DEMOGRAPHIC

AND

HEALTH

SURVEYS

DHS WORKING PAPERS

2015 No. 120

Clara Ladi Ejembi

Tukur Dahiru

Alhaji A. Aliyu

September 2015

This document was produced for review by the United States Agency for

International Development.

Contextual Factors Influencing Modern 

Contraceptive Use in Nigeria 

Contextual Factors Influencing Modern Contraceptive Use 

in Nigeria 

 

Clara Ladi Ejembi1

Tukur Dahiru1

Alhaji A. Aliyu1

ICF International 

Rockville, Maryland, USA 

September 2015 

1

Department of Community Medicine, Ahmadu Bello University 

Corresponding author: Clara Ladi Ejembi, Department of Community Medicine, Ahmadu Bello 

University, Zaria, Nigeria; Email: claraladiejembi@yahoo.com 
ACKNOWLEDGMENTS 

The authors would like to thank USAID for funding this research project, which was executed 

through the DHS Fellows Program implemented by ICF International. We are grateful to our able 

facilitators from ICF International, Wenjuan Wang and Sarah Staveteig. To the co-facilitators, 

former DHS Fellows Henock Yebyo, Adnan Juma Adinan and Anne Mwangi we thank you for 

your support, guidance and demonstration of what we too can become in the future if we apply 

ourselves. To our reviewer, Shireen Assaf, we are grateful for your careful review and comments 

that helped us improve the paper. Our appreciation also goes to Ahmadu Bello University for 

releasing us to participate in the program and the promised support towards implementation of the 

capacity building plan. To Toni Jones, who has worked tirelessly behind the scenes to organize 

the various fellowship activities, we say thank you. 

Editor: Bryant Robey 

Document Production: Natalie La Roche 

The DHS Working Papers series is a prepublication series of papers reporting on research in 

progress that is based on Demographic and Health Surveys (DHS) data. This research is carried 

out with support provided by the United States Agency for International Development (USAID) 

through The DHS Program (#AID-OAA-C-13-00095). The views expressed are those of the 

authors and do not necessarily reflect the views of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and 

evaluate population, health, and nutrition programs. For additional information about the DHS 

Program contact: DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 

20850, USA. Phone: +1 301-407-6500; Fax: +1 301-407-6501; Email: reports@dhsprogram.com; 

Internet: www. dhsprogram.com. 

Recommended citation: 

Ejembi, Clara Ladi, Tukur Dahiru, and Alhaji A. Aliyu. 2015. Contextual Factors Influencing 

Modern Contraceptive Use in Nigeria. DHS Working Papers No. 120. Rockville, Maryland, USA: 

ICF International.
iii 

ABSTRACT 

Background: Despite the acknowledged health and socioeconomic benefits of use of 

modern contraceptives, their use in Nigeria remains persistently low, with wide variations in 

pattern of use. Given Nigeria’s commitment to doubling her contraceptive prevalence within four 

years, it is imperative to investigate the mediating role of contextual factors in influencing 

contraceptive behavior, for more responsive programming. This study therefore aims to assess the 

role of contextual factors in determining use of modern contraceptives in Nigeria. 

Methods: A multilevel modelling was carried out using data from the 2013 Nigeria 

Demographic and Health Survey (NDHS) among women age 15-49. The weighted sample used in 

the analysis comprised 13,835 women of reproductive age who were married, fecund and did not 

desire a child within two years of the study, drawn from 904 clusters (enumeration areas) across 

the country. The clusters were taken as representative of communities. The outcome variable used 

in the modelling was current use of modern contraceptives. 

Results: Overall, individual and community level variables accounted for 82% of the 

variations in contraceptive use in Nigeria. Positive community-level predictors of contraceptive 

use level were the level of female autonomy, female education and access to health facilities within 

the community. Conversely, communities with higher proportions of Muslim and higher 

proportions of polygynous marriages negatively predicted use of modern contraceptives. Also, 

compared with the South West Zone, all the other zones of the country except the South Zone had 

significant lower odds of contraceptive use. Poverty and rural residence had no significant effect 

on use of modern contraceptives. 

Conclusion: Individual and community characteristics were significant predictors of use 

of modern contraceptives in Nigeria and thus these factors should be taken into account in 

programming for family planning in the country. 

Keywords: Nigeria, modern contraceptive use, contextual factors, multilevel models

1 

INTRODUCTION 

This study focuses on determining the community-level factors that influence modern 

contraceptive use in Nigeria, using multilevel analysis of the 2013 Nigeria Demographic and 

Health Survey (NDHS) data sets. Nigeria is committed to raising her current contraceptive 

prevalence rate to 36% by 2018. There is thus an urgent need to determine factors responsible for 

the persistent low coverage and the observed wide variations across the country. Recognizing that 

uptake of modern contraceptives tends to be socially and culturally nested, the findings of this 

study will be useful for retooling interventions to make them context specific, to achieve better 

results. 

Background 

Nigeria, the seventh most populous nation in the world, has a current estimated population 

of 183 million, which is projected to reach 285 million by 2050 (United Nations 2013). There are 

an estimated 35 million women of reproductive age in the country, with an annual number of births 

of approximately 7 million and annual population growth of 3.2% per annum. The country’s rapid 

population growth is attributable to a high total fertility rate (TFR) of 5.5 children per woman 

(National Population Commission and ICF International and 2014). Family planning—the ability 

of individuals and couples to attain their desired number and spacing of their children through 

contraceptive use—is one of the most cost-effective public health interventions and is pivotal to 

reducing the country’s fertility(Graff, 2014). 

Fertility decline is a means of achieving a demographic dividend, with the consequent 

potential of reducing poverty, boosting economic growth and contributing to the overall well-being 

of families and societies (Cleland et al. 2006; Graff and Bremner 2014; Gribble and Bremner 

2012). It has been estimated that in Nigeria a reduction in fertility by one child per woman would 

lead to a 13% increase in GDP per capita within 20 years (Ashraf, Weil, and Wilde 2013). While 

family planning impacts all the MDG goals, it is most directly associated with MDG 5, improving 

maternal health (Ezeh, Bongaarts, and Mberu 2012; UNFPA and PATH 2008). 

 Contraceptive use reduces the pregnancy rate, the number of unintended pregnancies and 

associated induced abortions and the proportion of high-risk pregnancies, therefore causing a 

reduction in maternal mortality and an improvement in maternal and child health. Studies have 
2 

estimated that 30% to 40% of maternal deaths (Ahmed et al. 2012; Cleland, Ndugwa, and Zulu 

2011; Collumbien, Gerressu, and Cleland 2004; Singh et al. 2009) and 90% of induced abortionrelated maternal deaths (Cleland et al. 2006) could be averted if all women who desired to use 

contraceptives had access to them. In addition, contraception makes significant contributions to 

reducing levels of infant, neonatal and under-five mortality (Tsui and ACreanga 2009). It is 

estimated that in developing countries as many as 1.8 million child deaths could be averted if all 

pregnancies were spaced by at least three years (Rutstein 2008). 

In the past few decades investments in family planning programs have raised the level of 

contraceptive use from 19% to 62% in the developing world and contributed to an estimated 75% 

decline in fertility (Greanga et al. 2011). However, despite the increase in supply of and demand 

for family planning services, gross inequities exist both between and within countries in the use of 

contraceptives, posing challenges to health policy and programming. Use of modern 

contraceptives in developing countries remains comparatively low, with West Africa having the 

lowest rates. In many countries the demand for contraceptives is still not being fulfilled. 

Worldwide, in 2010 12% of women currently married or in union who do not want any more 

children or want to postpone their next pregnancies for at least two years are not using any form 

of contraception—that is, they have an unmet need for family planning (Alkema et al. 2013). In 

developing countries an estimated 222 million women have an unmet need for modern 

contraception (Singh and Darroch 2012). The proportion of married women with unmet need for 

modern contraception is 18% in the developing world as a whole, but is much higher than average 

(30–37%) in Western Africa, Middle Africa, Eastern Africa and Western Asia, and is somewhat 

higher than average (22–24%) in South Asia and the Caribbean (Singh and Darroch 2012). 

Nigeria is yet to derive significant benefits of family planning, as her use of contraceptives 

has remained persistently low, prevalence of modern contraceptive use stagnating at 10% among 

currently married women (National Population Commission and ICF International and 2014), 

much lower than the African average. The resultant high fertility is a significant contributor to 

high maternal mortality in Nigeria. Even though Nigeria has only 2% of the global population, it 

contributes a disproportionate 14% to the global burden of 289,000 annual maternal deaths (World 

Health Organization 2014). 
3 

The context of family planning in Nigeria 

Nigeria’s family planning program began in 1964 with the National Family Planning 

Council of Nigeria (Oyediran 1969). Before the 1980s, however, family planning programs were 

not a priority for the government of Nigeria and consequently were driven by development partners 

and nongovernmental organizations. Following analysis of the consequences of unregulated 

population growth on health and development in Nigeria, starting in the late 1980s the country 

began formulating various policies aimed at improving reproductive health outcomes and reducing 

fertility levels through family planning. These include Nigeria’s national population policy, first 

enunciated in 1988 and revised in 2004. These policies focused on increasing uptake of modern 

contraceptives for health and national demographic goals (Federal Republic of Nigeria 1988). 

Targets of the first national population policy included increasing contraceptive prevalence to 80% 

and limiting the TFR to an average of four children per woman by 2000. The revised population 

policy calls for a reduction of maternal mortality by 75% by 2015, reduction of the fertility rate by 

0.6 children per woman every five years and a 2% annual increase in the proportion of women 

using contraceptives. More recently, following the 2012 London Summit on Family Planning, 

Nigeria developed a blueprint for accelerating uptake of family planning with a target of increasing 

the national contraceptive prevalence rate to 36% by 2018(Federal Republic of Nigeria 2014). 

Currently, family planning services are provided by both the public and private sectors, 

with the commodities provided free in public sector facilities. In spite of the various investments 

in family planning programs in the country, contraceptive prevalence has not shown any sign of 

increasing. According to the 2013 NDHS, while knowledge of contraceptives is generally high, 

uptake is low; only 15% of married women of reproductive age are using any contraceptive method 

and, as mentioned, only 10% are using a modern family planning method, while unmet need for 

contraception is 16% (National Population Commission and ICF 2014). The national rates have 

shown little change since 1990. Motivation to use contraceptives is low in the country, as pronatalism is one of the reasons for high fertility and low contraceptive prevalence (Federal Ministry 

of Health 2008). 

These national aggregate indicators mask wide variations in the uptake of contraceptives 

across the country. The southern zones of the country have higher contraceptive prevalence 

compared with the northern zones. The northern part of Nigeria has one of the lowest rates of 
4 

contraceptive use in the world. Across the states of the country, contraceptive prevalence ranges 

from 26% in Lagos State in South-western Nigeria to less than 1% in Jigawa and Kano States, 

North-western Nigeria. The 2013 NDHS data aggregated by zones showed wide variations in 

fertility intentions and contraceptive use. While the national total fertility rate is 5.5 children per 

woman, it ranges from 4.3 children per woman in the South Zone to 6.7 children per woman in the 

North West Zone. Use of modern contraceptives ranges from 3% in the North East Zone to 25% 

in the South West Zone. Also, the 2013NDHS showed variation in the method mix. For example 

while contraceptive prevalence was comparatively high in some of the eastern states of the country, 

contraceptive use includes more natural and traditional contraceptive methods. There are also 

variations in contraceptive use by religion, education, place of residence and socioeconomic status 

(National Population Commission and ICF International and 2014). 

In addition to the many socio-cultural drivers of high fertility, poor investment in strategic 

behavior change communication has contributed to low demand for family planning. The main 

sources of information on family planning in the country are friends or siblings, media, formal 

education and health workers (Ankomah, Anyanti, and Oladosu 2011; Monjok et al. 2010; OyeAdeniran et al. 2006). Additionally, a number of supply-related factors limit contraceptive use. 

These include erratic supply of modern contraceptives, gaps in logistics supply chain, donor 

dependence, poor-quality services and dearth of skilled health personnel to provide family 

planning services (Federal Government of Nigeria 2014). 

Variations in contraceptive use 

Wide variations exist in the pattern of contraceptive use between regions and countries of 

the world, and also at sub-national levels (Alkema et al. 2013; Dynes et al. 2012). Studies on 

reasons for the observed variations have tended to concentrate on individual and household factors. 

The findings show that a number of demographic, biological, socioeconomic and behavioral 

variables are associated with contraceptive use. 

Demographic factors influencing use of contraceptives include age, parity, marital status 

and marriage type. Women’s age has a curvilinear effect on contraceptive use, with lower levels 

of use at younger and at older ages (Njogu 1991). In Africa, sexually active single women are more 

likely to use contraceptives than married women (Adebayo et al. 2012; Caldwell, Orubukoye, and 
5 

Pat 1992). Marriage type has a mixed effect on uptake of contraceptives, which is made more 

complex by spousal age differences and inequalities between co-wives (Hertrich 2005). Polygamy 

has been associated with lower levels of contraceptive use (Johnson and Elmi 1989; Peterson 

1999). A study from Northeast Nigeria reported that women in polygamous unions are less likely 

to use contraceptives compared with women in monogamous unions (Audu et al. 2008). Polygamy, 

when coupled with youthful age at marriage and with a wide differences in age between spouses, 

may inhibit husband-wife interactions and perpetuate male dominance within the marriage (Ezeh 

1997). 

The demographic factors may be mitigated by biological and behavioral factors, such as 

fecundity, sexual activity and desire for children. African societies are pro-natalist and believe that 

children are a gift from God and are also social and economic investments; this has negative 

implications on use of contraceptives (Caldwell and Caldwell 2000). Couples and women who 

desire more children are less likely to use contraceptives (Mahmood and Ringheim 1999). Studies 

have found that an inverse relationship exists between the number of living children and use of 

modern contraceptives (Stephenson et al. 2007; Uchindi 2001; Yihunie et al. 2013). Evidence from 

a number of countries has pointed towards the partner’s disapproval and his desire for more 

children as key factors for non-use of contraception (Bongaarts and Bruce 1995). 

A strong relationship has been found between women’s education, especially completed 

primary education and entry into secondary level, and fertility reduction. Several studies have 

reported that women’s education has a strong positive impact on contraceptive use (Bawah 2002; 

Burgard 2004; Guilkey and Susan 1997; Kradval 2002). In Nigeria, education has been found to 

increase contraceptive use (Oye-Adeniran et al. 2006). Nigerian women with tertiary level 

education are one-and-a-half times more likely to have ever used contraception than women with 

secondary education (Asekun-Olarinmoye et al. 2013). Partner’s level of education is equally 

important, as it may operate through many of the same pathways (childbearing preferences) as the 

woman’s own education, given that education levels of husbands and wives are positively 

correlated (Malwade 2002). A study from Nigeria showed that the likelihood that a woman and 

her partner were using contraception was higher if at least one partner had a primary or higher 

education than if both had no education (Ibisomi 2014). However, women who are more educated 

than their husbands tend to use contraceptives more than women who are not as educated as their 
6 

husbands (Stephen and Enoch 2014). Level of education is a predictor of socioeconomic status, 

which correlates with contraceptive use. Thus, women of lower socioeconomic status have lower 

uptake rates of contraceptives (Acharya 1998; (Ibisomi 2014; Shah, Shah, and Radovanovic 1998; 

Stephenson and Tsui 2003). 

Independent of socioeconomic factors, knowledge of contraceptives is a determinant of 

contraceptive use. Exposure to mass media has strong effects on attitudes towards family planning 

through ideation, which has been found to contribute to observed fertility decline (Cleland and 

Christopher 1987). Evidence from a number of studies reveals that exposure to mass media 

messages promoting family planning may affect contraceptive behavior (Jato et al. 1999; Kane et 

al. 1998; Storey et al. 1999).In Nigeria, use of modern contraceptives, the intention to use them 

and desire for fewer children were found to be associated with exposure to media message about 

family planning (Bankole, Rodriguez, and Westoff 1996). 

Contextual factors and contraceptive use 

After accounting for the effects of individual and household factors, variations in 

contraceptive use still persist. There is thus an increasing call for health researchers to begin to 

focus on examination of how individual-level variables interact with group-level variables to cause 

health and disease (Diez-Roux 1998). Since individuals live in communities, communities 

evidently influence personal health behavior, as there are usually intersections between personal 

beliefs and attitudes and community norms. With regard to contraceptive use, women must 

navigate community norms to fulfill their ideals in terms of fertility and contraceptive decisionmaking (Colleran and Mace 2015). The community influences an individual’s use of 

contraceptives through multiple pathways: socioeconomic characteristics of the community, 

presence of health facilities and infrastructure and prevailing attitudes and behavior. Consequently, 

within the reproductive health field attention is now shifting to examining the role of contextual 

factors in explaining the observed variations in contraceptive use, with increasing attention being 

given to the role of the community in shaping reproductive health behavior of individuals, 

including contraception behavior (Dynes et al. 2012). 

In recent times, a number of studies have attempted to investigate the role of contextual 

factors in contraceptive use in African countries (Bogale et al. 2011; Dynes et al. 2012; Elfstrom 
7 

and Stephneson 2012; Kaggwa, Diop, and Storey 2008; Wang et al. 2013). The growing body of 

knowledge has identified a number of contextual factors that influence contraceptive use; they 

include presence and quality of reproductive health services, macroeconomic factors, community 

fertility norms, female autonomy, and availability of physical infrastructure. 

These studies suggest that considerable gains in understanding determinants of 

contraceptive use could be made from studying contextual influences, as they have demonstrated 

that, beyond individual and family factors; the context in which women live also influences their 

contraceptive decisions. They posit that a greater understanding of the contextual factors 

associated with modern contraceptive use has the potential to inform the development of 

community-level programs aimed at increasing contraceptive use and to allow for better targeting 

of programs to align with communities (Elfstrom and Stephneson 2012). 

In Nigeria, not much is known about how community characteristics affect contraceptive 

use among married women and about the causes of the observed variations by various 

characteristics across the zones of the country. There is a dearth of literature on contextual factors 

influencing contraceptive use in Nigeria. Few studies using multilevel modeling techniques 

identified contextual factors associated with contraceptive use but they are limited in the number 

of factors investigated. The study by Aremu was limited to determining contextual factors 

influencing choice of family planning provider and method choice (Aremu 2013). In a study by 

Omotola the contextual factors were limited to comparison of contraceptive uptake between the 

northern and southern parts of the country across a number of variables (Omotola 2013). We do 

know that wide variations exist in socioeconomic and cultural characteristics even within the two 

broad zones of the country, and grouping them as homogenous entities may mask these 

differences. A study by Ibisomi was limited to examining the effect of spousal age difference on 

contraceptive use (Ibisomi 2014), while Adebayo et al. examined variation in use of contraceptives 

with a focus on marital status (Adebayo et al. 2012). 
8 

Research Questions and Hypothesis 

The research question is, beyond individual and household factors, what community 

factors shape use of modern contraceptives in Nigeria? 

The main hypothesis is there is an association between community factors and use of 

modern contraceptives in Nigeria. 

The other hypothesis is that significant differences exist in contraceptive modern use across 

communities in Nigeria. 

Significance of the Study 

Nigeria has an ambitious target of more than doubling her contraceptive prevalence rate 

with four years (2014 – 2018), from 15% to 36%. This is against a backdrop of persistently low 

and stagnating contraceptive use. For effective policy implementation, the need to determine 

factors responsible for low coverage and the observed wide variations across the country is not 

only imperative but urgent if better results are to be achieved. 

In terms of policy and programming implications of the proposed study, we believe that 

presence of community-level effects on contraceptive uptake, if identified, will indicate the need 

for changes in family planning programming that will factor in community and service delivery 

characteristics (e.g., health campaigns, number and type of services), with positive influences on 

program and maternal health outcomes for whole communities. 

Conceptual Framework 

Figure 1 shows the conceptual framework for this study. The contextual factors indirectly 

influence fertility by acting on the proximate or intermediate (individual and household) 

determinants at different levels to influence a woman’s use of contraception. All the contextual 

factors either function independently or through their influences on the individual factors selected 

to influence use of modern contraceptives. 
9 

Figure 1. Conceptual framework 

Socioeconomic development 

The contextual regions used in this study were based on geo-political zones of the country, 

which was used by NDHS 2013. They are categorized into North West, North Central, North East, 

South West, South East and South zones based on the premise that they may have a strong 

relationship with contraceptive use since there are wide differentials in poverty levels, education, 

religion and infrastructural development across the zones. Place of residence is associated with 

contraceptive use. The DHS surveys have consistently showed that use of contraceptives is higher 

among women living in urban areas compared with women in rural areas. This is because urban 

areas in sub-Saharan Africa are associated with higher infrastructural development, better 

education and easier access to public and private medical care and services. However, while some 

contextual studies have found an association between residence and use of contraceptives (Yihunie 

et al. 2013), others have found no significant association (McNay, Arokiasamy, and Cassen 2003). 

Fertility Norms

Fertility preferences

Prevalence of polygynous 

unions

Socioeconomic Development

Region, Urban/Rural residence 

Community poverty level 

Religion

Female Empowerment

Spousal age difference

Female educational 

attainment

Ratio F:M employed

Women's control over HH

decision-making

Access to Family Planning 

Information & Services

Exposure to media messages 

on family planning

Access to any health care

Socio-demographic 

Characteristics

Age, Parity, Religion, 

Education (M&W), HH Wealth, 

Type of marriage, Past 

experience of child mortality

Fertility Preference

Desire for children

Access to Family Planning 

Information & Services

Exposure to media messages 

on family planning

Access to any health services

Modern

Contraceptive 

Use
10 

Household socioeconomic status and the community’s overall level of economic prosperity 

could impact women’s contraceptive use through several pathways. DeGraff et al reported that the 

presence of family planning services and community labour-market conditions and infrastructural 

development were strong influences on contraceptive use in the Philippines (Degraff, Bilsborrow, 

and Guilkey 1997). Other studies have examined the influence of community economic 

development (Diez-Roux 1998; Nazzar et al. 1995; Stephenson and Tsui 2002; Stephenson, Beke, 

and Tshibangu 2008) and of levels of school participation (Degraff, Bilsborrow, and Guilkey 1997) 

on contraceptive use. Other community-level measures of socioeconomic development have 

included the percentage of women with access to piped water (Kaggwa, Diop, and Storey 2008) 

and habitat type (Stephenson et al, 2007). However, these factors were not found to be 

determinants of contraceptive use. Others have used the community level of poverty, household 

amenity index as a proxy for level of economic development of a community and found an 

association (Clements et al. 2003, Elfstrom and Stephenson 2012). 

 The impact of religion on contraceptive use is mixed. One perspective is that, irrespective 

of religious affiliation, people with the same socioeconomic and demographic characteristics 

should have similar fertility limitations and practices (Goldsheider and Mosher 1998) while others 

emphasize the independent effect of religion on contraceptive use (Heaton 2011). Generally, 

studies have demonstrated lower contraceptive use and higher fertility among Muslims compared 

with Christians (Heaton 2011). Studies in Nigeria have also demonstrated lower use of 

contraceptives among Muslims (Obasahon 2015; Wusu 2014). 

Female empowerment 

Women’s education, a key measure of female empowerment, is a powerful correlate of 

contraceptive use (Larsson and Stanffors 2014). Studies have shown that the average community 

level of women’s education or literacy is associated with reproductive behaviour, including family 

planning, beyond contributions of individual level of education (Kravdal 2000, 2002). However, 

female empowerment is more than just education. It fundamentally has to do with agency and 

control over decision-making and choices. The DHS surveys collect information on various 

aspects of decision-making: economic decision-making, household decision-making and female 

mobility. Using these dimensions, higher levels of contraceptive use have been found to be 

associated with joint decision-making in these areas (Bogale et al. 2011; Do and Kurimoto 2012; 
11 

Elfstrom and Stephneson 2012; Feyisetan 2000; Hameed et al. 2014; Wang et al. 2013). A study 

among the Yorubas in Nigeria found a positive association between female empowerment and 

contraceptive use among older women (OlaOlorun and Hindin 2014). However, another study in 

Ethiopia found that, even though women make joint decisions with their husbands, they defer to 

them for the final verdict (Bogale et al. 2011). This may reflect lack of empowerment in other 

areas of their lives. A study of contextual influences on contraceptive use in 20 African countries 

found no association between contraceptive use and female empowerment (Elfstrom and 

Stephenson 2012). Another measure of empowerment is economic independence. Women who 

work for cash have been found to more significantly communicate with their spouses about family 

planning, thus increasing the likelihood of contraceptive use (Gage 1995). 

Spousal age difference is taken as a measure of gender inequality (Barbieri and Hertrich 

2002). Large age differences are often accompanied by differences in maturity, life experiences, 

social position and financial resources, which may make spousal relationships inherently unequal 

and a source of risk for women’s health (Darroch, Landry, and Oslak 1999; Luke 2005). The 

younger the wife is compared with her husband, the less her autonomy, limiting her ability to 

communicate with her spouse, challenge gender norms and adopt new practices (Barbieri and 

Hertrich 2002). This has implications for contraceptive use. However, research has provided mixed 

results; some studies have found an inverse relationship between spousal age difference and use 

of contraceptives (Barbieri and Hertrich 2002), while others have shown a lack of association 

(Ibisomi 2014). 

Fertility norms 

At the individual level, decisions are generally shaped by perceived prevailing attitudes 

and behaviours of other members of the community (Rimal and Real 2003; Colleran and Mace 

2015). Thus, community norms regarding the family and family planning are likely to impact 

women’s own attitudes, and ultimately influence their family planning behaviours (Bongaarts and 

Bruce 1995; Nazzar et al. 1995). Men and women can be influenced even more by their perception 

of community norms than by their personal preferences concerning their ideal number of children 

and contraceptive use. However, some studies have reported mixed findings. Kaggwa et al. 

reported that in Mali, after controlling for individual-level factors, they found no evidence that 

women’s use of modern contraceptives was impacted by community norms and desired family 
12 

size (Kaggwa, Diop, and Storey 2008; Nazzar et al. 1995). In contrast, Stephenson et al., after 

controlling for individual and other community factors, found that in four of six countries studied 

the percentage of women in the community who approved of family planning was positively 

associated with women’s own use of modern contraceptives (Stephenson et al. 2007). Also, a study 

in Kenya found that women whose number of living sons was lower than their perceived 

community norms were less likely to use contraceptives (Dynes et al. 2012). 

Also, family size preferences—an indicator of the demand for children—has been shown 

to be a measure of motivation to consciously limit fertility through use of contraceptives 

(Mahmood and Ringheim 1999). Husband’s demand for children is significantly related to the 

wife’s desired fertility and the couple’s fertility outcome. In Nigeria, women whose spouses desire 

more children have been found less likely to use contraceptives (Bankole and Singh 1998). Among 

the Yoruba in Nigeria, the fertility desires of both partners are important predictors of the couples’ 

fertility. Whereas the husband’s preferences are dominant in predicting the couple’s behaviour 

when the number of children is small, the wife’s becomes more important as the number of living 

children grows (Uchindi 2001). 

Access to family planning information and services 

Access to family planning information can enhance uptake of services. Most studies have 

shown that community-level exposure to family planning media messages increases the odds of 

contraceptive use (Bankole, Rodriguez, and Westoff 1996; McNay, Arokiasamy, and Cassen 2003; 

Stephenson et al. 2007; Wang et al. 2013). However, in a study of contextual factors influencing 

contraceptive use in 21 African countries, Elfstrom et al. found that exposure to media messages 

was positively associated with contraceptive use in only two countries, while the effect was 

negative in one country (Elfstrom and Stephenson 2012). 

 Expanding access to effective, accessible, acceptable and good-quality family planning 

services is critical to its uptake, especially clinical contraception. The majority of research on 

access to health care services has tended to focus on one dimension of access, geographical access. 

This refers to either the distance to service delivery points, which is measured by either the density 

of service delivery points in a given area or the time it takes to get to the service delivery point. 

Studies have found that access to family planning services increases the likelihood of contraceptive 

use, so also availability of family planning commodities (Wang et al. 2013). Stephenson et al. 
13 

(2007) reported that the presence of family planning services and community labour-market 

conditions and infrastructural development were strong influences on contraceptive use in the 

Philippines (Degraff, Bilsborrow, and Guilkey 1997). Other studies have examined the influence 

of community economic development (Diez-Roux 1998; Nazzar et al. 1995; Stephenson and Tsui 

2002; Stephenson, Beke, and Tshibangu 2008) of levels of school participation (Degraff, 

Bilsborrow, and Guilkey 1997) on contraceptive use. Other community-level measures of 

socioeconomic development have included the percentage of women with access to piped water 

(Kaggwa, Diop, and Storey 2008) and habitat type (Stephenson et al. 2007). However, these factors 

were not found to be determinants of contraceptive use. Others have used the community level of 

poverty, household amenity index as a proxy for level of economic development of a community 

and found an association (Clements et al. 2003; Elfstrom and Stephneson 2012). 

DATA AND METHODS 

Study Setting 

Nigeria’s population of 183 million people is spread across 774 Local Government Areas, 

which are grouped into 36 States plus the Federal Capital Territory. These states are further 

grouped into six geopolitical zones, the North West, North East, North Central, South East, South 

West and South zones. More than half (54%) of the population resides in the rural areas. The 

population is made up of 50% Muslims, 40% Christians and 10% traditional religionists. An 

estimated 57% of females are enrolled in school (primary, secondary or tertiary) compared with 

71% males. Even though Nigeria is said to have the largest economy in the Africa, with a per 

capita GDP of $2,710, the poverty level is high and an estimated 62% of Nigerians live below the 

poverty line 

Wide differences exist between the northern and the southern parts of the country and 

across the zones of the country in terms of levels of socioeconomic development, cultural 

practices, availability and access to health care services and use of contraceptives. The southern 

population is made up of mainly Yoruba in the South West and Ibo in the South East as the 

predominant Christian ethnic groups, while the majority of the North consists of Hausa/Fulani 

Muslims. As one moves from the more affluent and educated southern parts of the country to the 
14 

northern parts, the level of education declines and poverty levels deepen, so also availability of 

health services and their use. 

Data Source 

The data for this study come from the 2013 Nigeria DHS. The 2013 NDHS was the fifth 

in the series of surveys that have collected demographic and health information for program 

planning, implementation and monitoring. The survey used a three-stage cluster sampling design 

and covered all the states in the country. The sampling design was based on the 2006 census, where 

the enumeration areas served as the primary sampling unit (PSU). A total of 904 clusters (PSU) 

were sampled during the 2013 NDHS: 372 in urban areas and 532 in rural areas. About 20-30 

households were randomly selected in each cluster, yielding a representative sample of 40,680 

households. All women age 15-49present either as a permanent resident or as visitor in the 

household the night before the survey were eligible for the interview. The survey used basically 

three types of structured questionnaires: the Household Questionnaire, Woman’s Questionnaire 

and Man’s Questionnaire. The Household Questionnaire listed all usual household members and 

visitors to the sampled households; additional basic information collected was on the 

characteristics of each person listed, including age, sex, marital status, education and relationship 

to the head of the household. The Woman’s Questionnaire collected information on background 

characteristics, reproductive history, childhood mortality, knowledge and use family planning 

methods, fertility preferences, antenatal, delivery and postnatal care, female empowerment and a 

host of other health issues relating to specific diseases and disease-prevention 

programs/interventions. The Man’s Questionnaire is similar to the Woman’s Questionnaire except 

that it is shorter. At the end of the exercise, 99%, 98% and 95% response rates were recorded, 

respectively, for households, women and men [National Population Commission and ICF 2014]. 

Similar to its predecessors, the 2013 NDHS collected information on knowledge and current use 

of contraceptives among 38,948 eligible women. 

Sample derivation 

For the purpose of this analysis only married women considered to have a need for 

contraceptives were included in the sample—that is, the eligible respondents comprised only 
15 

married, fecund women who did not desire any children in the next two years. The final weighted 

sample size comprised 13,835 women. The sample size derivation is shown in Figure 2. 

Figure 2. Sample derivation flow chart 

Key Variables and Measurements 

Dependent variable: The dependent variable is current use of any modern contraceptive 

among the sub-sample of women. This is a binary variable and women were categorized into those 

using a modern contraceptive method (oral pills, injectables, male or female condoms, intrauterine 

devices, male or female sterilization, lactational amenorrhea) and those not using any 

contraceptive method or using periodic abstinence, withdrawal, or other traditional family 

planning methods. 

Independent variables: The individual-level and community-level explanatory variables 

selected for this analysis were drawn from DHS data, based on the literature review; they are 

outlined in our conceptual framework. The independent variables are broadly classified into two 

All women of reproductive age 

group = 38,948

Women in reproductive age 

group, married = 27,272

Women in reproductive age 

group, married, fecund = 

26,475

Women in reproductive age 

group, married, fecund & not 

pregnant = 22,150

Women in reproductive age 

group, married, fecund & desire 

no children in next 2 years = 

14,090*

Excluded

Not married 

11,676

Infecund

797

Pregnant

4,325

Desire 

children in 

next 2 years.

8,060

Women in reproductive age 

group, married, fecund, desire 

no children in next 2 years & 

not pregnant = 14,090* 
16 

main groups in line with our multilevel analytic approach: individual-level variables and 

community-level variables. 

Individual-level variables 

The individual-level variables are: age of woman at time of survey, household wealth 

index, highest level of educational attainment of the woman and that of her partner, parity, type of 

marriage, and exposure to media messages on family planning. Table 1 provides an operational 

definition and coding of these variables. 

Community-level factors 

The 2013 NDHS data had identifiers for the primary sampling units (PSU) where each 

respondent resided. Each PSU had between 20 and 30 households. For the purpose of this study, 

the PSU were considered to be representative of the community, and contextual factors were 

assessed at community level, derived from the DHS data by averaging individual-level values for 

each cluster.

The community-level factors are considered as the contextual factors operating within the 

communities in which individuals (women) live, determining community norms, which may in 

part shape women’s knowledge, attitudes and contraceptive use beyond individual traits and family 

composition. In this analysis we first calculated the community-level value for each variable and 

compared it with the national median value to categorize communities into high-level and lowlevel groups. In aggregating the individual values, we constructed a non-self-average by excluding 

the reference woman, since she cannot influence her own behavior and practice but could be 

influenced by others in her community. This procedure was applied for all the nine communitylevel factors except residence and geopolitical zone, which were directly collected in the survey. 

These community-level variables (from aggregation of individual characteristics) are :the 

community-level proportion of women with secondary education or more; the proportion of 

women in the communities who are involved in decision-making with respect to their own health 

care, household goods purchases and visitation to family; the proportion of women who were 

exposed to family planning messages in the media; the proportion of women who have access to 

health facilities in the community; the proportion of Muslims in the community; the proportion of 

women in the community who are in the middle or lower wealth quintiles; the proportion of women 
17 

in the community in polygynous marriages and the ratio of females-to-males working. We used 

the work of Yebyo and colleagues to guide the construction of the majority of these communitylevel variables (Yebyo, Gebreselassie, and Kahsay 2014). 

Community-level education: This is the average educational attainment of women in the 

community. From the survey data, number of years of formal education was obtained for each 

woman. The median years of formal education was computed for all women sampled; this was 

taken as the national aggregate. From the 2013 NDHS, the median years of female education was 

5.6 years. Clusters were classified as having lower or high levels of female education if their 

median level of female education was lower or higher than the national value, respectively. 

Community-level poverty: The survey classified households into five categories of 

wealth index. The composite median wealth index was computed for each community (cluster), 

and also a national value was derived. The median national wealth index was 3.1. Communities 

were classified as having lower or high poverty in relation to the national median value. 

Community-level prevalence of Muslims: This is a binary variable at the individual level 

but aggregated at the community level as follows: from national distributions of Muslims in 

clusters or communities, a benchmark ratio of 0.5 of cluster distribution of the Muslim population 

was taken as our cut-off point. Communities or clusters with less than 0.5 population of Muslims 

were classified ‘lower Muslim cluster’ while those with more than 0.5 were classified as ‘higher 

Muslim cluster’. 

Community-level prevalence of polygyny: This is also a binary variable at the individual 

level, and clusters are classified as having either a lower proportion of polygynous marriages or a 

higher proportion, based on cluster distribution of the type of marriage. Communities or clusters 

with 4% or less were classified ‘lower polygyny cluster’ while those with more than 4% or more 

were classified as ‘higher polygyny cluster’. 

Community-level of women’s autonomy: This is also a composite variable measuring 

women’s involvement in three dimensions of decision-making ability in their households: 

involvement in decision-making on her own health care, on large household purchases and on 

visitation to family and relatives. A woman is considered to have some level of autonomy if she 

alone or jointly with her partner makes decision on these three dimensions of autonomy; otherwise 
18 

she is considered to have no autonomy. A single index of autonomy was therefore generated using 

the proportion of women with high autonomy as the reference category compared with those with 

lower autonomy. 

Community-level ratio of women-to-men employed: Adopting a similar approach as for 

community-level proportion of Muslims, a ratio of women-to-men employed at the community 

level was also derived. Communities with a ratio of less than 0.5 were classified as ‘lower work 

ratio’, while those with work ratio of more than 0.5 were classified as ‘high work ratio’. However, 

this benchmark figure is arbitrary. 

Community-level access to health facility: In the absence of service delivery points in 

the DHS survey data, and recognizing the limitations of linking service delivery data with 

demographic survey data (Wang et al. 2014), we used visit to a health facility within 12 months of 

the NDHS survey as a proxy for service availability. Use of a health facility by a woman in the 12 

months preceding the NDHS survey was taken as a proxy for access to health services, including 

family planning. It is assumed that there is a health facility in the neighborhood/cluster that will 

warrant use. We also assumed that there are no barriers or only limited barriers to use of health 

facilities by the women and that women residing in a cluster or neighborhood will make use of the 

health facility. Thus, community-level access was constructed based on the use of health facility 

in the previous 12 months, classified as having access or no access. 
19 

Table 1. Definition of individual and community variables used in the analysis 

Variables Definition and Coding 

Individual and household variables 

Age of respondent Self-reported age of respondent at time survey coded as 1=15-19; 

2=20-29; 3=30-39; 4= 40-49 

Maternal educational attainment Highest educational level attained (none=0; primary=1; secondary and 

more =2) 

Husband’s educational attainment Highest educational level attained (none=0; primary=1; secondary and 

more =2) 

Parity Number of children given birth (None=0; 1-2=1;3-4=2;5+=3) 

Marriage type Monogamy =1, polygyny=2 

Wealth index Household wealth index (poorest =1; poorer =2; middle =3; richer=4 

richest =5. 

Media Exposure to FP messages Media exposure were radio, television and newspaper. Exposed to none 

=0; exposed to at least one =1; exposed to at least 2 = 2; exposed to all 

3=3 

Desire for children Partner wants same number of children as woman =1; partner wants 

more children than woman =2; partner wants fewer children than woman 

=3; don’t know =4 

Age difference between partner and 

woman 

woman older or same age =0; man older<10years = 1; man older> 10 

years = 2 

Community-Level Variables 

Geopolitical zone Geopolitical zone of residence (North Central=1, North East=2, 

NorthWest=3, South East=4, SouthSouth=5, SouthWest=6) 

Place of residence Current place of residence (rural=2, urban=1) 

Community level of female 

autonomy 

Coded as low=0, high=1 

Community level of poverty Coded as low=0, high=1 

Community level of education Coded as low=0, high=1 

Community level of women in 

polygynous marriages 

Code as low =0; high =1 

Community level of access to health 

facilities 

Coded as low=0, high=1 

Community level of exposure to 

media messages on 

contraceptives 

Coded as low=0, high=1 

Community level of monogamous 

marriage 

Coded as low=0, high=1 

Community level of Muslims Coded as low=0, high=1 

Community level of ratio of femaleto-men employment Coded as low=0, high=1 

Statistical Analysis 

Data analyses were performed at univariate, bivariate and multivariate levels. At the 

univariate level, frequencies and percentages of background characteristics were generated. At the 

bivariate level, background characteristics were cross-tabulated with use/non-use of contraceptives 

and associations tested using Chi square tests. At the multivariate level of analysis, a two-level 

multivariate logistic regression was fitted to examine, first, the relationship between the individual 

attributes and contraceptive use and, secondly, the effects of community-level aggregate factors 

on contraceptive use. The structure of the 2013 NDHS data allows for the application of multilevel 
20 

logistic regression, since the respondents (women) are nested within households that are further 

nested within clusters (or communities). Therefore, to assess the effects of both women’s 

individual characteristics and cluster (or community) characteristics on contraceptive use, a twolevel mixed logistic regression model is most appropriate and was thus fitted. 

Multilevel mixed effects logistic model has two parts: fixed and random. In a simplified 

model, the equation is of the form (Goldstein 2003). 

Log 















− ij

ij

π

π

1

= β0 + β1X1ij + ....βnXnij + u0j

Where, 

πij is the proportion of women who currently using modern contraceptive 

(1-πij) is the proportion not using modern contraceptive 

β0 is the intercept coefficient 

β1, ... βn are the coefficients of individual and community-level factors 

X1ij... Xnij are independent variables of individuals and communities 

u0j are random errors at cluster levels 

The effects of the fixed part of the model were measured by the odds ratio; while the 

contribution of the random part of the model (u0j) was assessed using intra-cluster correlation 

coefficient (or ICC). The odds ratios were derived by running logistic regression controlling for 

confounders. ICC is defined as the ratio of the between-cluster variance to the total variance (both 

between and within clusters), and therefore has a value between 0 and 1. It measures the relatedness 

of elements within the clusters, and an ICC of ‘0’ indicates that individuals within clusters are no 

more similar to each other than individuals from different clusters (there is no between-cluster 

variability), while an ICC of 1 indicates that individuals within the same cluster all have identical 

outcomes (there is no within-cluster variability or the individuals are homogenous (Killip, 

Mahfoud, and Pearce 2004). Mathematically, it is the ratio between cluster variability and total 

cluster variability (i.e., between-cluster and within-cluster variability). Thus, it is represented by 

rho (ρ): 

ρ = ( ) 22

2

wb

b

ss

s

+ . 
21 

Where 2

b S is variance between clusters and 2w S is variance within clusters. This equation 

can also be represented as follows: 

ρ= ( ) 3/ 22

2

πσ

σ

u +

u

Where σu2

 is the variance between clusters and π2/3 is the variance within clusters. It is 

assumed that within-cluster variability (that is, variation among the women within the cluster) is 

constant, estimated at π2/3 or 3.29. Proportional change in variance (PCV) is a measure of the 

contribution of cluster effect on women’s contraceptive use—that is, how much influence the 

cluster characteristics have on women’s contraceptive use. It is calculated using the ‘empty’ or 

‘null’ model as a reference model. It is mathematically computed as: 















 − =

e

mie

V

VV PCV

Where, 

Ve is the variance in woman’s use of contraceptives in empty model 

Vmi is the variance in woman’s use of contraceptives in model mi (or the subsequent 

model) 

To assess the effects of cluster variability on current use of contraceptives, we used Stata 

multilevel analysis command merqlogit. Four models were fitted as follows: 

Null model (Model 0): This is also called the empty model, since no factors were included in the 

model. It is aimed at testing the random effect of between-cluster variability. 

Model I: This model has only the individual-level variables included, thus it measures only the 

effect of individual characteristics on contraceptive use 

Model II: This model contains the community-level factors. It thus assessed the effects of 

community factors as they influence contraceptive use. 

Model III: This model has both the individual-level variables and community-level factors 

concurrently to determine their combined fixed and random effects on the use of contraceptives. 

This model was built sequentially by adding one community-level variable at a time in order to 
22 

avoid potentiality of collinearity with other variables and to see if addition of community-level 

variables improves the model. (With these, community-level access to media messages on 

contraceptives was dropped in the final model because of collinearity.) Also, variance inflation 

factors were estimated to assess risk of multicollinearity between variables. All analyses were 

conducted using Stata version 13 (StataCorp). 

RESULTS 

Background Characteristics of Individuals and Clusters 

Individual level 

We analyzed data from the 2013 NDHS on a subset of 13,835 fecund women of 

reproductive age who do not desire children in the two years following the survey. Table 2 presents 

the background characteristics of the sample analyzed. Except for age 15-19, the population 

appeared evenly distributed across other groups, with 72% below age 40. A majority of women 

had formal education (57%), were in monogamous marriages (69%) and were Islam by religion 

(54%). The population is characterized by high parity, with 48% of the women having more than 

five children. A third of the husbands (36%) had no formal education, and 39% of the women were 

in the lowest two household wealth quintiles. All but 1.5% of the women had spouses who were 

older than themselves, with 46% having a spousal age difference of more than 10 years. About a 

third (36%) of the women and their husbands desired the same number of children, while 36% of 

the husbands wanted more children than their wives. Almost two-thirds of the women (63%) 

reported no exposure to family planning messages from television, radio or newspapers within a 

few months of the survey. 
23 

Table 2. Percent distribution of currently married women age 15-49 who were fecund but desiring 

no children in next two years by background characteristics, Nigeria 2013 DHS 

Background characteristics Percent 

Number of 

women 

Age 

15-19 4.7 657 

20-29 32.8 4541 

30-39 34.2 4730 

40-49 28.2 3907 

Education of woman 

No education 43.0 5954 

Primary 21.7 3006 

Secondary and higher 35.2 4875 

Education of man* 

No education 35.5 4910 

Primary 19.9 2756 

Secondary and higher 44.6 6168 

Wealth index 

Poorest 19.9 2758 

Poor 19.3 2674 

Middle 18.7 2586 

Rich 20.5 2838 

Richest 21.5 2979 

Marriage type 

Monogamy 68.7 9504 

Polygyny 31.3 4330 

Religion 

Christianity 44.6 6176 

Islam 53.8 7447 

Traditional/others 1.5 211 

Age difference 

Woman same age or older than man 1.5 338 

Man older by < 10years 51.6 7143 

Man older by ≥10years 45.9 6354 

Parity 

None 1.3 172 

1-2 22.1 3052 

3-4 28.2 3908 

5+ 48.4 6702 

Exposure to media messages on FP

Not exposed 63.3 8759 

Exposed to at least one media 17.0 2359 

Exposed to at least two media 14.3 1975 

Exposed to all 5.4 743 

Desire for children 

Both desire same number 36.2 5014 

Husband desires more 35.6 4923 

Husband desires fewer 4.4 612 

Don’t know 22.3 3081 

Missing 1.5 206 

Total 100.0 13835 

*Missing and don’t know values merged 
24 

The cluster was the unit of analysis at this level and there were a total of 904 clusters 

sampled for the 2013 NDHS. Table 3 gives a distribution of the community-level characteristics. 

About two-thirds of the clusters were rural. There was an almost even distribution of proportions 

of clusters with higher and lower levels of education, wealth, level of female autonomy, access to 

health services and female-male work ratio. Slightly more than half of the clusters (53%) had a 

higher than national average proportion of Muslims and the same proportion had access to health 

facilities (53%). However, marked disparity was found in the proportional distribution of clusters 

with higher levels of polygamy (88%). 

Table 3. Percent distribution of clusters by community-level characteristics, Nigeria 2013 DHS 

Community-level variables Percentage 

Place of Residence 

Urban 37.5 

Rural 62.5 

Region 

North Central 17.6 

North East 18.0 

North West 23.7 

South East 8.9 

South 14.4 

South West 17.5 

Education 

Lower 52.6 

Higher 47.4 

Wealth index 

Lower 50.0 

Higher 50.0 

Religion (% of Muslims) 

Lower 46.9 

Higher 53.1 

Access to health facilities 

No access 47.0 

Have access 53.0 

Type of marriage (% Polygamy) 

Lower polygamy 12.0 

Higher polygamy 88.0 

Level of female autonomy 

Low 52.2 

High 47.8 

Work ratio (Female-to-Male) 

Low 49.9 

High 50.1 
25 

Modern Contraceptive Use by Individual and Community Factors 

Overall, 26% of the women were using any method of contraception, with 17% using a 

modern method and 9% using traditional means (Figure 3). 

Figure 3. Contraceptive prevalence rate by method type, Nigeria 2013 DHS 

Figure 4 depicts the method mix of modern contraceptives; injectable contraceptives 

appear to be the most popular, used by 6% of the women, followed by condoms and oral pills, at 

3% each. Use of permanent methods, notably sterilization, was negligible. 

25.6%

16.5%

9.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

Any method Modern method Traditional method
26 

Figure 4. Percentage of women who used different types of contraceptive method, Nigeria 2013 DHS 

At the individual level, socio-demographic differentials in use of modern contraceptives 

were evident, and the degree of association for these background characteristics was tested using 

X2

 tests. All of the socio-demographic characteristics tested were found to be statistically 

significantly associated with use of modern contraceptives, at p <0.000 (Table 4). 

As Table 4 shows, use of modern contraceptives increases with women’s age, from 4% at 

age 15-9 to 17% at age 40-49. Being Christian, being in a monogamous relationship and having 

two to four children were all significantly associated with higher rates of use of modern 

contraceptives (p <0000). Education of the woman and her spouse were all found to be 

significantly associated with use of modern contraceptives (p <0.000). The prevalence of 

contraceptive use increased with increase in the level of education of women and their husbands. 

Women and men with secondary school and above level of education were eight and six times, 

respectively, more likely to use contraceptives compared with women and men with no formal 

education. The wealth index was also found to be significantly associated with use of modern 

contraceptives; as wealth quintile increased, use of modern contraceptives increased (p <0.000) 

Women in the highest wealth quintile were 17 times more likely to use modern contraceptives 

5.7

3.4

3.2

2.0

1.5

0.8 0.7 0.7

0.2 0.1 0.02

Injectables Male condom Pill IUD Others* LAM Sterilization Implants SDM Diaphragm Female

condom

CPR(%)

SDM is standard days methods
27 

compared with women in the lowest wealth quintile, from 2% for women in the lowest quintile to 

35% for women in the highest quintile. 

There was an inverse association between spousal age differences and the level of 

contraceptive use: the wider the age gap between the woman and her partner, the lower the rates 

of modern contraceptive use. Women who were older than or the same age as their spouses had 

significantly higher rates of modern contraceptive use, with the lowest level of use among women 

whose husbands were older by more than 10 years. (p <0.000). Also, the level of convergence of 

desire for children between spouses was significantly associated with use of modern contraceptives 

(p <0.000). Where the husband wanted fewer children than the wife, or wanted the same number 

of children, the level of modern contraceptive use was higher than when the husband wanted more 

children than the wife. 

The level of exposure to media messages on family planning was significantly associated 

with use of modern contraceptives (p <0.000). Use of modern contraceptives increases from 10% 

for women not exposed to any media messages on family planning to 34% for women exposed to 

messages from at least two media sources and 38% for women exposed to messages from all three 

types of media sources. 
28 

Table 4. Percent distribution of currently married, fecund women age 15-49 not desiring children by 

contraceptive method currently using, according to individual characteristics, Nigeria 2013 DHS 

Individual characteristics 

Type of contraceptives used Chi-squared test 

None/traditional/

folkloric method

Modern 

method X2 value p value 

Age 177.6 0.000***

15-19 96.1 3.9

20-29 86.4 13.6

30-39 78.7 21.3

40-49 83.1 16.9

Education, woman 1300.0 0.000***

No Formal Education 96.4 3.6

Primary Education 79.8 20.2

Secondary and Above 70.5 29.5

Education, Man 967.0 0.000***

No Formal Education 96.4 3.7

Primary Education 82.2 17.8

Secondary and Above 74.1 26.0

Missing/DK 89.8 10.2

Wealth 1300.0 0.000***

Poorest 97.9 2.1

Poorer 93.1 6.9

Middle 84.3 15.7

Richer 77.4 22.6

Richest 65.2 34.8

Type of Marriage 172.8 0.000***

Monogamous 80.4 19.6

Polygynous 89.3 10.7

Religion 

Christianity 72.3 25.7 756.5 0.000***

Islam 91.5 8.5

Traditional/others 93.5 6.5

Age Difference 145.9 0.000***

Woman same age/older than man 74.3 25.7

Same age 77.3 22.7

Man older <10yrs 80.0 20.1

Man older 10yrs+ 87.3 12.7

Parity 64.1 0.000***

None 85.5 14.5

1-2 84.9 15.1

3-4 79.2 20.9

5+ 84.7 15.3

Exposure to messages on FP 1000.0 0.000***

Not exposed 90.2 9.8

Exposed to at least one 79.1 20.9

Exposed at least to two 66.1 33.9

Exposed to all 61.4 38.6

Desire for children 890.4 0.000***

Both want same 77.4 22.6

Husband wants more 90.1 9.9

Husband wants fewer 72.5 27.5

Don’t know 87.7 12.3

Missing 24.4 75.6
29 

There was a wide variability in contraceptive use by contextual variables (Table 5). All 

these differences were statistically significant at p <0.000. In urban clusters the level of modern 

contraceptive use, at 26%, was more than twice as high as in rural clusters, at 11%. In clusters 

located in the southern zones of the country use of modern contraceptives was more common than 

in clusters in the northern zones, from 6% in the North East and North West zones to 33% in the 

South West zone. Women living in communities with comparatively higher levels of female 

education were five times more likely to use modern contraceptives compared with women in 

communities with lower proportions of educated women (28% versus 6%). Also, rates of modern 

contraceptive use were higher in communities with lower levels of poverty, lower proportions of 

Moslem populations, lower levels of polygyny and greater access to health facilities. 

Table 5. Percent distribution of currently married, fecund women age 15-49 not desiring children by 

contraceptive method currently using, according to community characteristics, Nigeria 2013 DHS 

Types of Contraceptives Used X2 Test

Community characteristic 

None/traditional/

folkloric method

Modern 

method X2 p value 

Place of residence 531.4 0.000***

Urban 73.9 26.1

Rural 88.9 11.1

Contextual region 1100.0 0.000***

North Central 77.9 22.1

North East 93.7 6.3

North West 94.4 5.6

South East 83.8 16.3

South 77.7 22.3

South West 67.0 33.0

Community Education 1300.0 0.000***

Low 94.4 5.6 

High 72.1 27.9 

Community poverty 948.3 0.000***

Low 92.9 7.1

High 73.6 26.5

Community religion 900.7 0.000***

Low Muslims 73.8 26.2 

High Muslims 92.7 7.3 

Community female-male work ratio 354.3 0.000***

Low women-to-men ratio 89.2 10.8 

High women-to-men work ratio 77.3 22.7 

Community access to facility 425.6 0.000***

Have no access to facility 89.7 10.3 

Have access to facility 76.7 23.3

Community female autonomy index 967.4 0.000***

Low female autonomy 93.0 7.0 

High female autonomy 73.4 26.6 

Level of polygyny 232.9 0.000***

Lower 70.2 29.8

Higher 85.0 15.0 
30 

Multilevel Analysis of Predictors of Women’s Current Use of Modern Contraceptive 

Table 6 shows results of the multilevel analyses. We examined how variability in modern 

contraceptive use could be attributed to different sets of variables, with a focus on determining the 

contribution of community-level variables in accounting for the differences. The strength of 

association between the explanatory variables and contraceptive use was measured using the odds 

ratio. Odds ratios greater than one show a positive association, while there is a negative association 

when the odds ratio is less than one. The intra-cluster correlation coefficient (rho) was used to 

determine the proportion of differences in contraceptive use that could be due to intra-cluster 

variation. The impact of community-level factors was also assessed using the proportional change 

in variance (PCV). Four models were generated to assess the impact of individual and community 

variables on use of modern contraceptives. 

Model 0, the empty or null model, has no individual and contextual level variables added. 

It examines the random variable and intercept. The result shows a variance partition coefficient or 

intra-cluster correlation coefficient (ICC) of 38.5% (95%CI: 0.28-0.50) implying that as much as 

38.5% of the variations observed in the use of modern contraceptive could be explained by 

community-level variables. 
31 

Table 6. Multilevel regression results assessing effects of individual and community characteristics on 

contraceptive use among women in Nigeria, 2013 DHS 

Characteristics 

Null Model Model I Model II Model III 

 Individual 

characteristics 

Community-level 

variables 

Individual and community-

 level variables 

Empty model 

Odds 

Ratio 95% CI 

Odds 

ratio 95% CI 

Odds 

ratio 95% CI 

Fixed effects 

Age (ref.=30-39) 

15 - 19 0.44 0.28-0.70*** 0.54 0.34-0.86**

20 - 29 0.75 0.64-0.87*** 0.80 0.69-0.93**

40 - 49 0.70 0.62-0.80*** 0.68 0.60-0.78*** 

Educational attainment (ref.=no formal)

Primary 2.84 2.32-3.49*** 2.24 1.82-2.75***

Secondary and above 3.21 2.59-3.98*** 2.53 2.04-3.14*** 

Education, husband (ref.=no formal)

Primary 1.47 1.17-1.84*** 1.25 1.00-1.57¶

Secondary and above 1.49 1.19-1.86*** 1.26 1.01-1.58* 

Type of Marriage (ref.=monogamy) 

Polygynous 0.99 0.87-1.15 1,01 0.87-1.15 

Parity (3-4) 

None 1.41 0.81-2.45 1.47 0.84-2.57

 1 - 2 0.78 0.66-0.91** 0.77 0.65-0.90**

>5 1.22 1.07-1.40** 1.32 1.15-1.51** 

Household wealth (ref.=middle quintile) 

Poorest 0.29 0.21-0.41*** 0.48 0.34-0.71***

Poorer 0.60 0.49-0.74*** 0.70 0.56-0.87**

Richer 1.24 1.06-1.46** 1.15 0.98-1.36

Richest 1.67 1.40-2.00*** 1.44 1.19-1.75***

Media exposure (ref.=exposure to none) 

Exposure to at least one 1.44 1.23-1.67*** 1.39 1.20-1.61***

Exposure to two 1.75 1.52-2.03*** 1.63 1.41-1.89***

Exposure to 3 1.89 1.55-2.30*** 1.82 1.50-2.22***

 

Age difference (ref.=woman older or same age)

Partner older by < 10 years 1.00 0.74 - 1.37 0.99 0.73 - 1.35

Partner older by more than 10 years 0.87 0.64 - 1.19 0.90 0.66 - 1.23 

Desire for children (ref.=both wants same number)

Husband wants more 0.72 0.63-0.83*** 0.76 0.66-0.88***

Husband wants fewer 1.07 0.88-1.33 1.07 0.86-1.32

Don’t know 0.72 0.62-0.83*** 0.68 0.59-0.78*** 

Community level variables 

Geopolitical zone (ref.=South West)

North Central 1.15 0.92-1.44 0.62 0.47-0.84**

North East 0.63 0.46-0.88** 0.65 0.49-0.87**

North West 0.52 0.37-0.72*** 0.33 0.25-0.44***

South East 0.40 0.30-0.52*** 0.60 0.47-0.76***

South 0.75 0.59-0.94** 1.03 0.82-1.28 

Place of residence (ref.=urban) 

Rural 0.71 0.59-0.84*** 0.96 0.81-1.14 

Community-level female autonomy (ref.=low)

High 1.60 1.33-1.92*** 1.67 1.40-1.99*** 

Community-level female education (ref.=low level)

High 1.79 1.43-2.23*** 2.70 1.79-4.07***

(Continued)
32 

Table 6. − Continued

Characteristics 

Null Model Model I Model II Model III 

 Individual 

characteristics 

Community-level 

variables 

Individual & Community-

 level variables 

Empty model 

Odds 

Ratio 95% CI 

Odds 

ratio 95% CI Odds ratio 95% CI 

Community-level poverty (ref.=high poverty)

Low poverty 1.67 1.35-2.07*** 0.99 0.76-1.29 

Community-level religion (ref.=low proportion Muslim)

High 0.50 0.41-0.61*** 0.72 0.58-0.87** 

Community-level access to facility (ref.=no access)

High access 1.39 1.20-1.61*** 1.28 1.09-1.49** 

Community-level female women-men employment ratio (ref.=low)

High 1.02 0.86-1.21 0.92 0.78-1.08 

Community-level proportion of polygyny (ref.=low)

High 0.72 0.59-0.88** 0.78 0.64-0.95* 

Random effects 

ICC (%) 38.5 13.9 12.8 9.6 

PCV (%) Reference 74.2 77.0 82.9 

p <0.05 *, P <0.01**, p<0.001*** 

Model I includes individual-level variables only. This model accounted for 74.2 % of the 

variation in contraceptive use. Statistically significant positive predictors of current use of modern 

contraceptives were age of the woman, educational levels of the woman and her partner, household 

wealth level and media exposure to family planning messages. Compared with women age 30–39, 

the odds of using modern contraceptives were significantly lower in both the younger and older 

age groups. Education significantly increased the odds of contraceptive use. The likelihood of 

using modern contraceptives progressively increased with a woman’s level of education, with 

women having secondary-level education or above more than three times more likely to use 

modern contraceptives compared with women with no education (OR = 3.2, 95% CI: 2.59-3.98). 

Non-use of modern contraceptives was significantly associated with poverty. Compared with 

women in the middle wealth quintile, women in the lowest wealth and lower wealth quintile were 

81% and 40% less likely to use contraceptives, respectively, while women in the higher and highest 

wealth quintile were 1.2 times and 1.7 times more likely to use modern contraceptives; these 

associations were significant. Compared with women with three or four children, having no 

children was not significantly associated with increased use of contraceptives, while having more 

than five children significantly increased the odds of modern contraceptive use, and having one or 

two children significantly reduced the odds of modern contraceptive use. Exposure to media 
33 

messages on family planning was significantly associated with increased use of modern 

contraception. 

Being in a polygynous union reduced the odds of modern contraceptive use, as did having 

a husband who wanted more children. Also, the odds of using modern contraception increased for 

women whose partners were the same age or less than 10 years older than them. These differences 

were not significant, however. 

Model II examined the contextual factors of interest, excluding individual factors. Looking 

at zonal variation in contraceptive use, women the North Central zone were 1.2 times more likely 

to use modern contraceptives compared with the women in the South West zone, but the difference 

was not significant. However, comparatively, the odds of women using modern contraceptives 

were reduced by 51% in the South East, 60% in the North West, 37% in North East and 25% in 

South zones; these reduced odds were all significant. Low community levels of poverty, exposure 

to media messages on contraception, high community-level access to health facilities and high 

community levels of female autonomy also significantly increased the odds of use of modern 

contraceptives. The odds of contraceptive use were significantly reduced in communities with high 

levels of Moslem populations, poverty, polygyny and residence in rural areas. 

In the final model, Model III, when individual-level variables were added to the 

community-level variables, certain community-level variables lost their significance: rural 

residence and community poverty level. At the regional level, while the odds of contraceptive use 

were not significant for the North Central Zone when community level variables only were 

considered, in the final model they became significant, while the South Zone they became nonsignificant. Compared with the South West Zone, all the zones of the country had significantly 

reduced odds of modern contraceptive use, except the South Zone, with odds of 1.03 (CI 0.82 -

1.28), which was non-significant. High community levels of the female-to-male employment ratio 

now had non-significant reduced odds of modern contraceptive use (OR 0.92; CI 0.78 – 1.08). 

Religion remained an important significant predictor of use of modern contraceptives, with 

communities with higher proportion of Muslims having reduced odds (OR 72, CI 0.58 – 0.87). 

Other significant positive predictors of modern contraceptive use at the community level that 

remained in the final model were community level of female education (OR 2.27, CI 1.79 - 4.07), 

female autonomy (OR 1.67, CI 1.40 -1.99) and access to health facilities (OR 1.28, CI 1.09 - 1.49). 
34 

The direction in the associations between individual-level variables and contraceptive use 

remained the same, albeit with some variations in the strength of the association and levels of 

significance. 

Examining the ICC, there was a progressive decrease from 38.5% in the empty model to 

13.9% in Model I (individual-level variables only), to 12.8% in Model II (cluster-level factors) 

and to 9.6% in Model III (combined individual and cluster-level factors).The variance partition 

coefficient (VPC), which shows the contribution each of individual and community-level variables 

as they determine contraceptive use, progressively increased from 76.4% in Model I to 77.0% in 

Model II and 82.9% in Model III. This indicates that 82.9% of all the variations related to use of 

modern contraceptives in Nigeria are attributable to both individual characteristics and community 

factors. However, 17.1% of the factors responsible for the variation in contraceptive use could not 

be accounted for by individual and community factors.

DISCUSSION AND CONCLUSIONS 

The study investigated contextual determinants of modern contraceptive use among 

married, fecund women in Nigeria who do not desire to have a child in the next two years. This 

group is the key target of family planning programs. Our hypotheses were that there is an 

association between community-level factors and use of modern contraceptives and that wide 

differences exist across communities in the country. In summary, the contextual factors found to 

be positively associated with use of modern contraceptives were female education, female 

autonomy and access to health facilities. 

Our study found lower odds of use of modern contraceptives in the northern zones of 

country, which is similar to findings from other studies (Adebayo et al. 2012; Hailu 2015; Omotola 

2013; Oye-Adeniran et al. 2006). These findings persisted after individual-level factors were 

controlled, tending to suggest the role of contextual community factors in shaping contraceptive 

behavior in these regions. The northern regions are populated predominantly by Muslims, who 

have a more conservative culture. The religion may be acting in synergy with other areal factors 

to negatively influence uptake of contraceptives. This study confirmed previous findings of the 

negative association between predominantly Muslim communities and modern contraceptive use. 
35 

The study showed, for the first time, that the South East and South zones have lower odds 

of modern contraceptive use, though the odds were not statistically significant. Perhaps the greater 

preference for traditional/folkloric methods of contraception (National Population Commission 

and ICF 2014), which are of lower efficacy than modern methods, may be responsible for the lower 

odds of modern contraceptive use in these two southern states. These have important policy 

implications, as interventions aimed at scaling up family planning use in the country will have to 

be holistic in their approach, going beyond descriptive zonal variables. 

 This study found that, when individual-variables were controlled, rural residence and level 

of community poverty were no longer significantly associated with lower odds of contraceptive 

use. This is contrary to previous studies (Ibisomi 2014; Stephenson et al. 2007). It would appear 

that other mediating factors have mitigated the effects of place of residence; several studies have 

shown that urban residence is associated with increased use of modern contraceptives because of 

improved infrastructure and greater access to health services. It is unlikely that the modification 

of this association in this study is because of the recent increase in investments in family planning 

and free provision of the commodities. Surprisingly, community level of poverty was not 

significantly associated with use of modern contraceptives. 

 We also found that female education was positively associated with use of modern 

contraceptives. Improvements in women’s educational attainment increase the likelihood of use of 

modern contraceptives. This may be associated with the role of female education in empowering 

women through enhancing their autonomy and participation in decision-making, positively 

modifying health-seeking behavior and building social capital through expansion of social 

networks. The positive association found between female education and contraceptive use is 

consistent with several studies conducted in developing countries (Ainsworth, Beegle, and 

Nyamete 1996; Arokiasamy, and Cassen 2003; Hailu 2015; McNay, Kaggwa, Diop, and Storey 

2008). Education also increases women’s employment opportunities, which can result in increased 

economic independence and expanded autonomy in decision-making. This is expected to be 

associated with increased use of modern contraceptives. This association was not established by 

this study, however. To the contrary, we found that female employment reduced the odds of 

modern contraceptive use, though the association was not statistically significant. The reason for 

this is not clear and requires further investigation. Studies have suggested that in Africa paid female 

employment outside the home may be related to poverty, with the women employed in menial 
36 

jobs, and this would likely have a negative effect on use of maternal health services, including 

contraception. 

Female empowerment expands women’s choices and ability to make decisions, including 

reproductive health decisions, and it also leads to improved health-seeking behavior. It is believed 

that empowerment of women will lead to increased use of modern contraceptives. We examined 

three dimensions of female empowerment in relation to decision-making regarding mobility, 

financial decisions and decisions on use of contraceptives. Similar to other studies, we found that 

women who participate in decision-making along these dimensions were significantly more likely 

to use contraceptives. 

At the individual level, high parity, female education, husband’s education and household 

wealth were associated with increased likelihood of using modern contraceptives. This is 

consistent with previous studies (Gage 1995; Hogan, Betemariam, and Assefa 1999; White and 

Speizer 2007). Also, women in monogamous unions and women who were Christian had 

significantly higher odds of modern contraceptive use than women in polygynous unions and 

women who were Muslims. Younger and older ages were negatively associated with modern 

contraceptive use, while spousal age difference and polygyny had no significant association with 

use of modern contraceptives. This study confirms Ibisomi’s findings from Nigeria that did not 

demonstrate any association between spousal age difference and use of contraceptives (Ibisomi 

2014). However, this finding is in contrast to many other studies that established such an 

association (Darroch, Landry, and Oslak 1999; Longfield et al. 2004). After controlling for all 

other individual and community-level factors, we found that 83% of all variations related to use of 

modern contraceptives in Nigeria were attributable to both individual characteristics and 

community factors. 

Policy implications 

Because female education is positively associated with modern contraceptive use, it is 

evident that investment in female education should command the attention of health and 

development policy-makers in Nigeria. To this end, greater investment in the education of girls 

should be pursued beyond 2015, as it has multiplier effects in increasing uptake of modern 

contraceptives. In the spirit of inter-sectoral collaboration, the health sector should continually 
37 

engage with the education sector to advocate for girl-child education, for the reproductive health 

and empowerment benefits it offers for women. 

The largest religion in Nigeria is Islam. Given the negative association between Muslim 

faith and contraceptive use, there is a need to develop innovative and appropriate strategies to 

increase family planning demand among this population. Recognizing that Islam is not averse to 

contraceptives, but religious opposition has always been cited as the reasons for non-use of 

contraceptives, there is a need to involve the Islamic religious leaders in developing and 

implementing the communication plan. 

Additional research is needed to determine how best to meet women’s information needs 

efficiently on a sustainable basis and how to provide a continuous flow of information that is lively, 

interesting and culturally appropriate.

In Nigeria there are wide zonal variations in contraceptive use. The study findings showed 

that the South East and South South Zones have significantly lower odds of use of modern 

contraceptives. This part of the country has the largest population of Catholics, who are averse to 

the use of modern contraceptives andwho promote natural family planning methods only. This 

may be one of the reasons for this finding, as the use of traditional/folkloric methods is 

comparatively higher than in other zones. There is a need for further investigation of this finding, 

as we did not investigate the influence of Catholic religion on contraceptive use. This couldform 

the basis of context-specific interventions. 

Strengths and limitations

One of the important strengths of this research is that the data were collected based on a 

nationally representative sample of women. Therefore, a national average of contraceptive 

prevalence could be estimated. Further, because of its large sample size it was possible to estimate 

contraceptive prevalence rate at the sub-national zonal level. The hierarchical nature of the data 

allowed us to explore factors operating beyond the individual level to look at such variables at the 

community level. Employing this type of analysis has brought to the fore some factors which 

hitherto have not been explored to explain the persistent low levels of modern contraceptive use 

in Nigeria. Use of this analytic method has a policy implication of making programming examine 
38 

contextual factors affecting contraceptive use, rather than placing disproportionate emphasis on 

the individual. 

There are limitations to this study. Some women were excluded from the couple data set 

because their husbands were over age 49, and thus not surveyed. A survey that does not restrict 

data collection based on age of male partners might provide more information on modern 

contraceptive use. The fact that the data were collected using a cross-sectional survey constrained 

us from making causal inferences between the exposure variables (individual and community 

variables) and the outcome variable, current use of modern contraceptive. We were only able to 

estimate the strength of the association between the exposure variables and the outcome variable; 

identifying a definitive causal relationship is not possible with this type of study design. In 

particular, rather than predicting contraceptive use, discussion between spouses about family 

planning may actually have taken place after contraceptive acceptance. 

In addition, access to a health facility and exposure to media messages on family planning 

could not be adequately accounted for as far as the extent of access or exposure is concerned. 

Related to measurement error is the association between Islam and contraceptive use. This study 

did not explore respondents’ knowledge and perception of contraceptives based on their religious 

point of view. Finally, there is the issue of endogeneity, as the value of some independent variables 

might be determined or influenced by other covariates. For instance, exposure to family planning 

messages might be correlated with development of the community, which itself might be 

associated with contraceptive use. 
39 

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