a study of unmet need for family planning in nigeria
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The University of Manchester Research
A Study of Unmet Need For Family Planning In Nigeria
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A STUDY OF UNMET NEED FOR FAMILY PLANNING IN
NIGERIA
A dissertation submitted to The University of Manchester for the degree of MSc in
Social Research and Statistics in the Faculty of Humanities
2010
Omolade Allen-Alebiosu
Centre for Census and Survey Research,
School of Social Sciences
2
Lists of Content
List of Contents……………………………………………………………..2
List of Figures and Appendix...…………………………………………….4
List of Tables………………………………………………………………...6
Abstract……………………………………………………………………...7
Declaration…………………………………………………………………..8
Copyright Statement………………………………………………………..8
Acknowledgement…………………………………………………………...9
Abbreviations……………………………………………………………….10
1. Introduction………………………………………………………………….11
1.1. Fertility Transition In Nigeria…………………………………11
1.2. Background information on Nigeria…………………………..14
1.3. Overview Of The Structure Of The Project…………………..16
2. Fundamental Concepts and Literature Review……………………………...18
2.1. Introduction………………………………………………………18
2.2. Historical Development of Unmet Need for Family Planning.…18
2.3. The Concept and Measurement of Unmet Need…………………21
2.4. Categories of Unmet Need – Spacing and Limiting……………..24
2.5. Operationalisation of Unmet Need……………………………….25
2.6. Levels in Unmet Need…………………………………………...26
2.6.1. Unmet Need and Marital Status……………………………..26
2.6.2. Unmet Need and Age……………………………………......27
2.6.3. Unmet Need and Education……………………………….…28
2.6.4. Unmet Need and Residence………………………………….29
2.6.5. Unmet Need Culture………………………………………....30
2.6.6. Unmet Need and Other covariates………………………..….31
3
2.7. Demographic Significance Of Satisfying
Unmet Need for Family Planning……………………………..32
3. Methodology……………………………………………………………………34
3.1. Research Questions………………………………………………34
3.2. Research Strategy………………………………………………...34
3.3. Description of The NDHS Data………………………………….35
3.4. Sample…………………………………………………………...36
3.5. Data Analysis…………………………………………………….37
3.6. Demographic Significance Model……………………………….37
4. Results And Interpretation……………………………………………………39
4.1. Levels of Unmet Need Among Married Women……………….39
4.1.1. Overview……………………………………………..........39
4.1.2. Unmet Need For Spacing And limiting
By Demographic Characteristics………………………….40
4.1.3. Unmet Need For Spacing And limiting
By Socioeconomic Characteristics……………………….49
4.1.4. Unmet Need For Spacing And limiting
By Cultural Characteristics………………………………..55
4.2. Logistic Regression Models for Likelihood
of Having Unmet Need for Spacing or Limiting………......59
4.2.1. Logistic Regression Model: Unmet Need for Spacing…….60
4.2.2. Logistic Regression Model: Unmet Need for Limiting……65
4.3. Estimated Impact of Satisfying Unmet Need for
Family Planning on Total Fertility Rate
Among Currently Married Women…………………………69
5. Conclusions and Recommendation…………………………………………..71
5.1. Summary of Results……………………………………………….71
5.2. Policy Implication…………………………………………………73
5.3. Recommendation For Further Research…………………………...75
Bibliography………………………………………………………………………76
13,947 words
4
List of Figures and Appendix
Figure 1: Estimates of Total Fertility of Nigeria, 1971-2008………………………………11
Figure 2: Estimates of Child Mortality (per 1000 live births) of Nigeria, 1971-2008……..12
Figure 3: Total Population Structure in Nigeria, 2008……………………………...16
Figure 4: Unmet need for Family planning…………………………………………19
Figure 5: Indicators for Unmet need Computation…………………………………23
Figure 6: Percentage of Currently Married Women Having Unmet Need For
Spacing And Limiting By Age, 2008 NDHS………………………………………40
Figure 7: Percentage of Currently Married Women Having Unmet Need For
Spacing And Limiting By Region, 2008 NDHS…………………………………..43
Figure 8 Percentage of Currently Married Women Having Unmet Need For
Spacing And Limiting By Place 0f Residence, 2008 NDHS……………………..45
Figure 9: Unmet Need For Spacing And Limiting By Urban Place of Residence
Across Regions, 2008 NDHS……………………………………………………...46
Figure 10: Unmet Need For Spacing And Limiting By Rural Place of Residence
Across Regions, 2008 NDHS……………………………………………………..47
Figure 11: Percentage of Women Having Unmet Need For Spacing And
Limiting By Number Of Living Children, 2008 NDHS…………………………49
Figure 12: Differentials In Unmet Need For Spacing And Limiting Among Currently
Married Women By Wealth Index, 2008 NDHS………………………………..50
Figure 13: Differentials In Unmet Need For Spacing And Limiting Among Currently
Married Women By Educational Status, 2008 NDHS…………………………..51
Figure 14: Differentials in Unmet Need For Spacing And Limiting Among Currently
Married Women Who Are Employed, 2008 NDHS…………………………....53
5
Figure 15: Percentage of Currently Married Women With Unmet Need For Spacing
And Limiting By Exposure To Three Media Sources, 2008 NDHS…………..54
Figure 16: Differentials In Unmet Need For Spacing And Limiting Among Currently
Married Women By Religion, 2008 NDHS……………………………………56
Figure 17: Percentage of Currently Married Women With Unmet Need For Spacing
And Limiting By Ethnicity, 2008 NDHS……………………………………...57
Appendix 1: Map of Nigeria…………………………………………………….80
Appendix 2: Variables Used in the Analysis……………………………………81
Appendix 3: Variables Used in the Analysis (Derived)………………………...83
Appendix 4: SPSS Output for Selected Variables used in Bivariate Analysis…84.
6
List of Tables
Table 1: General Pattern of Fertility Preferences Among Married Women In Nigeria,
2008 NDHS……………………………………………………………………….39
Table 2: General Patterns of Unmet Need For Family Planning By Region,
2008 NDHS……………………………………………………………………….43
Table 3: Estimates of Unmet Need For Family Planning By Educational Level
2008 NDHS……………………………………………………………………….53
Table 4: Logistic Regression Model For The Likelihood Of Having Unmet Need For
Spacing Among Currently Married Women, 2008 NDHS………..………………61
Table 5: Logistic Regression Model For The Likelihood Of Having Unmet Need For
Limiting Among Currently Married Women, 2008 NDHS……………………….66
Table 6: Estimated Impact Of Satisfying Unmet Need For Family Planning On TFR
Among Currently Married Women, 2008 NDHS………………………………….70
7
Abstract
The past decade has seen a gradual shift in the gap between a woman’s knowledge,
attitude towards, and utilization of family planning services. Women who expressed
a desire to space or limit their family size but do not use family planning methods are
referred to as having ‘unmet need for family planning.’ In another sense, women
whose demand for family planning services are not been met are also referred to as
having ‘unmet need’. Currently, the fertility rate is Nigeria is stalled at 5.7 births per
woman. How much of this high fertility is due to unmet need for family planning?
This dissertation uses demographic, socioeconomic and cultural characteristics to
investigate the levels and determinants of unmet need for spacing and limiting
among currently married women in Nigeria. It also models the impact of 100 per
cent satisfaction of the current level of unmet need on total fertility rate. Using the
2008 Nigeria Demographic and Health Survey to appropriately model the likelihood
of having unmet need for family planning, results from this dissertation showed that,
number of living children is significantly associated with having unmet need, either
for spacing or for limiting. Education attained influences the type of unmet need a
woman may have: women with secondary education or higher tend to use family
planning method and have higher demand which is not been totally satisfied, hence
unmet need, likewise, women with no education do not use family planning
methods, yet express a desire to regulate their fertility, and thus, have unmet need.
The most striking finding from this dissertation is that, high fertility in Nigeria is not
due to ‘unmet need for family planning’ but persistent demand for large family size.
8
DECLARATION
No portion of the work referred to in the dissertation has been submitted in support
of an application for another degree or qualification of this or any other university or
other institute of learning.
COPYRIGHT STATEMENT
i. Copyright in text of this dissertation rests with the author. Copies (by any
process) either in full, or of extracts, may be made only in accordance with
instructions given by the author. Details may be obtained from the
appropriate Graduate Office. This page must form part of any such copies
made. Further copies (by any process) of copies made in accordance with
such instructions may not be made without the permission (in writing) of the
author.
ii. The ownership of any intellectual property rights which may be described in
this dissertation is vested in the University of Manchester, subject to any
prior agreement to the contrary, and may not be made available for use by
third parties without the written permission of the University, which will
prescribe the terms and conditions of any such agreement.
iii. Further information on the conditions under which disclosures and
exploitation may take place is available from the Head of the School of
Social Sciences.
9
Acknowledgement
Although the words written herein are mine, I have received help from various
people, especially in the acquisition of datasets, design, analysis and general
structure of the dissertation.
I am very grateful to my Supervisor, Dr Mark Brown, for his immense
contributions, his critical appraisal and keen interest in this work from the
beginning.
I appreciate the kindness of the management of Macro International (Measure
DHS) for the provision of the dataset used in this research.
Many thanks to Dr Akinrinola Bankole of The Alan Guttmacher Institute, for
elucidating the regression equation used in modelling the demographic
significance of satisfying unmet need.
Finally, this project is dedicated to all Nigerian women who desire to be educated.
10
Abbreviations
CPR Contraceptive Prevalence
DHS Demographic and Health Survey
NDHS Nigeria Demographic and Health Survey
PSU Primary Sampling Unit
TFR Total Fertility Rate
11
1 Introduction
1.1 Fertility Transition in Nigeria
The term fertility transition refers to the path from natural fertility to replacement
fertility (Garenne, 2007). In the past decade, there has been gradual shifts and
remarkable changes in the fertility preferences of women and couples in many Sub-
Saharan Africa (SSA) countries particularly Nigeria, which in the 1960s, 1970s and
1980s gave no indication of fertility transition. The reasons for the previous trends
have been empirically discussed from various social, cultural and economic
perspectives (Shapiro and Gebreselassie, 2007) as a possible basis for understanding
the changes observed by the early 1990s.
Figure 1: Estimates of Total Fertility of Nigeria, 1971-2008
Source: Feyisetan and Bankole (2009), 1990, 2003 & 2008 NDHS.
7.3 7
6.3 6.2
5.7 5.7
0
1
2
3
4
5
6
7
8
Total Fertility Rates
1971
1975
1986
1990
2003
2008
12
Based on empirical evidence (Ainsworth, 1996; Bongaarts, 2006; J. Cleland,
Onuoha, & Timaeus, 1994) from studies in other traditional African countries,
Nigeria has a relatively sustained high level of fertility. As shown in figure 1 above,
estimates from the analysis of national and sub-national data indicates that, in the
1970s, the total fertility rate (TFR) was between 7.0 and 7.3 births per woman. A
gradual decline to 6.3 TFR was observed in the mid-1980s and a further decline to
6.0 by the earlier 1990s. Recent evidence from the 2003 and 2008 Nigeria
Demographic and Health survey (NDHS) has shown a further reduction in the TFR
to 5.7 births per woman.
These high levels have been linked with child mortality, early marriage, the cultural
practice of polygyny, low use of contraception and high social values placed on child
bearing (B. J. Feyisetan & Bankole, 2009), and, many literatures have argued about
an association between child mortality and fertility transition. Compared to other
African countries (e.g Botswana, Zimbabwe and Kenya), the social structure of
Nigeria is resistant to fertility transition (Caldwell et al., 1992), probably due to high
child mortality rates observed in the 1970s till date.
13
Figure 2: Estimates of Child Mortality (per 1000 live births) of Nigeria, 1971-
2008
Source: Feyisetan and Bankole (2009), 1990, 2003 & 2008 NDHS.
From the data in figure 2 above, one is led to believe the relatively high child
mortality rates in Nigeria could be linked with the observed TFR (Figure.1) within
the same period. These child mortality rates are likely evidence for the rationale
behind the unusual high demand for large family, arising from fear of family
extinction prevalent in Nigeria. However, to date, there has been little agreement on
whether child mortality can be solely used to explain the persistent high fertility rates
in Nigeria. Recent empirical evidence from a study by Osili and Long (2008),
suggests the persistent high and stalling fertility rates in Nigeria may be linked to
limited female education and little demand for family planning.
The position of Osili and Long (2008) supports the empirical evidence (Caldwell and
Caldwell, 1987, Casterline et al., 1997, Casterline and Sinding, 2000), which has
178.7
144.5
115.2 103.3
97 88
0
20
40
60
80
100
120
140
160
180
200
Child Mortality Rates
1971
1975
1986
1990
2003
2008
14
conclusively shown that, high demand for large family size has a direct impact on
demand and utilization of family planning services and consequently, the level of
unmet need for family planning.
Further, findings from the national fertility surveys and the world fertility surveys of
1981/1982 in Nigeria have attributed the observed high levels of fertility to limited
use of family planning services. In the 1980s, only one per cent of married women
used any form of family planning services, a pattern which was observed to have
significantly improved to six per cent in the earlier 1990s (Federal Office of
Statistics, 1992). Recently, results from the 2008 NDHS indicate, the high fertility
may also be attributed to failure to meet the demand for family planning (National
Population Commission (NPC) [Nigeria] and ICF Macro, 2009)
Currently, with the national growth rate estimated at 3.2 per cent per annum, the total
fertility rate stalled at 5.7 births per woman (figure 1) and, only 15 per cent national
contraceptive prevalence, the level of unmet need for family planning in Nigeria
remains high (National Population Commission (NPC) [Nigeria] and ICF Macro,
2009), with corresponding stalling fertility rate. Therefore, one major theoretical
issue this study attempts to clarify is whether the persistent high fertility in Nigeria is
due to unmet need for family planning or insufficient demand for smaller families.
1.2. Background Information on Nigeria
It is broadly recognized that Nigeria is the most populous country in Africa, and the
only country in the world in which more than 80% of her citizens are blacks
15
(Unegbu, 2003, Ainsworth, 1996). As a country in the West African sub-region, it
lies between latitudes 4º16' and 13º53' north and longitudes 2º40' and 14º41' east. It
is bordered by Niger in the north, Chad in the northeast, Cameroon in the east, and
Benin in the west (see appendix 1). To the south, Nigeria is bordered by
approximately 850 kilometres of the Atlantic Ocean, stretching from Badagry in the
west to the Rio del Rey in the east. With a total land area of 923,768 square
kilometres, Nigeria is the fourteenth largest country in Africa (National Population
Commission (NPC) [Nigeria] and ICF Macro, 2009), with 36 states divided into six
regions and the federal capital territory.
Demographically, about 50 per cent of the population is female, and 50 per cent is
male. The sex ratio (the number of men per 100 women) is 99. The ratio in rural
areas is lower than that of urban areas (97 compared with 101). According to
population estimates from the office of National Statistics, Nigeria has an estimated
population of 150,199 million people, with a greater number of younger people than
older people. Forty-five per cent of the total population is under 15 years of age
while 4 per cent is 65 or older (National Population Commission (NPC) [Nigeria]
and ICF Macro, 2009). As age increases, the proportion of the people in each age
group decreases. The largest proportion of the population (17 per cent) is the
youngest age group (0-4), while the oldest age group (75-79) has the smallest
proportion (less than 1 per cent) of the total population (National Population
Commission (NPC) [Nigeria] and ICF Macro, 2009). Figure 3 below illustrates the
age structure of the national population in a population pyramid.
16
Data Source: 2008 NDHS, National Population Commission.
The population pyramid is suitable for illustrating the fertility transition of a
population and in deciding whether the population is young or old. Based on the
structure observed in figure.3, Nigeria’s population is young, due to the population
percentage at the base of the pyramid. This is similar to the observed trend in other
sub-Saharan African countries with similar higher fertility and mortality rates.
1.3 Overview of the Structure of the Study
The main objective of this study is to investigate the levels and determinants of
unmet need for family planning among currently married women aged 15-49 years in
Nigeria, and how these vary by individual demographic, socioeconomic and cultural
characteristics. An extension to this is to estimate the potential impact satisfying
unmet need has on the current total fertility rate (100% satisfaction of unmet need).
Figure 3: Total Population Structure in Nigeria, 2008.
20 15 10 5 0 5 10 15 20
a0-4
a10-14
a20-24
a30-34
a40-44
a50-54
a60-64
a70-74
a80+
Age
Percent
females
males
17
Chapter 2 begins by laying out the theoretical dimensions of the research, and
looks at key issues in unmet need, particularly, its concepts, measurement and
current trend among married women. Chapter 3 describes the research design, the
dataset and the methodology employed in this study. In chapter 4, the results of the
statistical analysis are presented with corresponding interpretation and discussion.
Lastly, the concluding chapter summarises the result, highlights the policy
implication and offer suggestions for potential further research.
18
2 Fundamental Concepts and Literature Review
2.1 Introduction
In recent years, there has been an increasing interest in incorporating unmet need for
family into the broad monitoring framework of the millennium development goals
(MDGs), particularly after the 2005 World Leaders summit. The fifth goal, which is
to improve maternal health, has unmet need for family planning as one of its
indicators for the target geared towards achieving universal access to reproductive
health (Outlook, 2008). The inclusion of unmet need for family planning as an
indicator for improving maternal health has contributed to the increasing amount of
literature on the concept. Thus, this chapter aim to enhance comprehension of the
concept of unmet need and its historical development, elucidate how unmet need is
measured and its trends, particularly among married women in Nigeria and
highlights the demographic significance of satisfying unmet need for family
planning.
2.2 Historical Development of Unmet Need for Family Planning
Historically, the concept of unmet need originated from surveys on knowledge,
attitudes and practise (KAP) of fertility regulation in high fertility countries of the
early 1960s. These surveys, also known as KAP-surveys (Bogue 1974, cited in
Casterline, 2000), gave indications of the existence of discrepancies between a
woman’s fertility preferences and her fertility behaviour. Although the KAP surveys
were useful in identifying this gap, they were limited in terms of measuring the
19
demand and importance of family planning services. Thus, the world fertility survey
(WFS) program of the 1970s and 1980s were introduced. With the advent of WFS, a
pattern of fertility preferences was established. Even though the WFS was limited in
establishing a link between fertility preferences and corresponding contraceptive use,
estimates from studies conducted in Asia were used by Westoff in 1978 to develop
the concept of ‘unmet need for family planning’ (Casterline, 2000). By developing
the concept of unmet need for family planning from the previous KAP and WFS,
Westoff was able to identify a link between fertility preferences and fertility
behaviour. Over the years, efforts have been made at refining the objectives of the
fertility surveys in order to enhance adequate measurement of fertility preferences
and contraceptive behaviour.
Figure 4: Unmet need for Family planning
As shown in figure 4, the early stages of the fertility surveys were useful in
classifying fecund woman, in a sexual union, who wants a child later, yet does not
No Yes No Yes
No Yes
Want a child now?
Are you fecund and in a sexual union?
Using family planning?
20
use family planning as having unmet need for family planning. Overtime, the
objectives of the KAP and world fertility surveys were refined into the sophisticated
demographic and health survey (DHS) of the late 1980s.
The KAP and WFS surveys of the early 1960s, 1970s and 1980s provided the policy
and theoretical context for developing effective family planning services. The first
serious discussions and analyses of the knowledge gap on fertility regulation
emerged during the 1970s with studies by Mauldin (1965); Berelson (1969) and
Bogue (1974) (cited in Casterline and Sinding, 2000). This documented evidence
served as the basis for the development of family planning services and for
measuring the rate of meeting the need for family planning. Despite efforts geared at
meeting the family planning needs of women who expressed the desire for fertility
regulation, Freedman and Coombs (1974) (cited in Casterline and Sinding, 2000)
maintained that, a significant number of women still refrained from utilising family
planning services despite its availability.
Recently, it was estimated that globally, 120 million women have unmet need for
family planning (Robey et al.,1992 cited in Bongaarts and Bruce, 1995). This
widening gap in a woman’s knowledge, attitude towards and use of birth control
methods have provided a key rationale for expanding family planning services
(Freedman, 1987 cited in Bongaarts and Bruce, 1995).
The non-utilisation of available family planning services has been a significant
research priority in the past decade, and has led to substantial increase in the number
of studies designed to understand the dynamics of unmet need for family planning in
21
many developing countries, particularly sub-Sahara Africa. Robey et al., (1993, cited
in Bongaarts and Bruce, 1995) discovered that, some of the women not utilising
family planning services do not have the financial resources. In context, the cost
component of unmet need is used broadly to include expenses for commodities,
travel and services, as well as health, psychological and social considerations a
woman employs in making an informed decision about using family services
(Easterlin, 1975, cited in Bongaarts and Bruce, 1995).
The investigation into the dynamics of utilisation of family planning services in sub-
Sahara Africa has occupied an important place in theoretical literature. Empirical
studies on population growth between 1965 and 1988 compared the observed trend
in Africa to other developed countries. In sub-Sahara Africa, a region which lagged
behind in economic development (Ainsworth, 1996), the mid-1970s demographic
theory of wealth flow (Caldwell, 2004) was unsuitable in explaining the rationale for
unmet need for family planning. However, with the advent of the demographic and
health surveys (DHS) in the late 1980s, there was better understanding into the
causes of unmet need for family planning. The quality of data generated from the
DHS also improved the measurement of trends in unmet need.
2.3 The concept and Measurement of Unmet Need
In the context of family planning, the term ‘unmet need’ has come to be used to refer
to women who would prefer to limit child bearing or space their next birth, yet
refrain from using any family planning method (Gribble and Haffey, 2008). In its
broad sense, it encompasses women who express a desire to regulate their fertility by
22
postponing their next birth for at least two years or completely put a stop to child
bearing. Unmet need is recognised as a core concept in population policy and family
planning (Casterline and Sinding, 2000).
Elucidating the concept, Westoff and Bankole (1995) refers to unmet need as the
‘motivation of women who are not currently using birth control to regulate their
fertility, but, at the same time, express a desire to postpone the next birth or to avoid
any further childbearing’ (1995: 2). Further on motivation, Westoff and Bankole
(1995) identify four categories of women with either strong or weak motivation for
fertility regulation. This included women who are ‘not very sexually active or who
do not intend to use any method at all’; women who are ‘ready to use contraception
but are currently pregnant or amenorrheic;’ women who are ‘ignorant of any
method’ and those ‘concerned about side effects of a particular method.
Within the last three decades, several approaches have been adopted to measure
unmet need for family planning. As a result of effort geared towards revising the
concept, due to quality data from DHS, the measurement of unmet need has evolved
overtime to accommodate the various categories of women who are ‘really unsure’
about their fertility preferences and those who are either pregnant or amenorrheic
(Bongaarts and Bruce, 1995, Westoff and Bankole, 1995, Westoff and Bankole,
1996, Westoff and Bankole, 2000). Due to this, the definition of unmet need used by
DHS has now been divided into definition one and definition two. The difference
between definition one and two is the clarification of fecundity status or exposure. It
is worthy to note that, the overall percentage of women with unmet need for family
is not affected by the definition used. Although differences of opinion still exist,
23
there appears to be some agreement that unmet need refers to the discrepancy
between a women’s expressed fertility desire and her fertility behaviour.
Figure 5: Indicators for Unmet need Computation
Source: Westoff and Bankole (1994)
Figure 5 above represent the ‘present-day’ measurement-cum-definition of unmet
need. The figure above was developed based on a structured algorithm resulting
from the modification of the KAP and WFS. As it can be seen, a pregnant woman
who says her pregnancy was mistimed or unwanted, was not sure if she wanted the
baby, or would have preferred a later birth is classified as having unmet need for
24
spacing. A fecund woman, though not pregnant, but does not use family planning
method is also classified as having unmet need for spacing. Likewise, a fecund
woman, pregnant or not, who does not want any more children is classified as having
unmet need for limiting.
2.4 Categories of Unmet Need – Spacing and Limiting
To enhance adequate measurement and conceptualisation of unmet need, it has been
divided into two broad categories. Women who are neither pregnant nor
amenorrheic, non-user of family planning methods, want a child soon, but classified
as fecund, are referred to as having unmet need for spacing. In the same vein, those
with a desire to limit their family size are referred to as having unmet need for
limiting (Westoff and Bankole, 1995).
These two categories are different, and thus, pose different fertility regulation
challenges. While it is important to space births, it is equally important to limit child
birth. In many sub-Saharan African countries, the highest unmet need for family
planning is for spacing (Westoff and Bankole, 1995; Khan, 2008), which means, the
most available family planning services are for birth spacing. The implication of this
is that, fertility rates remain persistently high, due to insufficient birth limiting
methods to meet the needs of those with unmet need for limiting.
25
2.5 Operationalisation of Unmet Need Variable
In context, the ‘unmet need’ variable was succinctly operationalised using an
algorithm. The algorithm, which was developed by Westoff and DHS, and adopted
by the United Nations, in the standard computation, includes in its numerator,
women (married or in union) who are not using contraception, fecund, and desire to
either limit childbearing or space their next birth by at least two years. It also
includes pregnant women whose current pregnancy was unwanted or mistimed, as
well as women who are in post-partum amenorrhea who are not using contraception
and, at the time they became pregnant, had wanted to delay or prevent the pregnancy
(United Nations Population Division, 2009). Since the algorithm was developed
based on responses to DHS questions, the following variables were used by DHS in
operationalizing the unmet need variable: Current marital status, current use of
contraceptive, whether last birth wanted, reproductive preferences and fecundity
status (including whether currently fecund, pregnant, amenorrheic or infecund).
Figure 5 above is a graphical representation of how the variables measured in the
DHS were computed in definition one of unmet need. This study adopts this
definition in the analysis. Based on this, 20.9%i of women are classified as having
unmet need for family planning in Nigeria according to the following criteria:
a) Women who are currently married within the reproductive age;
b) Women with either unmet need for spacing or for limiting;
c) Women, who were users of any method at the time of responding to survey
question;
26
Excluded from the analysis:
d) Women who are pregnant or amenorrheic intentionally; and,
e) Women who are pregnant as a result of family planning method failure.
2.6 Levels in unmet need
The knowledge about the levels in unmet need for family planning in sub-Sahara
Africa, is largely based upon empirical studies (Ainsworth, 1996, Ashford, 2003,
Bankole and Ezeh, 1999, Bongaarts, 2006, Bongaarts and Bruce, 1995, Caldwell et
al., 2002, Croft, 2009, Govindasamy, 2000, Khan, 2008, Magure, 2010, Westoff and
Bankole, 1995, Westoff and Bankole, 2000) that investigated how these trends vary
by selected background characteristics. Many of these studies have used marital
status, age of the woman, number of living children, residence, education, religion,
region, religion, wealth status and exposure to two or more media sources as
covariates in elucidating the levels in unmet need. Thus, this study will examine the
levels in unmet need by focusing on some of these covariates.
2.6.1 Unmet need and Marital Status.
Data from several sources (Agyei-Mensah, 2006, Ashford, 2003, Bongaarts, 2006,
Govindasamy, 2000, Khan, 2008, Sedgh et al., 2007) have established a relationship
between a woman’s marital status and her having unmet need for family planning.
Sedgh et al. (2007) analysed data from the DHS conducted in 53 countries in Asia,
Africa, and Latin America and concluded that, one in seven women who are married
27
have an unmet need for family planning. In addition, findings from another study
showed that, about 17 percent of all married women in developing countries are not
using any form of family planning but would prefer to avoid a pregnancy (Ross and
Winfrey, (2002) cited in Ashford, 2003), and in sub-Saharan Africa, 24 percent of
married women are estimated to have unmet need (Sedgh et al., 2007).
In another major study in Uganda, the highest level of unmet need was observed
among the currently married women (Khan, 2008) and empirical evidence from
studies in other sub-Saharan Africa countries, imply the existence of similar trends
of high level of unmet need among currently married women (Khan, 2008, Magure,
2010, Ojakaa, 2008).
2.6.2 Unmet Need and Age
Another important component worth considering in discussing trends in unmet need
among married women is age. The age of the women determines the level of unmet
need she is likely to have. Studies, particularly in sub-Saharan Africa demonstrates a
woman might have an unmet need for spacing or for limiting, depending on her age.
The previous estimates from the analysis of DHS data from 27 countries show a
literal relationship between age and unmet need. Findings from the analysis indicate
a woman can either have a need for spacing or a need for limiting. Women under 30
years tend to have higher need for spacing while, women between 35-44 years have
a greater need for limiting (Westoff and Bankole, 1995). A possible rationale for this
could be the age of marriage, as women who marry early are more susceptible to
higher parity.
28
Although studies (Pasha et al., 2001, Westoff and Bankole, 1995) in the some
developed countries imply no distinction between age and unmet need for family
planning, recent empirical evidence in sub-Saharan Africa had proven otherwise. In
the review of a decade (1988-1998) of trend in unmet need for family planning in
Ghana, Govindasamy and Boadi (2000) found that, about 33% of women aged 15-24
years had unmet need for spacing compared to 15% of women aged 40-49 years.
None of the younger women (15-24 years) have an unmet need for limiting
compared to 34% of women aged 40-49 years. Further, Ojakaa (2008), in the
analysis of trend and determinant of unmet need for family planning in Kenya,
reports that, unmet need for spacing is higher among women younger than 35 years,
unmet need for limiting is at its peak between ages 35-39 years and there exist a
gradual decline in unmet need for limiting at older ages.
2.6.3 Unmet Need and Education
The relationship between education and unmet need has been widely investigated
(Ainsworth, 1996, Bongaarts, 2006, Chaudhury, 2001, Khan, 2008, Magure, 2010,
Ojakaa, 2008, Sedgh et al., 2007, Westoff and Bankole, 1995, Westoff and Bankole,
1996) worldwide. As Ainsworth (1996) discussed, countries that substantially invest
in female education have high contraceptive prevalence and low unmet need for
family planning. The position of Ainsworth has been further supported by the
findings from the study by Bongaarts (2006) which linked female education with
low unmet need for family planning in Sri Lanka and India.
29
Previous empirical evidence has consistently demonstrated the existence of a link
between female education and low unmet need. One of this evidence is based on
findings from the analysis of DHS data for 27 countries by Westoff and Bankole
(1995), which shows a decline in unmet need as the level of schooling increased in
countries outside sub-Saharan Africa. From the same analysis, women with primary
education within sub-Saharan Africa typically have the highest proportion of unmet
need. Based on estimates from the cross-country analysis of fifteen sub-Saharan
Africa countries, with reference to Zimbabwe, Ainsworth (1996) posits that, the
impact of education varies substantially between countries, particular in countries
with public investment in female education.
Although there exists a positive correlation between female education and use of
modern contraceptive (e.g. in Zimbabwe), Bongaarts (2006) argues that, the high
levels of female literacy and schooling does not necessarily influence having unmet
need for family planning. His position is based on estimates from the analysis of
DHS data for seven countries to ascertain the causes of unmet need for in
contraception and fertility transition. Compared to estimates from other countries,
being educated alone does not appear to strengthen the fertility trend and unmet need
in Kenya. The plausible rationale for this may be due to increased demand for
smaller family size among educated women, which can affect their pattern of
contraceptive utilisation.
2.6.4 Unmet Need and Residence
Surveys such as the DHS and the further country – focused analysis have shown that,
there exist variations in unmet need for family planning by region of residence.
30
Chaudhury (2001) analysed the 1996/1997 – 1999/2000 DHS data for four south
Asian countries, Bangladesh, India, Nepal and Pakistan, and found higher estimates
of unmet need for family planning among women living in rural areas. This
correlates with the estimates from the further analysis of the 1995-2006 Uganda
DHS which shows that, 42.6% of the women in the rural areas have much higher
levels of unmet need for family planning compared to women in urban areas(27%)
(Khan, 2008). Other studies in sub-Saharan Africa have conclusively shown that
unmet need varies by place of residence, with higher levels observed in the rural
areas (Magure, 2010, Ojakaa, 2008, Westoff and Bankole, 1995).
2.6.5 Unmet Need and Culture
In Nigeria, cultural practices have been identified as a contributing factor for
acceptance and utilisation of family planning methods. Specifically, it has been
suggested that, ethnicity and religious practises are highly associated with fertility
behaviour (Feyisetan and Bankole, 2009; Renne, 1996). Studies in Nigeria have also
confirmed that, having unmet need for family planning could be linked with the
ethnic group a woman belongs to as well as her religious convictions (Caldwell,
1992; Renne 1996). In a study conducted by Renne (1996) among Muslim
(Religion), Hausa and Fulani-speaking (ethnicity) women of Northern Nigeria,ii he
observed that, some of the women interviewed believed children are from ‘Allah’
and one does not need to plan for them. In addition, family planning programs as
well as other ‘western-aided’ projects (such as education) are perceived with
suspicion. On the other hand, the Yoruba-speaking women of south-west have been
31
conclusively shown (Caldwell, 1992; Feyisetan and Bankole, 2009) to use and
demand family planning services.
Another important factor influenced by cultural practices in Nigeria is age at
married. Estimates from 2008 NDHS have shown that, while women from the
Northwest (Hausa women) marry at median age 15.2 years, the median age at
marriage among women from the south east is 22.8 years. In addition, the highest
prevalence (74.2%) of ‘no education’ was among women in the north-west, a region
predominantly inhabited by the Hausa-speaking, Muslim people. Thus, in this study,
a further extension of the objectives will be to ascertain whether cultural practises
(measured here by religion and ethnicity) are determinants of having unmet need for
family planning.
2.6.6 Unmet Need and Other Covariates
The further analysis of the DHS data for some sub-Saharan Africa countries has
shown similar paaterns in unmet need for spacing and limiting by wealth status,
number of living children, region of residence and exposure to mass media. For
example, Agyei-Mensah (2006) found that, women in Northern Ghana have the
highest level of unmet need. This has been supported by findings from Uganda and
Zimbabwe (Khan, 2008, Magure, 2010), which shows that, women who live in the
northern part of the country and have limited exposure to sources of mass media tend
to have high unmet need for family planning.
32
Although variations exist by country, unmet need for family planning among
married women tends to be similar, especially in developing countries. Women who
are younger, live in rural areas, have limited exposure to sources of mass media,
have limited education, tend to have a unmet need for spacing, while, being older,
being educated particularly to primary level, having more living children and higher
wealth status have been positively associated with having unmet need for limiting.
(Govindasamy, 2000, Khan, 2008, Magure, 2010, Ojakaa, 2008, Westoff and
Bankole, 2000).
2.7 Demographic Significance of Satisfying Unmet Need
Some analysts, particularly Pritchett 1994 (cited in Sedgh et al., 2007, Westoff and
Bankole, 1995) have raised concerns about the demographic significance of
satisfying unmet need, and whether satisfying the need has a direct impact on
fertility reduction. As a result of these concerns, several studies (Casterline and
Sinding, 2000, Feyisetan and Casterline, 2000, Westoff and Bankole, 1996) have
revealed that satisfying unmet need indeed directly have an impact on reducing high
levels of fertility.
Using the regression equation TRFi = 7.178 – 0.0682 (CPR) + ei , developed from
modelling DHS data for 86 countries, Westoff and Bankole (1995) discovered that,
the correlation between contraceptive prevalence (CPR) and total fertility rates
(TFR) is 0.94, with an unexplained variance of 12 per cent, which was attributed to
other proximate determinants of fertility (e.g. age at marriage, abortion). Based on
33
these Westoff and Bankole (1996) posits that, satisfying the unmet need for family
planning will realistically have significant impacts on fertility rates.
The regression equation was further employed in the analysis of DHS data for
currently married women in 27 developing countries. Conclusively, estimates from
the regression model suggest that, logically, satisfying unmet need could be expected
to account for 17% reduction in fertility in the 13 sub-Saharan African countries
analysed, and 18% in the other 14 countries. By extension, the authors imply this
could cover an average of 30% and more than 50% of the distance between current
fertility and replacement-level fertility in the 13 sub-Saharan African countries and
the remaining developing countries respectively.
Building on the fundamental concepts and literature reviewed in this chapter, the
next chapter discusses the methodology used in this study. It discusses in details the
objectives, research questions, research strategy and data analysis techniques.
i See chapter four for details.
ii Hausa and Fulani-speaking women are mainly Muslims, inhabiting Northern
Nigeria
34
3 Methodology
3.1 Research Questions
The objective of the study is to investigate the levels and differentials in unmet need
for family planning among currently married women aged 15-49 years in Nigeria
and the demographic significance of its 100 per cent satisfaction. The specific
research questions to be answered include:
a. What is the current level of unmet need for family planning among married
women in Nigeria?
b. Are there differentials the level in unmet need by demographic,
socioeconomic and cultural characteristics?
a. An extension to research question in b above is to examine whether a
difference exists in the level of unmet need among married women by
region, controlling for place of residence.
c. What impact does 100 per cent of satisfaction of the current level of unmet
need have on the total fertility rate?
3.2 Research Strategy
The strategy adopted in this research is the secondary analysis of the NDHS
quantitative data. Many of the previous researches on unmet need for family
planning have been based on the secondary analysis data generated from the
demographic and health survey (DHS), especially in sub-Saharan Africa. A notable
35
rationale for this, is based on the fact that, the DHS aimed at generating nationally
representative data. The empirical evidence on which is research is based is from
findings from the secondary analysis of the DHS. Although Casterline et al (1997)
combined quantitative and qualitative approaches in the identifying factors
underlying unmet need for family planning in the Philippines, the qualitative strategy
as part of that analysis was used to augment the DHS data.
Thus, taking into account the substantial limitation imposed by time, cost and
resources necessary to generate nationally representative data, this research hereby
uses secondary data to answer the research questions. The use of quantitative
strategy enhances statistical modelling and inference based on a large sample size.
3.3 Description of the NDHS Data
The 2008 NDHS was implemented by the National Population Commission from
June to October 2008 to provide up-to-date information on fertility levels focusing
on marriage patterns, fertility preferences, reproductive activity, knowledge and
utilization of family planning services and other basic demographic indicators. It
serves as a follow-up to the 1990, 1999 and 2003 NDHS and provides updated
estimates of basic health and demographic indicators measured in the earlier surveys.
The 2008 NDHS was conducted with the largest nationally representative sample
size of 36,298 households in order to provide estimates both at the state and regional
levels. Compared to the previous NDHS, the sample for the 2008 NDHS was
designed to enhance the calculation of specific indicators (e.g. contraceptive use) for
36
each of the six regions and the 36 states, including the federal capital territory. In the
same vein, the sampling frame was based on the list of enumeration areas developed
during the 2006 national population census. These enumeration areas served as the
basis for the primary sampling unit (PSU), also referred to as a cluster for the 2008
NDHS. Thus, using a stratified two-stage cluster design, the final sample was
selected to comprise of 888 in total, with 602 clusters in the rural areas and 286 in
the urban areas.i
The sampling was conducted in two stages. In the first stage, a complete listing of
households was carried out for each cluster in order to serve as the sampling frame
for household election in the second stage. Based on the list generated, an average of
41 households was selected in each cluster using equal probability systematic
sampling. Of the 36, 298 households selected for the 2008 NDHS, only 34,644 were
occupied, while 34, 070 were successfully interviewed. This yields a response rate of
98 per cent. On the individual level, 34,596 women and 16,722 men were identified
to be eligible for being interviewed. The corresponding response rates were 97 per
cent and 93 per cent respectively, with 33,385 women and 15, 486 men eventually
interviewed.
3.4 Sample
Due to the restriction of this study to currently married women aged 15-49 years as
described in chapter 2, 23, 954 women were selected from the original sample.
However, based on the eligibility criteria (see section 2.5 on Operationalisation of
Unmet Need), this sample was further restricted. Thus, only 5,006 currently married
37
women were selected for the analysis. Of this, 3,494 have unmet need for spacing,
while 1.512 have unmet need for limiting.ii
3.5 Data Analysis
Data management and analysis were performed using SPSS 16.0. Three types of data
analysis techniques were used in this study. Firstly, bivariate analysis was
conducted using ‘unmet need’ as the dependent variable with selected demographic,
socioeconomic and cultural characteristics as independent variables. The probability
of having unmet need for spacing or for limiting was tested differently using logistic
regression models. This resulted from the observed differences in the level of unmet
need among married women in Nigeria. Finally, the contraceptive prevalence rate
was imputed into the ‘demographic significance model’ to project the significance of
50 per cent and 100 per cent satisfaction of unmet need.
3.6 Demographic Significance Model
This study adapts the regression equation used in khan (2008) to estimate the
potential impact of satisfying unmet need for family planning in Nigeria. Using the
most recent data from the DHS conducted in 60 developing countries, Khan (2008)
developed the regression equation:
TFR = 6.5020 – 0.0561*CPR
The estimates in the equation were generated from the ordinary least square
regression of total fertility rate (TFR) on current use of contraception (CPR), with
38
country as the unit of analysis, where 6.5050 is the constant and 0.0561 is the slope
of the regression.
Three ‘satisfaction’ scenarios are proposed in this study. In this first scenario, there
is no satisfaction of unmet need, i.e. the current reality, with total demand estimated
at 35 per cent and current use of contraceptive estimated at 12.4 per cent. The second
scenario estimates the impact of 50% satisfaction of unmet need on the total fertility
rate, and in the final scenario, the impact of 100% satisfaction of unmet need is
estimated on the current total fertility rate to generate the ‘predicted TFR’. A caveat
on this ‘satisfaction model’ is that, the estimated impact on total fertility rate is based
on current use of contraceptive as the only determinant.
i The final survey sample included 886 instead of 888 clusters. During fieldwork, access was not
obtained in
one cluster due to flooding, and in another cluster due to inter-communal disturbances.
ii Details of the variables used, recodes and data transformation techniques are shown in appendices 2
and 3.
39
4 Results and Interpretation
4.1 Levels of Unmet Need among Married Women
4.1.1 Overview
The first set of analyses explored the general pattern of unmet need, contraceptive
use and fertility preferences among married women in Nigeria. The result obtained
from this preliminary analysis of unmet need is shown in Table 1 below.
Table 1: General Pattern of Fertility Preferences Among Married Women In
Nigeria, 2008 NDHS
Frequency
Percent
Category Unmet need to
space
3494 14.6
Unmet need to
limit
1512 6.3
Using to space 1776 7.4
Using to limit 1195 5.0
Desire birth < 2
yrs
12312 51.4
Infecund,
menopausal
3496 14.6
Total 23785 99.3
Missing 99 169 .7
Total 23954 100.0
As it can be seen in the table (above), 14.6% of the women have unmet need for
birth spacing while 6.3% have unmet need for birth limiting. Overall, about 21% of
currently married women have unmet need for family planning. This result shows a
40
limited desire for fertility regulation among married women in Nigeria in
comparison to other sub-Saharan African countries. Although the pattern of higher
unmet need to space than to limit is similar to findings from studies in Zimbabwe
and Uganda, overall, the estimates from this study are lower than estimates from
these two countries. The reason for this is not clear, but it may have something to do
with the percentage (51.4%) of women who desire a birth within two years after
2008. Thus, further analysis will be conducted using bivariate statistics in order to
explore the differentials in unmet need for spacing and limiting by demographic,
socioeconomic and cultural characteristics.
4.1.2 Unmet Need For Spacing And Limiting By Demographic Characteristics
As mentioned in the literature review, the level of unmet need for spacing and
limiting vary by demographic characteristics. The next set of results show the
differentials by age, region, place of residence and number of living children.
41
Figure 6: Percentage of Currently Married Women Having Unmet Need For
Spacing And Limiting By Age, 2008 NDHS
As figure 6 exhibits, younger women have the highest unmet need for spacing
compared to the older women. Although the highest (18.5%) unmet need for spacing
is among women aged 20-24, there appears to be little variations in the level for
spacing among women younger than 35 years. This result differs from some
published studies (Khan, 2008, Magure, 2010, Ojakaa, 2008), which suggest that, the
highest unmet need for spacing is among women aged 30-34 years. It is however
consistent with those of Govindasamy and Boadi (2000), which found that unmet
need is higher among women aged 15-24 in Ghana. A possible explanation for this
might be that, younger woman desire more children. According to estimates from
2008 NDHS, women between ages 20 and 24 years are the most fertile and the
largest married cohort. Thus, findings from this analysis indicate that, younger
women have a higher unmet need for spacing, probably due to the corresponding low
16.6 18.5 17.7
15.7 13.5
9.5 6.7
1.8 1.8 2.3 5 9
14.9
14.5
0
5
10
15
20
25
30
15-19 20-24 25-29 30-34 35-39 40-44 45-49
pe
rce
nt
Age
Limiting
Spacing
42
utilisation of birth spacing methods.1 In the study, it is rather interesting to observe
that, at age 39, 13.5 per cent of married women still desire to more children, hence
their unmet need for family planning.
Furthermore, as observed in figure 6 above, 14.9% of women aged 40-44 have
unmet need for limiting, with this being the highest, though there appears little
variation (14.5%) among women aged 45-49. This suggests that, women in Nigeria
still give birth until the end of their reproductive years, a finding which contradicts
results from other studies. A plausible rationale for this observed level is discussed
in the work by Feyisetan and Bankole (2009), which links the limited desire for
fertility regulation to high social values placed on child bearing.
While findings from this analysis have supported previous studies which suggest a
variation in unmet need by age, it has also shown that, little variation exists among
women with unmet need for spacing, with similar patterns observed among women
with unmet need for limiting. Interestingly, the results in figure 4 imply that, the 20.8
per cent total unmet need for family planning is relatively ‘equally’ distributed
within the women. While there are higher estimates of unmet need for spacing than
limiting, the observed difference cannot be regarded as remarkable. It seems possible
that these rather similar patterns are due to the prevalent cultural and social practices
which placed high values on children, and thus, motivate overall low utilisation of
family planning services.
1 See appendix 4 for SPSS outputs.
43
Table 2: General Patterns of Unmet Need For Family Planning By Region, 2008
NDHS.
Frequency Percent
Region North 16184 67.6
South 7770 32.4
Total 23954 100.0
As table 2 indicates, 67.6% of women in the north have unmet need for family
planning in comparison to the 32.4% observed in the south. Although these results
are in agreement with findings (Renne, 1996) from Nigeria, which suggests that,
women in the north are more resistant to utilising family planning services, further
analysis will be conducted across the six regions within the spacing and limiting
categories, to ascertain the differentials in unmet need for spacing and limiting by
region.
Figure 7: Percentage of Currently Married Women Having Unmet Need For
Spacing And Limiting By Region, 2008 NDHS
12.6 14.3
17.4
11.8 12
17.5
6.8 4.8
4.1
8.1 9.2
9.5
0
5
10
15
20
25
30
Northcentral
Northeast
Northwest
Southeast
Southsouth
Southwest
pe
rce
nt
Region
limiting
spacing
44
In the general preliminary analysis (Table 2), unmet need was higher among women
in the northern part of Nigeria compared to the southern part. However, to enhance
comparison between the six regions, result from further analysis showed a varied
pattern in unmet need. Based on estimates in figure 7, women in the southwest have
the highest (17.5%) unmet need for spacing and a corresponding highest (9.5%)
unmet need for limiting. Although 17.4% of women in the northwest region have
unmet need for spacing, only 4.1% have unmet need for limiting, being the lowest
unmet need for limiting across the six regions.
Across the regions of the country, there exists a higher unmet need for spacing than
for limiting. These results may explain the relatively good correlation between
region and ethnic groups. As indicated in the literature review (Caldwell et al., 1992,
Feyisetan and Bankole, 2009), the Yoruba speaking people of the south-west region
are more likely to have higher demand for family planning services than any other
ethnic group or region in the country. The probable rationale for this has been linked
to higher levels of education among the women in south west, and the prevalent
Christianity religion. Thus, the observed pattern of unmet need for spacing and
limiting in the south-west could be a result of higher demand for family planning
than the available services. In a sense, findings from this study support previous
studies (Agyei-Mensah, 2006, Khan, 2008, Magure, 2010) which suggests women in
the north tend to have more unmet need for family, as they are less likely to utilise
available services.
45
The combined estimates for the northern region indicate higher unmet need for
spacing, while women in the south have higher unmet need for limiting. Based on
the estimates, the researcher suggests a link between the young age at marriage,
limited education and subsequent low demand for family planning among northern
women could be responsible for the observed pattern of unmet need for spacing. In
the same vein, the researcher posits that, women in the south have higher estimates
for unmet need for limiting as a result of limited family planning services to meet
their need to limit their family size.
Figure 8 Percentage of Currently Married Women Having Unmet Need For
Spacing And Limiting By Place 0f Residence, 2008 NDHS
The result from the initial analysis of the unmet need for spacing and limiting by
place of residence indicates that, the highest unmet need for spacing is among
women in rural area, while women living in urban area have the highest unmet need
for limiting. This finding is in agreement with Khan’s (2008) findings which showed
13.7 15.1
7.1 6.1
0
5
10
15
20
25
Urban Rural
Pe
rce
nt
Place of Residence
limitng
spacing
46
that, unmet need for spacing is higher among women living in rural areas. However,
estimates from the crosstabulation analysis (see appendix 4) indicates that, women in
urban areas utilises family services more compared to women living in rural areas, in
which 55% of them desire a birth within two years. Thus, it is suggested that, the
estimates of unmet need for limiting, is a result of inadequate provision of service as
opposed to non-utilisation. Figures 9 and 10 below are further extensions of the
pattern observed in the differentials of unmet need by type of place of residence
across the regions.
Figure 9: Unmet Need For Spacing And Limiting By Urban Place of Residence
Across Regions, 2008 NDHS.
Figure 9 above illustrates the differentials in unmet need for spacing and limiting by
urban place of residence within the six regions. The estimates of unmet need for
spacing were highest (21.2%) in the North West and lowest (8.5%) in the south east.
As observed in this study, estimates of unmet need for spacing among women in
11.3
16.8
21.2
8.5
16.6
10
6.7 6.6 5.7
8 8.7
7.6
0
5
10
15
20
25
Northcentral
North east North west South east South west South south
Pe
rce
nt
Region
Spacing
Limiting
47
north east are comparable to those of women from south west regions. From the
graph above we can see that, there is higher unmet need for spacing compared to
limiting for women living in urban areas.
Although the pattern of unmet need for limiting appears similar in urban areas across
the regions, 8.7% of women in ‘urban’ south west have unmet need for limiting
compared to 5.7% in the northwest. In the current study, comparing unmet need for
spacing with unmet need for limiting by living in urban areas across regions showed
that, a vast difference exists in having unmet need particularly in the urban areas of
the north west region. It is somewhat surprising that a great similarity existed among
women with unmet need for spacing and limiting in the south east region. It seems
possible that these results are due to age of marriage in Nigeria, particularly in the
north-west regions where women marry early (and thus, have longer periods of
exposure to pregnancy) and south east region, where marriage occurs at later year.
Figure 10: Unmet Need For Spacing And Limiting By Rural Place of Residence
Across Regions, 2008 NDHS.
13.1 13.5
16.7
14.1
17.9
14.4
6.9
4.3 3.9
8.1
9.8
11
0
2
4
6
8
10
12
14
16
18
20
North central North east North west South east south west South south
Spacing
Limiting
48
Data from this figure (above) can be compared with the data in figure 9, which
shows that unmet need for spacing is higher in urban northwest and lowest in urban
southeast. Similarly, by rural place of residence across regions, unmet need for
spacing is clearly higher than unmet need for limiting. The single most striking
observation to emerge from the data comparison was that, women in rural south west
have the highest (17.9%) unmet need for spacing as well as the highest unmet need
for limiting by urban place of residence. Another unanticipated finding was that
women in rural south-south have the highest (11%) unmet need for limiting.
Contrary to the pattern observed in figure 9, there exist a distinct difference in unmet
need for spacing and limiting by rural place of residence in the southeast region.
Compared to other regions in the north, women living in the rural place of residence
in the northwest have the highest (16.7%) unmet need for spacing and the lowest
(3.9%) unmet need for limiting, a pattern similar to that observed in result presented
in figure 9.
49
Figure 11: Percentage of Women Having Unmet Need For Spacing And
Limiting By Number Of Living Children, 2008 NDHS
As shown in figure 11, unmet need for spacing is highest (16.4%) among women
with one living child, no difference exists in the estimates among women with two or
three living children, and unmet need for spacing decreases as the number of living
children increases. Based on the perception of the researcher, a woman with one
living child is likely to have higher demand for family planning methods, as she is
probably young and desire to have more children.
Based on estimates from this study, one is led to believe women with three children
still desire more children, hence the demand for family planning services for spacing,
and the subsequent unmet need. As would be expected, unmet need for limiting is
highest (16.3%) among women with six or more children, with a corresponding 11.2
per cent of women with five living children. This may be explained by the fact that,
having six or more children pose a high risk to maternal health and well as signifies a
11.3
16.4 16.3 16.3 15 13.7 12.6
0.9
2.1 1.9 3.6 7 11.2 16.3
0
5
10
15
20
25
30
35
0 1 2 3 4 5 6+
pe
rce
nt
No of Living Children
limiting
spacing
50
higher economic cost to adequately take care of the children. It is encouraging to
compare this finding with that found by Khan (2008) who found that, unmet need for
limiting is highest among women with five or more living children in Uganda.
Another interesting observation from this result is that, 15 per cent of women with
four children still have unmet need for spacing, a pattern which can be attributed to
the social value placed on children.
4.1.3 Unmet Need For Spacing And Limiting By Socioeconomic Characteristics
The results presented in this section explore the differentials in unmet need for
spacing and limiting by socioeconomic status. Specifically, estimates are presented
for observed differences by wealth status, education, whether the woman was
engaged in paid employment and exposure to three media sources.
Figure 12: Differentials In Unmet Need For Spacing And Limiting Among
Currently Married Women By Wealth Index, 2008 NDHS
14.6 15 15.3 15.8 12.5
4.4 6.2
7.4 8.1
6.7
0
5
10
15
20
25
30
Poorest Poorer Middle class Richer Richest
limiting
spacing
51
As mentioned in the literature review, women who have higher wealth status tend to
higher unmet need for limiting. This could be attributed to their being older,
employed and more likely to have achieved their desired family size, as well as have
the financial resources to afford family planning services. Estimates from this
analysis showed that unmet need for spacing and limiting is highest (15.8% and
8.1% respectively) among women classified as ‘richer’ by wealth status. Unmet need
for spacing is lowest (12.5%) among the richest category and being in the ‘poorest’
wealth class could be attributed to having the lowest (4.4%) unmet need for limiting.
In view of this, women who are classified as poor, might desire more children, and
thus not use family planning methods, while ‘richer’ women could have unmet need
due to insufficient satisfaction of demand. While the patterns observed in this study
corroborates previous research into differentials in unmet need by wealth status,
there appear a rather small difference (0.3%) between the poorer and middle class in
terms of having unmet need for spacing, although there exist a vast difference in
unmet need for limiting. The reason for this is not clear, but it may have something
to do with the socioeconomic classification in Nigeria, which means, women in
poorer or middle class may not be able to afford family planning services.
Figure 13: Differentials In Unmet Need For Spacing And Limiting Among
Currently Married Women By Educational Status, 2008 NDHS
52
Figure 13 shows the result obtained from the bivariate analysis of the differentials in
unmet need for spacing and limiting by education. Based on the findings from this
study, being educated to secondary level is associated with having the highest
(15.6%) unmet need for spacing, while primary education can be attributed to having
the highest (8.5%) unmet need for limiting. A possible explanation for this might be
that, women with higher education are likely to have financial resources to meet the
cost of family planning services, as well as want smaller families due to their
knowledge about the impact of child bearing on maternal health. Another possible
explanation for this is that, women with higher education have the highest estimates
for using family planning methods followed closely by women with secondary
education (see table 3 below). Thus, based on estimates from this analysis, a woman
with secondary or higher education has unmet need, as a result of higher demand for
family planning services, contrary to the observed pattern among women (table 3) as
opposed to women with no education, who do not use family planning service. The
results from this analysis corroborate that of Westoff and Bankole (1995) which
15 14.6 15.6
9.6
5.2 8.5 7
6
0
5
10
15
20
25
No education Primary Secondary Highereducation
limiting
spacing
53
found that, women with primary education have the highest unmet need in sub-
Saharan Africa.
Table 3: Estimates of Unmet Need For Family Planning By Educational Level,
2008 NDHS
Highest educational level
Primary Secondary Higher no
education
Total
Unmet
need
Unmet
need to
space
740 783 143 1828 3494
14.6% 15.6% 9.6% 15.0% 14.7%
Unmet
need to
limit
434 350 90 638 1512
8.5% 7.0% 6.0% 5.2% 6.4%
Using to
space
430 797 317 232 1776
8.5% 15.8% 21.3% 1.9% 7.5%
Using to
limit
355 436 215 189 1195
7.0% 8.7% 14.4% 1.6% 5.0%
Desire birth
< 2 yrs
2457 2220 544 7091 12312
48.4% 44.1% 36.6% 58.2% 51.8%
Infecund,
menopausal
665 447 179 2205 3496
13.1% 8.9% 12.0% 18.1% 14.7%
Total 5081 5033 1488 12183 23785
100.0% 100.0% 100.0% 100.0% 100.0%
As shown in table 3 above, findings from this study indicate that women with no
education have the lowest estimates across all categories of unmet need for family
planning. A probable rationale for this could be attributed to their limited educational
level. It is therefore not surprising to see that 58.2 per cent of married women with
no education desire a birth within two years from 2008, which correlates with the
observed pattern of use and non-use of family planning methods. Thus, findings
from this study confirm Magure’s (2010) findings, which show that, married women
in Zimbabwe with no education have the highest unmet need for spacing and
54
limiting, and that, unmet need for spacing and limiting decreases as education
increases.
Figure 14: Differentials in Unmet Need For Spacing And Limiting Among
Currently Married Women Who Are Employed, 2008 NDHS
As observed in figure 14 (above), women who are not in paid employment have the
highest (16.7%) unmet need for spacing, while women in paid employment have the
highest (7.2%) unmet need for limiting. Prior studies (Magure, 2010, National
Population Commission (NPC) [Nigeria] and ICF Macro, 2009, Ojakaa, 2008,
Feyisetan and Ainsworth, 1996) have noted the importance of employment on
having unmet need for spacing and limiting. The result presented in figure 14
corroborates previous findings (Agyei-Mensah, 2006, Khan, 2008, Magure, 2010)
into the links between unmet need for family planning and employment status. As
would be expected, women in paid employment are likely to have the financial
13.7
16.7
7.2
4.7
0
5
10
15
20
25
Yes No
limiting
spacing
55
resources to meet the cost of family planning methods, compared to women who are
not working.
Figure 15: Percentage of Currently Married Women With Unmet Need For
Spacing And Limiting By Exposure To Three Media Sources, 2008 NDHS
The bar chart above shows that, respectively, 14.3%, 10.9% and 2.1% of women
who were exposed to newspaper, radio and TV have unmet need for spacing. Unmet
need for limiting is lowest (6.3%) among women exposed to radio, while women
with exposure to TV and Newspaper tend to have comparable (7.3% and 7.1%
respectively) estimates. Khan (2008) has described the general pattern of unmet need
for family planning by exposure to two or more media sources in Uganda but did not
compare the estimates by the type of media source, thus, this pattern has not been
previously described. A possible explanation for the pattern observed among women
who are exposed to newspaper and TV is that, the media advertisement for family
planning services is predominantly on TV and rarely in the newspaper.
2.1
10.9
14.3 7.3
6.3
7.1
0
5
10
15
20
25
TV Radio Newspaper
Limting
Spacing
56
Thus, a woman who is only exposed to newspaper is more likely to have limited
knowledge of family planning services. It is therefore not surprising that, 7.3 per cent
of women who have access to TV have unmet need for limiting. It is also likely that,
women who have access to TV, may reside in urban areas, is educated to secondary
level or higher, belongs to higher wealth status as well as demand for family
planning services. Unmet need in this case could be said to result from insufficient
resources to meet the demand.
4.1.4 Unmet Need For Spacing And Limiting By Cultural Characteristics
Many studies have shown that Nigeria has high cultural values which have direct
impact on fertility preferences. Thus, this section of result explores the differentials
in unmet need for spacing and limiting using religion and ethnicity.
Figure 16: Differentials In Unmet Need For Spacing And Limiting Among
Currently Married Women By Religion, 2008 NDHS
12 13.5
15.9
12.3
6.1
9.3 8.6 4.5
7.6
12.1
0
5
10
15
20
25
Catholic OtherChristians
Islam Traditionalist Others
limiting
spacing
57
As shown in figure 16, Muslim (Islam) women have the highest (15.9%) unmet need
for spacing. This result may be explained by the fact that majority of the women who
practice Islamic religion lives in the northern region of Nigeria, and is in agreement
with Ojakaa’s (2008) findings that in 2003, unmet need for spacing was highest
among Muslim women in Kenya. Thus, data from this figure can be compared with
data presented in Table 2 which shows the general pattern of unmet need for family
planning by region. 12% of catholic women, 13.5% of other Christian women,
12.3% of women who said they were traditionalist and 6.1% of women who consider
themselves to belong to other religious categories have unmet need for spacing.
From this study, it is obvious that, catholic women have high unmet need for spacing
and limiting, a pattern which has been widely discussed in literature. These results
are consistent with those of other studies (Khan, 2008, Magure, 2010, Ojakaa, 2008)
and suggest that having unmet need for spacing and limiting is linked with the
religion of the woman.
Figure 17: Percentage of Currently Married Women With Unmet Need For
Spacing And Limiting By Ethnicity, 2008 NDHS
17.7
11.8
19.3
11.5 14.2
3.7
7.6
10.5
8.2 6.8
0
5
10
15
20
25
30
35
Hausa Igbo Ijaw/ Izon Yoruba Others
limiting
spacing
58
As shown in figure 17, the highest estimates of unmet need for spacing and limiting
(19.3% and 10.5% respectively) were among women belonging to the Ijaw/Izon
ethnic group. It is somewhat surprising that the Ijaw/Izon ethnic group has the
highest estimates. The reason for this is not clear, but it may have something to do
with Ijaw/Izon ethnic group being a predominant part of the rural south-south region,
the region, which has the highest unmet need for limiting. The 17.7 per cent estimate
for unmet need for spacing among Hausa women is expected, as the Hausa ethnic
group is predominantly settled in the north, particularly in the northwest.
Throughout this study, the results have shown that, a married woman in the north is
likely to have higher unmet need for spacing than limiting, as most of them desire a
birth soon (61.8%), as well as have limited or no education (see appendix 4).
Another significant observation is the 8.2 per cent result of unmet need for limiting
among the Yoruba ethnic group. This finding is comparable to the data presented in
Figure 9, which shows that women living in the urban south west have the highest
unmet need for limiting. The Yoruba-speaking people are predominantly settlers in
the south west region.
So far, this chapter has explored the differentials in unmet need for spacing and
limiting by selected demographic, socioeconomic and cultural characteristics.
Although the patterns observed from the results differ from some published studies
(Agyei-Mensah, 2006, Khan, 2008, Magure, 2010, Ojakaa, 2008) in other sub-
Saharan Africa countries, the findings corroborate the findings of a great deal of the
previous work in this field. Based on estimates from this analysis, women have
59
higher unmet need for spacing than limiting. A probable rationale for this striking
difference could be attributed to the age patterns of women. Nigeria as a country has
a ‘young’ population structure, with women younger than 35 years being a larger
part of the sample used in this analysis.
Thus, based on the bivariate analysis conducted in this study, a married woman in
Nigeria with the following characteristics is typically described has been likely to
have a higher unmet need for spacing. If she:
a. Is younger (20-24 years)
b. Lives in the rural place of residence
c. Resides in the northwest region, particularly the urban part, belongs to the
Hausa ethnic group and practice Islam as a religion
d. Has between one and three living children, is educated up to secondary level,
is not currently working, and has limited knowledge of family planning
services.
Similarly, a married woman in Nigeria with the following characteristics is typically
described has been likely to have a higher unmet need for limiting. If she:
e. Is older (40-44 years)
f. Lives in the urban place of residence
g. Resides in the south west region, especially the urban part, belongs to the
Yoruba ethnic group and a practicing catholic
h. Has six or more living children, has limited (Primary) education and is
currently working.
60
4.2 Logistic Regression Models For Likelihood Of Having Unmet Need For
Spacing Or Limiting
Considering the limitation of the bivariate analytic method in capturing the salient
differences in the selected background factors used in this study, further multivariate
analysis was conducted to create a statistical model of unmet need for spacing and
limiting. This section focuses on the investigation of the likelihood of a married
woman having unmet need for spacing or limiting. For this study, logistic regression
models were used to test the relationship between unmet need for spacing or limiting
and the demographic, socioeconomic and cultural characteristics used in the
bivariate analysis. As a result of the observed differentials in the levels and
determinants of unmet need for spacing and limiting, two logistic regression models
were separately constructed. For the purpose of the analysis and to meet the
assumptions of logistic regression, the ‘unmet need’ variable was recoded into two
variables – ‘unmet need for spacing’ and ‘unmet need for limiting.’ These derived
variables were further dichotomised into ‘unmetspace’ and ‘unmetlinmit.’i
4.2.1 Logistic Regression Model: Unmet Need For Spacing
Table 4 presents the results of the logistic regression model for the likelihood of
having unmet need for spacing, expressed as exponential of the beta coefficients, the
standard error for each of the variables included in the analysis, and the significance
of each variable. The result shows that, a woman’s likelihood of having unmet need
for spacing is highly related to age, number of living children, employment status,
wealth status, education and certain cultural characteristics.
61
Table 4: Logistic Regression Model For The Likelihood Of Having Unmet Need
For Spacing Among Currently Married Women, 2008 NDHS
Characteristics B S.E. Sig. Exp(B)
Age
15-19R
20-24 .136 .073 .063 1.146
25-29 .075 .070 287 1.078
30-34 -.069 .074 .349 .933
35-39 -.247 078 .001 .781
40-44 -.655 .089 .000 519
45-49 -1.026 .100 .000 359
Region
North CentralR
North East .143 .060 .052 .823
North West .378 .056 .222 .875
South East -.068 .084 .993 .999
South West .394 .068 .949 1.010
South South -.049 .071 .017 1.300
Place of
Residence
UrbanR
Rural
.112
.042 .007 1.119
Education
Primary
educationR
Secondary
education -.032 .047 504 .969
Higher
education .048 .046 .300 1.049
No education -.508 .091 .000 .602
62
Religion
CatholicR
Other
Christians
.738 .733 .314 2.093
Islam .877 .730 .230 2.404
Traditionalist 1.064 .730 .145 2.899
Others .773 .743 .298 2.165
Wealth Status
PoorestR
Poorer .176 .062 .004 1.193
Middle class .211 .063 .001 1.235
Richer .235 .065 .000 1.265
Richest .272 .066 .000 1.312
Number of
living children
0R
1 -.120 .079 .128 .887
2 .315 .065 .000 1.370
3 .297 .064 .000 1.346
4 .302 .064 .000 1.353
5 .204 .067 .002 1.226
6+ .097 .073 .188 1.102
Currently
working
NoR
Yes .235 .038 .000
1.265
Ethnicity
HausaR
63
Igbo -.472 .071 .000 .624
Ijaw/Izon .106 .104 .308 1.111
Yoruba -.496 .065 .000 .609
Others -.269 .042 .000 .764
R – Reference category.
Model statistics; Chi-square = 583.408 (p<.000); -2 Log likelihood = 19013.134;
Cox & Snell R Square = .024; Nagelkerke R Square = 0.043
The results showed that, the likelihood of having unmet need for spacing is highly
related to age: younger women (20-29 years) are more likely to have unmet need for
spacing compared to the reference category. Significantly, women within ages 35
and 49 years are less likely to have unmet need for spacing, compared to the
reference category, a pattern similar to the bivariate analysis in the previous section.
Even though women in the south (south-south and south-west) are more likely to
have unmet need for spacing compared to married women in the north central, these
estimate are not statistically significant. From this data, it is observed that, the
likelihood of having unmet need for spacing increases as the wealth status increases,
as well as the number of living children.
As would be expected, women having between two and five children are
significantly more likely to have unmet need for spacing compared to the reference
category. This result shed further light on the result from the bivariate analysis,
implying that, women in Nigeria desire large family size. Several factors could be
responsible for this, but the most prominent determinant of this rather persistent
demand for children is the cultural practices prevalent in Nigeria.
64
Another interesting finding from this analysis is that, a woman who is currently
working is significantly more likely to have unmet need for spacing than a woman
who is not working, as well as living in the rural area. Women from the Yoruba,
Igbo or other ethnic groups are less likely to have unmet need for spacing compared
to the Hausa ethnic group. This is also similar to findings from the bivariate analysis.
As previously discussed, it is not surprising that women with higher education are
more likely to have unmet need for spacing. This category of women constitutes the
largest group of women using family planning methods, hence the non-significant
result. Although a woman with no education is less likely to have unmet need for
spacing, the estimates from the analysis show this to be highly significant. Thus, as
previously discussed, women with no education significantly have unmet need for
family planning as a result of their desire for more children and their educational
status.
Contrary to expectations, this study did not find a significant difference between
unmet need for spacing and the different religious groups in Nigeria. From the
coefficients, women in any of the religious groups in Nigeria are two times more
likely to have unmet need for spacing compared to women who practice
Catholicism. This result is comparable with results from the bivariate analysis which
showed that, women who practice Catholicism are more likely to have unmet need
for spacing.
Based on the coefficients from the logistic regression analysis, a married woman,
between ages 20-24 years, from the southern region, living in the rural area,
65
belonging to the richest wealth category, with secondary or higher level of education,
currently working, with two or more children is more likely to have unmet need for
spacing. The most striking result to emerge from this analysis is that, wealth status
and number of living children are highly associated with having unmet need for
spacing.
4.2.2 Logistic Regression Model: Unmet Need For Limiting
Results of the analysis for the model on unmet need for limiting are shown in Table
5. Coefficients from this analysis indicate a difference in the relationship between
the demographic, socioeconomic and cultural characteristics compared to the
observation in the unmet need for spacing model. For the unmet need for spacing
model, wealth status was strongly associated with having unmet need spacing,
whereas, the striking effect is absent in this result. In relation to age, older people
(40-44 years) are 9.6 times more likely to have unmet need for limiting, the most
striking result from this analysis. This is consistent with estimates from the bivariate
analysis, and contradicts some findings of a great deal of the previous work in unmet
need for family planning.
66
Table 5: Logistic Regression Model For The Likelihood Of Having Unmet Need
For Limiting Among Currently Married Women, 2008 NDHS
Characteristics B S.E. Sig. Exp(B)
Age
15-19R
20-24 .035 .210 .866 1.036
25-29 .291 .194 .133 1.338
30-34 1.089 .185 .000 2.971
35-39 1.712 .180 .000 5.542
40-44 2.267 .179 .000 9.647
45-49 2.241 .180 .000 9.404
Region
North CentralR
North East -.327 .086 .000 .721
North West -.703 .090 .000 .495
South East -.852 .087 .000 .426
South West -.144 .104 .168 .866
South South .040 .090 .656 1.041
Place of
Residence
UrbanR
Rural
-.169
.058
.003
.844
Education
Primary
educationR
Secondary
education -.221 .075 .003 .802
Higher
education -.377 .120 .002 .686
No education -.528 .065 .000 .590
Religion
CatholicR
-.299
.539
.579
.742
67
Other
Christians
Islam -.386 .535 .470 .680
Traditionalist -1.081 .535 .043 .339
Others -.527 .562 .348 .590
Wealth Status
PoorestR
Poorer -.441 .090 .000 .643
Middle class -.083 .087 .336 .920
Richer .113 .087 .196 1.119
Richest .202 .088 .022 1.224
Number of
living children
0R
1 .837 .244 .001 2.310
2 .752 .245 .002 2.122
3 1.407 .231 .000 4.084
4 2.111 .225 .000 8.256
5 2.632 .223 .000 13.901
6+ 3.055 .218 .000 21.219
Currently
working
NoR
Yes .466 .061 .000 1.594
Ethnicity
HausaR
Igbo -.640 .076 .000 .527
Ijaw/Izon .121 .085 .157 1.128
68
Yoruba .478 .132 .000 1.612
Others .203 .076 .008 1.225
R – Reference category.
Model statistics; Chi-square = 1578.648 (p<.000); -2 Log likelihood = 9536.354;
Cox & Snell R Square = .065; Nagelkerke R Square = .172
As table 5 shows, married women from the northern regions and those who live in
the rural place of residence are significantly less likely to have unmet need for
limiting. Although education is a significant determinant of unmet need for limiting,
estimates from this logistic analysis indicate that, both highly educated and non-
educated women are less likely to have unmet need for limiting compared to women
with primary education. It is possible therefore, that, younger women are more
educated and likely to demand and use family planning methods compared to older
women. Estimates from this analysis are comparable with results from the likelihood
of having unmet need for spacing, which showed that, religion is not a significant
determinant of having unmet need for family planning.
The most striking result to emerge from this further analysis is that number of living
children is significantly associated with having unmet need for limiting. This is
comparable with the result of the likelihood of having unmet need for spacing.
Compared to women with no children, a woman with six or more children is 21
times more likely to have unmet need for limiting. The observed increase in the
correlation between the number of living children and having unmet need for
limiting could be attributed to the fact that, these women seem to have achieved their
desired family size.
69
As observed in the likelihood of having unmet need for spacing, significantly, a
woman who is currently working is 1.5 times more likely to have unmet need for
limiting than a woman who is not working, and Yoruba women are 1.6 times more
likely to have unmet need for limiting than Hausa women. This finding is consistent
with the result from the bivariate analysis and further confirms that, women in the
south west region, especially the Yoruba speaking ones, are more likely to have
unmet for limiting.
4.3 Demographic Significance Of Satisfying Unmet Need For Family Planning
The result of the estimated effect of satisfying unmet need for family planning and
increasing the current use of contraceptive on total fertility rate (TFR) is presented in
Table 6. Using the regression equation:
TFR = 6.5020 – 0.0561*CPR
Where the total fertility rate is modelled using the contraceptive prevalence.
In scenario 1, the level of unmet need and current contraceptive prevalence is the
same as in 2008 NDHS, and the estimated TFR is 5.8 children per woman. It is
important to note that this figure differs from the actual TFR of 5.7 because the study
uses data for currently married women, as well as the calculated unmet need for this
analysis, whereas the actual TFR is based on data from all women sample.
70
Table 6: Estimated Impact Of Satisfying Unmet Need For Family Planning On
TFR Among Currently Married Women, 2008 NDHS
Scenario Current Total Adjusted
Adjusted Estimated TFR
TFR Demand Unmet Need
CPR based adjusted CPR
Scenario 1:
No unmet
need is
satisfied
5.7
35
21
12.4
5.8
Scenario 2:
50%
unmet
need is
satisfied
Scenario 3:
100%
satisfaction
of unmet
need
5.7
35 10.5 22.9 5.2
5.7
35
0.0
35
4.5
In scenario 2, the theoretical satisfaction of the current unmet need by 50% reduces
the estimated TFR to 5.2. It is somewhat surprising that 100% satisfaction of unmet
need only reduces the current TFR by 1.2 births per woman. These findings are
rather disappointing, as it clearly indicates that, the high fertility in Nigeria is not due
to unmet need for family planning, but insufficient demand for smaller families by
women. As shown in table 6, 100 per cent satisfaction of the current family planning
demand will only reduce the current national TFR of 5.7 to 4.5, a TFR still higher
than replacement level fertility.
iSee appendix 3 for details of variable derivation.
71
5 Conclusions and Recommendations
5.1 Summary
This dissertation has investigated the levels and differentials in unmet need for
family planning among married women in Nigeria. It highlighted the history of
fertility transition in Nigeria, discussed the concept of unmet need for family
planning, its measurement and the demographic significance of satisfying the
identified unmet need for family planning. As expounded in this study, unmet need
for family planning refers to the observed differences between a woman’s fertility
desire and her fertility behaviour.
Returning to the research question posed at the beginning of this study, it is now
possible to state that differentials exist in the levels of unmet need for family
planning among married women in Nigeria. In consistency with previous work in
unmet need for family planning, there are two categories of unmet need for family
planning in Nigeria. As observed, a woman either has unmet need for spacing or
limiting, depending on selected demographic, socioeconomic and cultural
characteristics.
The analysis used in this study was based on data from 2008 NDHS and was limited
to currently married women who expressed a desire to space or limit their family size
72
but do not use family planning method. The results of this investigation show that,
women who are younger, living in rural areas, have between one and three children,
are currently working and have limited exposure to family planning in the media
may typically have unmet need for spacing. Also, unmet need for limiting is
associated with being older, higher parity, higher wealth status, living in the southern
region and belonging to the Yoruba ethnic group.
The most obvious finding to emerge from this study is that, unmet need for family
planning is strongly associated with number of living children. While women with
less than three children have a higher unmet need for spacing, women with six or
more children have unmet need for limiting. It is rather interesting to note that, a
high proportion of women (13.5%) with five living children have unmet need for
spacing, and thus desire another child soon.
After controlling for the selected demographic, socioeconomic and cultural
characteristics used in the bivariate analysis, coefficients from the logistic regression
analysis indicate that, unmet need for spacing and limiting increases with education
and wealth status, and women who are working are more likely to have unmet need
for family planning compared to those who are not working. One unanticipated
finding was that, religion is not a significant determinant of whether a woman has
unmet need for family planning. Estimates from this study show no striking
difference among women of the various religious groups in relation to unmet need
for spacing or limiting, compared to women who practice Catholicism.
73
Also very striking is the evidence from this study suggests that, 50 per cent
satisfaction of unmet need for contraception will reduce the total fertility rate to 5.2,
and 100 per cent satisfaction will result in further reduction by 0.7. Based on this, it
appears 100 per cent satisfaction of the current level of unmet need will only reduce
the TFR to 4.5, a level which is still very higher than the fertility replacement level.
Throughout this study, effort has been made to explain this rather persistent demand
for large family size by women in Nigeria. Estimates from this study, therefore,
support the position of Feyisetan and Bankole (2009), and Osili and Long (2008),
which linked the observed persistent high demand for children to prevalent cultural
practices in Nigeria that place high social value on children and limited female
education. This observed pattern has serious implications for family planning
services.
5.2 Policy Implication
The findings from this study have important implications for developing appropriate
intervention to increase the level of contraceptive use for family planning in Nigeria.
Since data from this study indicates that, a woman can either have unmet need for
spacing or limiting by age and number of living, the implication of this is that,
unintended pregnancies are likely to occur which directly impact on women’s health,
74
leading to mortality in certain instances, impact on child’s growth, and pose an
unacceptable risk for society.
Thus, the combination of findings provides some support for the conceptual premise
that, national effort be geared towards improving the current level of family planning
services in Nigeria by enhancing its accessibility, acceptability and affordability.
Specifically, efforts need to be geared towards adequate provision of family planning
services for birth limiting. Estimates from this study show that, a woman with six or
more living children is 21 times more likely to have unmet need for limiting
compared to a woman without a living child.
Another issue that emerged from these findings is that, as the level of education
increases, wealth status increases, unmet need for family planning increases. In
general, therefore, it seems that, women with higher level of education tend to
demand for smaller families and can afford to use family planning services.
However, based on the proportion of highly educated women with unmet need for
family planning identified in this study, it seems available family planning services
are very limited.
From the results of this study, one is led to believe that, demand for smaller families
(birth limiting) is usually among older women, hence the need for availability of
appropriate family planning methods to meet the expressed need for birth limiting.
75
The implication of this is that, the availability and utilisation of appropriate family
planning services for birth limiting will contribute to the desired reduction of the
current total fertility rate.
5.3 Recommendation for Further Research
The present study confirms previous findings in unmet need for family planning and
contributes additional evidence that suggests, women with higher educational
attainment are more likely to have unmet need for family planning, probably due to
age, number of living children and demand for smaller families.
This research has thrown up many questions in need of further investigation. First,
the reported level of unmet need in Nigeria is relatively very low and there exists a
persistent demand for large family size. Thus, it is recommended that further
research be undertaken to investigate the determinant of large family size,
particularly, women’s rationale for their ‘ideal family size.
While this study uses only married women, it is recommended that subsequent
studies be focused on couples, in order to enhance the holistic understanding of
factors influencing demand and ideal family size. More broadly, research is also
needed to determine why a majority of the women in Nigeria does not use family
planning methods despite its availability.
76
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80
Appendix 1 – Map of Nigeria
References:
81
Appendix 2: Variables Used in the Analysis
Variables Description Categories
Age Age 5-year groups 1 = 15-19
2 = 20-24
3 = 25-29
4 = 30-34
5 = 35-39
6 = 40-44
7 = 45-49
Region Region 1 = North Central
2 = North East
3 = North West
4 = South East
5 = South South
6 = South West
Residence Type of place of residence 1 = Urban
2 =Rural
Religion
Religion 1 = Catholic
2 = Other Christians
3 = Islam
4 = Traditionalist
5 = Others
Education Highest educational level 0 = No education
1 = Primary
2 = Secondary
3 = Higher
4 = No education
Ethnic Ethnic group 1 = Hausa
2 = Igbo
3 = Ijaw/Izon
4 = Yoruba
5 = Others
82
Wealth_index Wealth Index 1 = Poorest
2 = Poorer
3 = Middle class
4 = Richer
5 = Richest
Living_children
Number of living children 0 = 0
1 = 1
2 = 2
3 = 3
4 = 4
5 = 5
6 = 6+
FP_radio
Heard FP on radio last months 0 = No
1 = Yes
FP_TV
Heard FP on TV last months 0 = No
1 = Yes
FP_newspaper
Heard FP newspaper last months 0 = No
1 = Yes
Marital_status
Current marital status 0 = Never married
1 = Married
2 = Living together
3 = Widowed
4 = Divorced
5 = Not living together
Unmet Unmet need 1 = Unmet need to space
2 = Unmet need to limit
3 = Using to Space
4 = Using to limit
7 = Desire a birth < 2 yrs
9 = Infecund or menopausal
employed
Respondent currently working 0 = No
1 = yes
83
Appendix 3: Derived variables used in the Analysis
Variables Description Categories Derivation
Unmet Unmet need for
spacing
0 = not selected
1 = unmet need
to space
Recode (1=1) (ELSE=0)
INTO = unmetspace
Unmet Unmet need for
limiting
0 = not selected
1 = unmet need
to limit
Recode (2=1) (ELSE=0)
INTO = unmetlimit
84
Unmet need * Number of living children
Number of living children
0 1 2 3 4 5 6+ Total
Unmet
need
Unmet need to
space
276 592 617 623 500 358 528 3494
11.3% 16.4% 16.3% 16.3% 15.0% 13.7% 12.6% 14.7%
Unmet need to
limit
22 74 72 137 233 294 680 1512
.9% 2.1% 1.9% 3.6% 7.0% 11.2% 16.3% 6.4%
Using to space 71 315 425 429 308 134 94 1776
2.9% 8.7% 11.2% 11.2% 9.2% 5.1% 2.2% 7.5%
Using to limit 1 8 40 135 294 305 412 1195
.0% .2% 1.1% 3.5% 8.8% 11.7% 9.9% 5.0%
Desire birth < 2
yrs
1667 2284 2229 2025 1509 1094 1504 12312
68.5% 63.4% 58.7% 53.0% 45.3% 41.8% 36.0% 51.8%
Infecund,
menopausal
396 329 413 475 489 433 961 3496
16.3% 9.1% 10.9% 12.4% 14.7% 16.5% 23.0% 14.7%
Appendix 4: SPSS Output of Selected Variables used in the Bivariate Analysis
85
Unmet need * Highest educational level
Highest educational level
Primary Secondary Higher
no
education Total
Unmet need Unmet need to space 740 783 143 1828 3494
14.6% 15.6% 9.6% 15.0% 14.7%
Unmet need to limit 434 350 90 638 1512
8.5% 7.0% 6.0% 5.2% 6.4%
Using to space 430 797 317 232 1776
8.5% 15.8% 21.3% 1.9% 7.5%
Using to limit 355 436 215 189 1195
7.0% 8.7% 14.4% 1.6% 5.0%
Desire birth < 2 yrs 2457 2220 544 7091 12312
48.4% 44.1% 36.6% 58.2% 51.8%
Infecund, menopausal 665 447 179 2205 3496
13.1% 8.9% 12.0% 18.1% 14.7%
Total 5081 5033 1488 12183 23785
100.0% 100.0% 100.0% 100.0% 100.0%
86
Unmet need * ethnic group
ethnic group
Hausa Igbo Ijaw/Izon Yoruba Others Total
Unmet need Unmet need to space 1135 287 128 352 1592 3494
17.7% 11.8% 19.3% 11.5% 14.2% 14.7%
Unmet need to limit 238 185 70 250 769 1512
3.7% 7.6% 10.5% 8.2% 6.8% 6.4%
Using to space 104 333 72 509 758 1776
1.6% 13.7% 10.8% 16.7% 6.7% 7.5%
Using to limit 37 237 22 412 487 1195
.6% 9.8% 3.3% 13.5% 4.3% 5.0%
Desire birth < 2 yrs 3955 968 285 1117 5987 12312
61.8% 39.9% 42.9% 36.6% 53.2% 51.8%
Infecund, menopausal 928 417 87 409 1655 3496
14.5% 17.2% 13.1% 13.4% 14.7% 14.7%
Total 6397 2427 664 3049 11248 23785
100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
87
Unmet need * Age 5-year groups
Age 5-year groups
15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total
Unmet
need
Unmet need to
space
332 697 918 645 479 256 167 3494
16.6% 18.5% 17.7% 15.7% 13.5% 9.5% 6.7% 14.7%
Unmet need to
limit
35 68 121 207 320 401 360 1512
1.8% 1.8% 2.3% 5.0% 9.0% 14.9% 14.5% 6.4%
Using to space 52 316 579 464 254 87 24 1776
2.6% 8.4% 11.1% 11.3% 7.2% 3.2% 1.0% 7.5%
Using to limit 0 17 60 190 355 363 210 1195
.0% .5% 1.2% 4.6% 10.0% 13.5% 8.4% 5.0%
Desire birth < 2
yrs
1487 2536 3230 2260 1617 811 371 12312
74.5% 67.5% 62.2% 55.0% 45.7% 30.1% 14.9% 51.8%
Infecund,
menopausal
91 125 287 343 516 778 1356 3496
4.6% 3.3% 5.5% 8.3% 14.6% 28.9% 54.5% 14.7%
Total 1997 3759 5195 4109 3541 2696 2488 23785
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
88
Unmet need * Wealth index
Wealth index
Poorest Poorer Middle Richer Richest Total
Unmet need Unmet need to space 910 813 685 629 457 3494
14.6% 15.0% 15.3% 15.8% 12.5% 14.7%
Unmet need to limit 276 336 333 322 245 1512
4.4% 6.2% 7.4% 8.1% 6.7% 6.4%
Using to space 126 165 279 499 707 1776
2.0% 3.0% 6.2% 12.5% 19.3% 7.5%
Using to limit 72 118 204 299 502 1195
1.2% 2.2% 4.6% 7.5% 13.7% 5.0%
Desire birth < 2 yrs 3846 3136 2312 1707 1311 12312
61.6% 57.8% 51.6% 42.9% 35.8% 51.8%
Infecund, menopausal 1013 855 664 521 443 3496
16.2% 15.8% 14.8% 13.1% 12.1% 14.7%
Total 6243 5423 4477 3977 3665 23785
100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
89
Unmet need * Type of place of residence
Type of place of residence
Urban Rural Total
Unmet need Unmet need to space 895 2599 3494
13.7% 15.1% 14.7%
Unmet need to limit 465 1047 1512
7.1% 6.1% 6.4%
Using to space 876 900 1776
13.4% 5.2% 7.5%
Using to limit 619 576 1195
9.5% 3.3% 5.0%
Desire birth < 2 yrs 2833 9479 12312
43.4% 55.0% 51.8%
Infecund, menopausal 847 2649 3496
13.0% 15.4% 14.7%
Total 6535 17250 23785
100.0% 100.0% 100.0%