Effect on population structure of Human Fertility

The effect on population structure of Human Fertility

CHAPTER ONE

1.0 INTRODUCTION

1.1. BACKGROUND OF THE STUDY

The ceaseless existence of mankind is dependent on his ability to produce offspring. This leads to fertility analysis which is an important component of demographic changes most nations are interested in to see the significance of their population growth from the stand point of human welfare (Adamu, 2016).

As every adult who keeps informed on current events knows, within the past 300 years there has been a remarkable acceleration in the rate of growth among the human population and within the past 25 years even the pace of acceleration has increased. This has occurred through man’s steady progress in reducing his death rate, while making much smaller and tardier reductions in his birth rate. Many nations are undergoing severe political and economic crises in which a very rapid population growth threatens to nullify or even outrun the gains they are making in industrializing and modernizing their economies (Adamu, 2016).

Fertility behaviour is conditioned by both biological and social factors. As in other traditional African societies, several factors have contributed to sustain relatively high levels of fertility in Nigeria. These factors include high level of infant and child mortality, early and universal marriage, early child bearing as well as child bearing within much of the reproductive life span, low use of contraception and high social values placed on child bearing. In the face of perceived high infant and child mortality, the fear of extinction encourage high procreation with the hope that some of the births would survive to carry on the lineage. The traditionally high values placed on marriage ensured not only its universality but also its occurrence early in life with the consequence that child bearing started early in life and in most cases continued until late in the reproductive span. The institution of polygamy which sometimes promotes competition for child bearing among co-wives also contributed to sustain high fertility. Use of modern contraception was traditionally unacceptable as it’s violated the natural process of procreation. The traditional long period of breast-feeding and postpartum abstinence guaranteed adequate spacing between children. Available evidence suggests that there have been changes in these socio-cultural factors over time. Age at marriage appears to have increased, though minimally when viewed at the national level. Use of modern contraception has increased, and improved education (especially of women) appears to have gradually eroded some of the traditional values placed on child bearing.

Fertility is the capability to produce offspring through reproduction following the onset of sexual maturity. The fertility rate is the average number of children born by a female during her lifetime and is quantified demographically. Fertility is addressed when there is a difficulty or an inability to reproduce naturally, which is referred to as infertility. Infertility is widespread, with fertility specialists available all over the world to assist mothers and couples who experience difficulties having a baby. Human fertility depends on factors of nutrition, sexualbehaviour, consanguinity, culture, instinct, endocrinology, timing, economics, personality, way of life, and emotions (Frank, 2017).

Fertility differs from fecundity, which is defined as the potential for reproduction (influenced by gamete production, fertilization and carrying a pregnancy to term). Where a woman or the lack of fertility is infertility while a lack of fecundity would be called sterility (Frank, 2017).

1.1.1 TYPES OF FERTILITY

1. Primary infertility refers to couples who have not become pregnant after at least 1 year having sex without using birth control methods.

2. Secondary infertility refers to couples who have been able to get pregnant at least once, but now are unable.

WHAT REDUCES FERTILITY

Age. The quality and quantity of a woman's eggs begin to decline with age.

Smoking. Besides damaging your cervix and fallopian tubes, smoking increases your risk of miscarriage and ectopic pregnancy.

Weight. Being overweight or significantly underweight may affect ovulation.

Sexual history.

Alcohol.

1.1.2 FERTILITY DETERMINANTS

1. MARRIAGE: The role of marriage in determining fertility levels in societies where most of child bearing is confined within marriage is well documented. Changes in the proportion of marriage as well as increases in age at marriage have been identified as one of the factors responsible for fertility decline in some North African countries (National research council, 2012). In decomposing the factors responsible for differences in fertility among sub-population groups in Nigeria, Makinwa-Adebusoye and Feyisetan using Bongart’s framework (Bongarts, 1978) found that marriage was the second most important factors. For the entire country, the fertility inhibiting effect of marriage is 25 per cent. Again, the national value masks the large differences among the regions (45 per cent in the Southwest; 41 per cent in the Southeast; 9 per cent in the Northwest and 8 per cent in the Northeast).

2. WOMEN EDUCATION: Studies have shown that the influence of education on fertility varies greatly between countries with different levels of schooling (Perpillou et al., 2018). In most cases, the relationship between women’s education influences fertility. In Nigeria, studies have consistently indicated lower fertility among women with secondary and higher levels of education, implying that significant increases in women’s education at these levels will be accompanied by a decline in fertility. Female enrolment at all levels of education has increased over the years (FOS, 2019) and there is no reason to anticipate a reversal in the trend.

3. FEMALE EMPLOYMENT: The participation of women in the labour force has also increased over the years in Nigeria. However, decreasing employment prospects are reducing the impact of employment. Women employed in the formal sector have usually been noted to have fewer children but unemployment is also becoming associated with lower fertility. Like their male counterparts, being unemployed denies women the access to resources with which to prepare for marriage and child rearing immediately after leaving school. Thus, they are forced to postpone marriage and child rearing in order to consolidate their earning capacity. Because men’s resources are becoming increasingly inadequate to meet household needs, increasing proportion of men now look for employed women as partners, thus reducing marriage chances of unemployed women (Rasheed et al., 2018)

4. ABORTION: The impact of abortion on fertility has also been documented. An increase in abortion rate has usually been accompanied by a decline in fertility especially in high to medium fertility populations. Data on abortion are very scanty because the procedure is illegal. Henshaw et al. (2017) estimated the incidence of induced abortion in Nigeria in 2018. The result indicates that each year, Nigerian women obtain approximately 610,000 abortions, a rate of 25 abortions per 1000 women age 15-44. About 40 per cent of abortions are estimated to be performed by physicians in established health facilities, while the rest are performed by non physician providers. Although it is difficult to determine precisely its incidence, evidence from health facility based studies suggest an increase in the incidence of abortion over time in Nigeria. Unfortunately, it is illegal except under certain conditions, a high percentage of abortion in Nigeria is performed by unqualified personnel who only encourage their clients to seek modern medical care when there are complications.

1.1.3 FERTILITY RATE

1.1.3.1 SPECIFIC FERTILITY RATE (S.F.R)

The concept of specific fertility or specific births rate (S.B.R) arises out of the fact that fertility is affected by a number of factors such as age, marriage, state or region, urban-rural characteristics, etc. When fertility is calculated on the basis of age distribution, it is called age-specific fertility rate. While calculating age-specific fertility rate women of different ages in the child-bearing age are placed in the small age groups so as to put them at par with others of child-bearing capacity.

1.1.3.2 GENERAL FERTILITY RATE (G.F.R.)

This rate refers to the proportion of the number of children born per 1,000 of females, the reproductive or child-bearing age. Thus the numerator of this would remain the same as the crude rate, but denominator would be limited to the age- sex group of the population able to contribute to the birth rate.

1.1.3.3 TOTAL FERTILITY RATE (T.F.R)

In order to measure correctly the population growth we calculate the number of child born per thousand females in the child-bearing age divided into different age-group. This leads to the total fertility rate which is calculated by adding up the specific fertility rates belonging to different age groups.

1.1.4 REPRODUCTION RATE

The fertility rates are unsuitable for given an idea of the rate of population growth because they ignore the sex of newly born children and their mortality. If the majority of births are those are those of boys the population is bound to decrease while the reverse will be the case if the majority of birth are girls. Similarly, if mortality is ignored a correct idea of the rate of growth of population cannot be formed because it is possible a number of female children may die before reaching the child-bearing age. For measuring the rate of growth of population, we calculate the reproduction rates. Reproduction rates are of two types:

Gross Reproduction Rate(G.R.R), and

Net Reproduction rate (N.R.R).

1.1.4.1 GROSS REPRODUCTION RATE

Gross reproduction rate measures the rate at which a new born female would, on an average, add to total female population, if they remained alive and experienced age-specific fertility rate throughout the end of the child-bearing period. It is the sum of fertility rate at the end of the child-bearing period. It is the sum age-specific fertility rates calculated from female births for each single year of age. It shows the rate at which mothers would be replaced by daughters and the old generation by new if no mother died or migrated before reaching the upper limits of the child bearing age, i.e. 49 years. Another underlying assumption is that the same fertility rate continued to be in operation. If the gross reproduction rate of a population is exactly 1, it indicates that the sex under consideration is exactly replacing itself; if it is less than 1; the population would decline, no matter how low the death rate may be.

1.1.4.2 NET REPRODUCTION RATE (N.R.R)

Though gross reproduction rate gives an idea about the growth of the population, it excludes the effect of mortality on the birth rate. The rate estimate the average number of daughters that would be produce by women throughout their lifetime if they were exposed at each age to the fertility and mortality rates on which the calculation is based. It thus indicates the rate at which the number of female births would eventually grow per generation if the same fertility and mortality rates remain in operation. A net reproduction rate of 1 indicates that on the basis of the current fertility and female mortality, the present female generation is exactly maintaining itself.

1.1.5 CAUSES OF INFERTILITY

1.1.5.1 FEMALE INFERTILITY

For a woman to conceive, certain things to happen: vaginal intercourse must take place around the time when egg is released from her ovary; the system that produce eggs has to be working at optimum levels and her hormones must be balanced. For women, problems with fertilization arise mainly from either structural problems in the Fallopian tube or uterus or problem releasing eggs. Infertility may be caused by blockage of the Fallopian tube due to malformation, infections such as Chlamydia and or scar tissue. For example, endometriosis can cause infertility with the growth of endometrial tissue in the Fallopian tubes and or around the ovaries, Endometriosis is more common in women in their mid- twenties and older, especially when postponed childbirth has taken place (Lessy, 2008). Another major cause of infertility in women may be inability to ovulate. Malformations of the eggs themselves may complicate conception. For example, polycystic ovarian syndrome in which eggs only partially developed within ovary and there is excess of male hormones. Some women are infertile because their ovaries do not mature and release eggs. In this case synthetic FSH injection or Clomid (Clomiphene citrate) via pill can be given to stimulate follicles to mature in the ovaries. Other factors that can affect a woman’s chances of conceiving include being overweight or underweight or her age as female fertility declines after the age of 30 (NYC,2015).

Common contributory factors-causes of infertility of females include:

Ovarian problems (e.g. Polycystic ovarian syndrome-PCOS), the leading reason why women present to fertility clinic due to anovulatory infertility (Balen et al., 2006).

Tubal blockage

Pelvic inflammatory disease (PID) caused by infections like tuberculosis

Age related factors

Uterine problems

Previous tubal ligation

Endometriosis

Advance maternal age

1.1.5.2 MALE INFERTILITY

The main cause of male infertility is low semen quality. In men who have the necessary reproductive organs to procreate, infertility can be caused by low sperm count due to endocrine problems, drugs, radiation, or infection. There may be testicular malformation, hormone imbalance, or blockage of man‟s duct system. Although many these can be treated through surgery or hormonal substitutions, some may be indefinite (Mishail, n.d). Infertility associated with immotile sperm may be caused by primary ciliary dyskinesia. The sperm must provide the zygote with DNA centrioles, and activation factor for the embryo to develop. A defect in these sperm structures may result in infertility that will not be detected by semen analysis (Avidor-Reiss et al., 2015). Environmental factors like exposure to chemical dust and pesticides have adverse effect of male fertility (Mendio et al., 2008). Widely used pesticides DDT (1,1,1-trichloro-2,22-bis (p-chlorophenyl) ethane) and industrial chemical e.g. PCBs (Polychlorinated biphenyls),and environmental pollutants such as dioxin and human therapeutics such as anti-cancer drugs (D’Souza, 2003; D’Souza, 2004). Perry and associates also showed the effects of environmental and occupational pesticide on human sperm (Perry, 2008). Hossain et al. (2010) and colleagues in a series of 160 subjects, with 52 (32.5%) exposed, advocate that overall the decline in semen quality may adversely affect the fertility index of exposed subjects.

Immunological or genetics; it may be that each partner is independently fertile but the couple cannot conceive together without assistance (Avidor-Reiss et al., 2015).

1.2 POPULATION SIZE AND GROWTH

In late 2011, the world’s population surpassed the 7 billion mark and is currently growing by an additional 82 million persons every year (United Nations, 2013a). By 2050, the world’s population is likely to reach an unprecedented size between 8.3 billion and 10.9 billion people.

Most of the future population growth will occur in developing countries, particularly in least developed countries. Presently, many developing countries still have population growth rates that, if sustained, would undermine their development and put pressure on future generations.

Consequently, stabilizing population growth is a goal in many of these countries that must be achieved in order to preserve the options for the future and ensure sustainable development. In contrast, developed countries and some middle income countries are experiencing below- replacement fertility levels (less than 2.1 children per woman), declining population growth rates, and in some cases, declining population size. These countries are facing shrinking working-age populations, rapid population ageing and associated implications for renewability of the labour force and sustainability of social security and health care systems (United Nations, 2013a).

Since the International Conference on Population and Development (ICPD) in 1994, many Governments in developing countries have realized the importance of reducing high rates of population growth in order to ease pressures on resources, combat climate change, prevent food shortages, and provide decent employment and basic social services to all their inhabitants.

Many of these Governments have also realized that effective implementation of population policies requires the creation of an institutional framework that ensures the integration of population variables into development planning with adequate mechanisms for monitoring and evaluation. While Governments in developing countries have adopted measures to reduce population growth rates, a growing number of Governments in developed countries have expressed concerns about low rates of population growth (International Council on Social Welfare, 2010).

The demographic transition associated with declining fertility and mortality levels is causing unprecedented changes in population age structures around the world. Different countries have been affected differently according to their stage of demographic transition and level of development. On the one hand, most developed countries and some developing countries have already attained older age structures and are experiencing declining proportions of youth and working-age adults, with negative consequences for labour supply and old-age support ratios. On the other hand, many developing countries are experiencing increasing numbers and proportions of youth and working-age populations, which, under the right circumstances, can lead to a short-run demographic bonus but at the same time create obvious challenges in terms of providing education and creating employment opportunities (International Council on Social Welfare, 2010).

1.2.1 FACTORS AFFECTING POPULATION

The factors which influence the distribution of population in West Africa are mainly historical and physical conditions of climate, relief, drainage, and availability of water supplies. The sparse population of the Middle Belt for example is greatly due to the large scale depopulation of the region during the period of slave trade. During the period, many towns and villages were completely destroyed in the inter-tribal wars and slave raids, and in many districts the entire population was carried away into slavery or driven to seek refuge in inaccessible hilly areas. The Middle Belt suffered very much from both the Sudanese kingdoms which supplied slaves to Arab slave traders as well as from the coastal chiefs who raided the area for slaves which were sold to European slave dealers (Micheal et al., 2020).

In the Sudan zone which lies north of the Middle Belt, the main centres of population concentration are the district which were ruled by powerful chiefs who were able to provide protection and good government to their people. The fortified city of Kano which is located in a rich agricultural district therefore attracted thousands of people from the neighbouring districts. The concentration of people around Sokoto and Mossi capital of Ouagadougou also came about in the same way (Micheal et al., 2020).

The areas of high population densities in South-Eastern Nigeria are more difficult to explain, particularly since areas have some of the poorest soils in West Africa. Slave wars were rare in this part of West Africa because the slaves were obtained largely through the medium of a bogus god called the Long Juju as well as sales of social undesirables such as stubborn children, thieves and adulterers (Chukuma and Otagburuagu, 2020).

1.2.2 CHELLENGES OF OVER POPULATION

In an ideal state of equilibrium everyone would have an income that would enable him to live comfortably while actively producing wealth for the benefit of others. But the flood of population continues to rise, and estimates already picture the future with numbers that are sometimes astronomical and arouse fear of general overpopulation throughout the world and the ruin of mankind by poverty and hunger. Are such problems correctly stated, and more especially can they be so stated by pure theorists, economists, or sociologists of certain schools without reference to solid geographical foundation? Such a problem is far from admitting the dogmatic solutions that are also too often put forward (Monga, 2019).

A country’s desirable population was one that came nearest the supportable maximum. This idea was justifiable so long as the total remained constantly at a fairly low level owing to war, disease, epidemic and, famine. Things became quite different when industrial development, which took place in England first of all, had stimulated an increase in population.

1.3 STATEMENT OF THE STUDY

For a woman to conceive, certain things to happen: vaginal intercourse must take place around the time when egg is released from her ovary; the system that produce eggs has to be working at optimum levels and her hormones must be balanced (Mendio et al., 2008). For women, problems with fertilization arise mainly from either structural problems in the Fallopian tube or uterus or problem releasing eggs. Infertility may be caused by blockage of the Fallopian tube due to malformation, infections such as Chlamydia and or scar tissue. For example, endometriosis can cause infertility with the growth of endometrial tissue in the Fallopian tubes and or around the ovaries, Endometriosis is more common in women in their mid- twenties and older, especially when postponed childbirth has taken place (Lessy, 2000). Another major cause of infertility in women may be inability to ovulate. Malformations of the eggs themselves may complicate conception. For example, polycystic ovarian syndrome in which eggs only partially developed within ovary and there is excess of male hormones. Some women are infertile because their ovaries do not mature and release eggs. In this case synthetic FSH injection or Clomid (Clomiphene citrate) via pill can be given to stimulate follicles to mature in the ovaries. Other factors that can affect a woman’s chances of conceiving include being overweight or underweight or her age as female fertility declines after the age of 30 (NYC, 2015).

1.4 AIM AND OBJECTIVES

The general goal of this research study is to analyze the statistic of human fertility using child birth with the following specific objectives:

To determine fertility relationship between gender and year

To determine the trend of birth rate in years.

1.5 SCOPE AND LIMITATION

The information and data collected are limited to GENERAL HOSPITAL ALIERO. The data were collected for the period of ten (10) years from 2011 to 2020.

1.6 SIGNIFICANCE OF THE STUDY

The significance of this study is to provide

1. Adequate and relevant information on population control

2. It will be use for planning, governance, policy formulation and developmental statistics concerning the patients of the hospital to measures needed so as to improve capacity performance.

1.7 ABBREVIATION

Meaning of some important notations:

1. ASBR = Age specific birth rate

2. B = Annual births

3. P = Annual mean population

4. LF = Number of live births which occurred to female of a given age group

5. FP = Female population of a given age group

6. Lb = Live births of a population of a given geographic area in a given year,

7. F15 – 49 = Population of women of (15 -49) year age group

8. bi = Number of female births to women in age group i

9. Pi = Population of women in age group i

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 INTRODUCTION

Fertility has been a central topic of research within the discipline of demography, but has also achieved considerable interest within sociology, anthropology, economics, medicine and psychology. During the last two decades, research about fertility in advanced societies in which birth control is the default option has flourished. It is not surprising, therefore, that several reviews of the existing fertility literature have been undertaken (Morgan and Taylor, 2006; Mills et al., 2011). These reviews have provided important insights (although sometimes focusing on specific disciplines or geographical areas), while simultaneously European and Asian countries reached very low fertility levels (Caldwell and Schindlmayr, 2003) and virtually all advanced societies witnessed a ‘postponement’ transition (Kohler et al., 2002a, b). During the late 2000s, a reversal of the fertility decline in most advanced countries albeit with great heterogeneity has drawn considerable attention (Goldstein et al., 2009). Furthermore, the impact of economic uncertainty and the recent economic recession on fertility is another emerging topic (Sobotka et al., 2011).

2.1 REVIEW OF RELATED WORKS

Caudill and Mix (1995) developed censored regression model for fertility data, along the line (Winkelmannn and Zimermann, 1994) developed the generalized event on model which subsumed the poison, the negative binomial and binomial.

The much work on household fertility decision was stimulated by (Becker, 1960) who developed an economic theory of the family. In this similar work Becker suggested that children can be viewed as durable good yielding primary psychic income to parent in neoclassical economic frame work.

Household fertility decision are determine by female wage and faming income which supposed to measure time cost of raising children and earn potential (Becker, 1990).

Tazi-Preve et al. (2004) demonstrates that the unequal distribution of household labor lowered men’s fertility intentions in Austria. This concurs with the work of Olah (2003), who in a comparison of Sweden and Hungary finds that a more equal gender division in household tasks accelerates the transition to the second child, noting that specific policies in Sweden supported this transition. In a study on Italy and Spain, Cooke (2009) finds that increases in employment equity between partners increased equity in the division of household labor, which had beneficial effects on the progression to a second child. The effects, however, differed across countries.

In a comparative study of the Netherlands and Italy, Mills et al. (2008) find that an unequal division of household labor significantly impacts women’s fertility intentions when they already have a heavy load (more work hours, children), which is particularly salient for working women in Italy.

Begall and Mills (2011) also demonstrate that the degree of work–family conflict plays an important role for women across many European countries, with the prevalence of part-time work and higher perceived control over work significantly predicting the intention to become a mother. 2.4 Stepfamily Fertility The increase in unstable and multiple unions has also brought a growth in the study of stepfamily fertility. This body of research demonstrates that partners who already have children from previous unions are more likely to have a child together, often considered as a union commitment effect (Prskawetz et al., 2003).

Jefferies et al. (2000) for instance, find that among British women, almost half of those who experienced a marital dissolution subsequently experience a conception within twelve months, with age of the woman and age of her youngest child being the most important factors, together with repartnering. Repartnering might therefore further fuel higher fertility quantum. Given that one child is enough to indicate commitment in a partnership, multiple relationships and subsequent partnerships might significantly contribute to total fertility.

Using a different social-psychological approach, Miller and Pasta (1994, 1995) adopt the traits-desires-intentions-behavior framework (T-D-I-B), where fertility intentions are placed within a complex decision-making framework. Miller (2011) argues that having a child is the result of a sequence of motivational traits that translate into desires, which in turn form the fertility intention. That intention then translates into the behavior of avoiding or realizing a pregnancy. An alternative model to explain human fertility is the theory of conjunctural action (TCA), recently introduced by Morgan and Bachrach (2011).

Changes in partnership dynamics experienced in the past decades across advanced societies has been linked to the postponement of parenthood. A growing number of studies has shown a parallel tendency to delay union formation and parenthood

(Corijn and Klijzing, 2001; Mills and coworkers, 2005), an increased frequency to have several partners before the first child (Wu and Schimmele, 2005), and a rise in unmarried cohabitation, which has been associated with a later age at entry marriage (Mills 2004), if not a ‘retreat from marriage’ (Gibson-Davis et al., 2005).

Abdulazeez (2013) conducted a research focus on the fertility rate of data set from Kebbi state. She used simple linear regression model and analysis of variance ANOVA. In an attempt to study the influence of fertility in Kebbi State of Nigeria. A data set of fertility was collected and analyzed using simple linear regression. Also Analysis of variance ANOVA, she observed that is existing a variation among the age categories and gender, She finally concluded that the ranges of age between 20-24 and 25-29 has the highest fertility rate.

CHAPTER THREE

RESEARCH METHODOLOGY

Research methodology is a process to carry out a research. This means the method used for data collection, source of data, type of data and techniques used for data analysis. There are different approaches to the method of collecting data about which a research is base; this depends on the type of research to be carried out and the type of data needed for the subject matter.

3.1 DATA COLLECTION METHODS

There are many methods to collect data, depending on the research design and the methodologies employed. Secondary data were used

3.2 TYPES OF DATA

Data can be divided into two types, namely quantitative and qualitative. Quantitative data is numerical in nature and can be mathematically computed. Quantitative data measure uses different scales, which can be classified as nominal scale, ordinal scale, interval scale and ratio scale. Qualitative data are mostly non-numerical and usually descriptive or nominal in nature. This means the data collected are in the form of words and sentences

3.3SOURCES OF DATA

Basically, statistical data usually occurs in two forms: primary and secondary. Those in qualitative forms are obtained as a result of categorical response, while those in quantitative forms arise from random variable and yield numerical responses which may be described in nature.

The data used in this project work are obtained from the hospital (GENERAL HOSPITAL ALIERO, KEBBI STATE). The data are purely secondary

3.4. STATISTICAL METHODS

In order to study the speed at which the population is increasing, fertility rates are used which are of various types. Important amongst these are:

3.4.1 CRUDE BIRTH RATE (C.B.R)

It is the simplest method of measuring fertility. It acts as an index of the relative speed at which additions are being made to the population through child-birth. In this method, the numbers of births are related to the total population. Since it is only a live birth that signifies an addition to the existing population, live births alone are considered in measuring fertility, thus excluding still births.

The annual crude birth rate is defined as:

C.B.R = 2.1

where B= Annual births

P= Annual mean population.

In this measure, the births are related to the mean population and not to the population at particular date. The crude birth rate of a given year tells us at what rate births have augmented the population over the course of the year.

The crude birth rate usually lies between 10 and 35 per 1,000. The level of the crude birth rate is determined by:

The sex and age distribution of the population: and

The fertility of the population, i.e the average rate of child-bearing of females.

3.4.2. SPECIFIC FERTILITY RATE (S.F.R)

S.F.R 2.2

where LF= live births which occurred to female of a given age group

FP = female population of a given age group.

3.4.3. GENERAL FERTILITY RATE (G.F.R.)

G.F.R = 2.3

where B = annual births

F15-49= female population of 15-49 years age group.

3.4.4. TOTAL FERTILITY RATE (T.F.R)

In order to calculate the total fertility rate we shall have to calculate the specific rates and then add them. Total fertility rate is thus the sum of the age-specific fertility rates from a given age to the last point of child-bearing age of a female. In practice, we can shorten this procedure by working in quinquennial age groups. We define specific fertility rate for group years and under () as before by:

2.4

Such a specific fertility rate is the rate per 1,000 per annum at which the females in the particular age-group produce offspring.

If we add the quinquennial specific fertility rates and multiply by 5, we shall have the total number of children which 1,000 females aged 15 will bear over their lifetimes. A calculation based on quinquennial age-groups involves only one-fifth of the arithmetic of one based on single age groups and is very nearly as accurate. Symbolically,

T.F.R 2.5

where t = magnitude of the age class

3.4.5. GROSS REPRODUCTION RATE

G.F.R 2.6 where FB= Number of female births

N= Total number of births

The G.F.R. is used as a measure of fertility in a population. It is useful for comparing fertility in different areas or in the same area at different time periods. The G.F.R could in theory range from 0 to about 5.

Gross reproduction rate has an advantage over the total fertility rate because in it computation we take into account only the female babies who are the future mothers whereas in the total fertility rate we include both male and female that are born.

3.5 DISCUSSION OF THE RESULT

Table 3.1: Population Distribution According to Age and Sex (2011-2020)

Age Group

2011

2012

2013

2014

2015

0-4

569

311

520

461

401

262

116

169

218

453

5-9

479

522

230

548

321

173

631

199

130

160

10-14

432

313

375

349

226

131

360

299

625

180

15-19

527

172

171

581

165

122

102

268

174

153

288

150

179

20-24

159

747

676

715

431

1434

552

603

204

569

212

783

154

155

313

366

170

671

233

120

25-29

233

1172

111

815

200

1876

683

642

178

658

282

252

212

262

281

123

322

990

461

243

30-34

162

1614

638

630

277

2472

910

360

671

237

215

670

336

324

520

371

301

35-39

131

614

299

320

163

466

131

169

289

213

229

221

40-44

709

115

321

181

243

101

45-49

109

50-54

102

128

542

232

237

124

163

55-59

112

328

138

112

160

591

60+

287

218

160

740

197

202

304

190

107

Total

2818

6560

1933

2707

3190

7287

2428

1933

2162

3610

887

1378

2435

3314

904

606

2451

4296

1171

717

Age Group

2016

2017

2018

2019

2020

0-4

628

325

473

320

392

193

132

250

130

450

5-9

489

532

330

448

221

331

521

192

525

195

10-14

532

413

395

249

326

184

260

199

250

189

15-19

172

627

182

191

681

295

132

105

278

184

253

189

150

179

20-24

259

1747

666

615

331

1334

551

503

202

439

232

183

252

512

212

166

270

615

222

177

25-29

323

2172

911

855

209

1876

783

742

108

858

383

352

222

887

386

323

222

997

366

343

30-34

167

1614

538

530

177

1472

520

460

579

247

235

570

261

226

590

271

236

35-39

139

609

199

220

183

566

193

189

289

113

227

133

243

40-44

229

125

322

143

142

45-49

127

50-54

192

337

642

132

257

324

322

55-59

182

218

338

102

162

60+

297

387

170

840

102

297

102

322

180

312

Total

3,481

9,337

2,544

2455

3,047

8,808

2,220

2,044

2,156

3,993

1,009

895

2,118

3,933

985

813

2,197

48,358

1001

876

Source: General Hospital Aliero, Births Record book 2011-2020

Table 3.2: SUMMARY STATISTICS FOR THE POPULATION

YEARS

PARAMETERS

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

POPULATION

10125

10479

5760

5305

6777

12818

11855

6149

6051

6555

REPRODUCTIVE

WOMEN

5492

5511

2498

2695

2672

7125

9573

2629

2404

2768

BIRTHS

4643

4361

1653

1846

1888

4999

4264

1904

1798

1877

CRUDE BIRTH RATE (CBR) FOR THE YEAR 2011,

=459

Total number of live births per thousand of the population for the year is 459

Similarly, the results for the rest of the years are shown in table 3.1

AGE SPECIFIC BIRTH RATE (ASBR)

For 15-19 age group in 2011

=651

The number of live births by women within the age 15-19 per thousand of women population is 651.

Similarly, the results for the age groups for the rest of the years are shown in table 3.3

GENERAL FERTILITY RATE (GFR)

For the year 2011,

=951.614

This is saying that the number of live births per thousand of women within the reproductive age is 952 for the year.

Similarly, the results for the rest of the years are shown in table 3.3

TOTAL FERTILITY RATE (TFR)

For the year 2011,

= 138+8077+706+514+644+237+162=11698

T.F.R= 11698

This implies that the sum of total number of births to women within the age 15-49 per thousand of women within the reproductive age is 11698

Similarly, the results for the rest of the years are shown in table 3.3

GROSS REPRODUCTION RATE (GRR)

For 15-19 age group in 2011.

GRR

Summing the GRR from 15-49 years age group will give G.R.R= 3418

This implies the number of daughters that will replace their mothers for the year, assuming no mortality till they reach the highest limit of child bearing age i.e. 49 years is 3418

Similarly, the results for the age group for the rest of the years are shown in table

Table 3.3: the Fertility Indices Between “2011-2020”

Year

A.C.B.R

G.F.R

G.R.R

T.F.R

2011

459

952

3418

449

2012

416

967

6307

11698

2013

287

662

5956

8269

2014

348

1089

2250

4167

2015

279

707

4788

3897

2016

390

702

9714

3914

2017

360

714

9775

4081

2018

310

724

8610

3753

2019

286

724

8450

3037

2020

297

688

9365

4095

Table 3.4: The Distribution of Age Specific Fertility Rate Between “2011-2020”

AGE GROUP

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

15-19

651

1358

322

219

285

595

603

299

328

363

20-24

1862

8077

5408

588

526

733

790

770

738

652

25-29

788

706

939

1542

711

810

814

857

834

859

30-34

787

514

670

742

1292

662

661

832

799

711

35-39

1008

644

292

686

362

628

675

654

559

605

40-44

121

237

155

450

271

275

236

341

491

684

45-59

162

483

682

450

102

231

167

220

Fertility trend from (2011-2020)

Figure 3.1: Population Distribution of the Age Specific Fertility Rate Trend (2011-2020)

3.6. INTERPRETATION OF RESULTS

Using Table. 3.3, the number of births per thousand of the entire population (C.B.R) decreased slightly from 2011-2020. After a careful analysis of the number of births in each age group per thousand of women population in that age group (specific birth rate or specific fertility rate, S.B.R or, S.F.R) , it is obvious that from each year, the age S.F.R increases from age group (15-19) to (20-24), and then to (25-29) years where it reaches its peak point. From there started to decrease significantly to age group (30-34) to (45-49).

Finally, it can be concluded that the averagely high birth rate throughout the ten years occurs at the age group (25-29) years while, the averagely low birth rate throughout the ten years occurs at the age group (45-49) years.

From the analysis of the gross reproductive rate (G.R.R), it increases from 2015 to 2017. On getting to 2017 it begins to decrease significantly, after which it increase in 2020 again. Also the analysis of the total fertility rate follows the same pattern with that of the gross reproduction rate.

Crude birth rate (C.B.R) and general fertility rate (G.F.R) did not explain the analysis well due to their limitations on the exclusion of mortality and age-sex distribution of the population in their computation.

CHAPTER FOUR

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

4.1. SUMMARY

This project is carried out on human fertility focus on birth registration in General Hospital Aliero from 2016-2020.This project started with the introduction part of the write up where the definition of fertility was made known. It went further in explaining the scope of the study as well as the significance of the study. It also proceeds in presenting the limitation of the study in the course of carrying out the project. Chapter two discussed the literature review

In chapter three of this project, the source of data collected employed in this project work was discussed as well as the statistical method and formulae used. The data collected were also presented in this chapter, and analyzing the data using statistical indices such as crude births rate, specific fertility rate, etc. at the same time, the numerical results were interpreted as a norm of any statistical analysis.

4.2. CONCLUSIONS

Base on the analysis in the proceeding chapter, it is being concluded that the crude birth rate decreases slightly along the year illustrated in table 3.3. While the growth reproduction rate and total fertility rate decrease significantly in the first three consecutive years and, then started to increase again. In table 3.4, the age specific fertility rate is averagely high among the women in the age group (25-29) years and the rate is averagely low between the age group (45-49) years.

4.3. RECOMMENDATIONS

In order for the government to keep on industrializing and modernizing its economy, while maintaining the gains from these processes, public awareness must be carried out through different channels of the mass media. Because it is evidently shown that population crises tends to nullify the gains made by government through industrializing and modernizing its economy.

This awareness must penetrate through the villages where level of illiteracy is high and, rate of enrolment to school is low. On the process of this awareness, the significance of the female child education must be emphasized. As it is statistically proved that, the population of rural areas reduces due to the high level of literacy and, high rate of enrolment to school of the female child.

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Effect on population structure of Human Fertility

Effect on population structure of Human Fertility

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