DHS COMPARATIVE

REPORTS 44

WOMEN’S MARITAL STATUS,

CONTRACEPTIVE USE, AND UNMET 

NEED IN SUB-SAHARAN AFRICA,

LATIN AMERICA, AND THE CARIBBEAN

July 2017

This publication was produced for review by the United States Agency for International Development (USAID). The report was prepared by 

Wenjuan Wang, Sarah Staveteig, Rebecca Winter, and Courtney Allen.

DHS Comparative Reports No. 44 

Women’s Marital Status, Contraceptive Use, and Unmet 

Need in Sub-Saharan Africa, Latin America, and the 

Caribbean 

Wenjuan Wang1

Sarah Staveteig2

Rebecca Winter3

Courtney Allen1

ICF 

Rockville, Maryland, USA 

July 2017 

1

 The DHS Program, ICF 

2

 The DHS Program, Avenir Health 

3

 DC Department of Health 

Corresponding author: Wenjuan Wang, International Health and Development, ICF, 530 Gaither Road, 

Suite 500, Rockville, MD 20850, USA; Telephone: +1 301-407-6500; Fax: +1 301-407-6501; 

E-mail: wenjuan.wang@icf.com 
Acknowledgments: The authors would like to thank Soumya Alva for reviewing this report and providing 

helpful comments; Trevor Croft for providing guidance on calendar data; Tom Pullum for guiding the 

research effort; and Shireen Assaf for helpful discussions of the Stata programs used for this report. 

Editor: Bryant Robey 

Document Production: Audrey Shenett 

This study was carried out with support provided by the United States Agency for International 

Development (USAID) through The DHS Program (#AIDOAA-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, 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: 

Wang, Wenjuan, Sarah Staveteig, Rebecca Winter, and Courtney Allen. 2017. Women’s Marital Status, 

Contraceptive Use, and Unmet Need in Sub-Saharan Africa, Latin America, and the Caribbean. DHS 

Comparative Reports No. 44. Rockville, Maryland, USA: ICF.
iii 

Contents 

Tables ........................................................................................................................................................... v 

Figures ......................................................................................................................................................... vi 

Preface ........................................................................................................................................................ vii 

Abstract ....................................................................................................................................................... ix 

1. Introduction ........................................................................................................................................... 1 

2. Data and Methods ................................................................................................................................. 5 

2.1. Data ........................................................................................................................................... 5 

2.2. Measures .................................................................................................................................... 5 

2.3 Analysis ..................................................................................................................................... 7 

2.4 Limitations ................................................................................................................................. 8 

3. Results .................................................................................................................................................... 9 

3.1 Socioeconomic Profiles of Women by Marital Status ............................................................... 9 

3.2 Contraceptive Use and Marital Status ..................................................................................... 15 

3.3 Unmet Need for Family Planning and Marital Status .............................................................. 31 

3.4 Contraceptive Use and Unmet Need among Polygynous Women .......................................... 48 

4. Discussion and Conclusions ................................................................................................................ 57 

References .......................................................................................................................................................... 61 

Appendix Tables ............................................................................................................................................... 64

v 

Tables 

Table 1 DHS surveys included in the analysis ....................................................................................... 5 

Table 2 Percent distribution of currently married women by background characteristics ................... 12 

Table 3 Percent distribution of never-married women by background characteristics ........................ 13 

Table 4 Percent distribution of formerly married women by background characteristics .................... 14 

Table 5 Contraceptive prevalence for sexually active currently married, never-married, and 

formerly married women, by women’s age ............................................................................. 26 

Table 6 Contraceptive prevalence for sexually active currently married, never-married, and 

formerly married women, by number of living children ......................................................... 27 

Table 7 Contraceptive prevalence for sexually active currently married, never-married, and 

formerly married women, by women’s education ................................................................... 28 

Table 8 Contraceptive prevalence among sexually active currently married, never-married, 

and formerly married women, by wealth quintile ................................................................... 29 

Table 9 Contraceptive prevalence among sexually active currently married, never-married, 

and formerly married women, by employment status ............................................................. 30 

Table 10 Contraceptive prevalence among sexually active currently married, never-married, 

and formerly married women, by residence ............................................................................ 31 

Table 11 Percentage of sexually active currently married, never-married, and formerly married 

women with an unmet need for family planning, by women’s age ......................................... 40 

Table 12 Percentage of sexually active currently married, never-married, and formerly married 

women with an unmet need for family planning, by number of living children ..................... 41 

Table 13 Percentage of sexually active currently married, never-married, and formerly married 

women with an unmet need for family planning, by women’s education ............................... 42 

Table 14 Percentage of sexually active currently married, never-married, and formerly married 

women with an unmet need for family planning, by household wealth quintile ..................... 43 

Table 15 Percentage of sexually active currently married, never-married, and formerly married 

women with an unmet need for family planning, by women’s employment status ................ 44 

Table 16 Percentage of sexually active currently married, never-married, and formerly married 

women with an unmet need for family planning, by residence ............................................... 45 

Appendix Table 1 Unweighted number of women who were sexually active in last month, by 

marital status .............................................................................................................. 63 

Appendix Table 2 Modern contraceptive prevalence (mCPR) among unmarried sexually active 

women based on calendar data and women's report of "current use" ........................ 64 

 
vi 

Figures 

Figure 1 Percent distribution of all women by marital status .................................................................. 10 

Figure 2 Contraceptive prevalence among sexually active currently married women ............................ 16 

Figure 3 Contraceptive prevalence among sexually active never-married women ................................. 18 

Figure 4 Contraceptive prevalence among sexually active formerly married women ............................ 20 

Figure 5 Contraceptive prevalence among sexually active women by marital status, most recent 

survey only ................................................................................................................................ 22 

Figure 6 Method mix among sexually active women who use modern contraception by marital 

status, most recent survey only ................................................................................................. 24 

Figure 7 Percent distribution of sexually active currently married women by unmet need status .......... 32 

Figure 8 Percent distribution of sexually active never-married women by unmet need status ............... 34 

Figure 9 Percent distribution of sexually active formerly married women by unmet need status ........... 36 

Figure 10 Percentage of sexually active women with demand for family planning satisfied, by 

marital status ............................................................................................................................. 38 

Figure 11 Odds ratios of sexually active never-married women compared with sexually active 

currently married women from multivariable regressions of demand satisfied ........................ 46 

Figure 12 Odds ratios of sexually active formerly married women compared with sexually active 

currently married women from multivariable regressions of demand satisfied ........................ 47 

Figure 13 Percentage of married women in polygynous marriages .......................................................... 48 

Figure 14a Percent distribution of women for each marriage type by age .................................................. 49 

Figure 14b Percent distribution of women for each marriage type by number of children ......................... 49 

Figure 14c Percent distribution of women for each marriage type by education ........................................ 50 

Figure 14d Percent distribution of women for each marriage type by wealth ............................................. 50 

Figure 14e Percent distribution of women for each marriage type by employment status ......................... 51 

Figure 14f Percent distribution of women for each marriage type by urban-rural residence ..................... 51 

Figure 15 Contraceptive prevalence among sexually active currently married women, by marriage 

type ........................................................................................................................................... 52 

Figure 16 Method mix among sexually active currently married women who use modern 

contraception, by marriage type ................................................................................................ 53 

Figure 17 Percent distribution of sexually active currently married women according to the status 

of unmet need for family planning, by marriage type ............................................................... 54 

Figure 18 Odds ratios of polygyny compared with monogamy from multivariable regressions of 

any contraceptive use ................................................................................................................ 55 

Figure 19 Odds ratios of polygyny compared with monogamy from multivariable regressions of 

modern contraceptive use ......................................................................................................... 55 
vii 

Preface 

The Demographic and Health Surveys (DHS) Program is one of the principal sources of international data 

on fertility, family planning, maternal and child health, nutrition, mortality, environmental health, 

HIV/AIDS, malaria, and provision of health services. 

One of the objectives of The DHS Program is to provide policymakers and program managers in low- and 

middle-income countries with easily accessible data on levels and trends for a wide range of health and 

demographic indicators. DHS Comparative Reports provide such information, usually for a large number 

of countries, in each report. These reports are largely descriptive, without multivariate methods, but where 

possible they include confidence intervals, statistical tests, or both. 

The topics in the DHS Comparative Reports series are selected by The DHS Program in consultation with 

the U.S. Agency for International Development. 

It is hoped that the DHS Comparative Reports will be useful to researchers, policymakers, and survey 

specialists, particularly those engaged in work in low- and middle-income countries. 

Sunita Kishor 

Director, The DHS Program 

ix 

Abstract 

This comparative report analyzes contraceptive use and unmet need for family planning among sexually 

active women age 15-49 in 21 countries of sub-Saharan Africa, Latin America, and the Caribbean. Sexually 

active unmarried women are an important and increasing sub-population typically excluded from largescale studies of contraception and unmet need. In this study we disaggregate sexually active women into 

three marital groups: currently married, never-married, and formerly married. 

Overall, countries in Latin America and the Caribbean have the highest levels of contraceptive use and 

lowest levels of unmet need for family planning. Differentials in contraceptive use and unmet need by 

women’s marital status are negligible in this region. Family planning practices vary substantially within 

sub-Saharan Africa. Western African and Central African countries generally have lower contraceptive 

prevalence than Eastern and Southern African countries. A considerable proportion of women in Central 

and West Africa have no need for family planning. Sub-Saharan Africa as a whole shows greater variation 

in contraceptive use by marital status. Never-married women usually have the highest contraceptive 

prevalence, and currently married women have the lowest. Women in sub-Saharan Africa rely on a very 

limited number of modern methods, and the predominant method differs by their marital status. While 

never-married women tend to use condoms, currently married and formerly married women are more likely 

to use injectables or pills. The differences in contraceptive use and unmet need by individual and household 

characteristics are largely consistent across the three marriage groups. Regression results indicate that in a 

number of countries, compared with currently married women, never-married women are significantly 

more likely to have their demand for contraceptive use satisfied, but formerly married women are less 

likely. We also found that women in polygynous marriages are less likely to use a contraceptive method 

compared with women in monogamous marriages. Both groups share a similar method mix. 

While the findings about never-married women are somewhat encouraging, when taken as a whole these 

results underscore the importance of ensuring equitable access to family planning among all marital groups, 

particularly in countries where nonmarital sex may be stigmatized, and of anticipating the particular 

contraceptive needs of unmarried women. The results for polygynous versus monogamous women suggest 

the importance of demand generation activities in areas where polygyny is prevalent. 

Key words: Marital status, contraceptive prevalence, unmet need for family planning, demand satisfied, 

polygynous marriage, sub-Saharan Africa, Latin America, and the Caribbean 

1 

1. Introduction 

Among the proximate determinants, contraceptive use has the greatest effect on fertility (Bongaarts and 

Potter 1983; Becker and Costenbader 2001), and contraceptive use is one of the most cost-effective health 

behaviors due to its positive impact on maternal and infant health outcomes (Creanga et al. 2011). Family 

planning programs are an ideal and distinctive public health intervention because of their capacity to affect 

both individual and population-level outcomes. As well as improving maternal and child survival, 

contraceptive use has been shown to have beneficial spillover effects on poverty reduction, environmental 

sustainability, gender equality, and women’s empowerment (Carr et al. 2012; Cleland et al. 2006; Singh et 

al. 2009). The ability to plan and space children not only benefits women’s health but also gives women 

the possibility to participate in non-domestic activities, to join the labor force, and to take advantage of 

educational opportunities (Cleland et al. 2006; Tsui, McDonald-Mosley, and Burke 2010). 

Although there is a wealth of literature on contraceptive use, relatively few studies investigate contraceptive 

use by women’s marital status. For global estimations of contraceptive use and unmet need for family 

planning, unmarried women—an important and increasing population—are often left out of research due 

to lack of data, particularly in Asia and North Africa (United Nations Department of Economic and Social 

Affairs 2015). Thus it is difficult to compare various regional and global estimates of contraceptive use and 

unmet need. Some studies have included sexually active unmarried women (Howse 2014; Howse and 

Nanitashvili 2014; Ross and Winfrey 2002) while others have focused solely on married women. Moreover, 

in studies that differentiate between never-married and formerly married women, the latter group is 

sometimes excluded from such estimates altogether due to too small sample sizes for independent analysis 

and too dissimilar circumstances for comparison (Sedgh, Ashford, and Hussain 2007). 

The level of contraceptive use in sub-Saharan Africa among married or in-union women is lower than in 

any other region of the world (FP2020 2015; Howse and Nanitashvili 2014; United Nations Department of 

Economic and Social Affairs 2015). When considering contraceptive use among women in Africa by 

marital status, data have shown that unmarried women are more likely to use contraception than currently 

married women (Cleland, Ali, and Shah 2006; Howse and Nanitashvili 2014). Similarly, the Latin America 

and Caribbean region shows higher levels of contraceptive use among unmarried women than married 

women (Howse 2014). This region has the highest level of contraceptive use of any developing region 

worldwide (Bertrand, Ward, and Santiso-Gálvez 2015; United Nations Department of Economic and Social 

Affairs 2015). 

Unmarried women usually want to avoid becoming pregnant (Blanc et al. 2009; Howse and Nanitashvili 

2014). Thus, despite more sporadic sexual activity compared with married women, unmarried women tend 

to have a higher prevalence of contraceptive use (Cleland, Ali, and Shah 2006; Ross and Winfrey 2002). 

They also are more likely than their married counterparts to negotiate contraceptive use with their partners 

(Wellings et al. 2006). Globally, among all women at risk of becoming pregnant, a larger proportion are 

married than are unmarried and sexually active (Wellings et al. 2006), even among young women age 15-

19 (Blanc et al. 2009). 

The fact that single unmarried women may have sex infrequently is an important factor for their method 

choice or non-use of contraception. Secondary abstinence among unmarried women—defined as women 

who report in surveys that they have had sex but not within the last three months—has increased in recent 

years, along with the proportion of single unmarried women in sub-Saharan Africa who use condoms. In 

contrast, the increase in the proportion of married women using condoms has been negligible (Cleland and 

Ali 2006; Cleland, Ali, and Shah 2006). In only a few countries in sub-Saharan Africa—Botswana, 

Cameroon, Congo, Democratic Republic of the Congo, Gabon—do married women report condoms as their 

main method of contraception (United Nations 2017). 
2 

Among married women of reproductive age (15-49), injectables are the most common method used in most 

African countries, followed distantly by the pill (United Nations Department of Economic and Social 

Affairs 2015). Injectables also are the most common method used by young married women age 15-24 in 

Africa, while in four of every five sub-Saharan African countries condoms are the method of choice among 

young sexually active unmarried women. The second most common method among unmarried young 

women is injectables, exceeding condom use in a few African countries (Howse and Nanitashvili 2014). 

In Latin America and the Caribbean, there is much variation between countries in method choice and in 

overall use of contraception. Accounting for all reproductive ages, sterilization is the most common form 

of contraception in this region (United Nations Department of Economic and Social Affairs 2015). 

Considering only young married women, sterilization is uncommon, and injectable contraception is the 

most common method, although in a few countries the pill is most used, and in one country the IUD is the 

most commonly used method. As in Africa, the condom is the principal method among young unmarried 

women in Latin America and the Caribbean (Howse 2014), and one study found that condom use rose 

significantly between 1994 and 2004 in eight countries (Blanc et al. 2009). In a few countries of Latin 

America and the Caribbean—Ecuador, Dominican Republic, El Salvador, Guatemala—use of the pill or 

injectables has overtaken the condom as the most used modern method among sexually active unmarried 

women age 20-24. In two Latin American countries, Bolivia (age 20-24) and Ecuador (age 15-19), 

unmarried women rely principally on traditional methods. The method mix among married women is more 

varied than among unmarried women (Howse 2014). 

In 2015, an estimated 133 million married women worldwide had an unmet need for family planning, 

approximately one in every five married women in the FP2020 partnership’s 69 focus countries. By this 

estimate, 27% of the global unmet need is among married women in sub-Saharan Africa, while only 1% is 

among married women in Latin America and the Caribbean (FP2020 2015). Regionally, for married 

women, unmet need in sub-Saharan Africa is approximately 24%, twice the level of 12% in Latin America 

and the Caribbean (Sedgh, Ashford, and Hussain 2007). In Latin America and the Caribbean, a larger 

proportion of young married women than all married women have an unmet need for family planning, while 

in sub-Saharan Africa the proportion is similar. Globally, an estimated one-third of all unmet need is among 

young married women (Ross and Winfrey 2002). 

Recent global estimates of unmet need, however, exclude unmarried women because of insufficient data 

on this group. Estimates of unmet need that include sexually active unmarried women have found that 

unmet need among unmarried women is much lower compared with married women, at 9% in sub-Saharan 

Africa and 5% in Latin America and the Caribbean (Sedgh, Ashford, and Hussain 2007). 

In many low- and middle-income countries the determinants of unmet need are similar, including 

socioeconomic factors, number of children, fear of side effects, knowledge, and infrequent sex (Blanc et al. 

2009; Cleland, Ali, and Shah 2006; Sedgh, Ashford, and Hussain 2007; Wulifan et al. 2016). Although 

unmet need in Latin America and the Caribbean is the lowest in the developing world, it varies substantially 

among countries. Some countries are outliers, such as Haiti, with one of the highest levels of unmet need 

in the world, at 40%. In sub-Saharan Africa the majority of women with an unmet need say they want to 

have more children in the future (unmet need for spacing), while women in Latin America and the 

Caribbean are divided between wanting to delay having the next birth or to stop childbearing altogether 

(unmet need for limiting) (Sedgh, Ashford, and Hussain 2007). A study of unmet need among previously 

married women in sub-Saharan Africa found that previously married young women had a higher level of 

unmet need than never-married young women, at approximately 15% (age 15-19) and 16% (age 20-24) 

(Ross and Winfrey 2002). 
3 

The existence of unmet need reflects women’s contraceptive use and fertility desires, both of which can be 

affected by successful family planning programs. Because the desire to space or limit births occurs before 

and determines demand for contraception, however, there is often an increase in unmet need as more women 

want to control their fertility but have not yet initiated contraceptive use—suggesting that increases in 

unmet need may not be an indication that family planning programs are unsuccessful, but rather reveal 

growing demand for contraception that has not yet been satisfied. These short-term rises in the proportion 

of women experiencing unmet need are particularly likely to occur in countries with very low contraceptive 

prevalence (Brown et al. 2014). Moreover, an absence of available modern methods is not the main cause 

of unmet need, as many women say they avoid use of modern contraception for reasons that include health 

risks and side effects of modern methods, or infrequent sex. Two-thirds of all women in sub-Saharan Africa 

with unmet need give method-related reasons for non-use. Additionally, even when contraceptive methods 

are widely available, this may not reduce levels of unmet need where there are societal or financial barriers 

to their use, or opposition from sexual partners (Darroch, Sedgh, and Ball 2011). 

Although monogamy is the prevailing marital norm, some currently married women may be in polygynous 

unions (Wellings et al. 2006). In Nigeria, a study found that women in polygynous marriages were more 

likely to use contraception than those in monogamous marriages. However, certain factors such as older 

age, having more female children, or having no male children were associated with not using contraception 

among women in polygynous marriages (Audu et al. 2008). In Malawi, women in polygynous unions had 

a lower level of contraceptive use than their monogamous counterparts, and there was a higher incidence 

of covert use (Baschieri et al. 2013). The finding that polygynous women have lower contraceptive 

prevalence compared with monogamous women is in line with findings from other studies (Becker and 

Costenbader 2001; Bove and Valeggia 2009). Couples in polygynous unions have different decisionmaking processes and less spousal communication than monogamous couples, which may negatively 

impact a couple’s ability to effectively use contraception (Baschieri et al. 2013; Bove and Valeggia 2009). 

In Ghana and Kenya, research has shown that polygynous women are more able than their monogamous 

counterparts to effectively implement their desires for lower fertility, because they have weaker relational 

ties and more frequent separation from their husbands (Dodoo 1998). Conversely, in sub-Saharan Africa as 

a whole, polygynous woman may want more children because of the competition with other wives (Bove 

and Valeggia 2009). 

Research on contraceptive use and unmet need often focuses solely on married women, in part because this 

focus enables cross-country standardization of results. As mentioned, some surveys of contraceptive use 

exclude unmarried women entirely, particularly in Asia and North Africa. Additionally, including 

unmarried women in study findings requires the caveat that sexual behavior and contraceptive use are likely 

to be underreported among this group. For example, a study in Malawi found that unmarried women 

underreport their sexual behavior, although some factors such as higher social status of their partners may 

be associated with better reporting of sexual relationships (Nnko et al. 2004). Research that includes 

unmarried women in cross-national estimates of contraceptive use and unmet need typically acknowledges 

a possible bias arising from underreporting of sexual activity (Darroch and Singh 2013; Wellings et al. 

2006; Westoff 2006). However, the magnitude of underreporting is unknown; moreover, family planning 

use among women who do not report sexual activity is also unknown. Trend analysis among unmarried 

women is challenging, because social norms and cultural attitudes toward sexual behavior are changing. 

Thus it is difficult to know whether the increasing tendency in recent years for unmarried women to report 

sexual activity is the result of a change in sexual behavior or if unmarried women simply feel more 

comfortable reporting sexual activity (Wellings et al. 2006). 

 
4 

This study investigates contraceptive use and unmet need for family planning among sexually active women age 

15-49 in 21 countries of sub-Saharan Africa and Latin America. We disaggregate our analysis into three marital 

groups of women—currently married, never-married, and formerly married—in order to provide a comparative 

picture of each group. We explore method mix and levels of contraceptive use, unmet need, met need, and 

demand satisfied, showing differences by background characteristics. Additionally, we test the effect of marital 

status on demand satisfied and the effect of being in a polygynous union on the likelihood of using contraception. 

 
5 

2. Data and Methods 

2.1. Data 

The study used data from Demographic and Health Surveys 

(DHS) in 21 countries in sub-Saharan Africa, Latin America, 

and the Caribbean. The selection of these countries was based 

on two criteria: 1) the country’s most recent survey was 

conducted in 2010 or after, in order to provide a recent level of 

indicators; 2) the country’s most recent survey included a 

sufficient number of currently married, never-married, and 

formerly married women who were sexually active (150 or 

more), to allow examination of family planning practices by 

women’s background characteristics. A woman was 

considered sexually active if her last sex occurred in the last

month (30 days preceding the survey). 

For each country, to examine trends, we included the most 

recent survey and also an earlier survey conducted 

approximately 10 years before the most recent survey. In a few 

countries—Congo, Congo Democratic Republic, Liberia, 

Sierra Leone, and Honduras—the gap between the two surveys 

was 5-6 years due to unavailability of a survey conducted 

earlier. Table 1 lists the countries and surveys included in this 

study, with the sub-Saharan African countries organized in 

three geographic sub-regions: Central Africa, Western Africa, 

and Eastern and Southern Africa. Table 1 also indicates 

countries that were included in the analysis on women in 

polygynous marriages—Cameroon, Congo Democratic Republic, Cote d’Ivoire, Nigeria, Sierra Leone, 

Mozambique, and Tanzania. These countries were included because of a relatively high prevalence of 

polygyny (18% or higher among currently married women). 

This analysis focused on sexually active women age 15-49. Appendix Table 1 provides the number of 

women included in each marital group—currently married, never married, and formerly married—in each 

survey. 

2.2. Measures 

This section describes definitions of key measures used in the analysis, including marital status, 

contraceptive use, and unmet need for family planning, and demand for family planning satisfied. 

Marital status 

The study compared family planning practices by women’s marital status: currently married, never married, 

and formerly married. Women who are currently married (or living together with a man as if married) are 

considered to be in this category regardless of whether they have been previously divorced or widowed. 

Currently married women were further divided into two groups: women in monogamous marriages—that 

is, those whose spouses do not have other wives; and women in polygynous marriages—that is, those whose 

spouses have one or more other wives. Formerly married women include those who are widowed, divorced, 

or separated and not currently living with a partner as if married. Most of the analysis focused on sexually 

Table 1 DHS surveys included in the analysis 

 

Country Survey 1 Survey 2 

Central Africa 

Cameroon* 2004 2011 

Congo 2005 2011-12 

Congo Democratic 

Republic (DR Congo)* 

2007 2013-14 

Gabon 2000 2012 

 

Western Africa 

Cote d'Ivoire* 1998 2011-12 

Ghana 2003 2014 

Liberia 2007 2013 

Nigeria* 2003 2013 

Sierra Leone* 2008 2013 

 

Eastern and Southern Africa 

Kenya 2003 2014 

Lesotho 2004 2014 

Malawi 2004 2015-16 

Mozambique* 2003 2011 

Namibia 2006-07 2013 

Tanzania* 2004-05 2015-16 

Zambia 2001-02 2013-14 

Zimbabwe 2005-06 2015 

Latin America and the Caribbean 

Colombia 2000 2010 

Dominican Republic 2002 2013 

Honduras 2005-06 2011-12 

Peru 2000 2012 

*Countries included in the analysis of women in polygynous 

marriages 

 
6 

active women in these three categories of marital status. Comparisons in contraceptive use and unmet need 

were also made between women in monogamous marriages and those in polygynous marriages. 

Contraceptive use 

We explored several ways to measure “current” contraceptive use. Since unmarried women (never married 

or formerly married) are more likely than currently married women to be abstinent or have sporadic sex, it 

could be difficult to assess whether these women use contraceptive methods during sex, because the 

standard DHS question on “current” use of contraception in the woman’s interview asks “Are you currently 

doing something or using any method to delay or avoid getting pregnant?” A woman might not respond 

that she is currently using a method if her last sexual activity was 60 days ago, even if she used a 

contraceptive method at that time. For this reason, we considered using information from the contraceptive 

calendar, which contains month-by-month information about women’s use of contraception over the last 

five years, rather than relying on their reports of current use. Since unmarried women may have more 

sporadic sexual activity than currently married women, we considered including women who were sexually 

active in the last three months (90 days), rather than in the last one month (30 days), in the definition of 

“sexually active”, and measuring contraceptive use in the corresponding calendar month. This would be 

more inclusive of unmarried women who are sexually active but only sporadically. 

To assess the different measures of the recency of sex and use of contraception, we compared contraceptive 

prevalence among three groups, using the selected DHS surveys that included the contraceptive calendar 

(see Appendix Table 2). In the first group, we included women who had sex in the last 90 days, and used 

data from the contraceptive calendar to assess whether the woman used contraceptives in the three months 

before the interview. In the second group, we included women who had sex in the last three months, but 

defined contraceptive use on the basis of the woman’s report of current use. In the third group, we included 

women sexually active in the last 30 days, and measured contraceptive using the woman’s report of current 

use. The results showed that contraceptive prevalence was similar in the first and third groups—with a 

difference of less than 1 percentage point in seven surveys, and 3 percentage points in almost all the other 

surveys. Contraceptive prevalence was slightly lower as measured for the second group. 

Based on these findings, and also because the contraceptive calendar is not included in all surveys, we 

decided to define contraceptive use based on women’s reports of current use among those who had sexual 

activity in the last 30 days. 

Contraceptive prevalence was defined as the percentage of women who reported current use of a 

contraceptive method. It comprises use of modern methods and use of traditional methods. Modern methods 

include sterilization (female sterilization and male sterilization), pill, intrauterine contraceptive device 

(IUD), injectables, implants, male condom, and other modern contraceptive methods (e.g., emergency 

contraception, lactational amenorrhea method (LAM), standard day method (SDM), female condom, 

diaphragm, contraceptive foam and contraceptive jelly, etc.). Traditional methods include withdrawal, 

periodic abstinence, folkloric methods, and other country-specific traditional methods. 

Unmet need, met need, and demand for family planning satisfied 

We used the revised DHS definition of unmet need for family planning (Bradley et al. 2012). A variable of 

unmet need was generated to have four categories: unmet need for limiting; unmet need for spacing; met 

need; and no need. 

A woman is considered to have unmet need for limiting births if she meets one of the following conditions: 

1) She is not pregnant and not postpartum amenorrheic and is not considered fecund and 

wants no more children but is not using a contraceptive method; 
7 

2) She is currently pregnant but the pregnancy is unwanted; 

3) She is postpartum amenorrheic and her last birth in the last two years was unwanted. 

A woman is considered to have unmet need for spacing births if she meets one of the following conditions: 

1) She is not pregnant and not postpartum amenorrheic and is not considered fecund and 

wants to postpone the next birth for two or more years but is not using a contraceptive 

method; 

2) She is currently pregnant but the pregnancy is mistimed; 

3) She is postpartum amenorrheic and her last birth in the last two years was mistimed. 

Women using any contraception are considered to have a met need for family planning. Women with unmet 

need and those with met need together represent the total demand for family planning. Demand satisfied 

was calculated as the percentage of women who have a met need divided by the total demand. No need for 

family planning includes women who are infecund and those who are fecund but want a child in the next 

two years. 

Typically, calculations of unmet need assume all married women are sexually active and thus at risk of 

unmet need if they are not using contraception. This analysis deviates from that standard by measuring 

unmet need only among sexually active women in all three categories of marital status—currently married, 

formerly married, and unmarried. 

Background variables 

We assessed the differences in levels of contraceptive use and unmet need by a number of relevant 

individual and household characteristics. These include woman’s age, number of living children, education, 

household wealth quintile, employment status, and urban-rural residence. These variables were also 

included in the regression models assessing these differences by marital status. 

2.3 Analysis 

This report is primarily descriptive. First, we tabulated the distribution of all surveyed women by marital 

status. We used data from both surveys in each country to identify trends over the survey period. Then, 

within each marital group, we assessed women’s age, educational attainment, household wealth, 

employment status, and urban-rural residence. 

Second, we analyzed trends in contraceptive prevalence among sexually active women in each of the marital 

groups. We also examined differentials in contraceptive use by background characteristics for each marital 

group, based on the country’s most recent survey. We compared the contraceptive method mix among users 

of modern methods in the three marital groups. 
8 

Third, we analyzed unmet need for family planning by categorizing it into four groups: unmet need for 

spacing, unmet need for liming, met need, and no need. Trends in unmet need were tabulated for each 

country. We made comparisons by marital status on demand for family planning satisfied. Multivariable 

logistic regression models were fitted to examine the relationship between marital status and unmet need 

after adjusting for women’s background characteristics. 

Finally, we assessed contraceptive use and unmet need among women in polygynous marriages in seven 

countries with a relatively high prevalence of polygyny: Cameroon, Congo Democratic Republic, Cote 

d’Ivoire, Nigeria, Sierra Leone, Mozambique, and Tanzania. Comparisons were made with women in 

monogamous marriages. We used logistic regressions models to quantify the differences in any 

contraceptive use and modern contraceptive use between the two groups after adjusting for other covariates. 

All analyses were conducted with Stata 14. DHS complex sample design was accounted for in the 

estimation. 

2.4 Limitations 

The analysis was limited to women who were sexually active in last 30 days. Never-married women and 

formerly married women may underreport recent sexual activity due to concerns about social acceptability. 

This could bias our estimates either upward or downward, depending on their use of contraception. 

Moreover, restricting the analysis to sexually active women has an impact on estimation of unmet need in 

that we are underrepresenting pregnant and postpartum amenorrheic women, whose unmet need 

classification is intended to be unrelated to current sexual activity. However, we wanted to maintain a 

consistent denominator with the analysis on contraceptive use. Finally, contraceptive prevalence was 

estimated based on women’s own reports of “current” use. Our analysis showed that this measure provides 

estimates similar to estimates based on the calendar data for sexually unmarried women. However, 

underreporting of contraceptive use could be still possible for unmarried women, since they are more likely 

to be sexually active sporadically. For example, if a woman’s most recent sexual activity was several weeks 

before the survey, but within the last 30 days, she might not consider that she is currently using 

contraception. 
9 

3. Results 

The results are presented in four sections: 

(1) The distribution of women by marital status and socioeconomic profiles; 

(2) Contraceptive prevalence, method mix, and differentials in contraceptive use by 

background characteristics for each marriage group; 

(3) Levels and trends of unmet need for family planning and demand for family planning 

satisfied, as well as correlates of demand satisfied for each marriage group; 

(4) Analysis using logistic regression models to assess if contraceptive use differs between 

polygynous marriages and monogamous marriages after controlling for women’s age, 

number of living children, education, household wealth, employment status, and urbanrural residence 

3.1 Socioeconomic Profiles of Women by Marital Status 

Figure 1 shows the trend in distribution of women age 15-49 by marital status, for both surveys in each of 

the 21 countries studied. The percentage of women who have never been married ranges widely across 

countries and survey periods, from 16% in Mozambique (2003) to 60% in Namibia (2013). In the majority 

of surveys, between 25% and 35% of women have never been married. 

In each geographic region, the largest percentage of women age 15-49 are currently married and in 

monogamous partnerships—from 32% in Namibia (2016) to 60% in Malawi (2004). Polygynous marriages 

are most prevalent in Central and West Africa. In Cameroon, Cote d’Ivoire, Nigeria, and Sierra Leone, in 

at least one survey, more than 20% of women are in polygynous marriages. Polygynous marriages are also 

prevalent in some Eastern and Southern African countries. In Kenya, Malawi, Mozambique, Tanzania, and 

Zambia, in at least one survey, at least 10% of women are in polygamous marriages. Data on polygyny 

were not collected in Latin American and Caribbean countries. 
10 

Figure 1 Percent distribution of all women by marital status 

0

908070605040302010

100

2004

2011

2005

2011-12

2007

2013-14

2000

2012

1998

2011-12

2003

2014

2007

2013

2003

2013

2008

2013

2003

2014

2004

2014

2004

2015-16

2003

2011

2006-07

2013

2004-05

2015-16

2001-02

2013-14

2005-06

2015

2000

2010

2002

2013

2005-06

2011-12

2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia NigeriaSierra Leone Kenya Lesotho MalawiMozambiqueNamibia Tanzania Zambia ZimbabweColombiaDom. Rep.Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

Never married Monogamy Polygyny Separated/divorced Widowed
11 

Across study countries, the percentage of women who are separated or divorced ranges from 2% in Nigeria 

(2013) to 21% in the Dominican Republic (2013). Generally, the prevalence of separated or divorced 

women is highest in Latin America and the Caribbean. Widowhood, by contrast, is least common in Latin 

America and the Caribbean, ranging from 0.4% to 2%, and most common in Eastern and Southern Africa, 

ranging from 1% to 9%. 

Tables 2-4 present the percent distributions by background characteristics, separately for currently married, 

never-married, and formerly married women. As Table 2 shows, in most countries, women age 15-19 make 

up the smallest percentage of currently married women. While in most countries more than 50% of currently 

married women live in rural areas, the percentage varies widely, from 13% in Gabon (2012) to 84% in 

Malawi (2004 and 2015-16). In all regions, currently married women are roughly evenly distributed across 

the wealth quintiles, but educational attainment differs across regions. At one extreme, in Western Africa 

between 28% and 78% of currently married women have no education. All other regions have a lower 

prevalence of currently married women without educational attainment—with a range of 7% to 29% in 

Central Africa, 1% to 48% in Eastern and Southern Africa, and 3% to 8% in Latin America and the 

Caribbean. 

In countries of Central and Western Africa, the level of employment is high among currently married 

women, with about two-thirds employed except in Gabon, Liberia, and Nigeria. In the other regions, the 

percent employed ranges more widely, from 33% to 84% in Eastern and Southern Africa and from 38% to 

63% in Latin America and the Caribbean. In all surveys except Zambia (2013-14) and Congo Democratic 

Republic (2013-14), women with 1-2 children are the largest percentage of currently married women. 

Between 24% (Cameroon 2004) and 39% (Dominican Republic 2002) of married women have 3-4 children, 

while between 8% (Colombia 2010) and 33% (Congo Democratic Republic 2013-14) have 5 or more. 

Table 3 shows that in all countries except Colombia (2010), the greatest share of never-married women are 

age 15-19, followed by age 20-24; in all countries, less than 4% of never-married women are age 45-49. 

The percentage of never-married women living in rural areas varies widely, from 9% in Gabon (2012) to 

74% in Malawi (2015-16). Compared with currently married women, lack of education is less prevalent 

among never-married women. It is most prevalent in West Africa, ranging from 4% in Ghana (2014) to 

38% in Cote d'Ivoire (1998-99), and is lowest in Latin America and the Caribbean, at below 3%. Nevermarried women are concentrated in the fourth and highest wealth levels, with a range from 47% in Namibia 

(2006-7) to 70% in Sierra Leone (2008) in these two top quintiles. Employment among never-married 

women ranges from 16% in Gabon (2000) to 61% in Cote d’Ivoire (1998-9). In most countries, the great 

majority of never-married women have no living children. 

As Table 4 shows, formerly married women tend to be fairly evenly distributed across the age groups 

between 25 and 49 years, but with a smaller percentage age 20-24 and an even smaller percentage age 15-

19. Between 12% (Gabon 2012) and 86% (Malawi) of formerly married women live in rural areas. The 

formerly married are slightly under-represented in the lowest wealth quintile; in 31 of the 42 surveys less 

than 20% are in the lowest quintile. The level of employment is high among formerly married women, at 

50% or higher in all surveys except Kenya (2014) and Zimbabwe (2005-06), and at 75% or higher in 18 

surveys. On average, formerly married women are most likely to have 1-2 children. 
12 

Table 2 Percent distribution of currently married women by background characteristics Country/Survey 

Age Number of living children Education Wealth Employment Residence 

15-19 20-24 25-29 30-34 35-39 40-44 45-49 None 1-2 3-4 5+ None Primary

Secondary+ Lowest Second Middle Fourth Highest Un- employed Em- ployed Urban Rural 

Central Africa

Cameroon 2004 11.6 21.8 20.2 16.0 13.0 9.6 7.8 14.4 35.3 24.8 25.4 28.7 40.3 31.0 22.9 18.4 19.0 19.9 19.8 32.9 67.1 48.8 51.2

Cameroon 2011 8.9 19.8 21.7 16.5 14.2 10.2 8.8 10.9 34.5 27.8 26.8 27.3 37.5 35.2 20.3 19.4 19.0 20.7 20.6 29.8 70.2 47.3 52.7Congo 2005 6.5 21.0 21.3 18.5 15.2 10.0 7.5 9.6 40.7 30.0 19.7 9.0 30.4 60.5 19.6 19.4 19.3 20.4 21.4 31.5 68.5 52.7 47.3 Congo 2011-12 6.6 17.2 22.8 18.5 16.7 10.1 8.1 6.3 40.5 32.1 21.1 7.2 26.7 66.1 19.3 19.4 20.3 21.4 19.6 26.0 74.0 64.1 35.9 DR Congo 2007 6.9 22.4 20.1 17.5 13.5 11.1 8.6 9.9 34.4 25.8 29.9 24.0 41.5 34.5 19.1 22.2 22.2 19.5 17.0 26.1 73.9 40.3 59.7 DR Congo 2013-14 7.1 18.4 23.3 18.2 15.0 10.4 7.5 7.7 31.6 27.7 32.9 19.2 41.9 38.9 20.1 22.1 20.6 19.1 18.0 24.4 75.6 32.1 67.9 Gabon 2000 8.6 19.8 19.2 19.3 14.9 10.7 7.6 13.9 35.6 24.3 26.2 7.9 38.7 53.4 16.2 20.3 20.9 21.9 20.8 52.0 48.0 76.3 23.7 Gabon 2012 5.4 15.9 21.8 19.1 17.2 12.3 8.3 11.2 39.6 28.4 20.8 7.0 24.9 68.0 15.5 19.7 22.0 22.7 20.2 47.2 52.8 86.8 13.2 

Western Africa

Cote d'Ivoire 1998 10.0 18.7 19.7 18.2 15.5 10.1 7.8 11.4 35.7 24.9 28.0 65.7 25.5 8.8 24.6 19.5 19.4 20.0 16.5 16.3 83.7 34.3 65.7 

Cote d'Ivoire 2011-12 6.6 17.3 22.0 19.2 15.2 11.3 8.4 8.8 34.8 29.9 26.5 63.7 24.4 11.9 21.5 19.5 19.5 20.5 19.0 27.3 72.7 41.6 58.4 Ghana 2003 3.9 14.9 20.8 18.9 17.5 13.3 10.6 8.7 36.1 30.2 25.0 38.1 20.0 41.8 21.2 19.4 19.5 19.6 20.3 11.7 88.3 40.5 59.5 Ghana 2014 2.0 11.4 20.0 20.3 19.5 15.4 11.5 7.0 35.7 33.7 23.6 27.8 18.4 53.8 19.1 18.1 18.8 20.5 23.5 15.5 84.5 50.1 49.9 Liberia 2007 5.5 16.3 18.6 17.7 17.9 12.0 11.9 6.7 35.5 32.1 25.8 52.3 28.7 18.9 20.7 21.9 20.9 19.2 17.2 32.3 67.7 33.9 66.1 Liberia 2013 5.5 16.0 21.7 17.8 17.2 11.5 10.3 5.6 36.6 31.3 26.4 44.9 26.8 28.3 21.0 20.3 20.1 20.6 18.0 36.4 63.6 53.8 46.2 Nigeria 2003 10.2 17.1 21.5 15.9 14.3 11.6 9.4 12.3 32.8 27.1 27.7 53.9 22.0 24.1 21.5 21.4 20.4 17.9 18.8 35.6 64.4 30.6 69.4Nigeria 2013 8.1 15.7 21.2 17.5 15.5 11.6 10.4 10.1 31.0 29.8 29.0 48.4 19.2 32.4 23.1 21.5 17.9 18.1 19.4 30.6 69.4 36.4 63.6Sierra Leone 2008 6.5 14.7 25.9 16.3 18.5 10.4 7.8 9.3 38.7 32.4 19.5 77.5 10.9 11.7 21.3 20.7 21.5 19.0 17.5 21.1 78.9 28.2 71.8 Sierra Leone 2013 6.7 14.4 21.3 18.6 18.1 10.7 10.1 7.6 34.9 34.2 23.2 72.2 13.1 14.7 21.5 21.3 21.2 19.1 16.9 21.7 78.3 26.8 73.2 

Eastern and southern Africa 

Kenya 2003 6.8 19.6 21.5 17.7 14.0 12.5 7.9 7.2 34.8 29.9 28.1 15.5 58.6 25.9 19.3 19.4 18.6 19.6 23.1 35.1 64.9 22.2 77.8 Kenya 2014 3.7 16.9 24.6 19.2 15.6 11.3 8.7 5.9 39.6 32.0 22.6 9.1 54.4 36.5 17.1 17.7 18.9 21.3 24.9 67.4 32.6 39.3 60.7 

Lesotho 2004 7.9 21.0 18.9 16.0 13.1 12.9 10.3 10.4 46.9 26.1 16.5 2.3 63.5 34.2 15.5 19.1 17.5 23.0 24.9 57.4 42.6 19.9 80.1 Lesotho 2014 7.1 19.4 21.0 18.5 15.1 10.4 8.6 9.8 56.6 25.0 8.6 1.3 44.4 54.3 16.4 16.7 18.7 23.4 24.8 59.5 40.5 31.8 68.2 Malawi 2004 9.5 27.5 21.8 14.7 10.9 9.1 6.6 9.3 40.0 27.9 22.8 25.9 62.8 11.3 15.1 21.5 22.3 21.4 19.7 41.6 58.4 16.1 83.9 Malawi 2015-16 7.7 22.6 19.9 18.5 14.4 9.6 7.2 6.6 37.6 32.2 23.6 14.2 64.3 21.5 18.7 20.9 19.8 19.5 21.1 32.7 67.3 16.2 83.8 Mozambique 2003 10.7 20.0 20.7 17.1 13.3 10.0 8.2 12.1 36.3 28.7 22.9 48.2 47.5 4.3 25.9 19.0 21.3 16.7 17.1 21.9 78.1 29.0 71.0 .0Mozambique 2011 12.2 19.3 19.2 17.1 14.5 9.7 8.1 11.6 36.1 28.6 23.7 36.1 52.0 11.9 20.1 20.9 20.3 20.5 18.3 58.6 41.4 29.5 70.5 Namibia 2006-07 3.4 11.5 18.1 21.8 17.7 15.1 12.3 7.8 42.0 30.8 19.4 11.8 30.3 57.8 17.1 14.5 20.2 23.1 25.0 46.5 53.5 50.2 49.8 Namibia 2013 3.3 11.2 17.9 20.3 19.0 15.9 12.4 8.2 43.2 32.0 16.7 7.5 23 69.5 17.9 17.3 19.2 20.0 25.7 48.3 51.7 58.3 41.7 Tanzania 2004-05 8.5 20.1 21.7 18.6 12.7 10.0 8.3 9.4 37.0 28.2 25.5 28.7 65.9 5.4 19.3 20.5 19.9 19.6 20.7 15.8 84.2 23.7 76.3 Tanzania 2015-16 8.1 18.0 19.7 16.8 15.9 12.6 8.9 8.1 36.4 29.0 26.4 19.0 66.0 15.0 20.3 18.6 18.8 20.0 22.3 21.6 78.4 30.9 69.1 Zambia 2001-02 9.3 23.1 22.5 16.1 12.6 9.6 6.8 8.9 35.8 27.3 28.0 14.1 61.9 24.0 19.8 19.1 21.8 20.1 19.2 40.0 60.0 35.4 64.6 Zambia 2013-14 6.2 17.1 22.1 20.0 15.9 11.2 7.4 4.9 31.3 30.9 32.8 11 55.0 34.0 19.2 20.3 19.8 20.9 19.8 44.5 55.5 40.1 59.9 Zimbabwe 2005-06 8.7 23.3 21.9 18.1 10.8 9.4 7.7 9.0 47.1 26.5 17.4 5.4 37.1 57.5 20.1 19.4 17.6 23.0 19.9 62.2 37.8 33.9 66.1Zimbabwe 2015 7.0 17.0 20.8 21.7 15.8 11.5 6.2 6.9 43.7 36.3 13.1 1.4 29.7 68.9 19.4 19.4 17.4 22.8 21.0 55.9 44.1 34.1 65.9 

Latin America and the Caribbean 

Colombia 2000 5.5 13.7 17.5 18.4 18.3 14.9 11.6 7.5 50.2 31.6 10.8 4.4 39.7 56.0 18.3 21.3 21.5 20.3 18.7 52.8 47.2 71.9 28.1 Colombia 2010 0.1 4.8 12.2 16.8 17.5 16.9 16.9 8.5 55.0 29.0 7.5 2.4 29.5 68.1 19.8 20.8 21.0 20.3 18.2 47.3 52.7 74.4 25.6 Dom. Rep. 2002 7.3 15.4 17.8 18.2 17.2 13.1 10.9 8.6 40.0 39.1 12.3 5.0 51.7 43.2 17.0 20.9 21.2 20.8 20.1 60.7 39.3 65.2 34.8

Dom. Rep. 2013 7.4 15.6 16.6 17.7 15.8 14.3 12.5 10.3 46.0 36.0 7.8 2.8 36.7 60.5 18.6 21.6 20.7 19.8 19.4 50.8 49.2 73.6 26.4Honduras 2005-06 7.9 17.5 20.7 17.7 14.6 12.1 9.5 6.8 40.6 29.9 22.6 7.9 66.0 26.1 17.7 18.9 20.5 21.9 20.9 62.1 37.9 49.0 51.0 Honduras 2011-12 8.9 16.3 19.2 17.8 15.5 12.4 10.0 8.8 45.0 30.6 15.7 4.9 59.9 35.2 18.6 19.3 20.7 21.6 19.7 59.0 41.0 48.7 51.3 Peru 2000 3.7 12.6 17.6 20.0 17.5 16.2 12.3 5.4 44.5 30.2 19.9 7.4 36.9 55.8 18.5 20.5 21.8 20.9 18.3 42.1 57.9 63.9 36.1 Peru 2012 3.6 11.3 15.9 18.7 18.5 17.1 14.8 6.1 52.2 29.5 12.2 3.4 30.4 66.1 18.5 21.4 22.2 19.9 18.0 37.1 62.9 70.0 30.0 
13 

Table 3 Percent distribution of never-married women by background characteristics Country/Survey

Age Education Wealth Employment Number of living children Residence 

15-19 20-24 25-29 30-34 35-39 40-44 45-49 None 

Primary Secon- dary+ Lowest Second Middle Fourth Highest Un- employed Em- ployed None 1-2 3-4 5+ Urban Rural 

Central Africa 

Cameroon 2004 70.0 20.5 5.7 2.0 0.9 0.7 0.2 5.7 31.8 62.4 9.5 11.2 17.8 24.5 37.0 71.1 28.9 86.0 12.9 1.0 0.1 68.9 31.1 Cameroon 2011 61.6 23.6 8.7 3.5 1.4 0.9 0.4 4.2 23 72.8 8.1 14.4 17.9 26.7 33.0 61.0 39.0 81.0 16.5 1.9 0.6 66.0 34.0 Congo 2005 60.2 23.3 9.9 2.6 2.7 .01 0.3 3.5 30.3 66.2 14.4 16.8 19.8 21.8 27.2 66.1 33.9 75.6 21.4 2.6 0.5 62.5 37.5 Congo 2011-12 59.6 23.7 9.5 3.4 1.9 1.4 0.6 2.3 17.2 80.5 11.3 15.3 19.5 24.0 29.9 65.6 34.4 76.2 21.8 1.9 0.1 76.7 23.3 DR Congo 2007 63.0 25.2 7.8 2.1 1.3 0.3 0.3 10.1 31.0 58.9 12.4 12.2 16.3 18.8 40.3 66.9 33.1 91.1 8.3 0.5 0.2 60.3 39.7 DR Congo 2013-14 62.9 24.2 7.5 2.7 1.2 0.9 0.5 5.3 23.5 71.2 11.8 13.3 14.4 20.3 40.3 58.3 41.7 84.3 14.5 1.0 0.2 53.7 46.3 Gabon 2000 61.1 24.2 8.7 3.4 1.4 1.0 0.3 2.5 29.0 68.6 11.4 16.3 21.3 21.1 29.9 84.1 15.9 65.6 28.7 4.2 1.4 86.2 13.8 Gabon 2012 49.8 26.4 10.9 6.0 3.3 2.3 1.4 1.5 13.9 84.6 12.3 17.6 20.2 22.2 27.7 76 24.0 64.0 29.3 4.4 2.4 91.5 8.5 

Western Africa

Cote d'Ivoire 1998 62.5 22.3 9.4 3.5 1.8 0.3 0.1 38.1 33.6 28.3 8.1 14.3 12.3 23.4 42.0 39.3 60.7 75.3 21.7 1.7 1.2 56.6 43.4 

Cote d'Ivoire 2011-12 52.2 25.9 13.4 4.8 2.0 1.1 0.6 32.4 26.5 41.1 8.7 13.6 18.5 21.1 38.2 46.7 53.3 71.7 25.8 2.0 0.5 69.9 30.1 Ghana 2003 61.3 26.4 8.5 2.5 1.0 0.2 0.1 8.8 18.6 72.5 8.9 11.3 15.5 26.0 38.2 58.0 42.0 92.7 7.0 0.2 0.1 65.1 34.9 Ghana 2014 48.7 30.2 14.1 4.4 1.9 0.4 0.3 4.3 14.9 80.7 13.1 16.0 20.6 25.0 25.3 50.4 49.6 82.9 15.7 1.2 0.2 59.1 40.9 Liberia 2007 56.4 28.4 10.2 2.8 1.5 0.6 0.2 14.9 46.3 38.7 9.2 12.4 15.2 26.4 36.7 65.4 34.6 63.3 33.3 2.9 0.5 61.6 38.4 Liberia 2013 61.1 23.5 9.9 3.4 1.5 0.4 0.2 8.3 41.0 50.7 9.5 12.3 17.1 25.3 35.8 65.5 34.5 64.2 32.2 3.2 0.4 73.8 26.2 Nigeria 2003 59.4 28.0 8.8 2.5 0.7 0.3 0.3 6.5 18.8 74.7 10.2 12.2 18.9 24.2 34.5 69.4 30.6 93.0 6.8 0.1 0.0 43.8 56.2 Nigeria 2013 59.1 24.0 10.8 3.9 1.4 0.6 0.3 7.3 9.4 83.3 5.7 11.7 21.5 27.0 34.2 64.8 35.2 93.8 5.9 0.2 0.1 58.4 41.6 Sierra Leone 2008 59.1 24.2 8.5 5.1 1.4 1.2 0.5 19.4 21.2 59.4 8.5 10.0 12.0 21.9 47.6 58.5 41.5 74.1 23.0 1.6 1.3 64.9 35.1 Sierra Leone 2013 65.8 21.4 8.0 2.2 1.7 0.6 0.4 15.8 16.4 67.8 11.9 11.4 14.1 23.2 39.3 58.2 41.8 76.0 22.0 1.7 0.3 54.6 45.4 

Eastern and Southern Africa

Kenya 2003 60.5 25.1 8.4 2.6 1.4 1.2 0.7 3.7 57.3 39.0 11.8 15.7 17.9 22.8 31.8 60.6 39.4 81.3 16.7 1.5 0.5 29.3 70.7 Kenya 2014 56.2 24.7 9.5 4.0 2.8 1.6 1.2 1.6 38.5 59.9 12.0 16.7 20.4 20.3 30.7 82.5 17.5 78.5 19.4 1.4 0.6 42.5 57.5 Lesotho 2004 59.1 24.8 8.1 3.2 2.3 1.8 0.8 0.6 49.7 49.7 9.7 15.5 18.3 22.4 34.0 73.7 26.3 81.3 16.9 1.4 0.4 30.0 70.0 Lesotho 2014 53.6 24.9 10.6 5.7 2.4 1.5 1.3 0.2 23.7 76.1 10.6 13.1 18.4 27.1 30.8 73.9 26.1 78.8 19.3 1.6 0.3 43.0 57.0 Malawi 2004 77.4 17.5 3.7 0.7 0.4 0.2 0.2 2.7 61.1 36.2 13.3 11.9 15.5 21.1 38.2 67.5 32.5 90.6 9.3 0.1 0.1 27.1 72.9 Malawi 2015-16 74.5 18.9 4.2 1.3 0.5 0.4 0.2 2.0 54.8 43.2 12.4 13.8 17.7 20.6 35.5 61.3 38.7 87.4 11.6 0.7 0.2 26.4 73.6 Mozambique 2003 71.0 19.5 5.5 1.8 1.0 0.7 0.6 12.6 62.8 24.6 10.3 10.8 11.2 20.6 47.0 60.8 39.2 79.1 18.8 1.5 0.5 61.4 38.6 Mozambique 2011 71.8 15.0 6.5 3.0 1.7 1.0 1.0 9.5 45.3 45.2 11.1 12.2 14.3 18.6 43.8 76.6 23.4 79.2 17.2 2.5 1.1 51.8 48.2 Namibia 2006-07 37.4 24.8 15.8 9.9 5.7 4.3 2.1 2.8 20.0 77.1 15.5 18.4 18.8 23.5 23.9 62.2 37.8 54.9 33.7 8.7 2.7 47.8 52.2 Namibia 2013 32.9 25.5 15.8 10.2 7.4 5.1 3.1 2.6 16.6 80.8 13.7 18.1 20.0 24.6 23.6 64.0 36.0 50.2 36.7 10.3 2.8 55.5 44.5 Tanzania 2004-05 68.2 20.2 7.2 2.7 0.7 0.3 0.8 11.9 68.5 19.6 12.4 13.8 15.7 18.6 39.4 43.4 56.6 83.4 14.8 1.4 0.3 40.7 59.3 Tanzania 2015-16 64.7 22.3 7.2 2.6 2.0 0.8 0.5 3.3 47.2 49.6 9.2 12.0 14.2 24.2 40.4 51.3 48.7 81.5 16.8 1.2 0.4 48.2 51.8 Zambia 2001-02 69.7 21.6 5.8 2.3 0.3 0.2 0.1 5.4 47.5 47.2 14.0 13.1 16.1 21.4 35.4 66.2 33.8 81.2 17.8 0.8 0.2 49.8 50.2 Zambia 2013-14 64.5 23.9 6.7 2.9 1.2 0.6 0.1 1.8 27.2 71.0 10.9 12.2 16.2 21.8 38.9 74.4 25.6 77.4 21.3 1.1 0.2 58.0 42.0 Zimbabwe 2005-06 68.2 23.1 5.5 1.8 1.0 0.2 0.2 0.4 18.7 80.9 11.6 12.2 16.0 20.9 39.3 72.6 27.4 89.4 9.8 0.7 0.1 50.9 49.1 Zimbabwe 2015 67.6 19.7 6.3 3.2 1.3 0.9 1.0 0.3 14.5 85.2 11.2 13.5 17.1 22.1 36.1 75.2 24.8 88.2 11.2 0.5 0.1 47.3 52.7 

Latin America and the Caribbean 

Colombia 2000 47.3 25.2 11.3 6.7 4.0 3.4 2.1 1.5 17.9 80.6 11.7 14.4 19.4 25.7 28.9 58.3 41.7 83.8 15.1 0.9 0.3 82.2 17.8 Colombia 2010 18.9 38.9 19.2 9.3 5.0 3.0 2.7 0.4 9.5 90.2 14.1 17.3 20.7 23.6 24.3 65.0 35.0 84.7 14.3 0.8 0.2 81.6 18.4 Dom. Rep. 2002 59.6 25.4 8.7 3.3 1.6 0.9 0.6 0.8 25.8 73.4 9.0 13.7 19.0 25.0 33.3 69.8 30.2 94.0 5.5 0.4 0.0 72.9 27.1 Dom. Rep. 2013 58.0 24.9 10.4 2.4 1.7 1.5 1.1 0.4 11.7 87.9 9.9 14.5 19.0 25.2 31.4 67.7 32.3 92.9 6.5 0.5 0.0 78.2 21.8 Honduras 2005-06 61.0 22.9 8.2 3.0 2.5 1.5 0.9 2.5 40.5 57.0 11.3 15.0 18.4 24.1 31.3 61.5 38.5 90.4 8.5 0.8 0.3 60.1 39.9 Honduras 2011-12 56.7 23.4 9.5 4.9 2.5 1.7 1.3 1.3 28.2 70.5 12.6 15.1 19.3 24.3 28.7 60.0 40.0 88.3 10.4 1.0 0.3 60.2 39.8 Peru 2000 50.2 25.1 12.0 5.6 3.2 2.3 1.7 1.3 15.3 83.5 9.3 13.7 19.2 24.5 33.3 50.4 49.6 89.6 9.8 0.5 0.1 77.6 22.4 Peru 2012 49.3 22.4 11.8 6.5 4.5 3.3 2.2 0.6 8.6 90.7 11.5 14.6 19.8 24.2 29.9 45.8 54.2 87.5 11.9 0.6 0.0 80.4 19.6 
14 

Table 4 Percent distribution of formerly married women by background characteristics Country/Survey 

Age Education Wealth Employment Number of living children Residence 

15-19 20-24 25-29 30-34 35-39 40-44 45-49 None Primary

Secondary+ Lowest Second Middle Fourth Highest Un- employed Em- ployed None 1-2 3-4 5+ Urban Rural 

Central Africa 

Cameroon 2004 6.9 17.5 16.5 16.1 13.9 13.2 15.9 19.2 43.7 37.1 13.4 16.3 24.3 24.4 21.5 31.7 68.3 14.5 39.4 21.3 24.8 61.8 38.2 Cameroon 2011 5.1 13.4 14.7 13.3 17.1 15.6 20.9 17.6 41.2 41.3 11.0 17.3 22.3 25.8 23.6 21.7 78.3 13.4 38.0 26.6 22.0 62.7 37.3 Congo 2005 5.6 17.5 18.5 14.5 17.1 13.3 13.6 7.9 30.0 62.1 16.3 20.9 22.7 24.1 16.0 33.5 66.5 7.6 47.9 26.4 18.0 59.8 40.2 Congo 2011-12 6.6 16.3 18.5 17.4 14.7 13.8 12.7 6.3 24.0 69.7 16.3 27.2 23.8 19.2 13.5 23.1 76.9 4.6 49.5 31.2 14.7 71.8 28.2 DR Congo 2007 4.4 18.7 14.4 14.2 12.7 18.0 17.6 25.8 37.2 37.0 24.8 21.0 19.0 15.0 20.3 24.1 75.9 11.3 38.9 25.7 24.1 43.0 57.0 DR Congo 2013-14 5.9 15.3 18.9 15.5 16.7 13.0 14.7 17.7 39.6 42.8 26.5 14.2 17.5 18.8 23.0 20.4 79.6 7.6 37.7 30.5 24.2 38.9 61.1 Gabon 2000 8.3 13.4 19.4 18.4 17.0 14.7 8.8 4.3 39.7 56.1 17.2 21.9 25.6 21.8 13.5 43.5 56.5 10.8 40.0 24.8 24.4 81.1 18.9 Gabon 2012 3.0 13.5 19.9 19.1 12.7 14.2 17.6 1.5 27.5 71.0 17.2 22.5 20.6 21.0 18.6 34.9 65.1 11.7 46.1 21.1 21.1 88.0 12.0 

Western Africa

Cote d'Ivoire 1998 4.6 8.8 18.7 18.9 16.8 15.6 16.5 48.8 35.5 15.7 19.4 14.5 19.2 22.5 24.4 14.3 85.7 10.8 40.1 24.9 24.1 44.6 55.4 Cote d'Ivoire 2011-12 2.7 10.1 18.0 21.3 15.7 15.1 17.0 48.6 29.1 22.2 15.5 18.8 16.3 26.6 22.9 24.4 75.6 12.0 42.0 27.9 18.0 59.0 41.0 Ghana 2003 3.7 10.6 14.3 17.3 16.0 19.5 18.6 21.2 23.6 55.2 13.8 15.0 24.2 24.7 22.3 12.3 87.7 12.5 39.7 28.7 19.1 50.7 49.3 

Ghana 2014 1.4 7.4 11.0 16.1 19.9 19.9 24.3 18.3 23.6 58.1 9.2 18.2 30.5 25.8 16.3 12.0 88.0 5.7 46.4 29.6 18.2 56.8 43.2 Liberia 2007 2.2 14.1 18.5 14.2 16.7 15.8 18.5 50.9 24.3 24.8 19.8 15.4 18.1 31.4 15.3 31.3 68.7 5.1 38.4 33.8 22.6 45.1 54.9 Liberia 2013 3.0 10.7 16.1 14.7 21.5 18.4 15.6 41.7 25.7 32.5 17.9 18.1 21.1 21.5 21.5 32.8 67.2 4.3 40.5 30.8 24.3 62.7 37.3 Nigeria 2003 7.3 12.1 18.6 12.6 10.9 17.8 20.7 46.9 25.6 27.4 18.9 17.5 17.8 28.6 17.2 29.3 70.7 14.4 35.4 20.9 29.2 42.4 57.6

Nigeria 2013 3.4 8.9 12.4 12.9 16.1 19.0 27.4 32.2 29.0 38.7 9.9 19.6 28.0 24.2 18.3 18.7 81.3 9.9 30.7 30.7 28.6 47.1 52.9 Sierra Leone 2008 2.7 8.0 21.2 16.2 19.9 14.0 18.0 68.4 14.0 17.6 18.8 18.9 16.6 25.6 20.2 20.3 79.7 8.6 40.4 30.7 20.3 41.4 58.6 Sierra Leone 2013 3.3 10.1 13.9 14.6 20.2 16.1 21.8 66.0 12.6 21.4 17.8 17.7 16.3 19.9 28.2 18.8 81.2 7.5 37.6 33.6 21.3 41.5 58.5 

Eastern and Southern Africa 

Kenya 2003 5.3 13.8 14.5 17.8 17.3 17.4 13.8 22.2 56.8 21.0 15.5 16.5 18.1 22.9 27.0 24.4 75.6 7.0 37.2 29.3 26.5 29.8 70.2 Kenya 2014 2.1 10.7 19.5 16.5 17.7 18.4 15.1 9.6 58.9 31.5 16.6 18.9 19.7 21.7 23.1 61.4 38.6 3.6 44.2 32.5 19.7 44.8 55.2 Lesotho 2004 1.5 9.4 14.9 14.7 18.8 21.8 18.9 4.5 66.5 29.0 17.9 21.4 17.3 20.7 22.7 48.6 51.4 7.1 41.6 31.9 19.4 22.8 77.2 Lesotho 2014 1.2 9.8 12.7 20.1 18.0 18.6 19.7 2.1 52.5 45.4 16.5 17.6 20.1 20.5 25.3 42.9 57.1 8.8 52.6 28.3 10.3 40.0 60.0 Malawi 2004 5.6 17.1 19.1 16.9 14.6 12.5 14.2 30.6 58.3 11.1 36.6 18.1 16.1 11.7 17.5 32.0 68.0 6.9 41.1 28.6 23.4 14.5 85.5 Malawi 2015-16 5.4 16.2 15.9 18.8 17.6 13.8 12.2 17.8 62.8 19.4 33.6 18.5 16.3 14.2 17.5 22.8 77.2 4.5 35.7 34.4 25.5 15.9 84.1 Mozambique 2003 7.3 19.0 17.7 15.2 13.6 14.0 13.2 37.2 56.3 6.4 20.1 17.1 14.8 22.7 25.2 23.3 76.7 11.9 42.2 28.4 17.4 46.9 53.1 Mozambique 2011 6.2 14.4 17.0 17.3 16.1 12.1 16.9 36.2 48.1 15.7 23.3 15.7 16.8 21.3 22.9 49.7 50.3 10.6 39.9 30.6 19.0 37.8 62.2 Namibia 2006-07 0.8 7.0 14.5 15.2 16.4 24.2 21.8 11.9 37.1 50.9 22.7 18.0 17.8 24.1 17.6 46.2 53.8 5.1 38.2 34.4 22.2 48.1 51.9 Namibia 2013 1.6 7.7 11.8 11.6 18.7 23.3 25.3 7.5 28.9 63.6 20.4 16.5 17.6 24.9 20.6 43 57.0 6.2 43.1 31.8 19.0 57.2 42.8 Tanzania 2004-05 3.7 12.8 20.3 18.4 15.2 13.3 16.4 22.5 72.9 4.6 20.3 19.1 19.0 19.6 22.0 9.9 90.1 7.5 42.2 27.3 22.9 32.0 68.0 Tanzania 2015-16 3.9 15.1 15.8 16.8 15.7 17.9 14.9 16.3 71.3 12.4 15.7 20.5 18.3 21.6 23.8 10.7 89.3 6.9 41.1 28.4 23.6 38.8 61.2 Zambia 2001-02 4.8 15.8 19.6 16.2 15.8 13.8 13.9 15.0 59.3 25.7 24.3 16.2 18.5 23.0 18.0 32.4 67.6 10.1 38.9 26.4 24.6 43.7 56.3 Zambia 2013-14 3.2 11.5 16.4 18.5 19.2 17.0 14.2 10.8 51.4 37.8 24.0 15.2 19.3 22.8 18.7 31.3 68.7 4.4 38.2 32.8 24.6 49.6 50.4 Zimbabwe 2005-06 4.7 14.5 15.3 17.7 18.6 15.4 13.8 7.0 39.9 53.1 17.6 15.2 18.9 23.6 24.7 50.1 49.9 8.2 47.0 29.1 15.8 39.4 60.6 Zimbabwe 2015 5.3 12.2 17.2 15.9 17.7 18.2 13.6 2.4 29.4 68.2 17.7 12.7 19.0 27.1 23.5 39.9 60.1 5.3 54.2 32.2 8.3 41.8 58.2 

Latin America and the Caribbean 

Colombia 2000 4.3 10.7 14.2 15.6 18.9 18.4 18.0 3.7 36.8 59.4 11.0 18.3 24.1 23.6 23.0 31.3 68.7 7.2 55.3 27.5 10.0 85.4 14.6 Colombia 2010 0.1 3.9 10.5 14.2 15.7 16.2 19.1 2.1 27.0 70.9 12.7 21.1 25.4 22.3 18.6 25.8 74.2 7.6 58.2 27.1 7.1 85.0 15.0 Dom. Rep. 2002 8.1 15.6 16.5 14.0 16.8 13.1 15.9 3.7 50.5 45.9 13.3 21.1 21.8 23.0 20.8 45.0 55.0 11.2 51.4 28.6 8.9 74.5 25.5Dom. Rep. 2013 7.5 14.8 14.8 16.2 14.8 14.5 17.4 1.8 34.5 63.7 16.2 21.0 22.5 23.9 16.5 37.6 62.4 10.7 52.2 29.7 7.3 78.7 21.3Honduras 2005-06 7.4 15.3 15.8 15.4 16.1 14.4 15.6 6.8 62.7 30.5 12.1 15.2 22.9 27.0 22.8 39.5 60.5 7.4 46.2 29.0 17.4 61.3 38.7 Honduras 2011-12 6.9 15.2 15.1 17.9 16.2 15.0 13.6 5.1 55.2 39.7 11.8 17.4 24.5 24.7 21.6 34.9 65.1 8.1 50.2 29.1 12.6 63.4 36.6 Peru 2000 2.5 11.7 13.2 17.7 18.8 16.5 19.7 6.9 30.5 62.6 13.0 17.8 22.7 23.1 23.4 22.7 77.3 5.6 52.9 26.7 14.8 76.7 23.3 Peru 2012 2.7 9.2 12.4 15.8 18.0 20.5 21.4 2.5 21.9 75.6 9.9 18.0 24.4 27.1 20.6 15.7 84.3 6.0 60.8 23.3 9.9 83.4 16.6 
15 

3.2 Contraceptive Use and Marital Status 

Levels and trends in contraceptive use by marital status 

Figures 2-4 show contraceptive prevalence (both modern and traditional methods) among currently married, 

never-married, and formerly married women who were sexually active in the last month before the survey. 

Overall, currently married women in the Latin American and Caribbean countries studied have the highest 

contraceptive prevalence. Among the most recent surveys, contraceptive prevalence ranges from 74% in 

Dominican Republic (2013) to 82% in Colombia (2010) and Peru (2012). Married women in this region 

predominantly use modern contraceptive methods. For example, in Colombia (2010), three-quarters of 

married women reported using a modern method and only 6% reported using a traditional method. 

Traditional method use is generally low, except in Peru (2012), where 26% of married women reported 

using a traditional method an increase from 20% in the earlier survey. While contraceptive prevalence 

increased overall between the two surveys in all four countries, the changes were small, averaging 4 

percentage points. In Colombia and Honduras use of modern contraceptive methods increased more, by 9 

and 6 percentage points, respectively. 
16 

Figure 2 Contraceptive prevalence among sexually active currently married women 

15 16 14 21

7 9

15

22

10 15

26 27

13

23

9 10 9

21

38

59

41

66

32

64

18 14

59 58

23

36

30

48

63

70 67

76

68 70

63

69

55 56

14 11

36 29

15 14

21

13

10

7

8 6

1

2

4 6 2

2

9

5

2

1

5

1

3

0

2 1

7

7

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5

2

1

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6

4 4 10 11 20 26

0

908070605040302010

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2007

2013

2003

2013

2008

2013

2003

2014

2004

2014

2004

2015-16

2003

2011

2006-07

2013

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2013-14

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2000

2010

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2005-06

2011-12

2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

Modern method Traditional method
17 

Among the three sub-regions of sub-Saharan Africa, married women in Eastern and Southern Africa have 

the highest contraceptive prevalence. Contraceptive prevalence among married women is 60% or higher in 

both surveys in Zimbabwe and Namibia, and in the most recent survey in Malawi, Lesotho, and Kenya. An 

increasing trend in contraceptive prevalence among married women is also found in all Eastern and 

Southern African countries except Mozambique, where the prevalence decreased from 21% in 2003 to 14% 

in 2011. Five countries—Zambia, Tanzania, Kenya, Lesotho, and Malawi—show the highest increases, 

from 13 percentage points in Tanzania to 28 percentage points in Malawi. The rise is largely due to the 

increased use of modern methods. Use of traditional methods among currently married women is low in all 

of these countries, at 10% or lower. 

In Central Africa and West Africa, married women generally reported low levels of contraceptive use, 

below 30% in most of the study countries. Married women in Central Africa reported more use of traditional 

methods than modern methods. For example, while half of married women in Congo Democratic Republic 

reported using contraception, most of them (60% to 70%) used a traditional method. The overall 

contraceptive prevalence in Central African countries remains little changed between the two surveys. In 

West Africa, contraceptive prevalence increased most in Liberia and Sierra Leone, especially for modern 

methods. 

Figure 3 shows contraceptive prevalence among sexually active never-married women. Similar to married 

women, never-married women in Latin America and the Caribbean reported the highest levels of 

contraceptive use, from 65% in Dominican Republic (2013) to 87% in Peru (2012). Between the two 

surveys, use of modern methods increased by 10 percentage points in Colombia and Honduras and 23 

percentage points in Peru, while use of traditional methods declined in three of the four countries. 
18 

Figure 3 Contraceptive prevalence among sexually active never-married women 

55 53 25 42 28 22 33 48 30 30 32 29 24 35 41 55 27 57 44 66 50 69 23 34 49 33 79 78 35 41 26 33 50 58 63 74 43 53 56 59 436622

11

51

32

28

24

33

11

32

9

14 18

5

3

13

16

10

4

13

5

1

2

1

1

3

4

13

4

1

1

3

24

8

17

12

14

17

36

21

0

908070605040302010

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2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia NigeriaSierra Leone Kenya Lesotho MalawiMozambiqueNamibia Tanzania Zambia ZimbabweColombiaDom. Rep.Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

Traditional method Modern method
19 

In sub-Saharan Africa, overall contraceptive prevalence appears to be higher among never-married women 

than currently married women, especially in Central Africa and Western Africa. Most of the Eastern and 

Southern African countries show increasing contraceptive prevalence among never-married women. The 

greatest increase has occurred in Malawi, Kenya, Lesotho, and Tanzania, ranging from 11 percentage points 

in Malawi to 20 percentage points in Lesotho. 

In Central Africa, the overall contraceptive prevalence has declined in all countries, most notably in 

Cameroon and Congo Democratic Republic, where contraceptive use dropped by 10 percentage points or 

more. Use of modern methods, however, has increased in Congo and Gabon, by 17 and 16 percentage 

points, respectively. Conversely, the use of traditional method in these two countries has declined, by about 

20 percentage points. 

In West Africa, contraceptive prevalence has increased in Liberia, Nigeria, and Sierra Leone, mainly due 

to increasing use of modern methods. In Sierra Leone, 57% of never-married women in 2008 reported use 

of a modern method, more than twice the 27% in 2013. In Cote d’Ivoire, modern contraceptive use remained 

the same between 1998 and 2011-12, but use of traditional methods decreased substantially, from 32% to 

9%. 

Figure 4 shows contraceptive prevalence among formerly married women who were sexually active in the 

last month before the survey. The study countries in Latin America and the Caribbean have experienced a 

minor increase in overall contraceptive use among formerly married women. Increases in modern 

contraceptive use are more prominent in Colombia than the other three countries, from 66% in 2000 to 77% 

in 2010. In all Eastern and Southern African countries except Mozambique, contraceptive use among 

formerly married women increased during the study period, varying by country, with large increases in 

Lesotho and Malawi. In Lesotho, 76% of formerly married women used a contraceptive method in 2014 

compared with 43% in 2004. 

Changes in contraceptive prevalence are less apparent in both Central Africa and West Africa, except 

Liberia and Sierra Leone. In both these countries, the use of modern contraception has risen by 10 

percentage points or more. 
20 

Figure 4 Contraceptive prevalence among sexually 

active formerly married women 

31 34 30 32

11 15

26

36

16

30 30 33

21

31 29 33

13

45 45

56

43

76

26

54

34

26

66 69

37

50

35

46

69 72 66

77

60

66 67

73

52

59

21

9

37 33

17

18

23

14

21

13

5

6

3

2 4

19

6

2

6

4

2

3

1

3

0

1

1

6

4

2

2

1

0 14

4

4

4 5

6

20

23

0

908070605040302010

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2012

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2007

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2003

2013

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2004

2014

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2001-02

2013-14

2005-06

2015

2000

2010

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2005-06

2011-12

2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

Modern method Traditional method
21 

To facilitate comparisons of contraceptive prevalence by marital status, Figure 5 presents the percentage of 

women in each marriage group using a modern or traditional method, based on the country’s most recent 

survey. In Latin America and the Caribbean, differences in contraceptive prevalence by marital status are 

negligible. In sub-Saharan Africa, however, variations by marital status are more apparent. In more than 

half of the countries, never-married women are more likely to use a contraceptive method compared with 

currently married women and formerly married women. In the majority of countries, a higher percentage 

of never-married women reported use of a modern method than the other two marriage groups. Within subSaharan Africa, the most prominent differences by marital status are observed in Central Africa. In all four 

Central African countries studied, never-married women reported the highest levels of use of any 

contraceptive method and also of modern methods, followed by formerly married women. Currently 

married women have the lowest contraceptive prevalence for any method and for modern methods. Most 

countries in West Africa and Eastern and Southern Africa show a similar pattern, with a few exceptions 

including Malawi, Zambia, and Zimbabwe, where never-married women have lower contraceptive 

prevalence than the other two groups. 
22 

Figure 5 Contraceptive prevalence among sexually active women by marital status, most recent survey only 

16

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Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa Western Africa Eastern and Southern Africa Latin America and Caribean

Modern method Traditional method
23 

Method mix by marital status 

Figure 6 shows the method mix—the share of use of each method—among users of modern methods for 

the three marriage groups, based on the most recent survey in each country studied. Countries in all three 

African sub-regions show a skewed method mix in all three groups. In Central Africa, condoms appear to 

be the major contraceptive method used, accounting for 45% to 67% of modern contraceptive use among 

currently married women, 90% or more among never-married women, and 61-92% among formerly 

married women. Condoms are also commonly used in some Western African countries, including Cote 

d’Ivoire and Nigeria, particularly among never-married and formerly married women. Injectables are the 

most widely used method in Liberia and Sierra Leone, irrespective of women’s marital status. The pill is 

also used, at various levels, in all Western African countries by all marriage groups. The IUD and 

sterilization, however, are little used. 
24 

Figure 6 Method mix among sexually active women who use modern contraception by marital status, most recent survey only 

0

908070605040302010

100

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Cameroon Congo DRC Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Other modernCondomImplantInjectableIUDPillSterilization
25 

In almost all Eastern and Southern African countries, the most commonly used method among currently 

and formerly married women is injectables, but condom use is most common among never-married women. 

Use of the pill is uncommon in most countries but is widespread among currently married women in 

Zimbabwe, reported by 63% of currently married modern-method users. 

Study countries in Latin America and the Caribbean appear to have a more balanced mix of methods 

compared with African countries. Notably, sterilization is the predominant method in Colombia, Dominican 

Republic, and Honduras among currently and formerly married women. Similar to African regions, condom 

use is more prevalent among never-married women than among the other two marriage groups in Latin 

America and the Caribbean. 

Differentials in contraceptive use by background characteristics 

Tables 5-10 present percentages of currently married, never-married, and formerly married women who 

reported use of a contraceptive method, by women’s background characteristics—age, number of living 

children, education, household wealth status, employment status, and urban-rural residence. Data for these 

tables come from the most recent survey of each country. 

Age 

Table 5 shows contraceptive prevalence by age for each marriage group. Among currently married women 

contraceptive prevalence appears to have an inverted U-shaped relationship with age. While women in the 

youngest age group (15-19) and women in the oldest age group (45-49) have the lowest level of 

contraceptive use; women in middle age groups (25-29, 30-34, and 35-39) have the highest contraceptive 

use. Variations in contraceptive use by age are more apparent in Eastern and Southern Africa than in other 

regions. Most never-married women are age 15-29 and few are over age 30. Comparing age groups on 

which there are sufficient numbers of never-married women for analysis, in a majority of countries women 

age 15-19 reported the lowest contraceptive prevalence (15 of 21 countries), and women age 20-24 reported 

the highest (11 of 21 countries). In many countries, the assessment of age patterns among formerly married 

women is limited by the small number of women in this group. Nevertheless, in countries with a sufficient 

number of formerly married women, the inverted U-shaped relationship between contraceptive prevalence 

and age generally holds in most age groups, for example, in Central Africa and Latin America and the 

Caribbean. 
26 

Table 5 Contraceptive prevalence for sexually active currently married, never-married, and formerly married women, by women’s ageCountry 

Currently married Never-married Formerly married 

15-19 20-24 25-29 30-34 35-39 40-44 45-49 15-19 20-24 25-29 30-34 35-39 40-44 45-49 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Central Africa 

Cameroon 2011 12.3 17.2 18.3 17.7 18.2 14.4 9.3 50.8 60.5 55.0 51.8 (28.5) * * * 31 43.5 31.8 41.1 (20.7) (23.4) 

Congo 2011-12 28.2 21.0 24.7 22.6 21.7 13.6 5.0 40.6 47.1 41.4 (34.0) * * * (35.4) 38.2 39.5 30.1 50.9 14.4 4.6 DR Congo 2013-14 6.3 9.5 7.7 10.9 8.9 8.6 5.3 19.0 26.3 21.9 (23.9) * * * (13.5) 16.6 20.9 12.6 22.2 9.1 (5.6) Gabon 2012 19.8 26.4 25.0 28.4 18.4 14.5 11.3 51.7 49.6 41.2 38.7 (26.2) * * * (49.2) 42.6 27.6 24.0 44.9 (2.8) 

Western Africa 

Cote d'Ivoire 2011-12 6.4 15.4 17.3 17.0 17.9 13.5 6.9 29.5 30.1 36.3 (17.5) * * * * (45.6) (22.1) 48.1 * * * 

Ghana 2014 27.2 30.7 33.1 27.8 26.2 21.4 19.8 30.1 31.2 28.3 (8.0) * * * * * (41.5) 46.0 (15.0) * * Liberia 2013 14.7 30.1 26.3 28.4 23.5 17.2 7.1 30.9 39.9 34.9 (42.0) * * * * (44.1) 43.6 38.7 22.0 (24.0) (7.4) Nigeria 2013 1.1 6.4 9.2 13.3 14.7 15.5 8.7 47.2 59.8 58.1 51.9 (54.3) * * * * (34.3) 42.5 25.2 (28.5) (33.2) Sierra Leone 2013 9.8 20.7 22.3 26.9 23.1 19.1 10.4 53.7 62.9 58.5 67.8 (47.8) * * * * 52.4 54.8 44.3 (22.9) (32.0) 

Eastern and Southern Africa

Kenya 2014 41.8 56.1 62.6 64.8 61.7 57.8 40.5 47.0 76.3 (68.7) (59.5) * * * * (25.6) 71.0 75.4 (49.0) 35.4 (59.4) 

Lesotho 2014 45.3 64.7 69.2 71.7 77.0 63.3 40.7 68.6 63.6 82.9 (81.5) * * * * * (80.6) 78.9 (82.0) 76.1 * Malawi 2015-16 41.5 61.6 68.2 71.2 69.2 64.6 53.6 31.4 35.9 (27.5) * * * * (37.6) 55.1 57.2 55.6 58.2 63.9 * Mozambique 2011 7.4 15.6 18.9 16.9 15.8 10.3 7.0 27.1 43.6 43.1 (28.3) * * * (21.4) 28.3 30.0 29.6 33.9 11.4 (13.6) Namibia 2013 34.0 56.9 59.7 61.6 59.4 58.3 55.7 71.9 78.2 84.4 74.8 79.2 80.3 (72.7) * * * 67.0 (77.7) 72.5 * 

Tanzania 2015-16 15.6 35.0 41.0 41.1 40.8 35.0 29.1 35.0 47.5 44.6 * * * * * 63.4 52.0 53.0 52.2 39.1 (39.4) 

Zambia 2013-14 38.3 48.5 52.5 52.2 50.6 47.7 29.6 17.2 45.3 57.3 (43.7) * * * * (50.7) 39.2 53.7 58.4 37.5 * Zimbabwe 2015 46.2 67.9 72.8 73.9 74.6 70.4 58.3 (34.4) 76.7 (65.7) * * * * * (57.5) (77.8) 77.9 (69.3) 82.2 * 

Latin America and the Caribbean

Colombia 2010 (58.4) 70.4 75.5 80.3 80.3 78.2 71.1 70.5 80.0 77.7 69.5 65.9 62.6 40.1 * 73.9 80.3 80.6 76.6 76.6 70.9 

Dom. Rep. 2013 53.8 59.6 69.2 70.9 79.3 76.8 75.3 51.6 48.9 (65.2) * * * NA 58.8 56.3 71.3 76.3 69.0 64.8 (61.7) 

Honduras 2011-12 55.1 67.7 69.0 73.8 74.7 72.1 60.5 56.1 62.8 63.4 (55.6) * * * (44.5) 66.3 80.7 78.3 75.6 (80.8) (64.8) 

Peru 2012 57.6 64.3 59.7 58.7 59.5 52.2 43.5 61.4 74.0 71.5 64.6 55.6 (30.8) * * 64.2 55.7 67.8 63.3 52.5 47.7 

Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. This applies to subsequent tables. 
27 

Number of Living Children 

Table 6 shows that among currently married women there is generally a negative relationship between 

contraceptive use and number of living children. In all countries, contraceptive prevalence is lowest among 

currently married women without children and highest among those with 3-4 children. The difference 

between these two groups is 50 percentage points or more in eight countries, including Kenya, Lesotho, 

Malawi, Zambia, Zimbabwe, Colombia, Dominican Republic, and Honduras. While in most countries 

contraceptive use is rare among women without children (less than 10%), contraceptive prevalence reaches 

30% or more for this group in a few countries—Namibia, Dominican Republic, Honduras, and Peru. The 

inverted relationship between contraceptive use and number of children generally holds among nevermarried and formerly married women although only in a few countries never married women have more 

than 2 children. Differences are particularly notable in the Latin America and the Caribbean countries 

studied. For example, in Dominican Republic and Honduras contraceptive prevalence among women with 

3-4 children is 50 percentage points higher than among women with no children. 

Table 6 Contraceptive prevalence for sexually active currently married, never-married, and formerly married women, by number of living children 

 

Country 

Currently married Never-married Formerly married 

None 1-2 3-4 5+ None 1-2 3-4 5+ None 1-2 3-4 5+ 

Central Africa 

Cameroon 2011 15.6 15.6 17.6 16.2 56.8 50.1 (32.8) * (25.5) 37.2 29.6 36.1 

Congo 2011-12 6.7 24.3 21.7 16.9 43.1 38.3 * * (27.1) 36.4 30.5 18.2 

DR Congo 2013-14 2.2 9.1 8.7 9.8 22.8 19.1 * * (17.4) 17.9 11.6 14.8 

Gabon 2012 10.9 23.6 25.9 20.8 48.7 47.8 (39.4) * (41.5) 40.9 33.0 22.8 

Western Africa 

Cote d'Ivoire 2011-12 3.6 13.8 18.9 17.0 31.4 27.0 (22.0) * (25.2) 30.6 (34.1) * 

Ghana 2014 13.5 25.4 30.5 29.9 28.0 29.8 * * * 27.7 (37.8) * 

Liberia 2013 6.7 22.9 24.9 24.5 26.4 49.9 (55.4) * * 30.3 35.1 28.0 

Nigeria 2013 1.2 8.8 14.0 11.8 56.4 46.3 * * * 45.8 33.3 23.7 

Sierra Leone 2013 5.1 19.4 24.5 24.1 54.7 64.6 (56.9) * * 40.9 62.7 (36.2) 

Eastern and Southern Africa 

Kenya 2014 14.3 62.6 66.6 52.6 56.8 84.9 * * * 57.7 66.9 37.8 

Lesotho 2014 19.2 72.1 73.9 53.5 66.5 80.2 * * * 80.1 (73.9) * 

Malawi 2015-16 4.0 65.3 71.2 70.7 26.7 60.9 * * (12.4) 47.3 70.1 60.2 

Mozambique 2011 1.5 16.1 18.3 14.3 30.9 41.5 * * 11.8 31.7 28.0 18.9 

Namibia 2013 31.3 59.5 67.1 52.6 74.1 81.7 78.9 77.7 * 57.8 81.4 * 

Tanzania 2015-16 2.6 37.2 43.0 38.1 33.7 54.3 * * (25.8) 50.8 53.8 51.1 

Zambia 2013-14 4.0 48.7 54.3 49.5 21.3 53.6 * * (14.9) 48.9 54.9 39.8 

Zimbabwe 2015 6.2 71.7 78.6 71.9 47.9 70.0 * * * 70.2 77.1 * 

Latin America and the Caribbean 

Colombia 2010 36.0 75.9 85.6 78.9 72.1 80.5 (79.1) * 49.6 77.1 85.7 81.4 

Dom. Rep. 2013 27.8 65.5 85.2 84.6 50.0 66.2 * * 37.3 61.0 89.4 (75.9) 

Honduras 2011-12 28.6 71.5 78.5 65.2 54.4 68.7 * * 35.8 74.0 86.2 73.9 

Peru 2012 30.3 60.2 59.0 45.5 65.5 69.3 * * (66.1) 56.8 62.0 (56.3) 

 
28 

Education 

Table 7 indicates that generally the likelihood of using contraception is positively associated with women’s 

level of education attainment among all three marriage groups. Among currently married women, the 

difference in contraceptive prevalence between women with secondary or higher education and women 

with no education is 20 percentage points or higher in six countries, including Cameroon, Nigeria, Kenya, 

Mozambique, Namibia, and Zambia. In most countries, few never-married women have no education. 

Comparing never-married women having a primary education and those with secondary or higher 

education, the difference in contraceptive prevalence reaches 30 percentage points or more in three 

countries: Cameroon, Sierra Leone, and Namibia. Among formerly married women the difference in 

contraceptive use between women with primary education and those with secondary or higher education 

was small except in Mozambique, at 25 percentage points. 

Table 7 Contraceptive prevalence for sexually active currently married, never-married, and formerly married women, by 

women’s education 

Country 

Currently married Never-married Formerly married 

None Primary Secondary None Primary Secondary None Primary Secondary 

Central Africa 

Cameroon 2011 3.7 15.1 27.6 * 31.2 60.7 (2.4) 33.6 38.9 

Congo 2011-12 12.2 15.0 23.7 (29.5) 23.5 46.1 (13.3) 23.3 36.4

DR Congo 2013-14 4.5 5.5 13.8 (7.5) 14.4 25.1 12.4 7.2 22.9 

Gabon 2012 12.8 15.1 25.2 * 33 50.3 * 25.9 40.8 

Western Africa 

Cote d'Ivoire 2011-12 11.6 19.7 22.6 15.2 31.1 39.6 31.1 26.3 (32.3) 

Ghana 2014 23.7 31.3 27.1 (23.8) 28.9 28.8 * (37.2) 28.0 

Liberia 2013 18.1 21.8 31.1 20.1 26.8 42.3 31.8 23.6 35.7 

Nigeria 2013 1.7 15.2 22.0 (12.8) 40.1 57.0 (17.5) 32.6 39.7 

Sierra Leone 2013 17.3 25.8 32.2 39.4 36 64.8 42.9 (54.3) 41.5 

Eastern and Southern Africa 

Kenya 2014 21.0 60.1 64.6 * 51.3 71.3 (40.0) 57.9 56.6 

Lesotho 2014 (35.0) 60.7 69.9 * 63.3 70.9 * 72.6 80.8 

Malawi 2015-16 58.5 65.3 64.7 * 28.4 39.2 42.7 56.1 56.1 

Mozambique 2011 6.4 13.5 38.9 (2.8) 15.0 47.9 6.4 25.3 49.8 

Namibia 2013 36.5 51.3 62.7 52.6 71.9 80.7 * (56.9) 72.7 

Tanzania 2015-16 28.2 37.9 37.3 * 41.8 42.6 45.5 51.4 43.8 

Zambia 2013-14 35.7 45.7 56.4 * 23.9 37.2 * 47.6 45.9 

Zimbabwe 2015 56.2 65.9 71.4 * (53.7) 60.1 * 74.2 70.3 

Latin America and the Caribbean 

Colombia 2010 66.6 76.8 75.3 * 65.7 74.5 * 78.4 76.2 

Dom. Rep. 2013 58.9 71.1 70.2 * (44.9) 54.2 * 69.6 64.8 

Honduras 2011-12 54.2 68.5 71.6 * 61.3 58.4 * 71.3 76.2 

Peru 2012 44.2 49.1 60.3 * 57.0 66.8 * 57.2 58.8 

Household Wealth 

As Table 8 shows, contraceptive use among currently married women is generally positively associated 

with the level of household wealth. In most countries, contraceptive prevalence is highest among married 

women in the richest household quintile and lowest among those in the poorest. Wealth-related disparities 

in contraceptive use are greater in countries with low contraceptive prevalence than in those with high 

prevalence. For example, in Nigeria and Mozambique women in the richest wealth quintile are 9-10 times 

more likely than women in the poorest quintile to report contraceptive use. In Latin America and the 

Caribbean, where the overall contraceptive prevalence is high, the differences between the richest and 

poorest are smaller. In Colombia, contraceptive prevalence is higher than 70% across all wealth groups. 

Excluding wealth groups with only a few women who have never married, the positive relationship between 

contraceptive prevalence and household wealth generally holds among never-married women. Such a 

relationship generally holds among formerly married women in Central Africa but not in Latin America 

and the Caribbean. The assessment in West Africa and Eastern and Southern Africa is limited because of 

the small number of women in various wealth groups.
29 

Table 8 Contraceptive prevalence among sexually active currently married, never-married, and formerly married women, by wealth quintile Country 

Currently married Never-married Formerly married 

Lowest Second Middle Fourth Highest Lowest Second Middle Fourth Highest lowest Second Middle Fourth Highest 

Central Africa 

Cameroon 2011 3.0 8.5 16.4 23.5 28.2 (31.6) 33.7 41.7 55.9 65.8 * 25.3 29.1 34.3 41.3 

Congo 2011-12 9.9 15.7 21.1 23.7 31.0 19.5 31.2 36.4 52.1 51.4 17.3 29.6 31.5 35.5 (46.7) 

DR Congo 2013-14 3.5 5.2 4.9 11.9 18.7 12.8 20.0 17.8 31.2 24.1 11.0 7.0 13.5 22.4 20.0 Gabon 2012 13.6 21.4 24.3 23.9 23.7 29.4 36.5 39.0 60.9 59.3 28.8 39.3 37.6 36.2 (36.2) 

Western Africa 

Cote d'Ivoire 2011-12 9.6 13.1 12.2 18.1 21.8 16.3 20.4 26.0 33.0 37.6 (28.6) (30.6) (36.5) (20.9) (34.9) 

Ghana 2014 28.6 31.1 28.7 23.8 24.6 36.0 31.3 33.9 19.5 26.9 * (46.5) 33.3 (28.7) (17.8) 

Liberia 2013 16.5 19.6 26.5 28.5 23.0 22.5 24.9 36.8 41.6 35.7 32.1 32.5 36.7 (28.8) (27.2) 

Nigeria 2013 0.8 3.9 10.1 15.8 25.5 (21.3) 29.3 48.4 55.8 64.5 * (19.9) 30.5 39.9 (43.2) Sierra Leone 2013 14.9 15.1 17.0 25.1 32.4 46.5 47.5 44.8 59.0 65.6 (33.2) (29.8) (42.8) 48.1 51.2 

Eastern and Southern Africa

Kenya 2014 32.6 59.1 63.6 65.3 64.0 (40.7) (60.6) (66.9) 52.8 75.6 33.3 64.3 58.5 63.8 (54.7) 

Lesotho 2014 56.5 63.1 66.2 66.4 70.5 * (63.5) (67.9) 78.4 65.7 (60.8) (70.2) (79.1) (79.7) (84.0) 

Malawi 2015-16 58.2 64.0 64.8 66.2 66.8 (26.0) (25.6) 28.9 37.2 38.0 45.7 58.6 43.7 64.8 58.5 Mozambique 2011 3.7 6.7 8.9 18.1 35.8 (0.0) 3.3 10.3 20.1 52.1 9.2 2.6 22.6 31.0 43.2 Namibia 2013 45.4 57.1 58.1 60.3 64.7 71.6 78.6 79.0 77.6 82.3 (50.9) * (83.6) (81.1) (73.2) 

Tanzania 2015-16 24.0 31.8 40.2 44.4 38.3 (21.9) 37.5 49.1 41.3 44.1 47.6 43.4 48.7 46.3 57.9 Zambia 2013-14 34.9 44.0 47.6 53.0 60.1 27.0 25.1 24.0 37.4 42.3 44.6 51.3 51.0 45.1 (35.8) 

Zimbabwe 2015 66.5 65.8 66.7 71.9 74.7 * * * 52.8 60.6 (65.9) * (76.9) 71.7 65.6 

Latin America and the Caribbean

Colombia 2010 71.0 75.6 75.7 78.3 77.1 57.1 69.2 73.3 75.1 80.0 76.3 78.1 75.1 75.9 77.7 Dom. Rep. 2013 66.1 74.5 69.0 68.9 71.8 (74.8) (49.4) 51.6 44.7 55.7 69.1 75.6 69.6 57.2 59.8 Honduras 2011-12 60.6 67.4 70.4 72.1 73.4 (73.4) 57.9 53.3 63.3 56.6 70.8 66.3 73.8 73.8 76.5 Peru 2012 45.2 56.4 57.6 58.4 63.8 44.3 56.8 67.1 67.8 69.4 (52.2) 51.4 64.4 50.0 65.9 
30 

Employment Status 

Among currently married women and formerly married women, contraceptive prevalence is generally 

higher among employed women than unemployed women (Table 9). Overall the employment-related 

differences are greater in Eastern and Southern Africa than in the other regions. Never-married women 

share a similar pattern, except in Central Africa, where unemployed women have higher contraceptive 

prevalence than employed women. The difference is 9-10 percentage points in three of the four countries 

studied. 

Table 9 Contraceptive prevalence among sexually active currently married, never-married, and formerly 

married women, by employment status 

 

Country 

Currently married Never-married Formerly married 

Unemployed Employed Unemployed Employed Unemployed Employed 

Central Africa 

Cameroon 2011 15.5 16.7 58.8 48.2 26.7 35.6 

Congo 2011-12 25.5 19.0 45.5 36.4 33.8 31.7 

DR Congo 2013-14 10.8 7.9 25.5 18.1 12.3 16.1 

Gabon 2012 19.8 23.8 50.2 40.8 42.5 32.2 

Western Africa 

Cote d'Ivoire 2011-12 12.8 15.8 34.5 26.7 (17.8) 33.6 

Ghana 2014 23.4 27.6 30.9 27.0 * 33.0 

Liberia 2013 21.4 23.7 32.9 39.1 29.9 32.1 

Nigeria 2013 4.9 12.9 55.5 54.5 * 33.9 

Sierra Leone 2013 22.1 20.2 59.4 55.0 45.1 44.7 

Eastern and Southern Africa 

Kenya 2014 51.6 61.7 66.0 65.5 (39.8) 59.7 

Lesotho 2014 60.2 72.3 64.6 75.0 65.6 82.5 

Malawi 2015-16 57.4 67.3 28.3 38.7 44.0 56.5 

Mozambique 2011 14.0 14.3 30.2 39.5 27.1 25.5 

Namibia 2013 51.5 63.9 72.3 83.7 71.7 67.2 

Tanzania 2015-16 31.7 37.1 34.8 44.3 (44.5) 50.0 

Zambia 2013-14 50.2 46.8 27.1 39.7 41.0 49.0 

Zimbabwe 2015 68.6 70.7 50.2 66.3 65.1 74.3 

Latin America and the Caribbean 

Colombia 2010 73.5 77.3 71.3 76.4 72.8 77.8 

Dom. Rep. 2013 69.1 71.3 53.8 52.6 68.9 64.8 

Honduras 2011-12 66.4 72.5 58.3 60.0 71.1 74.2 

Peru 2012 60.5 54.0 67.2 66.0 53.2 59.5 
31 

Urban-Rural Residence 

Table 10 indicates, irrespective of 

marital status, women in urban 

areas use contraception to a much 

greater extent than women in 

rural areas. Ghana is an 

exception, where rural women 

have higher contraceptive 

prevalence than urban women in 

all three marriage groups. Among 

other countries, the relative 

urban-rural difference is greatest 

among currently married women. 

In Cameroon, Congo, Congo 

Democratic Republic, Nigeria, 

and Mozambique, contraceptive 

prevalence among urban married 

women is more than double that 

of rural married women. Among 

never-married women, the 

relative urban-rural difference is 

greatest in Cote d’Ivoire, Mozambique, and Zambia. In Latin America and the Caribbean, differences 

between urban and rural areas in contraceptive use are minimal across all three marriage groups. 

3.3 Unmet Need for Family Planning and Marital Status 

Levels and trends in unmet need by marital status 

Unmet need for family planning among sexually active currently married women, never-married women, 

and formerly married women is shown in Figures 7, 8, and 9 respectively. The figures indicate the 

proportion of each group with unmet need (shown separately for spacing and for limiting), met need, and 

no need. Additionally, Figure 10 shows demand satisfied for each marriage group. 

According to Figure 7, total unmet need among sexually active married women ranges from 5% in Peru 

(2012) to 33% in Liberia (2007). On average across countries, 18% of sexually active married women have 

unmet need for family planning—11% for spacing and 7% for limiting births. An average of 45% of 

sexually active married women have their need met (by contraceptive use), while 37% do not need family 

planning. Unmet need is lowest in Latin America and the Caribbean and highest in West Africa. In 16 of 

21 countries, unmet need decreased between surveys. The decrease in unmet need among sexually active 

married women ranged from 0.1 percentage points in Gabon to 14 percentage points in Malawi, while the 

increase ranged from 1 percentage point in Congo to 6 percentage points in Mozambique. Only one 

surveyed country in Central Africa—Gabon—experienced a decrease in unmet need among married 

women, while all surveyed countries in Latin America and the Caribbean experienced decreases. 

Table 10 Contraceptive prevalence among sexually active currently married, never-married, 

and formerly married women, by residence 

 

Country 

Currently married Never-married Formerly married 

Urban Rural Urban Rural Urban Rural 

Central Africa 

Cameroon 2011 23.3 9.7 60.0 36.3 35.8 28.6 

Congo 2011-12 24.9 12.6 46.4 26.6 35.0 22.6 

DR Congo 2013-14 16.3 5.0 26.7 17.8 22.5 9.4 

Gabon 2012 23.2 13.2 48.8 32.6 37.8 24.7 

Western Africa 

Cote d'Ivoire 2011-12 18.6 12.3 35.4 16.6 29.3 31.3 

Ghana 2014 24.3 29.7 27.0 30.6 23.1 46.9 

Liberia 2013 18.6 5.8 62.9 43.9 33.5 31.8 

Nigeria 2013 30.7 16.5 63.6 48.8 49.9 37.8 

Sierra Leone 2013 25.7 19.4 36.6 30.7 30.8 32.0 

Eastern and Southern Africa 

Kenya 2014 62.9 55.9 73.6 54.0 58.1 53.3 

Lesotho 2014 70.0 63.1 70.4 67.8 81.0 71.9 

Malawi 2015-16 67.6 63.5 36.4 32.3 58.1 52.6 

Mozambique 2011 26.0 9.1 48.4 10.5 37.5 14.5 

Namibia 2013 61.7 52.5 80.8 74.3 75.4 57.3 

Tanzania 2015-16 39.1 34.7 39.8 42.9 54.7 45.1 

Zambia 2013-14 55.9 43.0 43.3 22.0 45.6 46.7 

Zimbabwe 2015 73.5 67.3 59.6 55.7 65.3 78.1 

Latin America and the Caribbean 

Colombia 2010 75.9 74.5 74.8 68.7 75.9 80.9 

Dom. Rep. 2013 69.4 72.2 54.1 48.9 64.2 74.8 

Honduras 2011-12 72.1 66.0 60.0 56.5 74.2 70.5 

Peru 2012 59.6 48.8 67.9 53.3 58.6 58.8 
32 

Figure 7 Percent distribution of sexually active currently married women by unmet need status 

0

908070605040302010

100

2004

2011

2005

2011-12

2007

2013-14

2000

2012

1998

2011-12

2003

2014

2007

2013

2003

2013

2008

2013

2003

2014

2004

2014

2004

2015-16

2003

2011

2006-07

2013

2004-05

2015-16

2001-02

2013-14

2005-06

2015

2000

2010

2002

2013

2005-06

2011-12

2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

No needMet needLimitingSpacing
33 

Unmet need among sexually active never-married women ranges from 7% in Peru (2012) to 60% in Malawi 

(2004) (Figure 8); it averages 30% across surveys. Meanwhile, the level of met need averages 58% across 

surveys, while a survey average of 12% of sexually active never-married women do not need family 

planning. Regional patterns in unmet need are similar to those among sexually active married women. In 

11 of 21 countries, prevalence of unmet need among sexually active never-married women decreased 

between surveys, ranging from 1 percentage point in Namibia to 20 percentage points in Nigeria. In 

countries where the level of unmet need increased, the range was from 2 percentage points in Congo to 21 

percentage points in Cote d’Ivoire. Eastern and Southern Africa had the largest share of countries where 

unmet need declined between surveys, while no surveyed countries in Central Africa had a decline in unmet 

need. 
34 

Figure 8 Percent distribution of sexually active never-married women by unmet need status 

0

908070605040302010

100

2004

2011

2005

2011-12

2007

2013-14

2000

2012

1998

2011-12

2003

2014

2007

2013

2003

2013

2008

2013

2003

2014

2004

2014

2004

2015-16

2003

2011

2006-07

2013

2004-05

2015-16

2001-02

2013-14

2005-06

2015

2000

2010

2002

2013

2005-06

2011-12

2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

No needMet needLimitingSpacing
35 

Figure 9 shows a range of unmet need among sexually active formerly married women, from 6% in Peru 

(2012) to 46% in Sierra Leone (2008). On average it is 25%, lower than among sexually active nevermarried women but higher than among sexually active married women. Regional patterns in unmet need 

among sexually active formerly married women are similar to those for their married and never-married 

counterparts. In 16 of 21 countries, unmet need among sexually active formerly married women decreased 

between surveys, ranging from 1 percentage point in Colombia to 21 percentage points in Lesotho. In 

countries where the level of unmet need increased, the range was from 2 percentage points in Cameroon to 

12 percentage points in Mozambique. Only two of the four surveyed countries in Central Africa experienced 

a decline in unmet need among formerly married women, while all four surveyed countries in Latin America 

and the Caribbean experienced a decline. 
36 

Figure 9 Percent distribution of sexually active formerly married women by unmet need status 

0

908070605040302010

100

2004

2011

2005

2011-12

2007

2013-14

2000

2012

1998

2011-12

2003

2014

2007

2013

2003

2013

2008

2013

2003

2014

2004

2014

2004

2015-16

2003

2011

2006-07

2013

2004-05

2015-16

2001-02

2013-14

2005-06

2015

2000

2010

2002

2013

2005-06

2011-12

2000

2012

Cameroon Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa West Africa Eastern and Southern Africa Latin America and the Caribbean

No needMet needLimitingSpacing
37 

Figure 10 shows demand satisfied for family planning among sexually active married, never-married, and 

formerly married women in the most recent country survey. It averages 70%, 66%, and 70%, for each group 

respectively. In 9 of 21 countries, the level of demand satisfied is highest among sexually active married 

women; in 5 countries it is highest among sexually active never-married women, and in the remaining 7 

countries it is highest among sexually active formerly married women. Malawi, Zambia, and Nigeria exhibit 

particularly strong differentials in demand satisfied among the groups. Among married women, demand 

satisfied is 41 percentage points higher than among formerly married women in Malawi (2015-16), 33 

percentage points higher in Zambia (2013-14), but 25 percentage points lower in Nigeria (2013). 

Conversely, Peru (2012), Ghana (2014), Tanzania (2015-16), Liberia (2013), and Namibia (2013) exhibit 

relatively small differentials in demand satisfied across the marital status groups. 
38 

Figure 10 Percentage of sexually active women with demand for family planning satisfied, by marital status 

57

75

47

60

47

55

47

52 53

82 82 82

39

79

69

74

91

93

89

92

95

74

82

52

66

45

51

43

77

69

74 75

42 42

85

66

40

72

87

71

85

93

67

85

44

73

60

54

50

66 65

69

83

66

43

78

72

59

80

90

83

88

94

Cameron Congo DR Congo Gabon Cote d'Ivoire Ghana Liberia Nigeria Sierra Leone Kenya Lesotho Malawi Mozambique Namibia Tanzania Zambia Zimbabwe Colombia Dom. Rep. Honduras Peru

Central Africa Western Africa Eastern and Southern Africa Latin America and Caribean

Currently married Never-married Formerly married
39 

Differentials in unmet need by background characteristics 

Age 

Table 11 shows unmet need by women’s marital status and age for the most recent survey by country. 

Among sexually active married women, average unmet need tends to have an inverse relationship with age 

group. In 10 of 21 countries, unmet need among sexually active married adolescents (age 15-19) is the 

highest of any age group, and as high as 37% in Liberia (2013). In Namibia (2013) there is a differential of 

11 percentage points in unmet need between women age 15-19 and women age 20-24, and in Gabon (2012) 

and Colombia (2010) a differential of 10 percentage points. 

Excluding never-married women age 45-49, who number too few to produce estimates in all but two 

countries, the average inverse relationship between unmet need and age also holds among sexually active 

never-married women who are predominantly age 15-34. Among this group, young women age 15-19 have 

the highest level of unmet need in 16 of the 21 countries. Unmet need among sexually active never-married 

adolescents is highest in Zambia (2013-14), where an estimated 67% of sexually active never-married 

women age 15-19 have an unmet need for family planning, followed by Liberia (2013), at 60%. The greatest 

difference in unmet need between women age 15-19 and women age 20-24 is in Zimbabwe (2015), at 32 

percentage points, followed by Zambia (2013-14), at 30 percentage points. 

Few countries have sufficient numbers of formerly married adolescents to compare with other age groups. 

On average, however, the inverse relationship between women’s age and unmet need also holds among 

sexually active formerly married women. In four of the six countries with sufficient numbers for 

comparison—Congo (2011-12), Honduras (2011-12), Malawi (2015-16), and Mozambique (2011)—unmet 

need among sexually active formerly married women is highest at age 15-19. 
40 

Table 11 Percentage of sexually active currently married, never-married, and formerly married women with an unmet need for family planning, by women’s age Country 

Currently married Never-married Formerly married 

15-19 20-24 25-29 30-34 35-39 40-44 45-49 15-19 20-24 25-29 30-34 35-39 40-44 45-49 15-19 20-24 25-29 30-34 35-39 40-44 45-49 

Central Africa 

Cameroon 2011 21.1 21.4 19.9 21.7 20.8 21.9 14.5 32.6 17.1 17.9 10.4 (23.6) * * * 30.6 22.5 27.3 13.3 (19.5) (5.5) Congo 2011-12 31.5 22.7 17.0 15.4 10.1 11.6 9.1 19.4 10.0 20.4 (7.5) * * * (28.8) 23.0 13.2 6.1 6.0 4.9 5.1 

DR Congo 2013-14 24.8 27.0 28.4 27.5 25.6 22.1 12.9 48.1 40.9 36.3 (34.6) * * * (49.7) 42.4 50.3 44.0 36.6 36.2 (28.8) Gabon 2012 35.6 25.9 23.2 21.6 23.0 21.6 17.7 31.8 29.1 33.8 21.3 (15.6) * * * (5.6) 19.4 21.9 30.2 10.5 (21.6) 

Western Africa 

Cote d'Ivoire 2011-12 21.2 30.4 29.3 21.7 24.4 24.7 12.2 57.7 46.9 32.6 (32.1) * * * * (9.2) (35.6) (20.2) * * * 

Ghana 2014 31.9 30.9 28.6 25.1 32.2 26.1 15.4 51.2 40.2 46.2 (43.9) * * * * * (21.0) (39.9) (45.9) * * Liberia 2013 37.2 35.2 31.8 24.3 29.1 24.4 12.2 59.7 45.4 34.2 (26.5) * * * * (42.6) 23.4 24.5 44.7 (24.8) (36.2) Nigeria 2013 11.9 14.9 15.5 15.6 14.8 15.5 11.4 35.3 16.4 15.3 11.2 (17.9) * * * * (19.8) 30.4 32.5 (28.1) (10.0) Sierra Leone 2013 22.1 18.8 19.3 16.5 22.9 22.6 17.8 36.0 19.5 20.8 3.9 (18.7) * * * * 31.1 19.8 19.5 (35.8) (30.0) 

Eastern and Southern Africa

Kenya 2014 18.4 15.8 11.8 11.9 15.4 18.4 15.6 45.8 16.7 (18.0) (29.2) * * * * (47.4) 22.7 14.1 (22.5) (49.2) (13.7) Lesotho 2014 17.4 16.1 15.8 12.2 10.4 17.7 15.1 27.3 28.2 7.0 (14.2) * * * * * (18.1) (16.7) (9.0) (9.6) * Malawi 2015-16 16.9 13.7 13.1 12.9 14.8 15.1 15.2 53.6 41.1 (51.5) * * * * (37.1) 30.8 24.7 30.2 28.1 (27.7) * Mozambique 2011 19.5 19.6 24.6 25.6 26.8 24.3 16.7 57.5 32.9 23.2 (33.5) * * * (40.2) 35.3 31.7 33.6 37.1 35.3 (35.4) Namibia 2013 29.4 18.9 17.5 12.8 16.5 16.6 9.9 23.5 16.5 9.3 11.7 7.9 8.6 (18.0) * * * * (8.6) (14.9) * Tanzania 2015-16 19.1 19.4 20.3 18.5 19.9 20.2 13.4 44.1 20.9 10.9 * * * * * 22.5 23.8 15.6 16.7 22.6 (28.0) Zambia 2013-14 21.8 19.4 16.4 18.5 20.8 21.2 15.3 66.9 36.8 27.9 (22.7) * * * * (43.2) 43.8 22.6 28.5 (37.9) * Zimbabwe 2015 7.6 6.9 7.3 5.6 8.6 10.1 7.0 (44.5) 12.4 (11.6) * * * * * (23.7) (16.0) 14.6 (26.6) (6.3) * 

Latin America and the Caribbean

Colombia 2010 (21.3) 11.1 6.6 4.5 3.7 4.2 5.1 18.8 10.4 8.5 5.4 4.7 8.1 23.0 * 15.7 7.3 7.1 9.5 9.8 7.3 Dom. Rep. 2013 24.2 18.2 9.5 6.9 4.7 3.5 4.6 36.3 28.9 (10.3) * * * * 18.7 27.5 13.6 8.0 9.1 13.5 (7.9) Honduras 2011-12 12.8 9.0 6.2 4.4 5.2 6.1 5.8 18.1 13.4 4.5 (24.8) * * * (25.9) 18.9 1.0 7.1 13.8 (5.5) (10.2) Peru 2012 10.9 7.5 6.2 4.1 3.7 3.9 2.6 10.7 5.0 6.3 7.8 0.0 (0.0) * * 14.4 5.8 6.5 2.9 6.0 0.2 
41 

Number of Living Children 

Table 12 shows unmet need by women’s number of living children and marital status. Among sexually 

active married women, average unmet need is highest among those with five or more children, and as high 

as 37% in Ghana (2014). In Tanzania and Mozambique married women with five or more children have 

more than five times the unmet need among nulliparous women. Among never-married sexually active 

women, average unmet need is highest among nulliparous women, reaching 60% in Zambia (2013-14). 

Among formerly married women, average unmet need is highest among those with five or more children, 

and as high as 50% in Mozambique (2011). In Gabon (2012) formerly married women with five or more 

children have nearly five times the level of unmet need as their nulliparous counterparts. 

Table 12 Percentage of sexually active currently married, never-married, and formerly married women with an unmet need for family planning, by number of living children

 

Country 

Currently married Never-married Formerly married 

None 1-2 3-4 5+ None 1-2 3-4 5+ None 1-2 3-4 5+ 

Central Africa 

Cameroon 2011 8.7 15.8 22.1 30.7 22.8 19.9 (35.4) * (15.7) 20.5 20.2 28.2 

Congo 2011-12 16.3 16.9 16.1 15.2 14.8 17.8 * * (0.0) 12.0 12.9 14.5 

DR Congo 2013-14 10.6 24.0 26.3 30.4 43.5 42.1 * * (29.4) 42.1 45.2 41.6 

Gabon 2012 12.4 21.1 26.3 30.8 28.8 29.1 (41.7) (37.9) (7.2) 12.7 27.6 35.2 

Western Africa 

Cote d'Ivoire 2011-12 8.7 22.8 27.0 31.6 46.5 49.7 (32.4) * (16.8) 29.5 (31.5) * 

Ghana 2014 7.9 24.5 28.3 36.7 45.8 43.3 * * * 31.5 (44.0) * 

Liberia 2013 15.7 27.1 29.8 28.6 57.0 37.1 (39.0) * * 31.6 32.4 47.2 

Nigeria 2013 4.7 13.4 14.8 19.7 20.3 23.1 * * * 21.2 21.3 35.6 

Sierra Leone 2013 11.9 15.7 21.0 27.7 30.1 21.1 (23.1) * * 25.9 18.4 (44.9) 

Eastern and Southern Africa 

Kenya 2014 9.4 11.2 12.5 24.1 30.5 12.4 * * * 29.4 20.9 39.2 

Lesotho 2014 12.2 12.9 17.0 19.9 23.3 18.8 * * * 16.8 (17.1) * 

Malawi 2015-16 15.2 13.1 14.1 15.3 54.3 29.4 * * (21.8) 36.0 26.1 22.1 

Mozambique 2011 6.3 18.6 28.4 33.2 47.8 36.7 * * 15.0 32.9 42.1 50.2 

Namibia 2013 16.2 14.2 13.8 24.3 18.2 11.1 11.3 (14.2) * 21.7 12.3 * 

Tanzania 2015-16 4.8 16.5 18.6 28.0 31.6 21.0 * * (13.8) 18.3 21.7 30.2 

Zambia 2013-14 9.8 16.6 17.8 23.4 59.7 31.4 * * (22.6) 39.6 31.8 32.3 

Zimbabwe 2015 7.0 6.6 7.0 11.2 27.2 19.0 * * * 17.9 16.4 * 

Latin America and the Caribbean 

Colombia 2010 13.4 6.2 4.3 6.9 13.1 8.9 (19.2) * 13.2 9.6 6.6 13.8 

Dom. Rep. 2013 16.8 12.3 4.2 6.1 29.2 15.0 * * 19.0 18.9 4.8 (13.2) 

Honduras 2011-12 10.8 6.6 4.8 8.8 14.9 10.5 * * 22.6 8.2 8.8 12.3 

Peru 2012 6.4 4.2 4.4 7.1 7.1 4.2 * * (1.6) 6.0 7.9 (0.0) 

Education 

Table 13 shows unmet need by women’s education and marital status. Notably, in only nine countries are 

there sufficient numbers of sexually active never-married women with no education about which to make 

estimates and in only eleven countries are there sufficient numbers of sexually active formerly married 

women with no education about which to make estimates. On average, unmet need has an inverse 

relationship with education—highest among women with no education and lowest among women with 

secondary education and above. This average association holds across all three marital status groups. 

Among married women, the greatest relative differential in unmet need by education is in Zimbabwe 

(2015), where women with no education are more than three times as likely to have an unmet need as 

women with secondary education and above. Data from countries with sufficient numbers of never-married 

women with no education show that the greatest relative differential in unmet need by education is in 

Nigeria (2013), where women with no education are more than three times as likely to have an unmet need 

as women with secondary education and above. Among countries with sufficient numbers of formerly 

married women with no education, the greatest relative differential in unmet need is in Cameroon (2011), 

where women with no education are more than twice as likely as women with secondary education and 

above to have an unmet need for family planning. 
42 

Table 13 Percentage of sexually active currently married, never-married, and formerly married women with an unmet need for family 

planning, by women’s education

 

Country 

Currently married Never-married Formerly married 

None Primary Secondary None Primary Secondary None Primary Secondary 

Central Africa 

Cameroon 2011 23.8 22.4 16.0 * 35.3 18.5 (43.9) 20.2 18.2 

Congo 2011-12 23.8 19.2 14.3 (17.3) 24.0 14.0 (10.0) 15.3 11.0 

DR Congo 2013-14 27.3 26.4 23.6 (64.4) 56.7 37.4 45.5 48.1 35.8

Gabon 2012 40.9 25.1 21.0 * 39.9 27.5 * 20.6 17.1 

Western Africa 

Cote d'Ivoire 2011-12 26.8 25.2 14.2 60.2 48.1 37.2 36.6 23.7 (22.1) 

Ghana 2014 28.1 28.0 26.2 (63.4) 47.9 43.2 * (40.0) 31.5 

Liberia 2013 26.6 29.8 27.3 48.0 58.7 44.8 35.8 36.0 31.1 

Nigeria 2013 14.5 17.1 13.4 (63.3) 34.0 19.0 (41.7) 27.9 18.1 

Sierra Leone 2013 19.9 18.8 20.0 33.3 45.3 23.5 24.4 (29.2) 23.7 

Eastern and Southern Africa 

Kenya 2014 27.4 15.5 10.0 * 40.4 19.7 (19.5) 25.3 36.5 

Lesotho 2014 (30.3) 17.1 12.1 * 30.9 21.2 * 19.3 13.2 

Malawi 2015-16 15.9 14.2 12.4 * 52.3 46.4 35.9 27.4 28.8 

Mozambique 2011 22.3 23.2 22.6 (36.0) 58.3 38.4 42.7 33.8 27.4 

Namibia 2013 27.2 21.9 12.7 24.9 17.2 12.7 * (24.6) 16.6 

Tanzania 2015-16 24.4 18.6 14.4 * 31.8 23.3 26.3 20.6 17.5 

Zambia 2013-14 23.6 20.5 14.7 * 55.9 47.4 * 29.9 38.2 

Zimbabwe 2015 20.3 9.1 6.4 * (30.5) 20.1 * 17.0 19.0 

Latin America and the Caribbean 

Colombia 2010 11.8 6.3 6.2 * 18.1 11.9 * 10.1 9.1 

Dom. Rep. 2013 12.4 9.2 9.3 * (36.7) 25.3 * 12.6 15.1 

Honduras 2011-12 11.1 6.8 6.0 * 11.9 13.8 * 13.6 6.8 

Peru 2012 6.3 6.3 3.9 * 15.7 6.0 * 11.6 4.9 

Household Wealth 

Table 14 shows unmet need by wealth and marital status. For sexually active married and for never-married 

women, average unmet need is highest in the poorest wealth quintile and lowest in the highest wealth 

quintile. For formerly married women, average unmet need is highest in the second wealth quintile and 

lowest in the highest wealth quintile. Among sexually active married women, the difference in unmet need 

between the lowest and highest wealth quintiles is greatest in Kenya (2014), at 18 percentage points. Among 

sexually active never-married women, the difference is greatest in Nigeria (2013), at 49 percentage points. 

And among sexually active formerly married women, the greatest difference between unmet need in the 

lowest and highest wealth quintiles is 23 percentage points in Sierra Leone (2013). 
43 

Table 14 Percentage of sexually active currently married, never-married, and formerly married women with an unmet need for family planning, by household wealth quintileCountry 

Currently married Never-married Formerly married 

Lowest Second Middle Fourth Highest Lowest Second Middle Fourth Highest Lowest Second Middle Fourth Highest 

Central Africa 

Cameroon 2011 25.3 21.7 21.3 19.3 15.6 (45.5) 39.6 26.0 23.2 12.5 * 18.8 31.9 19.8 14.8 

Congo 2011-12 16.0 20.2 14.7 17.8 13.0 25.7 17.6 15.4 14.6 12.7 19.2 13.4 11.0 12.0 (4.1) 

DR Congo 2013-14 26.6 25.9 25.3 27.1 22.1 48.6 49.4 44.9 45.3 35.1 43.8 57.8 36.1 42.5 35.9 

Gabon 2012 29.1 25.4 24.8 21.6 18.2 42.6 37.4 31.9 24.1 21.0 20.5 19.1 16.1 (19.9) (16.1) 

Western Africa 

Cote d'Ivoire 2011-12 27.8 29.1 25.4 24.9 16.9 63.8 49.1 49.9 46.1 41.5 (34.8) (22.7) (27.8) (37.9) (18.0) 

Ghana 2014 29.9 28.4 28.7 28.3 21.8 52.8 53.3 42.3 50.6 30.9 * (39.8) 34.8 (34.0) (30.6) 

Liberia 2013 32.1 30.0 28.2 27.0 20.4 58.2 57.9 48.4 46.8 48.3 31.0 32.8 41.6 (32.7) (30.0) 

Nigeria 2013 14.4 14.0 17.5 16.8 11.1 (62.4) 43.1 23.3 20.5 13.7 * (38.9) 36.0 16.9 (4.5) 

Sierra Leone 2013 20.4 20.7 19.6 18.1 20.0 30.7 35.2 37.0 30.4 20.3 (42.7) (41.6) (10.4) 25.6 20.2 

Eastern and Southern Africa

Kenya 2014 26.3 19.8 12.9 10.0 8.6 (49.6) (29.1) (26.9) 31.3 18.0 31.2 20.2 17.5 27.9 (42.1) 

Lesotho 2014 15.5 18.6 13.6 13.3 13.2 * (36.5) (26.5) 16.6 22.3 (22.4) (24.5) (15.7) (15.5) (7.0) 

Malawi 2015-16 16.7 15.6 13.7 13.0 11.7 (36.5) (60.7) 48.5 53.8 47.6 33.8 24.2 39.3 23.1 25.2 Mozambique 2011 24.2 25.6 20.3 20.1 23.6 (65.3) 60.3 66.1 56.4 31.8 42.0 41.5 30.3 38.6 27.2 

Namibia 2013 22.9 18.2 18.3 14.5 9.6 18.5 13.2 13.3 13.6 12.6 (33.4) * (15.2) (10.2) (22.6) 

Tanzania 2015-16 25.9 21.8 20.0 14.9 14.2 (39.6) 37.4 25.4 35.3 19.2 25.3 33.8 19.5 20.4 14.0 

Zambia 2013-14 23.4 22.8 21.3 16.3 11.2 54.4 49.1 60.3 49.7 39.9 31.2 41.5 25.4 43.3 (28.3) Zimbabwe 2015 8.7 8.7 5.9 8.6 5.1 * * * 22.3 22.0 (20.6) * (16.4) 18.4 24.0 

Latin America and the Caribbean

Colombia 2010 9.6 6.4 6.2 4.9 4.4 19.9 16.7 11.1 11.7 9.6 13.0 7.8 11.8 8.8 7.3 

Dom. Rep. 2013 12.8 9.5 10.6 8.5 5.4 (17.2) (35.6) 34.9 33.3 18.3 9.9 16.1 11.4 22.2 11.3 

Honduras 2011-12 10.2 7.4 5.6 5.7 5.2 (10.4) 16.1 8.9 15.2 13.9 9.9 16.7 13.6 6.7 7.3 

Peru 2012 8.3 5.4 3.7 3.4 3.1 12.6 5.5 3.3 6.3 7.7 (17.6) 9.7 5.7 3.7 3.7 
44 

Employment Status 

Table 15 shows unmet need by employment and marital status. Among sexually active unemployed married 

women, unmet need ranges from 6% in Peru (2012) to 38% in Ghana (2014), and for employed married 

women the range is from 4% in Peru (2012) to 26% in Liberia (2013) and Ghana (2014). In 19 of the 21 

countries, the level of unmet need is highest among sexually active married unemployed women. The same 

is true for unemployed sexually active never-married women in 17 countries, and for formerly married 

women in 14 countries. Ghana (2014) has the largest difference in unmet need between employed and 

unemployed married women, at 12 percentage points. For never-married women, the largest difference in 

unmet need between the employed and unemployed is in Tanzania (2015-16), at 19 percentage points. 

Malawi has the largest difference in unmet need between employed and unemployed formerly married 

women, at 20 percentage points. 

Table 15 Percentage of sexually active currently married, never-married, and formerly married women with an 

unmet need for family planning, by women’s employment status

Country 

Currently married Never-married Formerly married 

Unemployed Employed Unemployed Employed Unemployed Employed 

Central Africa 

Cameroon 2011 22.0 19.9 22.7 22.8 23.0 20.7 

Congo 2011-12 19.5 15.2 17.3 14.2 18.8 10.0 

DR Congo 2013-14 26.3 25.2 40.9 45.4 47.7 40.3 

Gabon 2012 26.7 20.5 29.4 30.1 21.0 16.4 

Western Africa 

Cote d'Ivoire 2011-12 24.7 24.8 43.7 49.4 (42.2) 23.7 

Ghana 2014 37.5 25.5 47.8 43.3 * 35.1 

Liberia 2013 31.8 25.5 53.4 43.9 35.8 32.5 

Nigeria 2013 14.2 14.8 24.2 18.1 * 24.3 

Sierra Leone 2013 22.5 19.1 28.6 26.4 22.8 25.6 

Eastern and Southern Africa 

Kenya 2014 18.8 12.5 30.3 22.1 (41.1) 24.4 

Lesotho 2014 17.1 11.2 29.8 15.3 21.6 12.5 

Malawi 2015-16 17.1 12.7 56.5 42.6 45.0 24.8 

Mozambique 2011 22.9 22.8 48.0 38.8 32.5 36.0 

Namibia 2013 20.7 11.7 20.1 8.4 18.8 20.0 

Tanzania 2015-16 22.8 18.1 41.4 22.5 (24.8) 20.9 

Zambia 2013-14 18.9 18.8 57.5 39.8 39.6 30.7 

Zimbabwe 2015 7.6 7.2 30.5 15.7 25.6 15.8 

Latin America and the Caribbean

Colombia 2010 8.2 4.7 16.5 8.6 10.2 9.2 

Dom. Rep. 2013 11.4 7.3 29.0 23.2 14.3 14.8 

Honduras 2011-12 8.0 4.9 15.6 11.6 10.9 10.1 

Peru 2012 6.0 4.0 7.2 6.2 5.0 5.7 

Residence 

Table 16 shows unmet need by residence and marital status. On average, unmet need is higher among rural 

women in every marital status group. In 17 of 21 countries it is higher among rural sexually active married 

women, and in 18 countries it is higher among rural sexually active never-married women, while in 14 

countries it is higher among rural sexually active formerly married women compared with their urban 

counterparts. The difference in unmet need between rural and urban married women is as high as 7 

percentage points in Zambia (2013-14). The difference in unmet need between rural and urban nevermarried women is as high as 25 percentage points in Mozambique (2011). And among formerly married 

women, the difference in unmet need between rural and urban women is as high as 13 percentage points in 

Nigeria (2013). 

 
45 

Table 16 Percentage of sexually active currently married, never-married, and formerly married women with an 

unmet need for family planning, by residence

 

Country 

Currently married Never-married Formerly married 

Urban Rural Urban Rural Urban Rural 

Central Africa 

Cameroon 2011 18.5 22.4 18.2 34.4 20.1 23.8 

Congo 2011-12 16.5 15.8 13.7 22.9 10.4 17.1 

DR Congo 2013-14 25.2 25.6 34.4 50.5 40.3 43.4 

Gabon 2012 22.9 26.7 28.7 40.3 17.7 21.8 

Western Africa 

Cote d'Ivoire 2011-12 22.4 26.6 44.0 54.6 28.5 26.7 

Ghana 2014 24.7 29.3 44.6 45.7 34.2 33.6 

Liberia 2013 26.0 29.6 48.5 54.3 30.8 41.5 

Nigeria 2013 13.4 15.2 14.9 29.4 19.0 31.8 

Sierra Leone 2013 20.3 19.6 23.3 33.5 20.9 30.9 

Eastern and Southern Africa 

Kenya 2014 10.8 16.8 19.4 34.0 32.5 21.8 

Lesotho 2014 12.4 15.6 24.1 22.3 12.3 19.1 

Malawi 2015-16 11.6 14.6 49.1 49.4 26.2 29.9 

Mozambique 2011 22.3 23.1 35.0 60.2 34.9 34.3 

Namibia 2013 13.4 19.8 11.6 17.6 15.3 27.2 

Tanzania 2015-16 16.0 20.4 26.2 30.6 19.5 22.7 

Zambia 2013-14 14.5 21.8 40.6 59.0 33.5 34.3 

Zimbabwe 2015 7.5 7.3 19.9 28.3 24.5 12.5 

Latin America and the Caribbean 

Colombia 2010 6.0 7.3 11.5 17.2 9.6 8.3 

Dom. Rep. 2013 9.6 8.8 28.0 18.3 15.1 12.7 

Honduras 2011-12 5.9 7.5 13.7 12.4 9.0 13.7 

Peru 2012 3.8 6.8 6.4 7.2 4.9 11.2 

Marital status and demand satisfied 

The relationship between marital status and demand satisfied—defined the percentage of women who are 

using contraception (met need) among women determined to have a need for contraception—was assessed 

using logistic regression for the most recent survey in each country. The dependent variable modeled was 

demand satisfied, and independent variables modeled were marital status, age, number of living children, 

education, wealth, employment, and urban-rural residence. 

Figure 11 plots the odds ratios and 95% confidence intervals of demand satisfied among never-married 

women relative to married women in the adjusted model. In 7 of 21 countries the coefficient on nevermarried women is statistically significant; in six of these seven cases—Colombia (2010), Cameroon (2011), 

Namibia (2013), Congo (2011-12), Sierra Leone (2013), and Nigeria (2013)—it is greater than one, 

indicating that, even after adjusting for background characteristics, never-married women are significantly 

more likely than married women to have their demand for family planning satisfied by using any 

contraceptive method. The coefficient point estimate is highest in Nigeria (2013), where it is estimated that 

never-married women have 3.2 times the odds of having their demand for family planning satisfied by any 

method than married women even after controlling for background characteristics. In Zambia (2013-14) 

the estimate is in the opposite direction: never-married women are estimated to have 43% lower odds of 

having their demand for family planning satisfied by any contraceptive method compared with married 

women even after controlling for background characteristics; this is the only odds ratio less than one that is 

statistically significant. 
46 

Figure 11 Odds ratios of sexually active never-married women compared with sexually 

active currently married women from multivariable regressions of demand satisfied 

Figure 12 shows odds ratios of demand satisfied among formerly married women relative to married women 

by country. In 9 of 21 countries the result is statistically significant even after adjusting for background 

characteristics. In six of these nine countries—Kenya (2014), Malawi (2015-16), Zambia (2013-14), 

Zimbabwe (2015), Colombia (2010), and Honduras (2011-12)—the coefficient is less than one, indicating 

that formerly married women are significantly less likely to have their demand for family planning satisfied 

by using contraception than married women. In the remaining three countries—Congo (2011-12), Gabon 

(2012), and Nigeria (2013)—the coefficient is greater than one and statistically significant, indicating that 

formerly married women are significantly more likely to have their demand for family planning satisfied 

than married women, even after controlling for background characteristics. 
47 

Figure 12 Odds ratios of sexually active formerly married women compared with 

sexually active currently married women from multivariable regressions of demand 

satisfied 
48 

3.4 Contraceptive Use and Unmet Need among Polygynous Women 

We further examined contraceptive use and unmet need among sexually active women in polygynous 

marriages and compared them with women in monogamous marriages in seven countries with a relatively 

high prevalence of polygyny (20% or higher in one of the two surveys analyzed)—Cameroon, Congo 

Democratic Republic, Cote d’Ivoire, Nigeria, Sierra Leone, Mozambique, and Tanzania. Figure 13 shows 

the percentage of married women whose husbands/partners had more than one wife in the two surveys of 

each country. The prevalence of polygyny, calculated from most recent survey in each country, ranges from 

18% in Tanzania (2015-16) to 35% in Sierra Leone (2013). Polygyny appears more common in West 

African countries than in the other African countries studied. For example, 33% of married women in 

Nigeria (2013) and 35% in Sierra Leone (2013) reported having one or more co-wives. All but one of the 

seven countries have experienced a slight decrease in the prevalence of polygyny between surveys. 

Figure 13 Percentage of married women in polygynous marriages 

Figures 14a-f present profiles of women in polygynous marriages compared with monogamous women by 

women’s age, number of living children, education, household wealth, employment status, and urban-rural 

residence. Compared with women married monogamously, women in polygynous marriages tend to be 

older, with more children, less educated, from poorer households, and living in rural areas. The two groups 

share a similar pattern of employment status. 

 

30 25 21 22

35

28

36 33 37 35

24 20 23 18

200420112007

2013-14

1998

2011-12

200320132008201320032011

2004-052015-16

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania
49 

Figure 14a Percent distribution of women for each marriage type by age 

Figure 14b Percent distribution of women for each 

marriage type by number of children 

0

10

20

30

40

50

60

70

80

90

100

Polygyny

Monogamy

Polygyny

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Monogamy

Polygyny

Monogamy

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Monogamy

Polygyny

Monogamy

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

15-19 20-24 25-29 30-34 35-39 40-44 45-49

0

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Polygyny

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Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

None 1-2 3-4 5+
50 

Figure 14c Percent distribution of women for each marriage type by education 

Figure 14d Percent distribution of women for each marriage type by wealth 

0

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Polygyny

Monogamy

Polygyny

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Monogamy

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

None Primary Secondary+

0

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Polygyny

Monogamy

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Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

Lowest Second Middle Fourth Highest
51 

Figure 14e Percent distribution of women for each 

marriage type by employment status 

Figure 14f Percent distribution of women for each 

marriage type by urban-rural residence 

 

0

10

20

30

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Polygyny

Monogamy

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Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

Unemployed Employed

0

10

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Polygyny

Monogamy

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Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

Urban Rural
52 

Contraceptive use and unmet need among women in polygynous marriages 

Figure 15 shows contraceptive prevalence for both polygynously and monogamously married women who 

were sexually active in last month based on the most recent survey in each of the seven countries. The 

overall contraceptive prevalence among polygynous women ranges from 8% in Nigeria to 32% in Tanzania, 

which is lower than among monogamous women in any of the countries. The greatest difference between 

the two groups is in Cameroon and Nigeria. In both countries, the percentage of women in polygynous 

marriages who use contraception is only half of that among women in monogamous marriages. 

Figure 15 Contraceptive prevalence among sexually active currently 

married women, by marriage type 

9 19 6 9 12 16 6 13 16 23 11 15 28 38 5

12

11 15 5

7

2

8 2

1

4

8

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Cameroon DR Congo Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

Modern method Traditional method
53 

Figure 16 shows comparisons of the modern contraceptive method mix by marriage type. In the studied 

countries as a whole, method mix among women in polygynous marriages is similar to that of women in 

monogamous marriages. For example, both groups in Central African countries reported common use of 

condoms and injectables. Pills and injectables are popular in both groups in other five African countries. 

In some countries, however, condom use is less common among polygynous women. For example, in 

Cameroon, 39% of modern method users in polygynous marriages reported condom use compared with 

54% of those in monogamous marriages. 

Figure 16 Method mix among sexually active currently married women who use 

modern contraception, by marriage type 

0

10

20

30

40

50

60

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Polygyny

Monogamy

Polygyny

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Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Cameroon DR Congo Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

Other modern

Condom

Implant

Injectable

IUD

Pill

Sterilization
54 

As Figure 17 shows, unmet need for spacing and limiting among polygynous women is largely similar to 

that among monogamous women. The percentages of women with no need for family planning, however, 

differ between the two groups. Overall, a higher percentage of women in polygynous marriages have no 

need for contraception compared with those in monogamous marriages. The difference between the two 

groups is 10 percentage points or more in Cameron, Congo Democratic Republic, Cote d’Ivoire, and 

Nigeria. Consequently, a lower percentage of women in polygynous marriages have an unmet need. 

Figure 17 Percent distribution of sexually active currently married women according to 

the status of unmet need for family planning, by marriage type 

Adjusted differences in contraceptive use by marriage type 

Logistic regression models were fitted to assess if contraceptive use is different between women in 

polygynous marriages and those in monogamous marriages after controlling for age, number of living 

children, education, household wealth, employment status, and urban-rural residence. Figure 18 plots the 

odds ratios and 95% confidence intervals of polygyny compared with monogamy from regressions of any 

contraceptive method use. In six of the seven countries – Nigeria, Tanzania, Cote d’Ivoire, Cameroon, 

Congo Democratic Republic, Sierra Leone- women in polygynous marriages are significantly less likely to 

use a contraceptive method. The odds ratio is lowest in Tanzania, at 0.59 (95% CI: 0.51-0.68), which means 

that women in polygynous unions have 51% lower odds of using any contraceptive method than women in 

monogamous unions after controlling for background characteristics. For modern contraceptive use, Figure 

19 indicates the difference associated with marriage type remains significant in three countries: Tanzania 

(OR=0.67, 95% CI: 0.56-0.81), Nigeria (OR=0.74, 95% CI: 0.63-0.87), and Sierra Leone (OR=0.76, 95% 

CI: 0.64-0.90). These numbers indicate the odds of using a modern method is 24% to 33% lower among 

polygynous women compared with monogamous women. 

13 13 16 20 15 19

11 11 10 13 12 15 15 13

10 7

7 6

8

7

3 3 9 8 11 8 8

5

14

31

17

24

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24

8

20 18

24

12 15

32 46

64

49

60

50

61

51

78

65 64

55

66 62

45

36

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

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Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Polygyny

Monogamy

Cameroon CongoDR Cote d'Ivoire Nigeria Sierra Leone Mozambique Tanzania

Unmet need for spacing Unmet need for limiting Met need No need
55 

Figure 18 Odds ratios of polygyny compared with monogamy from multivariable 

regressions of any contraceptive use 

Figure 19 Odds ratios of polygyny compared with monogamy from multivariable 

regressions of modern contraceptive use

57 

4. Discussion and Conclusions 

Analyzing data from 42 DHS surveys in 21 countries in sub-Saharan Africa, Latin America, and the 

Caribbean, this comparative study contributes to an understanding of current levels, trends, and differentials 

in contraceptive use and unmet need for family planning among sexually active women by their marital 

status—currently married, formerly married, and never married. We restricted the analysis to women who 

were sexually active, therefore at risk of pregnancy. This restriction yields different results than estimates 

of contraceptive prevalence and unmet need for family planning based on all married women. For example, 

our estimated contraceptive prevalence among currently married women is higher in all countries compared 

with estimates based on all married women1

 (ICF 2017). The difference is largest in Zambia, at 12 

percentage points. The unmet need estimates, however, are slightly lower (up to 5 percentage points in 

Sierra Leone, Malawi, and Peru) compared with estimates based on all married women (ICF 2017). 

Overall, countries in Latin America and the Caribbean have achieved great success in extending the reach 

of family planning programs. Women in all marriage groups in the four Latin American and the Caribbean 

countries studied reported high levels of any contraceptive use, as well as modern contraceptive use. 

Contraceptive prevalence reaches 80% or above in Colombia and Peru. Countries in Latin America and the 

Caribbean have the lowest levels of unmet need for family planning, at less than 10% in the most recent 

survey of each of the four study countries. Differentials in contraceptive use and unmet need by women’s 

marital status are negligible. Despite the substantial use of contraception, contraceptive prevalence 

continues to increase and unmet need continues to decline across all countries and marital groups, except 

in Colombia and Dominican Republic among never-married women. The Latin American and Caribbean 

countries have achieved not only a high level of contraceptive use but also a fairly balanced mix of modern 

methods. Long-acting and permanent methods are widely practiced and sterilization is adopted by a large 

proportion of currently married and formerly married women, a trend associated with the long history of 

promoting female sterilization as a contraceptive choice in the region. Never-married women are more 

likely to use condoms. 

Family planning practices vary substantially within sub-Saharan Africa. Overall, contraceptive prevalence 

is much lower than in Latin America and the Caribbean, and below 30% in most of the Central African and 

Western African countries studied. While the level of unmet need for family planning is higher and the 

level of demand satisfied lower in sub-Saharan Africa compared with Latin America and the Caribbean, 

the differences are not as striking as for contraceptive prevalence, especially among currently married 

women. This is because a considerable proportion of women in Central and West Africa have no need for 

family planning, which reflects a general desire for a larger number of children in sub-Saharan Africa 

(Bongaarts 2011). Within sub-Saharan Africa, Western African and Central African countries generally 

have lower contraceptive prevalence than Eastern and Southern African countries. Countries in Eastern and 

Southern Africa, however, present a wide range of contraceptive prevalence: from 14 to 71% among 

currently married women, 33 to 78% among never-married women, and 26 to 76% among formerly married 

women. Contraceptive prevalence has increased in Western, Eastern, and Southern African countries over 

the survey period. While total contraceptive prevalence has been largely stagnant in Central Africa, modern 

contraceptive use has risen in all four of its countries. In contrast, declines in unmet need are less noticeable 

in sub-Saharan Africa except in a few countries, including Kenya, Lesotho, Nigeria, Malawi, and Sierra 

Leone. Of the 17 sub-Saharan African countries included in this analysis, several appear to have 

experienced increases in unmet need: five countries among married women, eight among never-married 

women, and five among formerly married women. As discussed earlier, unmet need for family planning is 

associated with both contraceptive use and fertility desire. Unmet need could rise when family planning 

programs increase demand for spacing or limiting births but the demand is yet satisfied by using 

 

1

 Data on contraceptive prevalence and unmet need for all married women were drawn from the DHS Statcompiler 

(www.statcompiler.com) and are not shown in this report. 
58 

contraception due to a variety of reasons (Darroch, Sedge, and Ball 2011). Even so, these increases in unmet 

need deserve close investigation. 

Sub-Saharan Africa as a whole shows greater variation in contraceptive use by marital status. In most 

countries of this region, never-married women have higher contraceptive prevalence. Among the three 

marriage groups, currently married women usually have the lowest contraceptive prevalence. Women in 

sub-Saharan Africa rely on a very limited number of modern methods, and the predominant method differs 

by their marital status. In Eastern and Southern African countries, currently married and formerly married 

women predominantly use injectables, while never-married women tend to use condoms. The most skewed 

method mix is observed in Central Africa, especially among never-married women, who mostly use 

condoms. Condom use in the other two marriage groups in Central Africa is also common, but pills and 

injectables also contribute some share. In some Western African countries condoms are popular among 

never-married women, while pills and injectables are more prevalent among currently married and formerly 

married women. The skewness toward certain methods could be due to cultural reasons, lack of 

contraceptive choices, or provider bias (Bertrand et al. 2014)—a subject that warrants a more 

comprehensive analysis of data from multiple sources at the country level. 

Despite variations in contraceptive use by women’s marital status, the association between contraceptive 

prevalence and individual and household characteristics is similar across the three marriage groups. In 

general, contraceptive prevalence has an inverted U-shaped relationship with women’s age and a positive 

association with education and household wealth status. It is noteworthy that the disparities in contraceptive 

use by wealth and education are greater in countries with low contraceptive prevalence. 

In all countries except Ghana, urban women are more likely to use contraception than their rural 

counterparts. A mixed-methods follow-up study in Ghana found underreporting of method use in the 2014 

Ghana DHS, particularly traditional methods among urban respondents (Staveteig 2016). Although the 

study had a relatively small sample size, its results suggest disproportionate underreporting of method use 

in urban areas, which—combined with recent increases in contraceptive uptake in rural areas—could make 

rural method use appear comparatively larger. 

While a higher level of contraceptive use is usually associated with employment in most of the study 

countries, the association is opposite in Central Africa. The association between unmet need and women’s 

background characteristics is also largely consistent across marriage groups. Unmet need shows an inverse 

relationship with age, education, and wealth. Women in the youngest age group, women with no education, 

and women in the poorest wealth quintile have the highest levels of unmet need, regardless of their marital 

status. Unmet need is also associated with having a large number of children, being unemployed, and living 

in a rural area. 

Multivariable regressions of demand satisfied for family planning were run with background characteristics 

and marital status as predictors. The results show that even after controlling for background characteristics, 

being never-married and being formerly married (compared with being married) are significant predictors 

of demand satisfied in 7 and 9 of the 21 countries, respectively. The coefficients for both marriage groups 

are in different directions, depending on the country. In the majority of countries where being never-married 

is a significant predictor of demand satisfied, the odds ratio is greater than one, indicating that never-married 

women are significantly more likely to have their demand for contraceptive use satisfied compared with 

currently married women. Conversely, in a number of countries where being formerly married is 

statistically significant, the odds ratios are smaller than one, indicating that formerly married women are 

less likely to have their demand satisfied compared with currently married women. The diversity of these 

results suggests a need for further country-by-country review of programmatic and social factors 

influencing differences in contraceptive demand satisfied between unmarried and married women. 
59 

Data on polygyny collected in DHS surveys provide an opportunity to further examine family planning 

practices among women in polygynous marriages and to compare them with monogamous marriages. 

Polygyny is commonly practiced in Central African and Western African countries. Women in polygynous 

marriages are more likely to be older, have more children, be less educated, live in a poorer household, and 

reside in a rural area. Overall, women in polygynous marriages are less likely to use a contraceptive method 

compared with women in monogamous marriages. This association remains in most of the countries even 

after controlling for background characteristics. This finding agrees with other studies in Nigeria (Audu et 

al. 2008) and Malawi (Baschieri et al. 2013). When looking at modern contraceptive use, however, the 

significant association with the type of marriage is found in fewer countries. Women’s use of a modern 

method requires access to family planning services and to a range of methods. The two groups also have a 

similar method mix, which may suggest the primacy of the service environment in influencing choice of 

contraceptive method. Women in polygynous marriages have a similar level of unmet need as monogamous 

women, but a larger proportion of women married polygynously have no need for contraception compared 

with monogamous women. This result supports the findings from previous studies that women in 

polygynous marriages usually want more children because of the competition with other wives (Bove and 

Valeggia 2008). 

Taken as a whole, these findings generally reflect encouraging progress in family planning outreach and 

programmatic efforts in both regions. In particular, the countries in Latin America and the Caribbean had 

achieved relatively high levels of contraceptive prevalence and low levels of unmet need even by the earlier 

survey, while sub-Saharan Africa has seen a greater relative increase in contraceptive prevalence and 

greater relative reduction in unmet need. Even so, important sociodemographic gaps in contraceptive use 

and unmet need remain in both regions, and they are similar among sexually active women in the three 

marital status groups. Comparisons across marital groups of demand satisfied—a measure that excludes 

women who are or want to become pregnant in the next two years—find a more than ten percentage point 

relative deficiency in the level of demand satisfied among never married women compared with married 

women in four countries (Malawi, Zambia, Zimbabwe, and Dominican Republic) and among formerly 

married women compared with married women in four countries (Kenya, Malawi, Zambia, and Zimbabwe). 

Multivariable regression results of demand satisfied among never-married women were somewhat 

encouraging, but when balanced against results for formerly married women they serve as an important 

reminder that ensuring safe and equitable access to family planning methods among all marital groups is 

an important programmatic goal. The findings for polygynous women compared with their monogamous 

counterparts confirm the overall importance of demand generation activities in communities where 

polygyny is prevalent as a valuable complement to contraceptive outreach efforts. 

61 

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64 

Appendix Tables 

Appendix Table 1 Unweighted number of women who were sexually 

active in last month, by marital status 

Country/survey 

Currently 

married 

Nevermarried Formerly 

married 

Central Africa 

Cameroon 2004 4,794 391 206 

Cameroon 2011 6,754 817 309 

Congo 2005 2,861 699 291 

Congo 2011-12 4,857 925 579 

DR Congo 2007 4,535 466 187 

DR Congo 2013-14 8,902 916 400 

Gabon 2000 2,268 646 332 

Gabon 2012 3,225 1,094 386 

 

Western Africa 

Cote d'Ivoire 1998 1,093 284 78 

Cote d'Ivoire 2011-12 4,267 988 197 

Ghana 2003 2,131 184 73 

Ghana 2014 3,348 544 185 

Liberia 2007 3,026 814 231 

Liberia 2013 3,700 1,213 335 

Nigeria 2003 3,936 292 71 

Nigeria 2013 2,1978 1,344 233 

Sierra Leone 2008 2,887 443 108 

Sierra Leone 2013 6,544 1,769 290 

 

Eastern and Southern Africa 

Kenya 2003 3,642 148 119 

Kenya 2014 6,929 292 291 

Lesotho 2004 2,216 200 241 

Lesotho 2014 2,265 263 186 

Malawi 2004 6,216 131 128 

Malawi 2015-16 12,644 449 400 

Mozambique 2003 5,578 565 501 

Mozambique 2011 6,186 654 496 

Namibia 2006-07 2,429 1,209 131 

Namibia 2013 2,310 1,290 148 

Tanzania 2004-05 5,321 337 315 

Tanzania 2015-16 6,595 429 498 

Zambia 2001-02 3,451 189 133 

Zambia 2013-14 8,359 553 305 

Zimbabwe 2005-06 4,037 89 103 

Zimbabwe 2015 5,082 137 212 

 

Latin America and the Caribbean 

Colombia 2000 5,188 641 382 

Colombia 2010 22,979 4,167 2,236 

Dom. Rep. 2002 12,225 916 916 

Dom. Rep. 2013 4,366 670 670 

Honduras 2005-06 9,401 328 328 

Honduras 2011-12 10,770 504 504 

Peru 2000 12,981 306 306 

Peru 2012 11,408 508 508 

 

 
65 

Appendix Table 2 Modern contraceptive prevalence (mCPR) among unmarried sexually active women based on 

calendar data and women's report of "current use" 

country 

mCPR among 

unmarried 

sexually active 

(<3 months) 

women, based 

on calendar 

Number 

of women

mCPR among 

unmarried 

sexually active 

(<3 months) 

women, based 

on v312 

Number 

of women

mCPR among 

unmarried 

sexually active 

(last 1 month) 

women based 

on v312 

Number 

of women 

Western Africa 

Ghana 2014 32.6 1,230 31.0 1,230 31.7 729 

Liberia 2013 35.1 2,072 34.7 2,072 34.6 1,548 

Nigeria 2013 52.4 2,387 51.4 2,387 54.9 1,577 

Sierra Leone 2008 26.7 737 26.0 737 24.5 551 

Sierra Leone 2013 53.6 2,864 53.8 2,864 56.3 2,058 

Eastern and Southern Africa 

Kenya 2003 42.9 495 38.4 495 44.3 267 

Kenya 2014 58.3 1,258 53.9 1,258 60.9 583 

Lesotho 2014 78.4 900 68.6 900 72.1 450 

Malawi 2004 26.9 495 23.5 495 24.3 260 

Malawi 2015-16 44.8 1,708 42.5 1,708 43.2 849 

Mozambique 2011 29.5 1,607 29.0 1,607 30.1 1,150 

Namibia 2006-07 76.3 2,180 74.6 2,180 77.7 1,343 

Namibia 2013 76.4 2,307 75.2 2307 77.6 1,437 

Tanzania 2004-05 36.4 934 35.1 934 35.7 652 

Tanzania 2015-16 43.7 1,545 42.6 1545 45.8 928 

Zambia 2013-14 35.4 1,464 34.4 1,464 37.7 858 

Zimbabwe 2005-06 61.5 419 52.2 419 60.2 191 

Zimbabwe 2015 67.0 649 62.0 649 66.4 349 

Latin America and the Caribbean 

Colombia 2000 66.8 6,334 62.2 6,334 68.1 4,448 

Colombia 2010 74.5 9,595 69.6 9,595 74.9 6,403 

Dom. Rep. 2013 57.6 2,062 51.2 2,062 55.4 1,270 

Honduras 2005-06 59.0 908 51.0 908 62.1 581 

Honduras 2011-12 66.4 1,580 54.7 1,580 66.1 1,009 

Peru 2012 47.0 1,582 42.2 1,582 45.3 1,068