCES

APPENDIX



ABSTRACT

Nigeria is ranked as having one of the highest fertility rates in Africa and the world. Although there are many factors that can be considered to influence women's childbearing, socio-economic factors including education and religion are just parts of the major factors that mainly influence the fertility of women in Nigeria.

The research documents Muslim/Christian and Non-religious differences in the number of children ever born by women across Nigeria by considering possible explanations for these differences by taking a look at how religion influence women's mean number of children ever born. Also, references to education are made with relation only to educational attainment (i.e. primary, secondary or higher education and how it influence women's mean number of children ever born.

The primary focus of this study is to find the connection between how religion influences the rates of fertility in Nigeria. The expected research will be based on quantitative data from the 2013 National Demographic and Health Survey (NDHS) and available scientific paper. The results might be significant for fertility policies across the six geopolitical zones and the states in Nigeria.

Keywords: Female, Education, Fertility, Religion, Nigeria, Policy, Geo-political zones, Region, Survey, Demography, Population, Poisson.



CHAPTER ONE. INTRODUCTION

1.1 THE BACKGROUND OF THE STUDY

Demographers, social scientists and other policymakers from the developing world have been burdened with the search of policies on ways to tame the effect of high fertility to the fast-growing population and poor reproductive health policies. The focus of such programs in practice is mostly geared towards family planning in order to reduce high and unwanted fertility.

While most countries are adopting sure measures that are focused on achieving fertility decline, the result in sub- Sahara Africa has been however slow, especially Nigeria with the largest population in Africa.

Nigeria lies in West Africa, with its border to the Benin Republic in the west, Chad and Cameroon in the east, and Niger in the north. Nigeria is comprised of 36 states and the Federal Capital Territory. It is officially a democratic and secular country. Nigeria became a country as early as the 19th century during the British colonial era and assumed its current territorial shape after the merging of the Southern Nigeria Protectorate and Northern Nigeria Protectorate in 1914. It then officially became a federation in the year 1960.

A population of about 186 million inhabitants puts Nigeria as the most populated country in Africa by almost twice and the seventh most populated in the world (“2017 World Population Data Sheet,” n.d.), with a youthful population ranked as the third-largest in the world, after India and China. The youths account for approximately half of its population under age 18 and almost one in every four women in sub-Saharan Africa is most likely a Nigerian. It has been projected to be the fourth most populated country on earth by 2050 ( Lieberman & McClendon, 2013).

Nigeria is well documented for its religious and ethnic diversity. Religion has special significance and Nigeria is regarded as the only country with almost equal proportions of Christians (49.3% in 2010), located in the South, and Muslims (48.8% in 2010) living predominantly in the northern part of the country (NW, Washington, & Inquiries, 2012) and (Falola & Heaton, 2008).

Each religion has specific norms and ideology related to fertility behavior that has an impact on women's fertility and it differs from one religion to other religion within the country. Muslim women have a strong tendency to have one more child compared to other religions because they believe that children portray the strength of married women. Pronatalist characteristics in the Muslim community have a strong belief that the creator creates sexuality and determines procreation and barrenness (Obermeyer, 1992) and (Atighetchi, 1994).

The possible influence of religion on fertility raises questions such as: are Muslims more fertile than other religious groups in Nigeria? According to Voas (2003), demographic methods need more attention in the study of religion. He remarked that people enter exit and move within religion just as they are born. This is relevant because it shows how important values are linked to fertility behavior (Van de Kaa, 1987).

The future composition of the two major religions in Nigeria, however, might shift hence distorting the current balance as a result of the possible different paths of demographic change. While the Muslim-populated north has attributes favoring very high fertility rates, the rates for the predominantly Christian-south is on the decline. These diverging changes in demographic paths have the potential of leading to the end of the current equilibrium between the two religions with significant implications for the future of the country. Within this study, I examined possible reasons for divergent population trajectories along religious lines as well as the path that these trajectories may potentially take in the future.

Globally, topics about population and population growth are an important subject for debates and since the publication of the popular Malthusian Thesis on population, social scientists such as demographers and economists have made contributions towards understanding population control. At the International Conference on Population and Development (ICPD) program organized in Cairo, Egypt in 1994, governments and the international bodies were encouraged to formulate population and fertilities policies through improvement in gender matters concerning women and the general population (Ashford, 2001).

The question of what factors affect fertility is extremely complex because it needs to look at almost every aspect of human life such as biology, medicine, environmental factors, psychology, sociology, cultural anthropology, theology, economics, and many others. Knowledge from these disciplines can help comprehend the variations in the level of fertility from one individual to another and from one population to another although it cannot fully explain (in a deterministic way) the causality that results in having different numbers of children.

Bongaarts explained that the rate of fertility of a population is dependent on four indices: a marriage index, a contraception index, an abortion index, and finally, that of postpartum infecundability. He also argued that education through these indices can affect the fertility of a woman through knowledge of the use of contraceptives and marriage postponement (Bongaarts & Potter, 2013).

Religion as a variable of interest in understanding demographic behavior is receiving renewed attention in demography. My research examines the role religion plays in determining fertility and how this trend varies across the geopolitical zones in Nigeria since religion is a variable that can be assigned to everyone as either practicing a religion or not.

According to Hayford & Morgan (2008), an earlier study done in the United States using the 2002 National Survey of Family Growth (NSFG) noted that women who identified as being religious had higher rates of fertility, unlike women who said religion was either “less important” or “not important.” This prompted more fundamental questions: why do the more religious want more children? It was observed that those who viewed religion as important had more traditional family lifestyles that tend to lead to increasing fertility and these attitudinal differences account for a substantial part of the fertility differential. Higher fertility within Catholics has been linked with their religious beliefs banning contraceptives. Environments (religious inclusive) that grant women fewer rights might have higher rates of fertility as such influence could affect a woman's power over her fertility (Doepke, Tertilt, & Voena, 2012).

Also, factors (religious inclusive) that promote early marriage and pregnancy may increase female fertility. Currently, the highest ten fertility rates observed in the world are in Africa with western African having a mean total fertility rate of 5.4 while Nigeria's fertility rate is put to be around 5.5 in 2013, a decline from 6.3 in 1991 (Abuja, 2008).

Figure 1.1 below provides a diagrammatic representation of the fertility rate across Nigeria from the year 1960 to the year 2012. It shows almost a steady fertility rate between years 1960 to about 1970. An exponential increase was recorded between 1972 to around 1980, with a subsequent decrease till the year 2012.

Figure 1.1: The total fertility rate of Nigeria between 1960 and 2012

Source: (“Fertility rate, total (births per woman) | Data,” n.d.), The World Bank

Some of the earliest papers on the factors influencing fertility in Nigeria and sub-Saharan African were by Van de Walle (1968) and later Caldwell (1977) and ever since there have been lots of scientific publications on fertility issue in Nigeria but with rare research on the trends across the various state and this is what my research will be addressing.

For several decades, changes in fertility between Christians and Muslims have widened posing significant ethno-regional and religious political implications for its early democracy. The rates of fertility for Christians slumped from 6·1 to 4·5 children per woman between the year 1990 and 2013, on the contrary, that of Muslims gradually rose up from 6·4 to 6·8 and this corresponds to a period that characterizes the introduction of sharia law in northern Nigeria starting from 1999 (Stonawski, Potanиokovб, Cantele, & Skirbekk, 2016).

Although it has been suggested that education can be considered as one of the major means of decreasing high fertility rates, the rates of fertility in Nigeria has been on the decrease, but a relatively slow process when compared to the success made in female education, (Osili & Long, 2008) and (Basu, 2002). Other factors crucial to fertility decline include a region of residence, religion, availability, and use of contraceptives and ethnicity.

Religious belief and practices affect fertility rates by determining the age of marriage, use of contraceptives, abortion practice and the age of sexual initiation (McQuillan, 2004). In Nigeria, the belief system in most religion is that children are gifts from the creator and should be accepted (Nyarko, 2015) and such beliefs impede the family planning and ultimately increases the level of fertility.

The region where a woman resides is important in the discourse on reducing fertility rates because of the prevailing cultural environment which has pronounced effect fertility behavior. Fertility tends to be higher in developing or less developed regions as women struggle to replace children that might die due to malnutrition and diseases, hence ultimately resulting in higher number of children born and this is in line with the demographic transition.

The region of residence is a variable that either directly or indirectly affects education and ultimately fertility in Nigeria since the country has diverse ethnic and religious groups scattered geopolitically (Falola, 2001). In 1991, TFR of 8.05, 7.02, 6.54, and 5.96 were reported in Northwest, Northeast, Southeast, and Southwest respectively. The onset of childbearing in the north is quite different from what is obtainable in the south while childbearing begins around the age 20 in the north, in the south, it occurs around the 30s (Nyarko, 2015). And finally, the use of contraceptive is important when making fertility policies because it empowers women to have a voice in making fertility decisions.

1.2 RESEARCH QUESTION

nigeria political fertility abortion

The research question I intend to answer with this study is: Does religion impact the fertility rates across the regions in Nigeria?

1.3 PROFESSIONAL SIGNIFICANCE OF THE STUDY

This study is of primary significance as it will add to the body of research aimed at understanding of how religion impact fertility rates. This will aid in the effective targeting and implementation of educational and reproductive programs across Nigeria using religious leaders and religious organizations as an important medium in achieving such set objectives.



CHAPTER TWO. LITERATURE REVIEW

2.1 BACKGROUND

McQuillan (2004) gave important insight on how religion affects fertility using different case studies. He showed that firstly, religion matters for fertility when the religion actually has norms that guide fertility behavior, also religion affects fertility when it is able to enforce these norms and to communicate them to members, and finally, when members' religious affiliation matters greatly in their day to day routines. When these three conditions are not met, it is unlikely that religious affiliation matters for fertility.

Heaton (2011) analyzed information from 30 different developing countries and compared the fertility of Catholics, Muslims, and Protestants. He noted substantial differences between the fertility rates of Muslim and Christian, with more Muslims having higher fertility, but with little differences observed between congregants that are either Catholics or Protestants and concluded that those differences vary widely between the countries included in his sample. This showed that being a Muslim gave a positive fertility result when unlike those who had no religious affiliation, while the results for the Christian religions were less clear-cut.

Although, there has been lots of study on how religion and fertility interact in the United States, the focus largely been on Catholic-Protestant differences. These studies showed pronounced variations between Catholics and Protestants during the early twentieth century and during the baby boom period. Higher fertility seen in Catholics has been associated with Catholic's doctrine prohibiting contraceptives, and also due to education and differences in income between Catholics and Protestants, and also to the distinct culture of immigrant Catholic, and to the important place given to churches and religious schools in Catholic communities (Hayford & Morgan, 2008).

Religion often incorporates attitudes and values about appropriate family-related behavior. That is, religion overlaps with narratives about “family values.” Notwithstanding, the link between family and religious values has been portrayed across several layers of family structures, including marital stability, parent-child relationships, and attitudes toward premarital sex and cohabitation (Call & Heaton, 1997) and (Thornton, Axinn, & Hill, 1992).

The impact of religion on fertility is often not given much importance in studies, particularly in Western Europe, which has a pronounced decline in religious institutions.

Using available data from the Generations and Gender Program, religion was shown to affect fertility across different cohorts by resulting in reduced rates of fertility among the various religions in the USA and in Ireland (Goldscheider & Mosher, 1991), (Mosher, Williams, & Johnson, 1992) and (Grбda & Walsh, 1995).

Recent studies have shown a significant influence of religion on fertility behavior; for example, in America and Europe, females who identified as either Protestants or Catholics might have higher fertility rates compared with females who indicated no religion. Additionally, looking at each denomination, the more religious--by the frequency of service attendance and significance of religion in day-to-day lifestyle--the larger the family units (Frejka & Westoff, 2008).

Theories on how religion affects fertility patterns suggest religious institutions place an important value on family and children, alongside other fertility-focused doctrines, which encourages females to play more family roles (Lehrer, 2004) and (McQuillan, 2004). Also, some denominations may put greater importance on childbearing than others. For example, the higher fertility of Catholics when compared with Protestants as mentioned earlier (McQuillan, 2004).

Also, rigid sociocultural environments may determine the length to which religion influences fertility behaviors as some religious institutions might show greater influence on behaviors when congregants show a high sense of responsibility and attachment to the religious community, or when it is considered to be a valued way of identity. Furthermore, religious teachings on family and fertility influence behaviors when such religious places have the structure to pass these teachings to their congregants and to enforce compliance, through formal organizations or informal social pressure. This makes continuous service attendance to instill belief and commitment by repeated exposure to the doctrines and interaction with people of shared similar religion (McQuillan, 2004).

There are lots of research on the fertility effects of different religions, particularly analyzing the effects of Judaism and different Christian denominations using data from the USA and Europe. These studies have shown that there used to be a pronounced difference between Protestants and Catholics in the past, with Catholics having much higher fertility rates, but that this difference is gradually disappearing. Similarly, these studies have also pointed out that fertility rates among Jewish Americans are much lower (Lehrer, 1996).

In Nigeria, researches conducted on the possible effects of religion on fertility rates across different geopolitical zones are limited as research focuses on the Country as a whole. The aim of my thesis is to close part of this research gap by adding to the sparse previous literature.

As of 1960, Nigeria was a Federal State of three Regions namely: Northern, Western, and Eastern regions. In 1963, from the Western region, two extra regions were calved out to form the new Mid-Western Region which later became the Southern region. Nigeria has more than 350 ethnic groups speaking more than 450 languages and is currently grouped into six geopolitical zones that include:

North-Central- (7 States): Plateau, Kwara, Niger, Kogi, Benue, Nassarawa, and FCT.

North-East - (6 States): Bauchi, Gombe, Taraba, Borno, Yobe, Adamawa.

North-West - (7 States): Kebbi, Zamfara, Kano, Jigawa, Kaduna, Katsina, and Sokoto.

South-East- (5 States): Abia, Enugu, Imo, Ebonyi and Anambra

South-South - (6 States): Delta, Bayelsa, Akwa Ibom, Cross River, Edo, and Rivers.

South-West - (6 States): Lagos, Oyo, Osun, Ondo, Ekiti, and Ogun.

The diagram (figure 2.1) below gives a visual representation of the various geopolitical zones in Nigeria

Figure 2.1: Diagram showing the different geopolitical zones in Nigeria.

Adapted from: (Akinlua, Meakin, Umar, & Freemantle, 2015)

2.2 THEORETICAL FRAMEWORK

The theoretical framework that is extensively used in the study of fertility and religion looks at three conditions that can produce religious effects on fertility. First, such a religion might hold specific ideology about fertility-related behaviors. Secondly, the religious organization should be able to enforce conformity to these norms among its congregants -- either through social influence or through sanctions. Finally, religion has a greater ability to be influential when members feel a strong sense of religious solidarity, that is when an individual sees religion as an important part of her identity (McQuillan, 2004).

While it is possible to analyze religion's prescriptions with respect to fertility and check for the existence of pro-natalist norms, the first condition that the states for religion to matter for fertility outcomes, it is more difficult to empirically assess his second and also third condition, namely, that the religion needs institutions to enforce and communicate its doctrines and that religion has to matter greatly in the daily routines of believers. The different institutional development among the different religions and different levels of religiosity among the believers might provide an explanation for those results.

Lots of literature have tried explaining fertility differences between religions and sub-religious groups. Two of such additional theories on the impact of religion on fertility include:

the particularized ideology hypothesis;

Socialization hypothesis.

The particularized ideology theory states that religions are characterized by specific views about fertility, thus inducing fertility differences between specific religious groups and non-religious people. Accordingly, Lesthaeghe & Wilson (1986) showed that, during the Industrial Revolution, Catholics in Europe were characterized by the adherence to high fertility norms and family-oriented values.

The socialization theory argues that religious institutions play a major role in determining individual fertility as a result of the interactions taking place through these religious institutions, each member's decisions or lifestyle shapes the other members' behavior (Bisin & Verdier, 2001).

According to the rational actor model, the economic analysis of fertility behaviors showed that education and finance also affect religion with respect to fertility. The high cost of education per child might prevent women from having more children for those whose religion empower them to seek education and also, a woman's academic and financial power can play a major role in the discussion of optimal fertility (Pollak & Watkins, 1993). The Beckerian theory argues that children are time-consuming, especially for women, hence a higher female income or empowerment results in a lower fertility rate (Becker & Tomes, 1976).

The macro-sociological model argues that socio-economic indices do not directly control fertility; neither do they put a direct effect on the proximate determinants, that is, money or educational attainment does not directly make children or inhibits births. For this reason, an intermediate factor renders these socio-economic conditions into fertility behaviors.

Freedman (1963) and Freedman (1975) outlined differences on norm affecting the proximate determinants of fertility and norms that affect family size.

The diagram below (figure 2.2) shows religion and culture impacts the meta-norms which ultimately influences fertility.

Figure 2.2: A macro-sociological model explaining differential fertility.

Source: Adapted from (Freedman, 1975)



The role that religion plays in this process is that on one part, this "immaterial" factor may have direct effects on the norms about the proximate determinants (prohibition of contraceptives, foster early marriage, etc.). On the reverse side, it may be assumed to govern the complete process in which the determination of fertility takes place. The process in which certain environmental conditions mold family sizes cannot be regarded as being identical across cultures and stable over longer periods of time that include social transitions. The mechanisms are themselves subject to variation and because of the different ways people think, feel and behave with respect to the issues of the family. Norms that control such variations (can be called meta-norms) mainly based on the cultural and socio-religious environment in a given society. These meta-norms also control how reproductive behavior governs individual's rationality as opposed to social conformity. In other words, culture and religion do not only determine the contents of norms but also the degree of their comprehensiveness.

Religious teachings about fertility-related behavior and how institutions go about enforcing these norms may be a less important aspect of the association between religion and fertility. Instead, religious identity may become more important. For example, religious identities in the current United States may be understood as cultural, because they show different ways of “seeing the world” (Wuthnow, 1996).

2.3 HYPOTHESIS

The theories, as well as the empirical findings by Lehrer (1996) suggest testable hypotheses for the subsequent analyses which are: family size may be expected to be higher for women with religion compared to those with no religion.

There are various fertility measures in different kinds of literature but here I used the variable which is total children ever born to examine the association between women's fertility and religions.

My hypothesis states that:

Women with religious affiliation have a higher number of children ever born unlike those without religious affiliation across the regions in Nigeria

Muslim women have a higher number of children ever born than Christian women across the regions in Nigeria; and

Women with the least education (or no education) have the higher number of children than educated women across the regions in Nigeria.



CHAPTER THREE. METHODOLOGY

3.1 DATA SOURCE

Religion and its resultant effect on fertility rates were quantitatively studied using secondary retrospective data sources available from the Nigerian Demographic Health Survey (NDHS), mainly 2013 NDHS (which are the available database). This dataset is a nationally representative survey and contains information on the number of children a woman surveyed has had, the date of birth of every child, and other socioeconomic and demographic variables for nearly ten thousand Nigerian women.

The NDHS was used because by design it holds reliable data on levels and patterns in education, fertility, and family planning practices for a large number of women. Religion and the resultant regional difference in fertility rate is the primary focus of this paper.

3.2 SAMPLE DESIGN

DHS are national data that represent household surveys that provide data for a wide range of indicators in the areas of population, health, and nutrition at the national, zonal, and state levels. Surveys are conducted about every five years. The sample allowed for key indicators to be calculated for each of the six zones (and also for 36 states, and the Federal Capital Territory, Abuja in the 2013 NDHS data).

Information was collected on women aged 15-49 using separate questionnaires.

The questionnaires are structured along the model questionnaires developed by the MEASURE DHS program and modified according to the key requirements in Nigeria and the sample size of the available data set was 38,948.



3.3 DATA DESCRIPTION

3.3.1 Selected Variable

The model that I choose formalizes the hypothesis that shows relationship between the dependent variable fertility (relabeled from children ever born) while the independent variables are religious belief (relabeled as religion), the highest education ever attained (relabeled as education), geopolitical region of the country (relabeled as region), age-group, knowledge of contraceptives (relabeled as contraceptives) and marital status.

3.3.2 Description of Variables

To analyze women's fertility, the study uses women's characteristics such as religion and educational attainment as the predictor variable while total children ever born is the outcome variables.

Dependent Variables:

Total children ever born: By using the variable `total children ever born', it was relabeled as `fertility'. The data had no missing values.

2. Independent Variables:

Various categorical variables were created by re-coding the independent variables and as such forming the various sub-samples below:

Religion: I used this variable to generate a new variable called `religion' and it was further divided into subcategories such as:

Christians

Islam

Other Religions (and this includes traditionalist, other minority religion, and non-believers)

Christianity could not be further sub-divided because data for Protestants and other versions were lacking.

b. Region: I used this variable to generate a new variable called `region' and it was further categorized into:

North Central

North-East

North-West

South-East

South-West

South-South

c. Women's educational attainment: I used this variable to generate a new variable called `highestEducation' and then, it was further divided into:

No Education

Primary Education

Secondary Education

Higher Education

d. Age group: I use age group variable to generate a new variable called `ageGroup' and was divided into:

15-19

20-24

25-29

30-34

35-39

40-44

45-49

e. Knowledge of Contraceptives: I used this variable to generate a new variable called `knowledgeContraceptives' and it was further divided into subcategories such as:

Those who don't use any method

Those who use traditional methods

Those who rely on folktales

Those who use modern methods

f. Marital Status: I used this variable to generate a new variable called `maritalStatus' and It served as control variables and was grouped into:

Unmarried

Married

Cohabiting

Widowed

Separated

3.3.3 Analytical Strategy

In the course of the regressions, I looked at the relationship between religion and the number of children ever born (CEB) and not women's completed fertility, so, in essence, allowing a greater sample size and also to extend the study to a greater number of generations.

For the control variables, there are several results that can be used in line with previous research such as more educated women tend to have fewer children, and the age at marriage influences the number of children as well. The latter served as my control variable as not all women in the sample have completed their fertility, hence their age has a strong influence on their fertility. If religion does not have the same impact on all generations of women, restricting the analysis to older women could lead to biased estimations.

The older a woman is the higher her fertility. Furthermore, women over 45 are expected to have completed their reproduction process and this variable served as a control during the regression since directly introducing the respondent's age somewhat increases the overall fit of the model. However, the effect of age reflects much more complex phenomena than the simple position of the respondent in her “reproductive process”. Indeed, age also reflects important cohort effects.

Fertility at the micro level forms count variable and as such count data have to be analyzed with Poisson regressions or negative binomial regressions in order to avoid any doubt regarding inconsistency and inefficiency (Long & Freese, 2006). The Poisson regression is more appropriate than OLS because it accounts for:

1) Two possible underlying processes that lead to either zeros or positive outcomes; and

2) The discrete nature of the dependent variable.

The general model for Poisson regression is described by:

log[E(Y|x1, x2,…, xk)] = б0 + б1. x1 + б2.x2 + … + бk.xk

In order to attempt to answer the research question, the selected data were expressed in the general statistical model for Poisson Regression as:

Log[E(Fertility|highestEducation,region,religion,ageGroup,knowledgeContraceptives, maritalStatus)] = б0 + б1.religion + б2.region + б3. highestEducation + б4.ageGroup + б5.knowledgeContraceptives + б6.maritalStatus

The first part of the regression involved models showing the variation within each region while the second part of the regression showed variation from region to region.

3.4 DESCRIPTIVE STATISTICS

The variables of choice are presented below with the number of missing data:

Table 3.1: Table of independent and missing variables.

Variables of choice
		Available dataset	Missing dataset
Religion	Christianity	19,838	38,948	---
	Islam	18,578
	Others	532
Region	North-Central	6,251	38,948	---
	North-East	6,630
	North-West	9,673
	South-East	4,462
	South-West	5,874
	South-South	6,058
Highest Education	No Education	13,740	38,948	---
	Primary Education	7,104
	Secondary Education	14,407
	Tertiary Education	3,697
Age Group	15 -19	7,905	38,948	---
	20-24	6,714
	25 - 29	7,037
	30 - 34	5,373
	35 - 39	4,701
	40 - 44	3,663
	45 - 49	3,555
Contraceptives Knowledge	Knows No Method	5,635	38,948	---
	Folkloric Method	242
	Traditional Method	189
	Modern Method	32,882
Marital Status	Unmarried	9,820	38,948	---
	Married	26,403
	Cohabiting	871
	Widowed	993
	Separated	861

Source: Computed from NDHS, 2013 dataset.



CHAPTER FOUR. RESULT

4.1 DATA VISUALIZATION

Below is a summary of the results of the various models of Poisson regression across the regions in Nigeria with the significance level for the individual independent variables in brackets:

The following poisson commands were used:

poisson fertility i.religion i.education i.region i.ageGroup i.Contraceptives i.maritalStatus if northCentral==1, irr

This gave the descriptive information about the north-central part of Nigeria

poisson fertility i.religion i.education i.region i.ageGroup i.Contraceptives i.maritalStatus if northEast==1, irr

This gave the descriptive information about the north eastern part of Nigeria

poisson fertility i.religion i.education i.region i.ageGroup i.Contraceptives i.maritalStatus if northWest==1, irr

This gave the descriptive information about the north eastern part of Nigeria

poisson fertility i.religion i.education i.region i.ageGroup i.Contraceptives i.maritalStatus if southEast==1, irr

This gave the descriptive information about the south eastern part of Nigeria

poisson fertility i.religion i.education i.region i.ageGroup i.Contraceptives i.maritalStatus if southSouth==1, irr

This gave the descriptive information about the south-south region of Nigeria

poisson fertility i.religion i.education i.region i.ageGroup i.Contraceptives i.maritalStatus if southWest==1, irr

This gave descriptive information about the south-western part of Nigeria.

The results of the regressions are presented below:



Table 4.1: Results of The Incidence Rate Ratio (IRR) of Poisson Regression across the individual zones in Nigeria

North-Central	North-East	North-West	South-East	South-South	South-West
Educational Level (Reference: No Education)
Primary Edu	0.9820	1.0024	0.9965	1.0023	1.0265	1.0019
	(0.52) NS	(0.93) NS	(0.89) NS	(0.96) NS	(0.52) NS	(0.96) NS
Secondary Edu	0.8438	0.8877	0.8534	0.8412	0.8791	0.8897
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
Higher Edu	0.6563	0.7409	0.7878	0.6576	0.6427	0.6523
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)
Religion (Reference: Christian)
Islam	1.0142	1.0185	1.0843	0.9621	0.9846	1.0154
	(0.56) NS	(0.49) NS	(0.04)**	(0.89) NS	(0.83) NS	(0.54) NS
Other Religion	1.0319	0.9472	1.1699	1.0424	0.9243	1.0535
	(0.64) NS	(0.54) NS	(0.04) **	(0.58) NS	(0.39) NS	(0.72) NS
Age-group (Reference: 15-19)
20-24	2.0461	2.4114	2.3957	2.4009	2.2801	2.1814
	(0.00)***	(0.00) ***	(0.00) ***	(0.00) ***	(0.00) ***	(0.00)***
25-29	3.0680	3.7902	4.0644	3.2452	3.1267	3.1059
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
30-34	4.2477	4.7451	5.0615	4.4393	4.1802	3.9129
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
35-39	4.7717	5.1559	5.4706	4.7425	4.7877	4.7283
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
40-44	5.0445	5.2907	5.4138	5.0312	5.1609	5.1630
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
45-49	5.1655	5.1770	5.5660	5.3151	5.3446	5.4286
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
Contraceptives (Reference: No Contraceptives)
Folktales	1.1191	1.0951	1.0678	4.9140	0.7864	----
	(0.54) NS	(0.27) NS	(0.25) NS	(0.11) NS	(0.68) NS	----
Traditional	1.2442	1.0402	1.0400	1.0189	1.0907	1.0353
	(0.27) NS	(0.70) NS	(0.68) NS	(0.91) NS	(0.77) NS	(0.81) NS
Modern	1.0035	1.0511	1.0676	0.9889	1.0491	0.9528
	(0.91) NS	(0.04)**	(0.00)***	(0.85) NS	(0.54) NS	(0.47) NS
Marital Status (Reference: Unmarried)
Married	15.0362	11.0764	43.9196	11.3590	5.2078	12.8536
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
Cohabiting	11.5139	7.6999	36.7402	9.9945	4.7288	12.1301
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
Widowed	14.1091	9.7815	41.9435	11.2331	4.9340	11.8731
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***
Separated	11.8509	8.7486	37.8804	8.0133	4.3241	10.0488
	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***	(0.00)***

Source: Computed from NDHS, 2013 dataset.

Note: Poisson Regression. The figures in brackets show the various significance levels.

Keys: * shows significance at 10%; ** at 5%; *** at 1% while NS indicates no significant level and the figures in brackets represents standard errors.

Also, age-group and marital status serve as control variables in the regression and as expected the results were significant on all the P-values.

4.2 THE GEO-POLITICAL ZONES

The results presented below show the significant effects of both religion and region when considered simultaneously across the geopolitical zones in the country.

4.2.1 Fertility in the North-Central Geo-Political Zone in Nigeria.

From Table 4.1 above, a bar chart of fertility in the North Central geopolitical zone of Nigeria was plotted and the bars are shown below (figure 4.1). The bars show how fertility is affected by religion, education, and contraceptives use.

The result of the Poisson regression is presented below:



Figure 4.1: Bar chart of Fertility in North Central Nigeria

(NOTE: NS means `Not Significant').

Source: Computed from NDHS, 2013 dataset.

It is observed that the result in north-central for women who were Muslim and also those who were not religious had no significant difference compared to those who were Christians at p-values of both 5% and 10%.

The effect of other variables such as education showed that secondary and higher educations had a significant effect on fertility compared to primary education which did not have a significant result. Given the other variables are held constant, It was observed that women with secondary were about 0.8 times less likely to have one more child than those without education while women with tertiary education in north-central Nigeria were 0.65 times less likely to have one more child than those without education.

The use contraceptives in north-central showed no significant result at p-values of 1%, 5%, and 10%.

4.2.2 Fertility in the North-East Geo-Political Zone in Nigeria

From Table 4.1 above, a bar chart of fertility in the North Eastern geopolitical zone of Nigeria was plotted and the bars are shown below (figure 4.2).

Figure 4.2: Bar chart of Fertility in North East Nigeria

Source: Computed from NDHS, 2013 dataset.

Just like in north-central, the regression of religion on fertility in north-east showed that women with Islam as their religion and those that were neither Muslims nor Christians had no significant result at p-values of 5% and 10% when compared to those who were Christians.

The effect of education showed that while primary education had no significant result in north-east while those who had secondary education were 0.89 times less likely to have one more child compared to those who had no education while those had higher education were 0.74 times less likely to have one more child compared to those who had no education.

Unlike in north-central, the use of contraceptives was significant and was only significant for those who use a modern method of contraceptives and this showed that those who use modern contraceptives were 1.05 times more likely to have one more child than those who don't and it was significant on both 5% and 10%

4.2.3 Fertility in the North-West Geo-Political Zone in Nigeria

From Table 4.1 above, a bar chart of fertility in the North Western geopolitical zone of Nigeria was plotted and the bars are shown below (figure 4.3).

Figure 4.3: Bar chart of Fertility in North West Nigeria

Source: Computed from NDHS, 2013 dataset.

It was observed that those who had Islam as their religion in north-west were more than 1.08 times more likely to have one more child than those who were Christians and this was significant at both 5% and 10% while those who were neither Christians nor Muslims were more than 1.17 times more likely to have one more than child than those who were Christians and this was also significant on 5% and 10%.

The effect of education showed that while primary education had no significant result in north-east, those who had secondary education were 0.85 times less likely to have one more child compared to those who had no education while those had higher education were 0.79 times less likely to have one more child compared to those who had no education and they were significant on both 5% and 10%. Unlike in north-central and similar to the north-east, the use of contraceptives was significant only for those who use modern method of contraceptives and this showed that those who use modern contraceptives were 1.07 times more likely to have one more child than those who don't and it was significant on 1%, 5%, and 10%

4.2.4 Fertility in the South-East Geo-Political Zone in Nigeria

The bar chart, figure (4.4) shows the result of the Poisson regression of fertility in the South East geopolitical zone of Nigeria.

Figure 4.4: Bar chart of Fertility in South East Nigeria

Source: Computed from NDHS, 2013 dataset.

It was observed that just like north-central and north-east women who had Islam as their religion in the south-east and women who were neither Christians nor Muslims showed no significance at p-values of 1%, 5%, and 10%. The effect of education showed that while primary education had no significant result in north-east, those who had secondary education were 0.84 times less likely to have one more child compared to those who had no education while those had higher education were 0.66 times less likely to have one more child compared to those who had no education and they were significant on all p-values of 1%, 5%, and 10%. Like north-central, the use of contraceptives was not significant at all levels of p-values of 1%, 5%, and 10%.



4.2.5 Fertility in the South-South Geo-Political Zone in Nigeria

From Table 4.1 above, a bar chart of fertility in the South-South geopolitical zone of Nigeria was plotted and the bars are shown below (figure 4.5):

Figure 4.5: Bar chart of Fertility in South-South Nigeria

Source: Computed from NDHS, 2013 dataset.

The regression of religion on fertility in south-south did not show a significant result at 1%, 5%, and 10% when Muslim women were compared to those who were Christian.

The effect of education showed that while primary education had no significant result in north-east, those who had secondary education were 0.88 times less likely to have one more child compared to those who had no education while those had higher education were 0.64 times less likely to have one more child compared to those who had no education and they were significant on p-values of 1%, 5%, and 10%.

Like north-central and south-east, the use of contraceptives in south-south was not significant at all levels of p-values of 1%, 5%, and 10%.

4.2.6 Fertility in the South-West Geo-Political Zone in Nigeria

The bar chart of fertility in the South West geopolitical zone of Nigeria was plotted from the result of Table 4.1 and the bars are shown below (figure 4.6):

Figure 4.6: Bar chart of Fertility in South West Nigeria

Source: Computed from NDHS, 2013 dataset.

The regression of religion on fertility in south-west did not show a significant result at 1%, 5%, and 10% when compared to those who were Christians and it could be observed and concluded that religion was only significant in north-west only.

The effect of education showed that while primary education had no significant result in north-east. It can be also concluded that primary education had no significant result in the model when compared to those without education.

Those who had secondary education in south-west were 0.89 times less likely to have one more child compared to those who had no education while those had higher education were 0.65 times less likely to have one more child compared to those who had no education and they were significant on p-values of 1%, 5%, and 10%.

Like north-central, south-east and south-south, women who use contraceptives in the south-west region when compared to women who don't use had no significant p-values at 1%, 5%, and 10%

4.3 NATIONAL VIEW

For a holistic view of data comparable across the country, another model of Poisson regression done using the commands below:

poisson fertility i.education i.region i.religion i.ageGroup i.Contraceptives i.maritalStatus, irr

The results are presented below:

Table 4.2: Results of Poisson Regression across all the zones in Nigeria

	IRR	P-values
Religious affiliation
Islam	1.0236	(0.07)
Other Religion	1.028	(0.41)
Educational level (Reference: No Education)
Primary Edu	0.9961	(0.76)
Secondary Edu	0.8552	(0.00)
Higher Edu	0.6552	(0.00)
Region (Reference: North- Central)
North East	1.0647	(0.00)
North West	1.0706	(0.00)
South East	1.0183	(0.32)
South-South	1.0535	(0.00)
South West	0.9674	(0.04)
Age-groups (Reference: 15-19)
20-24	2.3949	(0.00)
25-29	3.6946	(0.00)
30-34	4.7394	(0.00)
35-39	5.2697	(0.00)

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