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

evaluate population, health, nutrition, and HIV/AIDS programs. Funded by the United States Agency for 

International Development (USAID) under Contract No. GPO-C-00-03-00002-00, MEASURE DHS is 

implemented by Macro International Inc. in Calverton, Maryland. 

The main objectives of the MEASURE DHS project are: 

• To provide decisionmakers in survey countries with information useful for informed policy choices; 

• To expand the international population and health database; 

• To advance survey methodology; and 

• To develop in participating countries the skills and resources necessary to conduct high-quality 

demographic and health surveys. 

Additional information about the MEASURE DHS project is available on the Internet at 

http://www.measuredhs.com or by contacting Macro International Inc., MEASURE DHS, 11785 Beltsville 

Drive, Suite 300, Calverton, MD 20705 USA; Telephone: 301-572-0200, Fax: 301-572-0999, E-mail: 

reports@measuredhs.com. 
DHS Comparative Reports No. 13 

Premarital Fertility and Ethnicity in Africa 

Michel Garenne 

French Institute for Research and Development (IRD) 

and Institut Pasteur, Paris 

Julien Zwang 

Institut des Cordeliers, Université de Paris VI, and 

Centre d’Etudes et de Recherches sur le Développement International (CERDI) 

Macro International Inc. 

Calverton, Maryland USA 

December 2006 

The authors’ views expressed in this publication do not necessarily reflect the views of the 

United States Agency for International Development or the United States Government.
This publication was made possible through support provided by the United States Agency for International Development (USAID) under Contract No. GPO-C-00-03-00002-00. 

Recommended citation: 

Garenne, Michel, and Julien Zwang. 2006. Premarital Fertility and Ethnicity in Africa. DHS Comparative 

Reports No. 13. Calverton, Maryland, USA: Macro International Inc. 
iii

In memory of Etienne van de Walle, 

A pioneer in the study of 

African nuptiality and fertility.
v

Contents 

Tables and Figures.............................................................................................................................................vii 

Preface................................................................................................................................................................ ix 

Acknowledgments .............................................................................................................................................. xi 

Executive Summary..........................................................................................................................................xiii 

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

2 Data and Methods........................................................................................................................................ 3 

 2.1 Datasets ..................................................................................................................................... 3 

 2.2 Ethnicity in DHS Surveys ......................................................................................................... 3 

 2.3 Sample Size and Grouping of Datasets ..................................................................................... 4

 2.4 Prevalence of Premarital Fertility.............................................................................................. 4 

 2.5 Socioeconomic Variables .......................................................................................................... 5 

 2.6 Methodology ............................................................................................................................. 6 

3 Results ......................................................................................................................................................... 7 

 3.1 Samples of Ethnic Groups......................................................................................................... 7 

 3.2 Premarital Fertility by Ethnicity................................................................................................ 8 

 3.3 Comparison with the Ethnographic Literature .......................................................................... 9 

 3.4 Demographic Factors and Socioeconomic Determinants........................................................ 10 

 3.5 Geographical Patterns.............................................................................................................. 11 

 3.6 Outliers from Demographic Variables .................................................................................... 14 

4 Conclusions ............................................................................................................................................... 15 

References ......................................................................................................................................................... 17 

Appendix ........................................................................................................................................................... 19 

vii

Tables and Figures 

Table 3.1 Ethnic groups in sub-Saharan Africa: Information from population and survey 

 data, various sources including WFS and DHS national sample surveys.............................. 7 

Table 3.2 Distribution of ethnic groups by level of premarital fertility, sub-Saharan Africa ................ 9 

Table 3.3 Norms of premarital sexual behavior in African ethnic groups in Murdock’s Atlas, 

and relationship with the prevalence of premarital fertility in DHS surveys......................... 9 

Table 3.4 Correlation of premarital fertility with demographic factors, modern contraception, 

and socioeconomic determinants, sub-Saharan Africa......................................................... 10 

Table 3.5 Correlation coefficients between socioeconomic determinants and demographic 

factors, sub-Saharan Africa (N = 263 ethnic groups)........................................................... 11 

Figure 3.1 Distribution of ethnic groups according to the prevalence of premarital fertility, 

25 countries in sub-Saharan Africa ........................................................................................ 8 

Figure 3.2 Prevalence of premarital fertility in Africa, by region ......................................................... 12 

Figure 3.3 Median age at first marriage in Africa, by region ................................................................ 13 

Figure 3.4 Relationship between prevalence of premarital fertility and median age at first 

marriage among 263 African ethnic groups......................................................................... 14 

ix

Preface 

One of the most significant contributions of the MEASURE DHS program is the creation of an 

internationally comparable body of data on the demographic and health characteristics of populations in 

developing countries. The DHS Comparative Reports series examines these data across countries in a 

comparative framework, and is primarily descriptive. The DHS Analytical Studies series focuses on 

technical analysis of specific topics. The principal objectives of both series are to provide information for 

policy formulation at the international level and to examine individual country results in an international 

context. 

DHS Comparative Reports covers a variable number of countries, depending on the availability 

of datasets. Where possible, data from previous DHS surveys are used to evaluate trends over time. Each 

report provides detailed tables and graphs organized by region. Survey-related issues such as 

questionnaire comparability, survey procedures, data quality, and methodological approaches are 

addressed as needed. 

The topics covered in the DHS Comparative Reports series are selected by MEASURE DHS staff 

in conjunction with the U.S. Agency for International Development. Some reports are updates of 

previously published reports. 

It is anticipated that the availability of comparable information for a large number of developing 

countries will enhance the understanding of important issues in the field of international population and 

health by analysts and policymakers. 

Martin Vaessen 

Project Director 

xi

Acknowledgments 

The authors would like to thank the U.S. Agency for International Development and Macro 

International Inc. for supporting this research and the Wellcome Trust for sponsoring the first part of the 

study. 

xiii

Executive Summary 

Premarital fertility, defined as giving birth before a woman’s first marriage, is prevalent in subSaharan Africa. According to DHS data from surveys in 25 countries, an average of one in five women 

has a birth before marriage. The prevalence of premarital fertility varies markedly, ranging from 2.4 to 

60.2 percent in the countries covered. The variation is even greater by ethnic group, ranging from 0.1 to 

76.2 percent. The level of premarital fertility is determined by a number of factors including age at first 

marriage, age at first intercourse, contraceptive use, and various cultural factors; and all of these factors 

vary by ethnicity. An analysis of 263 ethnic groups shows that age at first marriage is by far the most 

important factor. Variables linked to modernization—urban residence, modern education, wealth, and 

Christianity—have positive correlations with premarital fertility, whereas living in a polygynous union 

and being Muslim have negative correlations. Even taking into account demographic and socioeconomic 

factors, variations in the level of premarital fertility are substantial, indicating the strong effect of cultural 

factors. The demographic evidence presented in this analysis is consistent with the ethnographic record, 

which distinguishes between societies that are culturally conservative and societies that are more open 

and permissive. The Appendix presents detailed information on premarital fertility by ethnicity for the 

countries in the study. 
1

1 Introduction 

Premarital fertility, defined as giving birth before a woman’s first marriage, was of considerable 

interest to Europeans when they encountered African societies in the nineteenth and early twentieth 

centuries. Most Europeans came from cultures in which premarital sexual intercourse and premarital 

childbirth were highly stigmatized and repressed, and where marriage was strictly regulated, whether by 

civil law or by Christian religion. In Africa, they found a diversity of cultures that had very different 

world views about sexual intercourse and childbirth before marriage. Furthermore, marriage in Africa was 

guided by custom, with no equivalent to a marriage certificate. There was no official point in time before 

which intercourse or childbirth could be considered premarital. Marriage was a social process, an alliance 

between families or social groups. At the same time, marriage in African societies did follow clear rules, 

the rules were just different from those of European societies (Radcliffe-Brown and Forde, 1950; van de 

Walle, 1968). Observers of African cultures wrote extensively about premarital sexual relations and their 

relationship to marriage. For example, Grandidier (1913) described patterns of marriage and fertility at 

the turn of the twentieth century in Madagascar and presented numerous accounts of permissiveness 

toward premarital sexual behavior: some groups considered it normal for a woman to give birth before her 

first marriage. He further noted that permissiveness varied among ethnic groups, and also by social class. 

These patterns seem to have been resistant to change because, a century later, similar patterns were found 

in demographic survey data (Garenne and Zwang, 2005). 

Ethnographers working in Africa in the first part of the twentieth century spent considerable time 

and effort describing patterns of marriage and sexual permissiveness. There does not appear to be any 

review or synthesis of this abundant literature with regard to premarital fertility. However, in his classic 

work, Ethnographic Atlas, Murdock (1967) uses a series of characteristics taken from ethnographic 

literature to describe attitudes toward premarital sexual intercourse in different ethnic groups. Attitudes 

were categorized, ranging from very permissive to very repressive: (F) premarital sexual relations freely 

permitted and subject to no sanctions; (A) premarital sexual relations allowed, not sanctioned unless 

pregnancy results; (P) premarital sexual relations prohibited, but weakly sanctioned; (T) trial marriage; 

promiscuous relations prohibited; (E) premarital sexual relations precluded by very early age at marriage 

for females; (V) insistence on virginity; premarital sexual relations prohibited.1

 In his synthesis, Murdock 

analyzed 277 ethnic groups from sub-Saharan Africa. Only 114 (41 percent) had information on norms of 

sexual behavior. A majority of these (53 percent) were categorized as “permissive” (groups A and F); a 

smaller number (15 percent) were considered “tolerant” (group P); and the remainder (34 percent) were 

seen as “restrictive” (groups E and V). Those in the restrictive category included cultures with very early 

age at marriage for females and those with strong sanctions on premarital sexual relations. This overview 

points up the ethnographic diversity found in sub-Saharan Africa, which accounts for the diverse patterns 

of premarital fertility that emerge from demographic surveys. This diversity contrasts markedly with 

North African and European populations, for whom permissiveness has traditionally been rare. In the 

same Ethnographic Atlas, only one group in North Africa—the Tamasheq Kel Antessar in Southern 

Sahara—and only one small group in central Europe, fall into the (F) category. 

 

1

 While Murdock distinguished six categories of “norms of premarital sexual behavior,” only five pertain to Africa: 

F, A, P, E, V. 
2

The aim of this study is to examine the variations in levels of premarital fertility by ethnicity in 

sub-Saharan Africa. Much of the information on marriage, fertility, and ethnicity came from DHS 

datasets provided by the MEASURE DHS project. The main reason for emphasizing ethnicity stems from 

case studies conducted by the authors in South Africa, Namibia, and Madagascar. The research showed 

that ethnicity was the primary source of differential behavior in premarital fertility, and was much more 

important than socioeconomic factors such as urbanization, education, wealth, or religion (Garenne et al., 

2000; Garenne and Zwang, 2004; Garenne and Zwang, 2005; Zwang, 2004). This study goes beyond a 

description of the differentials in premarital fertility by analyzing the relationship between premarital 

fertility and socioeconomic determinants such as urbanization, education, wealth, and religion. From this 

perspective, it is an extension of previous research on the determinants of age at marriage in sub-Saharan 

Africa (Garenne, 2004). 
3

2 Data and Methods 

2.1 Datasets 

A11 World Fertility Surveys (WFS) and Demographic and Health Surveys (DHS) that were 

available in early 2005 were considered for this study. Surveys with samples based only on ever-married 

women and surveys without information on ethnicity were excluded. When several surveys were 

available for the same country, only those in which the coding of ethnicity was explicit and consistent 

were kept for final analysis. Information about the surveys kept for final analysis is shown by country in 

the Appendix, along with the reasons given for the choices. When several compatible surveys were 

selected in the same country, the computations regarding premarital fertility were made on the combined 

dataset. The main reason for combining datasets was to increase the sample size of ethnic groups in the 

country. Final results are provided at the country level only. The analysis covers 25 sub-Saharan 

countries, which accounts for a large proportion (about 75 percent) of the total population of the region. 

2.2 Ethnicity in DHS Surveys 

DHS surveys have been conducted in 32 African countries but several surveys did not include 

information on ethnicity. Also, while some surveys included information on ethnicity, they differed in the 

characterization of ethnic groups and in the level of detail provided. Some surveys (such as those in 

Zambia) included a comprehensive list of all of the ethnolinguistic groups while others (such as those in 

Senegal) included only a list of the largest groups, ignoring small minorities. Another group of surveys 

(such as those in Mali) included a short list of the main ethnic groups, and a large “other” category. In 

some cases, only large language families were provided (such as in Togo), and in a few surveys in 

Southern Africa, only race was included (such as in Zimbabwe). 

Information on ethnicity in DHS surveys is usually provided by the V131 variable of the 

Individual Recode file, although it appears in the S-section of country-specific variables in some surveys. 

In one case (Uganda 2001), the information was contained in the Household Recode file as the language 

in each cluster. In this case we merged the cluster with the individual file to determine the ethnicity of the 

person interviewed. 

Some countries recorded ethnicity confidentially in the questionnaires, and the labels of the ethnic 

groups were not available in the dataset code book. In some cases the labels could be retrieved from other 

information, such as language spoken, but in others the analysis had to be cancelled. 

Lastly, some surveys provided only the language usually spoken by the respondent as the sole 

information on ethnicity. This information was used in a few cases. However, information on the 

language used for the interview was not considered in this study because it may not reflect correct ethnic 

identity. Each case is detailed in the Appendix by country and survey. 

In some countries, when the necessary information was available, the ethnic distribution obtained 

from the DHS surveys was compared with the distribution obtained from the national censuses. Another 

source of information was the Ethnologue database, which provides names, locations, and population 

sizes of virtually all ethnolinguistic groups in Africa (Gordon, 2005). 

In terms of sample size, the cluster sampling method used in DHS surveys is unlikely to provide 

an accurate ethnic distribution in a country. Many clusters are likely to be ethnic-specific and, as a result, 

the ethnic distribution may show overestimates or underestimates, according to chance. It would be 

cumbersome to try to estimate the biases involved because they depend on the ethnic distribution in each 
4

enumeration area. However, since the emphasis of this study is on the specificity of ethnic groups, minor 

variations in sample size are unlikely to affect the main results. 

The spelling of ethnic groups was kept as indicated in the DHS code books. Some groups have 

English spelling; others have French or Portuguese spelling. Some ethnic group labels differ from those in 

the classical ethnographic literature, but no attempt was made to correct them. 

2.3 Sample Size and Grouping of Datasets

In many countries, more than one survey was conducted. When possible, the surveys were 

grouped together to increase the sample size of small groups and to reduce the confidence intervals 

associated with the prevalence of premarital fertility. This was done only in cases where the coding was 

consistent from survey to survey. Each case is detailed in the Appendix. 

A main limitation of the analysis of ethnicity in DHS surveys is sample size. The typical DHS 

survey has a sample of about 7,000 women. A minority group that makes up only 1 percent of the 

population will have only 70 women surveyed. This was considered too small a sample for this 

demographic analysis. Therefore, after grouping surveys in a country, ethnic groups with at least 250 

women were kept for analysis. This allowed even small groups to be included in countries where two or 

more surveys were conducted. A sample of 250 women will provide reasonable confidence intervals for 

the prevalence of premarital fertility. For example, a prevalence of 20 percent and a sample of 250 

women give a 95 percent confidence interval of 15.1 to 24.9 percent, which still allows a distinction 

between low, medium, and high levels of premarital fertility. Of course, larger sample sizes are desirable 

for finer estimation; however, because the aim of the study was to analyze ethnic diversity, it was 

preferable to include small groups with a wider confidence interval rather than ignore them. In a few 

cases, even smaller groups (such as the Twa in Rwanda) were included when they had special 

significance for ethnographic reasons. Proper testing of differences between groups is sometimes done 

after controlling for other factors. Readers who wish to do their own testing can do so using the tables in 

the Appendix, which include sample size. It is recommended to use simple testing based on sample size 

(unweighted number of women interviewed)—assuming random distribution of women within ethnic 

group—and to ignore the design effect associated with cluster sampling. This is suggested because most 

clusters in Africa are likely to be ethnic-specific. 

In the analysis of ethnicity, priority was given to specificity: well-defined groups were considered 

individually while others were lumped together in the “other and unknown” category. This was 

considered more informative than attempting to group them by language families or by geographical 

proximity. However, in cases of high ethnic diversity (such as in Nigeria and Cameroon), small ethnic 

groups were lumped together by geographical area, following the main divisions of the country. 

2.4 Prevalence of Premarital Fertility 

The DHS definition of marriage was used in this report for consistency. In DHS surveys, a 

woman is considered married if she is formally married (civil or religious union)2

 or if she is in an 

informal union (living together). For a discussion of discrepancies in African surveys regarding “married” 

and “in union,” see Garenne (2004). Terminal celibacy is defined as the probability of never marrying by 

age 50. It is approximated by the proportion of never-married women age 40-49 at the time of the survey. 

The Appendix shows two indicators of the prevalence of premarital fertility.3

 The first is the 

prevalence of premarital births, defined as the proportion of all births that occurred before the first 

 

2

 Includes customary marriages 

3

 Almost all DHS surveys interview women age 15-49 only and collect retrospective maternity histories. 
5

marriage. Dates are counted in months and years, as defined by the century month code (CMC) system of 

the DHS surveys (corresponding variables are V509 for first marriage and V211 for first birth). The 

second is the proportion of women who have had a premarital birth to all women who have ever given 

birth or who have ever been married. (Never-married women who never had a live birth were excluded 

from the calculations.)4

 The prevalence of premarital intercourse, defined as the proportion of women 

who had intercourse before their first marriage (V525 variable), was calculated wherever possible. 

Median age at first marriage was calculated by selecting all women age 25 and over and 

determining the age at which 50 percent of the women in each cohort were ever married. Because some 

women will never marry, this definition differs from the formal definition of median age at first marriage, 

which uses ever-married women as the population base. It is also different from mean age at first 

marriage, which is computed from life table analysis. In most cases the three values were found to be 

equivalent. Calculating life table estimates for each ethnic group would be cumbersome and would lead to 

erratic estimates in small ethnic groups. 

2.5 Socioeconomic Variables 

Several socioeconomic variables were considered as potential determinants of level of premarital 

fertility. Urban residence was measured by the proportion of interviewed women living in urban areas. 

This figure in DHS surveys sometimes varied substantially from the proportion urban as reported by the 

national census. Because of the cluster sampling method used in DHS surveys, some clusters for selected 

ethnic groups can end up primarily in one or the other residence categories (urban or rural). This 

introduces bias into the calculation of prevalence of premarital fertility for small ethnic groups. However, 

because this study focuses on diversity, the bias probably does not have much effect on the analysis. 

Religion was taken as reported in the DHS surveys, and grouped into three categories: Muslims, 

Christians, and “other and unknown.” First analyses revealed only minor differences among Christian 

groups (Protestants versus Catholics), although the distinction can be a major source of differentials when 

associated with other characteristics, as occurred in the case of Madagascar (Garenne and Zwang, 2004). 

Analyzing traditional religion is beyond the scope of this paper, and DHS surveys do not provide details 

on local religions, which are usually grouped under labels such as “traditional religion,” “animist,” or 

“spiritualist.” 

A wealth index was developed for this study, although it follows a model described elsewhere 

(Garenne and Hohmann, 2003). It is the sum of a group of dummy variables that count modern goods and 

amenities in the household. The wealth index was calculated the same way for all of the surveys so that it 

could be used comparatively and averaged for ethnic groups. It therefore differs from the DHS wealth 

index provided by some DHS surveys, which is based on principal components and wealth quintiles. 

Other data used for this analysis were straightforward and derived directly from the survey. Level of 

education was measured by the mean number of years of schooling (V133). Because use of a 

contraceptive method might be an important element in premarital fertility, “knowledge of any modern 

method” (V301), “ever use of any modern method” (V302), and “current use of any modern method” 

(V303) were considered separately. Use of contraception was examined only for women who had ever 

had intercourse and were never married—that is, use of contraception during the risk period for premarital 

births. Modern contraceptive methods were selected because they have the largest effect on unwanted 

pregnancies. 

 

4

 The two indicators refer to live premarital births; premarital pregnancies that resulted in miscarriage or abortion are 

not included. 
6

2.6 Methodology 

Premarital fertility is a period-specific measure of births that occur before marriage. The period of 

risk for premarital births is the interval between first intercourse and first marriage. Premarital fertility is 

the product of a series of demographic behaviors: first intercourse, first marriage, contraceptive use, and 

abstinence between first intercourse and first marriage. The prevalence of premarital births in a group is 

likely to be positively correlated with age at marriage, and negatively correlated with age at first 

intercourse and use of modern contraceptive methods. These demographic factors have a structural effect 

on premarital fertility. Other variables, labeled “socioeconomic determinants,” affect these intermediate 

variables, as well as attitudes. These include ethnicity, religion, urban-rural residence, level of education, 

polygyny, and wealth. 

This analysis aims to describe differentials in the prevalence of premarital fertility by ethnicity as 

well as by demographic and socioeconomic factors. While some of the analysis could have been done 

using individual-level data, the use of ethnic group as the unit of analysis offered the opportunity to 

include several factors that could not otherwise be included—in particular, age at first marriage and level 

of contraceptive use. These were found to be major factors determining premarital fertility at the group 

level, but were inappropriate at the individual level. For example, if a woman is never married but had a 

premarital birth, she does not have an age at marriage. 
7

3 Results 

3.1 Samples of Ethnic Groups 

Of the 51 countries in sub-Saharan Africa, 32 were covered by DHS surveys and 25 of these 

surveys had information on ethnicity (see Table 3.1). Altogether, 43 surveys were included in the 

analysis, 8 of which were WFS surveys and 35 were DHS surveys. Some 2,104 ethnic groups are 

included in the Ethnologue database for Africa, which is the most extensive count. It corresponds to an 

average of 310,600 persons per ethnic group, with populations ranging from a few individuals to several 

million. 

In the 43 surveys analyzed, 263 ethnic groups were kept for final analysis. They were usually the 

larger groups, and their average population size was more than five times that of the average group size 

for the whole set. DHS surveys primarily include large groups, whereas the ethnographic literature tends 

to emphasize small, well-defined groups with specific cultural characteristics. 

After grouping surveys, the average sample size per country was 12,915 women interviewed. The 

overall average of 1,228 women interviewed per ethnic group is an appropriate sample size for many 

demographic estimates, including premarital fertility. 

Table 3.1 Ethnic groups in sub-Saharan Africa: Information from population and survey data, 

various sources including WFS and DHS national sample surveys 

Coverage of DHS surveys 

Characteristic 

Total 

sub-Saharan

Africa Total 

Information 

on ethnicity 

Total population 

 Number of countries 51 32 25 

 Number of ethnic groups 2,104a

 1,804 1,648 

 Population covered (millions) 653.6b

 562.2 491.6 

 Mean size of ethnic groups 310,600c

 311,600 298,300 

Sample surveys (DHS, WFS) DHS and WFS surveys analyzed 

 Number of surveys analyzed 43 

 Number of ethnic groups 263 

 Mean population size per group 1,621,200 

 Average survey sample size (number of women interviewed) 12,915 

 Mean number of women interviewed per ethnic group 1,228 

a

 Ethnologue database (Gordon, 2005) 

b

 Population in year 2000 (United Nations, Population Division) c

 Mean size = population/number of ethnic groups 

 

 
8

3.2 Premarital Fertility by Ethnicity 

The prevalence of premarital fertility, defined as the proportion of women who had a premarital 

birth, varies considerably among the 263 ethnic groups examined, from 0.1 percent (Kanem-Bornou in 

Chad) to 76.2 percent (Herero in Namibia). The wide range is illustrated in Figure 3.1. The distribution of 

ethnic groups by premarital fertility is complex and does not follow a simple statistical distribution; 

instead, it shows wide heterogeneity. At one end of the range are low levels of premarital fertility, which 

could be interpreted (in repressive societies) as accidents or as deviant behavior by a small proportion of 

the population. A second group clusters between 10 and 13 percent; another group is 22 to 27 percent; 

another group is 38 to 41 percent; and a number of ethnic groups have very high levels of premarital 

fertility (50 percent and above). Such a wide range of prevalence of premarital fertility reflects the wide 

variety of behavioral norms described in the ethnographic literature, from societies that require girls to 

marry right after puberty—in which case premarital fertility is virtually impossible—to societies in which 

marriage occurs late and premarital intercourse is permitted. 

Figure 3.1 Distribution of ethnic groups according to the prevalence of 

premarital fertility, 25 countries in sub-Saharan Africa 

0 5 10 15 20 25

< 2

2-3

4-5

6-7

8-9

10-11

12-13

14-15

16-17

18-19

20-21

22-23

24-25

26-27

28-29

30-31

32-33

34-35

36-37

38-39

40-41

42-43

44-45

46-47

48-49

50-51

52-53

55-55

56-57

58-59

60+

Level of premarital fertility (%) ok

No. of ethnic groups
9

Five levels of premarital fertility can be defined: “Very Low” for levels below 9.0 percent, with 

an average of 4.7 percent; “Low” from 9.0 to 14.9 percent, with an average of 12.1 percent; “Medium” 

from 15.0 to 29.9 percent, with an average of 22.0 percent; “High” from 30.0 to 49.9 percent, with an 

average of 38.6 percent, and “Very high” above 50.0 percent, with an average of 66.5 percent (Table 3.2). 

The mean population size of ethnic groups did not indicate a linear relationship with level of premarital 

fertility; permissive and repressive behaviors were found in small and large groups alike. 

Table 3.2 Distribution of ethnic groups by level of premarital fertility, sub-Saharan Africa 

Level of premarital 

fertility 

Range 

(%) 

Number of 

ethnic groups 

Mean 

population 

per group 

Mean level of 

premarital 

fertility (%) 

Very low < 9 81 1,969,661 4.7 

Low 9-14 57 1,965,123 12.1 

Medium 15-29 73 1,160,181 22.0 

High 30-49 34 1,031,049 38.6 

Very high 50+ 18 1,949,115 66.5 

 

Total 263 1,621,245 17.9 

3.3 Comparison with the Ethnographic Literature 

Estimates of the prevalence of premarital fertility by ethnicity in DHS surveys were matched with 

ethnographic characteristics in Murdock’s Atlas (Table 3.3). Matching groups from the two sources was 

difficult because of the different ethnic categories and many missing values in the Atlas. Altogether, only 

91 ethnic groups could be matched; of these, 36 had ethnographic details on premarital norms. Despite the 

low coverage, a pattern emerged. Groups who were more repressive (V and E) had lower premarital 

fertility (9.2 percent and 12.9 percent), intermediate groups (P) had medium values (15.8 percent), and 

groups classified as permissive (A and F) had higher values (37.9 percent and 20.0 percent). Even though 

the sample of selected ethnic groups was obviously biased and the sample sizes of some groups were 

small, the average of selected groups (17.7 percent) was close to the African average, and the 

demographic classification approximately matched the ethnographic typology. 

Table 3.3 Norms of premarital sexual behavior in African ethnic groups from Murdock’s Atlas, and relationship 

between ethnicity and the prevalence of premarital fertility in DHS surveys 

Norms of premarital sexual behavior 

Number of 

groups in Atlas 

Number of 

groups found in 

DHS surveys 

Average percentage 

of women with a 

premarital birth 

A 

Premarital sexual relations allowed; no 

sanctions unless pregnancy results 12 4 37.9 

F Premarital sexual relations freely permitted; 

no sanctions 48 19 20.0 

P Premarital sexual relations prohibited; weak 

sanctions; not infrequent in fact 15 3 15.8 

E Premarital sexual relations precluded by 

early age at marriage for females 11 5 12.9 

V 

Insistence on virginity; premarital sexual 

relations prohibited; strong sanctions, rare 

in fact 

 28 5 9.2 

 Total, stated 114 36 17.7 

 Total, not stated 163 227 

 Total 277 263 17.7 

Source: Murdock Atlas (1967) and DHS surveys 
10

3.4 Demographic Factors and Socioeconomic Determinants 

Correlations of premarital fertility with demographic factors are shown in Table 3.4. Premarital 

fertility is positively correlated with age at first marriage (+0.779), age at first intercourse (+0.217), and 

terminal celibacy (+0.687). The first and third correlations are straightforward because later marriage and 

lower levels of marriage are likely to result in an increase in premarital fertility. The second correlation 

shows the results of the selection effect: women who marry later and have first intercourse at the time of 

marriage have higher age at first intercourse. In fact, if age at marriage is controlled, the net effect of age 

of first intercourse becomes negative. 

Table 3.4 Correlation of premarital fertility with demographic factors, modern 

contraception, and socioeconomic determinants, sub-Saharan Africa 

Variables 

Correlation 

coefficients P-value Significance 

Demographic factors 

Age at first marriage 0.779 6.10E-55 * 

Age at first intercourse 0.217 3.98E-04 * 

Terminal celibacy 0.687 4.46E-38 * 

Modern contraception 

Knowledge 0.319 1.30E-07 * 

Ever use 0.496 9.79E-18 * 

Current use 0.373 4.36E-10 * 

Socioeconomic determinants 

Urbanization 0.456 6.80E-15 * 

Education 0.692 9.45E-39 * 

Wealth index 0.588 7.98E-26 * 

Proportion Muslim -0.436 1.29E-13 * 

Proportion Christian 0.383 1.26E-10 * 

Polygyny -0.478 2.11E-16 * 

p = <0.05 

The effect of contraception is counterintuitive; all three variables (knowledge, ever use, and 

current use) had a positive correlation with premarital fertility, suggesting that greater use of 

contraception leads to higher fertility. Such a conclusion is the result of reverse causality because groups 

that have higher levels of premarital fertility are more likely to use contraception. So far, use of modern 

contraceptive methods before marriage has not had a large enough impact to allow women to prevent 

premarital births (assuming that this is their desire). Thus, the results in Table 3.4 imply that use of 

modern contraceptive methods is not an important factor in premarital fertility. 

Four socioeconomic variables were found to have a positive correlation with premarital fertility: 

urban residence, level of education, wealth, and Christianity. The effect of these variables is related 

primarily to higher age at first marriage, but also increased terminal celibacy (Table 3.5). 

The two remaining variables, Islam and polygyny, had negative correlations with premarital 

fertility. Here again, the effect is primarily related to nuptiality, particularly lower age at marriage, but 

also decreased terminal celibacy (Tables 3.4 and 3.5). Note that Islam and polygyny are correlated 

(0.493), and that both tend to encourage early and universal marriage for women. 

An analysis of premarital fertility shows that socioeconomic determinants explain about half 

(57 percent) of the total variance. The rest is due to ethnicity, thus emphasizing the strong role of cultural 

factors in childbearing before marriage. 
11

Table 3.5 Correlation coefficients between socioeconomic determinants and demographic factors, subSaharan Africa (N = 263 ethnic groups) 

Nuptiality Modern contraception 

Socioeconomic 

determinants 

Age at first 

marriage 

Age at first 

intercourse 

Terminal 

celibacy Knowledge 

Ever 

use 

Current 

use 

Urbanization (%) 0.358 0.112 0.270 0.290 0.338 0.173 

Education (No. of years) 0.681 0.461 0.450 0.470 0.496 0.312 

Wealth index 0.616 0.371 0.470 0.335 0.572 0.406 

Muslim (%) -0.458 -0.314 -0.265 -0.297 -0.328 -0.187 

Christian (%) 0.422 0.339 0.220 0.382 0.322 0.158 

Polygyny (%) -0.523 -0.338 -0.430 -0.329 -0.304 -0.247 

3.5 Geographical Patterns 

All these factors interact to shape geographical patterns of premarital fertility. Details at the 

country level are provided in the Appendix and show great diversity in countries with complex social 

systems and numerous ethnic groups. Some regional patterns emerge. Prevalence of premarital fertility is 

low in the West African Sahelian areas, medium in coastal West Africa and in Eastern Africa, and high to 

very high in Southern Africa (Figure 3.2). In Sahelian West Africa, there is a gradient from the most 

conservative area in the central part of the region, primarily rural and Muslim, to the more urbanized 

West, with the exception of Mandinka and Poular areas in Northern Guinea, which appear to be very 

Figure 3.2 Prevalence of premarital fertility in Africa, by region 
12

conservative. On the West African coast, Liberia and southern areas of Côte d’Ivoire appear as 

exceptions. In Central Africa, a pocket of high levels of premarital fertility ranges from southern 

Cameroon to Gabon. In Eastern Africa, pockets of higher premarital fertility are seen in southern Uganda, 

central Kenya and southern Tanzania. The highest levels of premarital fertility are found in Southern 

Africa; this includes Namibia, South Africa and Botswana, up to southern Zambia. In Madagascar, 

premarital fertility is more prevalent on the northeast coast and less prevalent in the central highlands. 

The geographical patterns for the prevalence of premarital fertility in sub-Saharan Africa are 

related to the patterns for age at first marriage (Figure 3.3). However, some exceptions can be noted. 

Premarital fertility is low in Rwanda, Burundi, and central Madagascar at the same time that age at first 

marriage is high. In these countries contraceptive use is low and there is strong social control of young 

women. 

Figure 3.3 Median age at first marriage in Africa, by region 
13

A better illustration of the relationship between premarital fertility and age at first marriage is 

seen in Figure 3.4. This figure reveals three situations: 

• Very low age at marriage (<15 years), which correlates with very low premarital fertility 

(<10 percent). 

• Very high age at marriage (≥22 years), which correlates with very high premarital fertility 

(≥50 percent). 

• Intermediate levels of age at first marriage (15-21 years) with a wide range of levels of premarital 

fertility. For instance, around age 18, premarital fertility ranges from virtually 0 to 40 percent or 

more. 

 This case highlights the importance of cultural factors that are not explained by the 

socioeconomic variables examined in this study, and which reveal the different norms regarding 

premarital fertility that are associated with the various ethnic groups. 

Figure 3.4 Relationship between prevalence of premarital fertility and 

median age at first marriage among 263 African ethnic groups 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

14 16 18 20 22 24 26 28 30 32

Median age at first marriage

% premarital women

3.6 Outliers from Demographic Variables 

Another way of showing how cultural factors shape the distribution of premarital fertility—beyond 

the effect of demographic factors—is looking at the outliers, groups that differ significantly from 

expected values based on median age at first marriage and median age at first intercourse. 

The negative outliers are groups with lower-than-expected premarital fertility, which indicates a 

more repressive attitude toward women who give birth before marriage. Groups differing by more than 10 

percent were found in several countries throughout Africa: many groups in Ghana (Akwapim, Asante, 

Ga-Adangbe, Fante, other Akan, Ewe, Guan, Mole-Dagbani, Grussi); several groups in southeastern 

Nigeria (Igbo, Ibibio, Annang, Ijaw, Urhobo) and the Yoruba; many groups in Malawi (Yao, Lomwe, 
14

Chewa, Sena, Anyanja); several groups in the Central African Republic (Yakoma-Sango, Mandjia, 

Banda, Zande-Nzakara, Gbaya); several groups in Benin (Yoa and Lokpa, Adja, Fon, Betamaribe, 

Yoruba); and two groups in Tanzania (Makonde, Sukuma). The average prevalence of premarital fertility 

for these groups was 11 percent, which is half of what was expected (22 percent) based on age at first 

marriage and age at first intercourse. 

The positive outliers are groups with higher-than-expected premarital fertility, which indicates a 

more permissive attitude toward women who give birth before marriage. Here again, groups differing by 

more than 10 percent were found throughout Africa: many groups in Liberia (Grebo, Vai, Krahn, 

Krou/Sapo, Gola, Bassa, Mano, Lorma); many groups in Gabon (Okande-Tsogho, Kota-Kele, NzabiDuma, Mbede-Teke, Shira-Punu/Vili, Fang); several groups in Tanzania (Pare, Ngoni, Iramba, Pogoro, 

Ndengereko); several groups in South Africa (Tsonga, Venda, Swazi), as well as in nearby Zimbabwe 

(Ndebele), Namibia (Caprivi/Lozi) and Southern Zambia (Mbunda, Bisa, Tonga); several groups in 

Cameroon (Boulou-Fang, other Adamaoua, Wimbum-Yamba, Bamoun, Gbaya); and small groups in 

southern Senegal (Diola, Manjaak/Mancagne/Balant). The average prevalence of premarital fertility for 

these groups was 43 percent, which is well above what was expected (30 percent) based on age at first 

marriage and age at first intercourse. 

4 Conclusions 

This study of the prevalence of premarital fertility by ethnicity shows wide variation throughout 

sub-Saharan Africa. A woman giving birth before marriage ranges from being a rare event to being 

almost universal. Such a broad range of behavior is unusual when compared with other demographic and 

social indicators. While problems of definition and sample size must be taken into consideration, the 

overall diversity of the results of this study are apparent from the data, and matches the diversity of 

behavior documented in the ethnographic literature. DHS surveys facilitate this kind of comparative 

analysis because they utilize consistent questions on age at first marriage, age at first intercourse, and age 

at first birth. 

The prevalence of premarital fertility has a structural component; it is bounded by the window of 

opportunity (for a birth to occur) between a woman’s first intercourse and her first marriage, assuming 

nonuse of contraception during this period. In the study, the correlation between age at marriage and 

premarital fertility was strong. Age at marriage, which varied widely among groups, was found to be the 

most important factor in premarital fertility. Age at first intercourse had varied less and had less impact on 

premarital fertility. However, age at first marriage and age at first intercourse do not explain everything. 

The study found that while attitudes and behaviors have considerable influence, contraceptive use has 

little impact. A number of ethnic groups were found to be particularly repressive in terms of premarital 

intercourse whereas others were generally permissive. These behaviors are ethnicity-specific even though 

other factors such as religion have an impact. 

Cultural change in the twentieth century has influenced patterns of premarital fertility in Africa. 

First, the spread of monotheistic religions has had a strong negative effect on premarital fertility. At the 

same time, increases in modern education and wage-based income have had a positive effect, with women 

delaying childbirth until after marriage. These contrasting forces explain to a large extent the higher levels 

of premarital fertility found in urban areas and in wealthier countries. The balance between positive and 

negative effects may explain the intermediate situation in some countries, while other countries have been 

more influenced by one set of factors than another. Here again, the variation within and between groups is 

substantial in sub-Saharan Africa, and modernization has further complicated an already diverse situation. 
15

This overview has several limitations. Above all, we regret the lack of details on ethnicity and its 

coding in many countries. However, now that a list of ethnic groups is available with standardized coding, 

we encourage the use of the list in demographic surveys. This will allow further analysis and, in some 

instances, the grouping of cases by language family or geographical proximity. Such activities promoting 

standardization would improve the quality of analyses. Some countries have chosen to ignore ethnicity in 

their demographic surveys for political reasons. However, failing to record this important information, 

which is needed for adequate program planning at national and regional levels, misses a valuable 

opportunity for analysis and deeper understanding of African societies. 

Ethnicity has long been neglected in demographic research, partly because of its complexity and 

its lack of standardization, but also because of lack of interest among those studying basic topics such as 

fertility and mortality. However, for topics such as nuptiality and migration, or the spread of HIV/AIDS, 

ethnicity may be one of the key factors in differentials by country or region. This study has shown the 

important effect of ethnicity on premarital fertility. The correlation of data on premarital fertility in subSaharan Africa by ethnic group has yielded new information that could not have been obtained using 

standard socioeconomic determinants alone. 
17

References 

Garenne, M. 2004. Age at marriage and modernization in sub-Saharan Africa. Southern African Journal 

of Demography 9(2):57-77. 

Garenne, M., and S. Hohmann. 2003. A wealth index to screen high risk families: Application to 

Morocco. Journal of Health, Population and Nutrition 21(3):235-242. 

Garenne, M., and J. Zwang. 2004. Social change and premarital fertility in Madagascar. Southern African 

Journal of Demography 9(1):27-48. 

Garenne, M., and J. Zwang, 2005. Premarital fertility in Namibia: Levels, trends and factors. Journal of 

Biosocial Science 37(1):1-23. 

Garenne, M., S. Tollman, and K. Kahn. 2000. Marital and premarital fertility in a rural area of South 

Africa: A challenge to existing population policy. Studies in Family Planning 31(1):47-54. 

Gordon, R.G., Jr. (ed.). 2005. Ethnologue: Languages of the world, Fifteenth edition. Dallas, Texas: SIL 

International. Available at http://www.ethnologue.com/. 

Grandidier, G. 1913. Le mariage à Madagascar. Bulletins et mémoires de la Société d'anthropologie de 

Paris, séance du 16 janvier 1913. 

Murdock, G.P. 1967. Ethnographic atlas: A summary. Ethnology 1:109-236. Pittsburgh: University of 

Pittsburgh Press. 

Radcliffe-Brown, A.R., and D. Forde. 1950. African systems of kinship and marriage. London: Routledge 

and Kegan. 

van de Walle, E. 1968. Marriage in African censuses and inquiries. In The demography of tropical Africa,

ed. W. Brass et al., 183-238. Princeton: Princeton University Press. 

Zwang, J. 2004. Perceptions and attitudes towards late marriage and premarital fertility in rural South 

Africa. Cahiers de l’IFAS, No. 4. Available at http://www.ifas.org.za 
Appendix 

Premarital Fertility and Ethnicity 

in Africa: 

Country Analysis
21

Overview of the Country Analysis 

This section presents estimates of premarital fertility by ethnicity for 25 countries in sub-Saharan 

Africa. A description of the methodology is presented in the main part of this report. The Appendix is 

organized by country with the data presented in the same format for each country: description of the 

available surveys, distribution of selected ethnic groups, and estimates of premarital fertility and its main 

correlates (median age at first marriage, percentage living in urban areas, and percentage that had sexual 

intercourse before marriage). 

A figure for each country illustrates the relationship between age at first marriage and premarital 

fertility, which is defined as the proportion of women who gave birth before marriage. Usually, the 

relationship is linear; that is, premarital fertility increases as age at marriage increases. However, in some 

countries the relationship is either absent (homogeneous countries) or complex (curvilinear relationship). 

A straight line is shown in each figure to guide the reader. 

The country analyses presented here are limited in scope. The aim was to explain how ethnic 

groups were selected for analysis and to describe the main relationships between premarital fertility, age 

at first marriage, and ethnicity, at the national level. All estimates were calculated using weighted samples 

(V005 in DHS files). 

Definitions 

Definitions for the indicators presented in Table 3 for each country are the following: 

Percent urban is the proportion of interviewed women living in urban areas. For some ethnic groups the 

percentage urban may differ from that cited in the national census. Because of the cluster sampling 

method used in DHS surveys, some clusters for selected ethnic groups can end up primarily in urban or 

rural areas. 

Median age at first marriage was obtained by selecting women age 25 and over and calculating for each 

cohort the age at which 50 percent of the women were ever married. This definition is different from life 

table estimates for median age at marriage. 

Percent never married is the proportion of women age 40-49 at the time of the survey who were never 

married. 

Percent premarital births is the proportion of births that occurred prior to the woman’s first marriage, 

dates being counted by month and year. 

Percent women with premarital birth is the proportion of women who had at least one premarital birth, 

among those who are either ever married or ever fertile. Never-married women who never had a live birth 

are excluded. 

Percent premarital intercourse is the proportion of women who had sexual intercourse prior to their 

first marriage, among those who ever had intercourse. 
22

BENIN 

Benin conducted one WFS survey in 1982 and two DHS surveys, in 1996 and 2001. The WFS 

survey code book did not provide the codes for ethnicity (V707), and it was not possible to recover the 

labels from the “language spoken at home” variable (S727), except for a few obvious cases. It was 

decided that only the data from the two DHS surveys would be used. The 1982 WFS survey included the 

42 official ethnic groups of Benin. The DHS surveys included only the eight main linguistic groups. 

These groups appear to have remained stable over the years and were also used in the census. 

Table 1 Sample size and main characteristics of surveys, Benin 

Benin WFS 

1982 

DHS 

1996 

DHS 

2001 

No. of women interviewed 4,018 5,491 6,219 

No. of ethnic categories, local 42 

No. of families of ethnic groups 8 8 

No. of ethnic categories, foreign 1 1 1 

Percent other and unknown 6.7 4.8 4.6 

The two DHS surveys were compatible, with coding of the ethnicity variable (V131) basically the 

same in both surveys (Table 2). There were, however, some minor differences, the most important being 

the higher proportion of Fon, the largest ethnic group in the country, in the second DHS survey, and a 

corresponding gap among the Bariba, Yoa and Lopka, Betamaribe, and Peulh. This pattern is related to 

the higher number of women who answered the questionnaire in Fon in the second survey (49.7 percent), 

compared with 1996 (35.3 percent) and 1982 (28.9 percent). 

 

Table 2 Distribution of ethnic groups by survey, Benin 

Difference 

between the two 

DHS surveys 

Ethnic group 

Census 

1992 

DHS 

1996 

DHS 

2001 P-value 

Significance 

Adja 15.6 14.6 15.1 0.438 

Bariba 8.6 9.5 8.2 0.014 * 

Dendi 2.8 2.5 2.7 0.548 

Fon 42.2 39.9 45.0 0.000 * 

Yoa and Lokpa 3.8 5.7 3.7 0.000 * 

Betamaribe 6.1 6.4 5.1 0.004 * 

Peulh 6.1 6.0 3.8 0.000 * 

Yoruba 12.1 10.7 11.9 0.042 * 

Other and unknown 2.7 4.8 4.6 0.642 

 

Total 100.0 100.0 100.0 7.37E-48 * 

*p <0.05 

It was decided that this minor difference between the two surveys would not seriously bias the 

estimates. In fact, it probably functioned to minimize differences between the Fon and the other groups 

because, increasingly, people in the other groups tended to assimilate themselves into the dominant group. 

In addition, the distribution of the population in the second DHS survey was similar to that of the 1992 

census, with some minor differences. The 1996 and 2001 DHS surveys were therefore combined for the 

final estimates. 
23

Premarital Fertility

 Premarital fertility is low in Benin compared with other African countries. The proportion of 

women with a premarital birth ranges from 4.9 percent among the Peulh to 13.6 percent among the 

Yoruba. The Yoruba are among the more urbanized groups and have a somewhat higher age at first 

marriage, whereas the Peulh are the least urbanized group and have a lower than average age at marriage. 

Overall, premarital fertility is low given the relatively high prevalence of premarital intercourse (55.0 

percent). 

Table 3 Premarital fertility and nuptiality indicators, Benin 

Ethnic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

 never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Adja 1,941 36.6 19.0 0.0 2.8 7.8 44.2 

Bariba 1,037 39.0 17.2 0.0 3.0 9.1 36.5 

Dendi 292 64.8 17.7 0.0 2.2 6.5 35.9 

Fon 4,761 40.5 18.8 0.7 3.4 9.2 58.2 

Yoa and Lokpa 590 30.2 18.1 0.8 1.6 5.6 31.9 

Betamaribe 751 28.1 16.8 1.7 4.3 9.8 37.2 

Peulh 589 14.9 17.5 0.0 1.8 4.9 20.1 

Yoruba 1,211 52.7 19.2 2.0 5.2 13.6 55.9 

Other and unknown 538 58.1 19.0 1.4 5.2 12.2 54.8 

 

Total 11,710 40.2 18.5 0.7 3.4 9.1 55.0 

Source: Authors’ calculations after merging data from 1996 and 2001 DHS surveys. 

 Correlation with age at marriage was low (ρ = 0.35). Figure 1 shows three groups: a group in the 

middle with expected values of medium age at marriage and low premarital fertility (Peulh, Dendi, Yoa 

and Lokpa); a group with low age at marriage and higher premarital fertility (Bariba, Betamaribe); and a 

group with higher age at marriage and higher premarital fertility (Yoruba, Fon, Adja). 

The correlation with urban residence was more straightforward, although it remained moderate 

(ρ = 0.40). The more urbanized groups also had higher premarital fertility. The only exception was the 

Dendi, who had lower than average premarital fertility despite the highest proportion of urban residence. 

 
24

Figure 1 Correlation between premarital fertility and age at first marriage, Benin % women with premarital birth

Betamaribe

Yoa & Lokpa Peulh

Yorouba

Adja

Fon

Dendi

Bariba

0

5

10

15

20

15 16 17 18 19 20

Median age at first marriage (years)
25

BURKINA FASO 

Burkina Faso conducted three DHS surveys, in 1993, 1996, and 2003. The second DHS survey 

included more ethnic groups (Bissa, Dafing, Dagara, Samo) than the first, although these disappeared in 

the last survey, with the exception of the Bissa. There are about 50 ethnolinguistic groups reported in 

Burkina Faso. Grouping them into 10 categories is a simplification, however the largest groups are well 

defined in the DHS surveys. 

Table 1 Sample size and main characteristics of DHS surveys, Burkina Faso 

Burkina Faso 

DHS 

1993 

DHS 

1996 

DHS 

2003 

No. of women interviewed 6,354 5,445 12,477 

No. of ethnic categories, local 9 13 10 

No. of ethnic categories, foreign 1 6 1 

Percent other and unknown 7.2 12.2 8.7 

Overall, the three DHS surveys were compatible with respect to ethnic distribution (Table 2), 

however there were several notable differences. The Dioula group almost disappeared in 1996 (0.5 

percent compared with 7.5 percent in 1993) then reappeared in the last survey (5.7 percent in 2003). 

According to census sources, however, Dioula speakers are assumed to make up about 9.3 percent of the 

population. 

 

Table 2 Distribution of ethnic groups by survey, Burkina Faso 

Difference between 

the first two 

DHS surveys 

Ethnic group 

DHS 

1993 

DHS 

1996 

DHS 

2003 P-value 

Significance 

Bobo 6.9 4.7 2.5 0.245 

Dioula 7.5 0.5 5.7 0.001 * 

Fulfude (Peulh) 5.3 6.5 6.3 0.561 

Gourmantche 4.2 8.2 6.9 0.056 

Gourounsi 5.8 5.3 3.4 0.796 

Lobi 4.4 1.3 5.2 0.016 * 

Mossi 56.1 58.8 56.5 0.519 

Senoufo 1.1 2.3 3.8 0.313 

Touareg 1.5 0.4 1.1 0.150 

Other and unknown 7.2 12.2 8.7 0.054 

 

Total 100.0 100.0 100.0 <E-99 * 

*p <0.05

The questions about ethnicity were the same in the three DHS surveys (Q117, Q119, and Q118 

respectively: Quelle est votre ethnie?). There was no evidence of a major bias in the sampling in 1999, 

and the provinces where Dioula are normally counted (Houet, Kadiago, Kenedougou, Kossi, Mouhoun, 

Sourou) were well represented in 1999, although somewhat less so than in 1993. Some of the Dioula 

could have been counted among the new categories in 1999, but these were not in the same provinces. It 

seems more likely that there was some confusion in 1999 between ethnic category, language of the 

interview, and language spoken at home, or some other unknown factor. Other smaller biases were 

identified in 1999; more people were counted as Gourmantche and fewer as Lobi. Other differences could 

be attributed to sample biases. 
26

Despite these small discrepancies, the three surveys were merged for the final analysis. It is likely 

that the Dioula category is underestimated. This might reduce the specificity of some of the other groups 

because some of the Dioula were probably merged with them. 

Premarital Fertility

 Premarital fertility in Burkina Faso is low compared with other African countries and marriage is 

virtually universal for women. The proportion of women with a premarital birth ranges from 2.6 percent 

among the Touareg to 12.4 percent among the Senoufo. 

Table 3 Premarital fertility and nuptiality indicators, Burkina Faso 

Ethnic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bobo 1,155 28.8 17.2 0.3 3.1 10.0 32.4 

Dioula 1,310 32.1 17.3 0.0 3.0 9.4 29.9 

Fulfulde (Peulh) 1,392 9.8 15.8 0.0 2.1 5.6 13.3 

Gourmantche 1,373 3.0 17.0 0.0 3.2 8.0 7.7 

Gourounsi 1,262 22.4 17.8 0.8 3.3 9.3 27.0 

Lobi 1,435 14.3 17.2 0.3 3.3 10.5 21.0 

Mossi 14,048 21.5 17.7 0.1 2.5 7.4 29.1 

Senoufo 922 28.8 16.8 0.0 4.3 12.4 34.3 

Touareg 243 3.4 15.1 0.0 1.1 2.6 5.5 

Bissa 758 17.1 17.8 0.0 2.9 8.3 20.0 

Other and unknown 1,378 22.9 17.4 0.0 3.9 10.6 30.8 

 

Total 25,276 20.1 17.4 0.1 2.8 8.1 26.1 

Source: Authors’ calculations after merging data from 1993, 1999, and 2003 DHS surveys. 

The main difference by ethnicity was between the pastoral groups (Fulfulde, Touareg) with low 

age at marriage, low urban residence, and low levels of premarital fertility, and the more urbanized 

groups (Dioula, Bobo, Senoufo) for whom the average age at first marriage is about 17 years. The 

Gourmantche and the Lobi had higher levels of premarital fertility than would be expected by their level 

of urban residence or age at marriage, whereas the Mossi and Gourounsi were well below the regression 

lines linking premarital fertility to urban residence or age at marriage. 

The correlation with urban residence was low (r = 0.26), as it is for the country in general. The 

correlation with age at first marriage was much higher (0.71), pointing up the gap of almost three years in 

median age at marriage between the Touareg and the Bissa (Figure 1). Differences in age at marriage are 

a major factor in the varying levels of premarital fertility in Burkina Faso. The main division is between 

the northern pastoral groups (Touareg, Peulh), which have very low age at first marriage, and all the other 

groups. 
27

Figure 1 Correlation between premarital fertility and age at first marriage, 

Burkina Faso 

Dioula

Peulh

Gourmantche

Bobo

Senoufo

Mossi

Gourounsi

Lobi

Touareg

Bissa

0

5

10

15

14 15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
28

CAMEROON 

Cameroon conducted one WFS survey in 1978 and three DHS surveys, in 1991, 1998, and 2004. 

Coding of ethnicity was very different in 1978 and not compatible with that of later DHS surveys. 

Ethnicity was not available in 1991. Coding of ethnicity was identical in the 1998 and 2004 surveys, 

therefore these two were combined for analysis. 

Table 1 Sample size and main characteristics of surveys, Cameroon 

Cameroon 

WFS 

1978 

DHS 

1991 

DHS 

1998 

DHS 

2004 

No. of women interviewed 8,219 3,871 5,501 10,656 

No. of ethnic categories, local 33 0 46 46 

No. of ethnic categories, foreign 1 1 1 1 

Percent other and unknown 4.8 0.2 1.4 3.9 

The 1998 and 2004 DHS surveys were largely compatible (Table 2). With the exception of the 

Bamileke, frequencies for ethnic groups were not significantly different in the two surveys. Because of 

the large number of ethnic groups in Cameroon—some 240 have been reported in the ethnographic 

literature—and the small sample size of some groups, only larger groups with at least 250 women were 

retained and merged according to regional residence. This resulted in 24 groups: 19 were well defined 

ethnically, 4 were regional groupings, and one comprised the category “other and unknown.” Because of 

the large sample size of the second survey and the merging of the two surveys, the differences in 

demographic behavior between groups were marked and most were significant. 

 

Table 2 Distribution of ethnic groups by survey, Cameroon 

Difference 

between the two 

DHS surveys 

V131 Ethnic group 

DHS 

1998 

DHS 

2004 P-value 

Significance 

1 Arabe Choa 0.9 0.9 0.965 

2 Peulh 4.5 5.6 0.479 

3 Haoussa 0.6 0.8 0.944 

4 Kanuri 0.3 1.0 0.690 

5 Bata 1.3 0.2 0.480 

6 Daba 0.1 0.7 0.678 

7 Guidar 1.2 1.3 0.919 

8 Kotoko 0.7 0.8 0.955 

9 Kwang/Kera 0.0 0.0 0.990 

10 Mafa 6.6 3.9 0.104 

11 Margui 1.0 0.3 0.657 

12 Massa 1.8 1.7 0.949 

14 Mousgoum 1.1 0.1 0.551 

15 Sara 0.9 0.6 0.872 

16 Wandala/Mandara 0.8 1.3 0.776 

17 Dourou 1.2 0.3 0.579 

18 Fali 2.6 1.2 0.400 

19 Gbaya 1.3 1.6 0.818 

21 Mambila 0.4 1.1 0.662 

22 Mboum 3.4 6.5 0.060 

23 Samba 0.1 0.2 0.948 

24 Banyang 1.2 0.8 0.820 

25 Bendi 0.1 0.1 0.997 

26 Efik-Korop 0.2 0.1 0.951 

27 Ejagham 0.1 0.2 0.960 

28 Mbembe 0.0 0.8 0.648 

29 Tiv 0.0 1.3 0.431 

 Continued... 
29

Table 2—Continued

Difference 

between the two 

DHS surveys 

V131 Ethnic group 

DHS 

1998 

DHS 

2004 P-value 

Significance 

30 Bebe 0.8 0.4 0.855 

31 Menchum 0.6 0.3 0.828 

32 Momo 3.0 2.0 0.542 

33 Ngemba 3.4 3.1 0.840 

34 Ring 4.3 3.4 0.572 

35 Wimbum-Yamba 1.8 1.6 0.894 

36 Bamoun 4.3 3.7 0.730 

37 Bamilike-Central 15.4 21.0 0.000 * 

38 Cotier 2.1 1.3 0.590 

39 Ngoe-Oroko 2.2 3.0 0.586 

40 Bafia 0.6 1.1 0.751 

41 Banen-Bandem 0.9 0.3 0.745 

42 Yambassa 1.4 1.1 0.828 

43 Bassa-Bakoko 4.7 4.8 0.962 

44 Beti 12.0 9.4 0.101 

45 Boulou-Fang 3.0 3.6 0.744 

46 Kako 1.1 0.8 0.834 

47 Meka 4.3 1.8 0.122 

48 Pygmee 0.5 0.1 0.809 

 Other and unknown 1.4 3.9 0.618 

 

 Total 100.0 100.0 

*p <0.05

The variation in demographic behavior by ethnicity is marked (Table 3). Age at first marriage 

ranged from 14.7 to 20.8 years; the proportion of women who had premarital intercourse was 4.8 to 79.2 

percent; the proportion of premarital births was 0.2 to 26.2 percent; and the proportion of women with a 

premarital birth was 1.0 to 49.1 percent. The diversity of behaviors associated with premarital fertility in 

Cameroon is almost as great as that of the entire African continent. 

Table 3 Premarital fertility and nuptiality indicators, Cameroon 

Ethnic group 

Number 

of women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

 never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Peulh 835 48.6 14.8 0.0 1.6 5.0 10.4 

Guidar 201 29.9 15.4 0.0 1.1 3.2 10.6 

Mafa 605 21.1 15.3 0.0 1.7 4.6 10.2 

Massa 215 29.9 15.1 0.0 0.9 2.5 11.0 

Other Northern 920 31.7 15.0 0.0 1.2 3.5 7.4 

Fali 233 15.1 14.7 0.0 0.2 1.0 4.8 

Gbaya 344 35.9 16.1 0.0 6.8 16.0 41.9 

Mboum 741 24.0 15.6 0.0 1.3 3.6 13.0 

Other Adamaoua 257 40.2 15.6 0.0 8.0 13.3 32.8 

Momo 332 36.5 18.2 0.0 10.7 27.6 61.7 

Ngemba 484 38.9 19.3 4.0 12.3 25.4 69.3 

Ring 511 39.7 19.3 8.8 15.4 32.6 64.5 

Wimbum/Yamba 244 30.9 18.3 15.8 15.5 30.2 59.1 

Other Western 516 46.5 17.9 0.0 13.6 29.1 61.9 

Bamoun 599 53.7 16.6 0.0 5.6 15.1 36.4 

Bamilike 3,275 75.4 18.8 1.3 7.0 16.4 58.4 

 Continued... 
30

Table 3—Continued 

Ethnic group 

Number 

of women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

 never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Cotier/Douala 284 73.1 20.8 2.9 19.8 37.2 76.9 

Ngoe-Oroko 491 40.7 19.1 3.5 17.4 34.4 68.0 

Bassa-Bakoko 899 67.8 19.9 1.4 18.7 38.4 75.2 

Beti 1,784 51.0 19.4 2.1 18.7 38.2 74.3 

Other Central Coast 466 58.3 19.7 7.4 17.7 34.4 67.4 

Boulou/Fang 733 44.3 20.3 0.0 26.2 49.1 79.2 

Meka 484 30.0 19.2 0.0 16.2 36.1 74.5 

Other South, East 219 24.6 17.1 0.0 8.6 19.5 59.3 

Other and unknown 485 52.7 16.5 0.0 5.6 14.8 39.0 

 

Total 16,157 48.1 17.8 1.4 8.9 20.4 48.3 

Source: Authors’ calculations after merging data from 1998 and 2004 DHS surveys. 

Correlations of the prevalence of premarital fertility with age at marriage (p = 0.942) and 

premarital sex (p = 0.955) were high, and the distribution of ethnic groups according to median age at 

marriage was basically linear (Figure 1). Correlation with urban residence was much lower (ρ = 0.488), 

and most of the differences could be attributed to differences in cultural patterns. 

Figure 1 Correlation between premarital fertility and age at first marriage, 

Cameroon

 

Guidar

Mafa Mboum

Massa

Other N

Fali

Peulh

Other Adamaoua

Gbaya Bamoun

Other S,E

Momo

Wimbum Yamba Other, WH

Bamileke

Beti

Bassa Bakoko

Cotier

Boulou Fang

Other W,C,C

Meka

Ngoe Oroko

Ngemba

Ring

0

10

20

30

40

50

14 15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
31

CENTRAL AFRICAN REPUBLIC 

The Central African Republic (CAR) conducted only one DHS survey, in 1994. Ethnicity was 

defined as the main language spoken at home (V131). The DHS survey coded nine ethnolinguistic group 

categories of African origin. 

Table 1 Sample size and main characteristics of DHS 

surveys, CAR 

CAR 

DHS 

1994 

No. of women interviewed 5,884 

No. of ethnic categories, African 9 

Percent other and unknown 2.1 

The distribution of ethnic groups is marked by two dominant groups (Gbaya, Banda) who account 

for more than half of the population, plus several groups common to Cameroon (Table 2). 

Table 2 Distribution of ethnic groups in survey, CAR 

Origin Ethnolinguistic group 

DHS 

1994 

African Hausa/Haoussa 4.9 

 Sara 6.1 

 Mboum 6.9 

 Gbaya 28.4 

 Mandjia 8.7 

 Banda 27.4 

 Ngbaka-Bantou 6.6 

 Yakoma-Sango 5.7 

 Zande-Nzakara 3.2 

Other Other and unknown 2.1 

 

Total 100.0 

Premarital Fertility by Ethnicity 

CAR has a medium age at first marriage (17.2 years), a low proportion of women who never 

marry (1.8 percent), and a moderate level of premarital fertility (5.9 percent for all births, 11.1 percent for 

women). Differentials in premarital fertility by ethnicity vary from 3.4 to 8.0 percent for all births, and 

from 6.6 to 16.8 percent for women. 

Correlation was negative with urban residence (-0.815), but positive with age at first marriage 

(+0.847). As in Cameroon, the relationship between age at marriage and the proportion of women with a 

premarital birth was straightforward, with the exception of the Hausa (Figure 1). However, premarital 

fertility and age at marriage were higher for the Mboum and Gbaya in CAR compared with their 

counterparts in Cameroon. 
32

 

Table 3 Premarital fertility and nuptiality indicators, CAR 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Hausa 290 60.1 15.6 0.0 3.4 6.6 26.8 

Sara 361 40.5 18.0 4.4 7.7 14.9 47.8 

Mboum 405 27.7 18.0 0.0 7.9 16.8 51.7 

Gbaya 1,673 35.5 17.3 3.1 7.2 13.4 53.7 

Mandjia 513 49.5 17.6 1.0 6.9 12.2 49.1 

Banda 1,610 40.8 17.0 1.5 4.1 8.3 44.6 

Ngbaka-Bantou 389 50.8 17.0 0.0 4.1 8.9 47.3 

Yakoma-Sango 335 64.3 17.1 0.0 4.4 8.0 42.0 

Zande-Nzakara 191 44.0 17.3 6.4 8.0 12.7 47.3 

Other and unknown 117 57.6 17.5 0.0 3.5 4.7 34.1 

 

Total 5,884 42.6 17.2 1.8 5.9 11.1 47.5 

Source: Authors’ calculations from 1994 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, 

Central African Republic 

Mboum

Sara

Mandjia

Zande Nzakara

Gbaya

Yakoma Sango

Ngbaka Bantou

Banda

Hausa

0

2

4

6

8

10

12

14

16

18

15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
33

CHAD 

Chad conducted only one DHS survey, in 1997. Ethnicity was defined as the main language 

spoken at home (V131). The DHS survey coded 12 ethnolinguistic group categories of African origin. 

Table 1 Sample size and main characteristics of DHS 

survey, Chad 

Chad 

DHS 

1997 

No. of women interviewed 7,454 

No. of ethnic categories, African 12 

Percent other and unknown 2.1 

 All groups were kept for final analysis, after grouping “other and unknown” (Table 2). 

Table 2 Distribution of ethnic groups in DHS survey, Chad 

Origin Ethnolinguistic group 

DHS 

1997 

African Gorane 5.2 

 Arab 10.4 

 Ouaddai 12.1 

 Baguirmien 1.5 

 Kanem-Bornou 9.5 

 Fitri-Batha 6.0 

 Hadjarai 5.4 

 Lac Iro 1.0 

 Sara 29.1 

 Tandjile 6.0 

 Peulh 1.9 

 Kebbi 9.7 

Others Other and unknown 2.1 

 

 Total 100.0 

Premarital Fertility by Ethnicity

Chad is a relatively homogenous country with a low age at first marriage (15.8 years), a low 

proportion of women who never marry (<0.1 percent), and a low level of premarital fertility (0.8 percent 

for all births, 2.4 percent for women). Differentials in premarital fertility by ethnicity do not vary much 

(from 0.1 to 1.7 percent for all births, and from 0.2 to 4.7 percent for women). The prevalence of 

premarital intercourse was somewhat higher (17.2 percent), though still low by African standards. 

Correlation of premarital fertility with age at first marriage was low (ρ = +0.197), and correlation with 

urban residence was negative (ρ = -0.431). 
34

Table 3 Premarital fertility and nuptiality indicators, Chad 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Gorane 453 41.4 15.8 0.0 0.3 0.9 12.7 

Arab 831 29.6 15.2 0.0 0.4 0.8 12.6 

Ouaddai 819 14.2 16.0 0.0 1.6 4.7 18.9 

Baguirmien 131 37.0 16.3 0.0 0.2 0.6 17.4 

Kanem-Bornou 698 20.4 15.0 0.0 0.1 0.2 6.7 

Fitri-Batha 455 22.7 16.3 0.0 0.6 1.3 15.3 

Hadjarai 433 29.3 15.3 0.0 0.5 2.0 19.0 

Lac Iro 66 11.4 15.1 0.0 1.7 4.7 42.1 

Sara 2,180 24.1 16.3 0.0 1.3 4.3 24.2 

Tandjile 416 16.4 15.5 0.0 0.5 1.9 18.5 

Peulh 142 25.1 14.8 0.0 0.2 1.0 12.5 

Kebbi 641 11.7 15.8 0.0 0.1 0.4 11.4 

Other and unknown 189 43.9 15.2 2.7 0.9 2.0 14.1 

 

Total 7,454 23.1 15.8 0.1 0.8 2.4 17.2 

Source: Authors’ calculations from 1997 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Chad 

Lac Iro Ouaddai

Sara

Hadjarai

Tandjile

Fitri Batha

Barguimien

Gorane Arab

Kanem Bornou Kebbi

Peulh

0

2

4

6

8

10

14 15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
35

CÔTE D’IVOIRE

Côte d’Ivoire conducted a WFS survey in 1980 and two DHS surveys in 1994 and 1999 (Table 1). 

The WFS survey included 16 ethnic groups and five larger language families. The 1994 DHS survey 

included 50 detailed ethnic groups plus many categories for foreigners by country of origin. 

Unfortunately, labels for these 50 detailed ethnic groups were not provided in the codebook, rendering 

them unusable. The 1999 survey, which was based on a small sample, provided only the five larger 

language families, which, fortunately, happened to be the same as in the 1980 survey. We therefore 

combined the 1980 and the 1999 surveys for final analysis. Côte d’Ivoire being a country of in-migration, 

the proportion of foreigners was high. 

Table 1 Sample size and main characteristics of surveys, Côte d’Ivoire 

Côte d’Ivoire 

WFS 

1980 

DHS 

1994 

DHS 

1999 

No. of women interviewed 5,764 8,099 3,040 

No. of ethnic categories, local 16 50 -- 

No. of ethnic categories, foreign 1 13 1 

Large ethnolinguistic families 5 -- 5 

Percent foreigner 24.4 22.2 22.2 

Percent other and unknown 0.3 0.2 0 

Differences in the distribution of large ethnolinguistic families between the two surveys were 

minor, though three of them were statistically significant (Table 2). However, these minor differences 

could not impact the final estimates based on the combined data sets. 

Table 2 Distribution of ethnic groups by survey, Côte d’Ivoire 

Difference between 

the two surveys 

Ethnic group 

WFS 

1980 

DHS 

1999 P-value 

Significance 

Akan 29.1 29.8 0.495 

Krou 13.3 11.0 0.002 * 

Mande North 12.0 12.1 0.932 

Mande South 9.7 10.3 0.395 

Voltaic 11.1 14.6 0.000 * 

Other and unknown 24.8 22.2 0.008 * 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

In Côte d’Ivoire, the level of urban residence is average, and age at marriage is medium, around 

17.7 years. However, premarital fertility varies markedly, between 5.0 and 18.7 percent for all births and 

between 14.6 and 40.5 percent for women. A majority of first sexual encounters are premarital, ranging 

from 48.2 to 80.1 percent by ethnic group. Correlation of premarital fertility with urban residence was 

small (0.295), but was much higher with age at first marriage (0.856). However, most of the correlation 

was due to the special situation of the Akan group, which has much higher age at marriage and higher 

premarital fertility than the other groups (Figure 1). 
36

Table 3 Premarital fertility and nuptiality indicators, Côte d’Ivoire 

Ethnolinguistic group 

(large family) 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Akan 2,626 45.6 18.8 0.5 18.7 40.5 79.6 

Krou 1,123 50.7 17.2 0.9 10.9 28.3 80.1 

Mande North 1,095 49.5 17.0 0.0 5.0 14.6 46.9 

Mande South 811 24.0 17.2 0.0 8.1 21.9 68.0 

Voltaic 1,029 30.3 17.4 0.0 6.0 17.5 48.2 

Other and unknown 2,120 44.5 17.3 1.0 4.9 11.8 39.1 

 

Total 8,804 41.9 17.7 0.5 10.2 23.9 61.1 

Source: Authors’ calculations after merging data from 1980 and 1999 surveys. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, 

Côte d’Ivoire 

Akan

Krou

Mande, North

Mande, South

Voltaic

0

10

20

30

40

50

15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
37

ETHIOPIA 

Ethiopia conducted a single DHS survey in 2000 (Table 1). The survey included 50 ethnic groups 

(V131), with virtually no unknowns, which covers a large proportion of the 79 languages ever recorded in 

the country. Unfortunately, the labels of the ethnic groups were not provided in the DHS codebook. 

Table 1 Sample size and main characteristics of 

DHS survey, Ethiopia 

Ethiopia 

DHS 

2000 

No. of women interviewed 15,367 

No. of ethnic categories, local 50 

Language of respondent 8 

Percent other and unknown 0.1 

However, the language of the respondent was recorded (SRESP), and could be matched with the 

ethnic group variable, which allowed the identification of main ethnic groups. The final list therefore 

included 12 ethnic groups, which accounted for some 90 percent of the population (Table 2). 

 

Table 2 Distribution of ethnic 

groups in survey, Ethiopia 

Ethnic group 

DHS 

2000 

Amara 31.8 

Oromo 34.6 

Tigraway 6.7 

Somali 1.2 

Gedeo 5.4 

Afar 0.8 

Anuak 0.1 

Sidama 3.9 

Weleyta 2.2 

Hadayya 0.2 

Gurage 1.8 

Kafa 1.4 

Other and unknown 10.0 

 

Total 100.0 

Premarital Fertility by Ethnicity

 Premarital fertility is low in Ethiopia, with a prevalence of 0.9 percent for all births and 2.7 

percent for women (Table 3). This is because of a variety of factors, including low median age at first 

marriage (16.1 years), low prevalence of premarital intercourse (10.9 percent), and low urban residence 

(18.2 percent). 
38

Table 3 Premarital fertility and nuptiality indicators, Ethiopia 

Ethnolinguistic group 

(large family) 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Amara 4,431 26.0 14.9 0.1 1.2 3.8 16.9 

Oromo 4,161 13.3 16.3 0.4 0.9 2.4 6.3 

Tigraway 1,483 29.5 15.6 1.0 1.0 3.2 20.0 

Somali 785 28.9 17.3 0.0 0.5 1.3 1.6 

Gedeo 862 26.1 18.3 0.2 1.1 2.9 9.3 

Afar 585 6.4 15.7 0.0 1.6 2.8 2.3 

Anuak 363 20.0 15.8 0.0 3.2 8.7 23.8 

Sidama 355 0.7 16.6 0.0 0.1 0.3 5.3 

Weleyta 230 13.4 16.8 0.0 0.8 2.6 5.9 

Hadayya 211 13.8 16.1 0.0 0.8 2.4 9.6 

Gurage 209 15.3 19.0 0.0 0.2 1.0 5.8 

Kafa 207 7.3 17.2 0.0 0.5 2.2 13.4 

Other and unknown 1,485 7.7 17.3 0.0 0.3 1.0 5.3 

 

Total 15,367 18.2 16.1 0.2 0.9 2.7 10.9 

Source: Authors’ calculations from 2000 DHS survey. 

Differences between ethnic groups were small given the low level of premarital fertility. In 

virtually all groups, premarital fertility was very low (<4 percent). The exception was the Anuak, a small 

group living in the marshland area of Gambela province. The province has a marginal position in the 

country and has recently been subject to discrimination and violence. The Anuak had somewhat higher 

premarital fertility despite low age at marriage (15.8 years). This is probably because of the higher 

prevalence of premarital intercourse (23.8 percent versus 10.9 percent for the country as a whole). 

 Correlation with age at first marriage was slightly negative (ρ = -0.339), which is unusual and is 

found in only a few countries. Correlation with urban residence was virtually nil (ρ = -0.067). 

 
39

Figure 1 Correlation between premarital fertility and age at first marriage, 

Ethiopia 

Anuak

Amara

Afar

Tigraway

Sidama

Weleyta

Somali

Gurage

Gedeo

Hadayya Oromo

Kafa

0

2

4

6

8

10

14 15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
40

GABON 

Gabon conducted only one DHS survey, in 2000. Ethnicity was defined as the main language 

spoken at home (V131). The DHS survey coded eight ethnolinguistic group categories of African origin. 

The large proportion of other and unknown is due to a large group of foreigners (17.9 percent of the 

sample). 

Table 1 Sample size and main characteristics 

of DHS survey, Gabon 

Gabon 

DHS 

2000 

No. of women interviewed 6,183 

No. of ethnic categories, African 8 

Percent other and unknown 19.6 

Although the ethnic groups were of unequal size, seven of them were large enough to be counted 

(Table 2). The Pygmy group was too small to be analyzed separately, and was merged with the “other and 

unknown” category in the final analysis. 

Table 2 Distribution of ethnic groups in survey, Gabon 

Origin Ethnolinguistic group 

DHS 

2000 

African Fang 25.2 

 Kota-Kele 6.5 

 Mbede-Teke 8.3 

 Myene 4.7 

 Nzabi-Duma 10.6 

 Okande-Tsogho 2.9 

 Shira-Punu/Vili 22.2 

 Pygmy 0.1 

Foreign 17.9 

 Other and unknown 1.7 

 

 Total 100.0 

Premarital Fertility by Ethnicity

 Gabon has a high level of urban residence, high age at first marriage, and high level of premarital 

fertility, with little variation by ethnic group. Differentials in premarital fertility by ethnicity vary from 

17.6 to 37.9 percent for all births, and from 41.0 to 55.2 percent for women. Although urban residence 

was high for all groups, the more urbanized groups had higher premarital fertility, with a positive 

correlation of 0.682. Age at first marriage is universally high, with a positive correlation of 0.735. A large 

majority of first intercourse is premarital (74.0), with minor differences by ethnic group. 
41

Table 3 Premarital fertility and nuptiality indicators, Gabon 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Fang 1,372 82.9 19.8 3.6 31.0 54.1 78.6 

Kota-Kele 491 60.3 19.1 3.9 27.6 53.0 78.9 

Mbede-Teke 642 82.1 19.3 5.9 30.2 51.8 78.4 

Myene 190 96.9 23.9 4.2 37.9 55.2 80.1 

Nzabi-Duma 783 74.5 18.2 0.0 21.7 42.4 73.0 

Okande-Tsogho 266 43.4 17.2 0.0 17.6 41.0 66.2 

Shira-Punu/Vili 1,428 78.7 19.3 3.4 26.8 51.1 74.9 

Other and unknown 1,011 88.6 20.3 2.7 19.6 30.3 64.2 

 

Total 6,183 80.2 19.6 3.1 26.4 46.7 74.0 

Source: Authors’ calculations from 2000 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Gabon 

Myene Fang

Kota Kele

Shira Punu Vili

Mbede Teke

Nzabi Duma

Okande Tsogho

0

10

20

30

40

50

60

15 16 17 18 19 20 21 22 23 24 25

Median age at first marriage (years)

% women with premarital birth
42

GHANA 

Ghana conducted one WFS survey in 1979 and four DHS surveys, in 1988, 1993, 1999 and 2003 

(Table 1). The WFS survey and the 1988 DHS survey each coded the same 7 ethnic groups; the 1993 

DHS survey coded 11 groups; the 1999 DHS survey coded 12 groups, 11 of which were identical to the 

previous survey; and the 2003 DHS survey coded 8 groups. The proportion of “other and unknown” was 

lowest in 1993 and 1999, due to the more detailed categories. 

Table 1 Sample size and main characteristics of surveys, Ghana 

Ghana 

WFS 

1979 

DHS 

1988 

DHS 

1993 

DHS 

1999 

DHS 

2003 

No. of women interviewed 6,125 4,488 4,562 4,843 5,691 

No. of ethnic categories, African 7 7 11 11 8 

Percent other and unknown 10.1 8.9 3.2 2.1 6.5 

For final analysis, the 1993 and the 1999 DHS surveys were combined since they offered the 

greatest number of groups and the smallest number of “other and unknown.” Overall, the distribution of 

ethnic groups was similar in the two surveys, though not identical (Table 2). 

 

Table 2 Distribution of ethnic groups by survey, Ghana 

Difference between 

the two DHS surveys 

Ethnic group 

DHS 

1993 

DHS 

1999 P-value 

Significance 

Asante 16.2 15.9 0.676 

Akwapim 3.2 4.1 0.025 * 

Fante 12.1 14.1 0.004 * 

Other Akan 18.1 19.5 0.083 

Ga-Adangbe 8.0 8.3 0.606 

Ewe 14.9 15.8 0.207 

Guan 2.2 1.5 0.015 * 

Mole-Dagbani 15.6 6.8 0.000 * 

Grussi 3.5 2.5 0.003 * 

Gruma 2.3 5.4 0.000 * 

Hausa/Haoussa 0.7 1.4 0.001 * 

Dagarti 2.5 na na 

Other and unknown 3.2 2.1 na na 

Total 100.0 100.0 9.0E-115 * 

*p <0.05

na = Not applicable

The Mole Dagbani group was lower in the second survey, partly because a new group emerged 

(Dagarti), with which it was probably combined in 1993. For final analysis, the Hausa group was dropped 

because it was too small (less than 100 women in the two surveys combined), but the Dagarti group was 

kept, because it was large enough, and had the lowest premarital fertility. 
43

Premarital Fertility by Ethnicity

 Premarital fertility in Ghana is low by African standards, with a prevalence of 4.0 percent for all 

births and 9.4 percent for women. This is despite a medium age at first marriage (18.9 years) and a high 

prevalence of premarital intercourse (57.4 percent) (Table 3). 

 

Table 3 Premarital fertility and nuptiality indicators, Ghana 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Asante 1,412 39.8 18.6 0.0 4.7 10.1 60.2 

Akwapim 319 46.0 20.3 0.0 6.9 14.2 66.5 

Fante 1,127 48.8 19.2 0.0 4.7 10.7 61.0 

Other Akan 1,650 33.7 18.7 0.8 5.7 12.7 65.5 

Ga-Adangbe 708 60.5 19.5 3.6 4.9 10.6 67.0 

Ewe 1,325 33.6 19.3 0.0 3.6 8.4 65.0 

Guan 170 34.5 18.8 0.0 3.5 9.2 51.3 

Mole-Dagbani 1,220 21.3 18.5 0.0 1.6 4.5 33.6 

Grussi 363 20.9 18.6 0.0 1.9 5.7 43.4 

Gruma 480 12.2 18.7 0.0 1.8 5.3 38.4 

Dagarti 288 15.3 18.6 0.0 1.0 3.4 23.3 

Other and unknown 343 42.5 18.6 0.0 3.1 7.4 51.8 

 

Total 9,405 36.8 18.9 0.4 4.0 9.4 57.4 

Source: Authors’ calculations after merging data from 1993 and 1999 DHS surveys. 

 

Differentials in premarital fertility by ethnicity were moderate, ranging from 3.4 percent (Dagarti) 

to 14.2 percent (Akwapim). Correlation with age at first marriage was high (0.669); the prevalence of 

premarital intercourse was high (0.911); and correlation with urban residence was high (0.795). The 

ethnic groups in northern Ghana (Mole-Dagbani, Grussi, Gruma, Dagarti) had lower age at marriage, 

lower prevalence of premarital intercourse, lower premarital fertility, and lower urban residence compared with those in the south. The Akwapim stand out with the highest level of premarital fertility and the 

highest age at marriage. They also have high prevalence of premarital intercourse, although they are not 

the most urbanized ethnic group. 
44

Figure 1 Correlation between premarital fertility and age at first marriage, Ghana 

Akwapim

Other Akan

Fante Ga-Adangbe

Ewe

Asante

Guan

Gruma Grussi

Dagarti

Mole-Dagbani

0

10

20

17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
45

GUINEA 

Guinea conducted two DHS surveys, in 1992 and 1999. However, access to the 1992 survey was 

restricted. In 1999, ethnicity was defined as the main language spoken at home (V131). The DHS survey 

coded six ethnolinguistic group categories of African origin (Table 1). 

Table 1 Sample size and main characteristics of DHS surveys, Guinea 

Guinea DHS 

1992 

DHS 

1999 

No. of women interviewed 6,065 7,143 

No. of ethnic categories, African na 6 

Percent other and unknown na 1.6 

na = Not applicable 

Three groups were dominant in the country: the Peulh, the Soussou and the Malinke. The other 

three were much smaller, although they still had enough cases of women interviewed to be analyzed 

separately (Table 2). 

Table 2 Distribution of ethnic groups in survey, Guinea 

Origin Ethnolinguistic group 

DHS 

1999 

African Sousou 19.8 

 Peulh 35.9 

 Malinke 27.8 

 Kissi 5.0 

 Toma 2.6 

 Guerze 7.3 

Other Other and unknown 1.6 

 

 Total 100.0 

Premarital Fertility by Ethnicity

Guinea has a low median age at first marriage (16.4 years), a low proportion of women who never 

marry (0.1 percent), and a low level of premarital fertility (3.3 percent for all births, 8.1 percent for 

women). Differentials in premarital fertility by ethnicity vary from 1.3 to 7.2 percent for all births, and 

from 4.3 to 18.1 percent for women. The prevalence of premarital intercourse is low, varying from 12 to 

37 percent. The only group that stands out is the Soussou, which have the highest level of urban 

residence. Correlation of premarital fertility with urban residence is high (0.871), whereas correlation 

with age at marriage is low. This is because the Soussou marry at about the same age as other groups 

(Malinke, Guerze) that have much lower premarital fertility. 
46

Table 3 Premarital fertility and nuptiality indicators, Guinea 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Sousou 1,389 50.4 17.1 0.0 7.2 18.1 37.1 

Peulh 2,222 25.2 15.8 0.0 2.4 5.6 11.7 

Malinke 1,985 34.2 16.8 0.3 2.5 6.2 24.8 

Kissi 353 21.8 15.6 0.0 2.9 6.4 22.1 

Toma 180 8.0 15.8 0.0 1.3 4.3 23.9 

Guerze 511 19.9 17.1 0.0 1.8 4.5 37.9 

Other and unknown 113 53.3 16.3 0.0 4.1 11.0 36.4 

 

Total 6,753 32.2 16.4 0.1 3.3 8.1 23.5 

Source: Authors’ calculations from 1999 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Guinea 

Soussou

Guerze

Malinke

Toma

Kissi

Peulh

0

10

20

14 15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
47

KENYA 

Kenya has a great wealth of high-quality demographic data: a WFS survey in 1978 and four DHS 

surveys, in 1988, 1993, 1998, and 2003, all of about the same sample size (Table 1). The WFS survey 

contained more details on ethnic groups with 42 distinct categories, but did not include what became one 

of the leading groups later on, the Kalenjin. However, the other categories were compatible with those of 

the DHS surveys. 

 

Table 1 Sample size and main characteristics of surveys, Kenya 

Kenya 

WFS 

1978 

DHS 

1988 

DHS 

1993 

DHS 

1998 

DHS 

2003 

No. of women interviewed 8,093 7,150 7,540 7,881 8,195 

No. of ethnic categories, African 42 9 10 11 14 

Percent other and unknown 1.0 6.7 4.8 2.9 1.4 

The four DHS surveys were quite compatible, with basically the same groups. We chose to 

combine the last three surveys (1993, 1998, and 2003), because this provided the opportunity to include 

three small but important groups: the Masai, the Somali, and the Taita/Taveta. The Masai and the 

Taita/Taveta were not detailed in the 1988 survey. Cumulating the three surveys gave more than 250 

women for these small groups. Note that the Masai were not detailed in 1993, but were in a large enough 

number in the last two surveys combined. 

Table 2 Distribution of ethnic groups by survey, Kenya 

Origin Ethnolinguistic group 

DHS 

1993 

DHS 

1998 

DHS 

2003 

African Kalenjin 11.7 12.6 10.1 

 Kamba 13.5 12.8 11.4 

 Kikuyu 20.6 17.9 23.0 

 Kisii 7.2 10.9 5.7 

 Luhya 16.1 14.5 15.0 

 Luo 11.4 13.6 12.0 

 Masai na 1.4 2.3 

 Meru/Embu 6.9 7.2 7.2 

 Mijikenda/Swahili 6.5 5.0 5.0 

 Somali 0.3 0.2 3.6 

 Taita/Taveta 1.1 1.0 1.2 

Other Other and unknown 4.8 2.9 3.4 

 

 Total 100.0 100.0 100.0 

na = Not applicable 

 

The consistency of ethnicity data was remarkable, and most likely the five surveys could have 

been combined if necessary (Table 2). Ethnicity was defined as the main language spoken at home 

(V131). The distribution of women 15-49 by main ethnolinguistic groups was similar in the three selected 

surveys. Only a few differences were statistically significant, but without consequence. Kalenjin and Kisii 

were somewhat over-represented and Kikuyu somewhat underrepresented in 1998, while none of the 

other groups were significantly different from the average in 1993 and 2003. 
48

Premarital Fertility by Ethnicity

Kenya is a country with relatively high age at first marriage (19.1 years), a low proportion of 

women who never marry (2.7 percent), and a high level of premarital fertility (11.2 percent for all births, 

30.7 percent for women). Differentials in premarital fertility by ethnicity were marked for all births (2.3 

to 16.6 percent), and for women (7.7 to 40.5 percent). The prevalence of premarital intercourse was high 

(65.7 percent), with marked differences among the ethnic groups, from 6.7 percent to 77.8 percent. 

Table 3 Premarital fertility and nuptiality indicators, Kenya 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Kalenjin 3,055 5.6 18.5 2.0 11.1 29.5 54.3 

Kamba 2,402 20.9 19.7 2.4 15.0 40.5 77.8 

Kikuyu 4,738 30.7 20.8 6.3 16.6 38.1 73.6 

Kisii 1,648 11.6 18.8 1.3 10.7 32.9 67.7 

Luhya 3,498 21.9 18.9 1.1 9.0 28.1 66.1 

Luo 2,745 29.8 17.2 0.3 8.6 27.9 74.9 

Masai 232 4.0 16.9 0.8 4.0 12.1 53.3 

Meru/Embu 1,428 13.7 20.6 3.9 14.3 36.3 75.3 

Mijikenda/Swahili 1,726 27.7 17.0 2.1 4.9 10.6 25.3 

Somali 638 38.0 18.2 1.3 2.3 7.7 6.7 

Taita/Taveta 702 30.0 20.3 8.8 9.0 22.9 51.8 

Other and unknown 804 33.7 19.2 0.1 6.1 15.0 47.7 

 

Total 23,616 22.1 19.1 2.7 11.2 30.7 65.7 

Source: Authors’ calculations after merging data from 1993, 1998, and 2003 DHS surveys. 

 

Surprisingly, correlation of premarital fertility with urban residence was not significant, and even 

somewhat negative (-0.209), whereas correlation with age at first marriage was positive (0.692), a value 

comparable with other countries. Note that Kenya is primarily rural (78 percent in the samples). 
49

Figure 1 Correlation between premarital fertility and age at first marriage, Kenya 

Meru Embu

Kikuyu

Kamba

Kisii

Luhya

Kalenjin Luo

Masai

Mijikenda Swahili

Taita Taveta

Somali

0

10

20

30

40

50

16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
50

LIBERIA 

Liberia has conducted only one DHS survey, in 1986, with details on 16 ethnic groups and using 

a reasonable sample size (Table 1). Liberia is one of the rare African countries in which high premarital 

fertility has been documented, the highest in West Africa. We therefore pushed our analysis to its limits, 

including some ethnic groups with less than 250 women. 

Table 1 Sample size and main characteristics of 

DHS survey, Liberia 

Liberia 

DHS 

1986 

No. of women interviewed 5,239 

No. of ethnic categories, African 16 

Percent other and unknown 4.3 

Among the small groups, all were kept except the Belle (14 women), the Dey (23 women), and 

the Mande (35 women). 

Table 2 Distribution of ethnic groups in survey, Liberia 

Origin Ethnolinguistic group 

DHS 

1986 

African Bassa 12.7 

 Gbandi 2.8 

 Gio 7.7 

 Gola 4.6 

 Grebo 7.3 

 Kissi 3.6 

 Kpelle 16.3 

 Krahn 4.2 

 Krou/Sapo 10.6 

 Lorma 6.0 

 Mandingue 6.1 

 Mano 7.9 

 Vai 3.8 

Other Other and unknown 6.6 

 

 Total 100.0 

 

Premarital Fertility by Ethnicity

Liberia has a medium age at first marriage (17.2 years), a low proportion of women who never 

marry (1.1 percent), and a high level of premarital fertility (13.0 percent for all births, 29.6 percent for 

women). Differentials in premarital fertility by ethnicity were small, from 8.0 to 16.8 percent for all 

births, and from 14.6 to 41.1 percent for women. The prevalence of premarital intercourse was high (68.4 

percent on average, ranging from 53.1 to 77.9 percent), with only minor differences among ethnic groups. 
51

Table 3 Premarital fertility and nuptiality indicators, Liberia 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bassa 490 43.4 17.0 1.5 14.1 28.4 65.8 

Gbandi 109 19.4 18.3 0.0 11.9 23.5 65.8 

Gio 294 26.5 15.9 0.0 11.7 24.6 60.0 

Gola 177 36.7 16.4 0.0 11.2 29.0 68.2 

Grebo 570 51.7 16.8 0.0 15.4 41.0 71.7 

Kissi 137 55.8 18.0 0.0 12.3 28.3 68.5 

Kpelle 661 31.4 18.3 2.4 12.6 31.9 77.9 

Krahn 521 34.4 16.7 1.8 13.3 32.4 67.9 

Krou/Sapo 1,039 60.1 17.7 3.0 16.8 41.1 76.6 

Lorma 230 50.6 17.4 0.0 12.6 30.6 73.6 

Mandingue 262 60.1 16.9 0.0 8.0 14.6 53.1 

Mano 301 15.3 15.3 0.0 8.1 19.8 55.3 

Vai 145 53.2 15.9 0.0 12.9 29.7 70.6 

Other and unknown 303 73.6 18.9 0.0 16.0 30.8 68.2 

 

Total 5,239 43.2 17.2 1.1 13.0 29.6 68.4 

Source: Authors’ calculations from 1986 DHS survey. 

 

Correlation of premarital fertility with urban residence was small but positive, (p = +0.343), as 

was the correlation with age at first marriage (p = +0.252). Both values are much lower than those of 

other countries. Note that overall, Liberia is almost half urban (43.2 percent in the samples). 

 Two groups stand out with higher than expected premarital fertility: the Grebo and the 

Krou/Sapo. Urban residence is also higher for these groups. In contrast, two groups stand out with lower 

than expected premarital fertility: the Mandingue (Mandinka), who are primarily urban, and the Mano, 

who are primarily rural. 
52

Figure 1 Correlation between premarital fertility and age at first marriage, Liberia 

Bassa

Krahn Lorma

Gola Kissi Vai

Gio

Mano

Mandingue

Gbandi

Kpelle

Grebo Krou Sapo

0

10

20

30

40

50

14 15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
53

MALAWI 

 Malawi has conducted two DHS surveys, in 1992 and 2000. The first survey did not provide 

ethnicity, but the second provided nine ethnic groups with a large sample size (Table 1). 

Table 1 Sample size and main characteristics of DHS surveys, Malawi 

Malawi 

DHS 

1992 

DHS 

2000 

No. of women interviewed 4,849 13,220 

No. of ethnic categories, African 0 9 

Percent other and unknown - 2.7 

Since the sample size was large enough in the 2000 survey, all ethnic groups were kept for final 

analysis (Table 2). 

Table 2 Distribution of ethnic groups in survey, Malawi 

Origin Ethnolinguistic group 

DHS 

2000 

African Chewa 32.3 

 Tumbuka 7.9 

 Lomwe 18.2 

 Tonga 1.8 

 Yao 13.8 

 Sena 4.0 

 Nkonde 1.3 

 Ngoni 12.6 

 Amanganja/Anyanja 5.5 

Other Other and unknown 2.7 

 

 Total 100.0 

 

Premarital Fertility by Ethnicity

Malawi is a homogenous country with respect to nuptiality and fertility indicators. Age at first 

marriage ranges from 17.2 to 18.3 years, (average of 17.8 years) and the proportion of women who never 

marry is negligible (0.2 percent). Premarital fertility ranges from 2.3 to 5.1 percent for all births (average 

of 3.7 percent) and from 5.8 to 14.0 percent for women (average of 9.9 percent). The prevalence of 

premarital intercourse ranges from 32.1 to 47.0 percent (average of 39.4 percent). 

 Unlike most African countries, premarital fertility in Malawi is not related to age at first marriage, 

and has only a moderate correlation with urban residence (ρ = 0.518). Two groups stand out from the 

others: the Ngoni, with higher premarital fertility (14.0 percent), and the Sena, who are primarily rural 

and have a lower level of premarital fertility (5.8 percent). 
54

Table 3 Premarital fertility and nuptiality indicators, Malawi. 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

Percent 

premarital 

intercourse 

Chewa 3,536 13.6 18.3 0.0 3.7 8.8 35.8 

Tumbuka 1,291 27.5 17.8 0.0 2.8 8.3 32.1 

Lomwe 2,589 13.2 17.2 0.4 3.7 10.1 45.7 

Tonga 286 30.9 17.5 2.1 5.1 12.1 45.1 

Yao 1,928 14.6 17.8 0.4 4.5 10.7 47.0 

Sena 455 8.5 17.8 0.0 2.3 5.8 32.4 

Nkonde 437 34.4 17.6 0.0 3.3 10.9 35.7 

Ngoni 1,462 21.6 17.9 0.5 4.4 14.0 38.0 

Amanganja/Anyanja 745 10.8 17.2 0.2 3.4 8.6 42.4 

Other and unknown 491 11.4 17.3 0.0 3.2 8.8 29.4 

 

Total 13,220 15.9 17.8 0.2 3.7 9.9 39.4 

Source: Authors’ calculations from 2000 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Malawi 

Ngoni

Sena

Tonga

Yao

Tumbuka Amanganja

Lomwe

Chewa

Nkonde

0

10

20

15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
55

MALI 

 

Mali has conducted three DHS surveys, in 1987, 1995, and 2001. The first survey provided six 

ethnic groups, while the two others provided nine groups with the same coding and larger sample sizes 

(Table 1). Furthermore the first survey gave higher than expected levels of premarital fertility. Therefore, 

the surveys of 1995 and 2001 were lumped together for final analysis. 

 

Table 1 Sample size and main characteristics of DHS surveys, Mali 

Mali 

DHS 

1987 

DHS 

1995 

DHS 

2001 

No. of women interviewed 3,200 9,740 12,849 

No. of ethnic categories, African 6 9 9 

Percent other and unknown 11.3 11.1 5.5 

The distribution of women age 15-49 by main ethnic group was basically the same in the two 

surveys. There were fewer “other and unknown” in the 2001 survey despite having the same ethnic 

groups. There were more Bambara, Sonrai, and Tamacheck, but fewer Dogon. These small differences do 

not matter for this study. 

Table 2 Distribution of ethnic groups by survey, Mali 

Ethnolinguistic group 

DHS 

1995 

DHS 

2001 P-value Significance 

Bambara 29.0 33.0 0.000 * 

Malinke 7.6 9.2 0.000 * 

Peulh 14.5 14.0 0.301 

Sarakole/Soninke 12.7 12.3 0.456 

Sonrai 3.3 5.9 0.000 * 

Dogon 8.8 7.3 0.000 * 

Tamacheck 0.8 2.0 0.000 * 

Senoufo/Minianka 8.9 8.3 0.127 

Bobo 3.3 3.8 0.066 

Other and unknown 11.1 4.2 0.000 * 

 

Total 100.0 100.0 

*p <0.05 

 

Premarital Fertility by Ethnicity

Mali is a homogenous country with respect to nuptiality and fertility indicators. Early marriage is 

common and the level of premarital fertility is low (Table 2). Age at first marriage ranges from 15.7 to 

17.0 years (average of 16.2 years), and the proportion of women who never marry is negligible (0.1 

percent). Premarital fertility estimates range from 1.5 to 3.6 percent for all births (average of 2.7 percent) 

and from 4.6 to 11.1 percent for women (average of 8.1 percent). The prevalence of premarital intercourse 

ranges from 18.6 to 34.0 percent (average of 26.0 percent). 

Unlike many African countries, premarital fertility is not related to age at first marriage 

(ρ = 0.088), and has no correlation with urban residence (ρ = 0.126). 
56

 Because of the large sample size, most differences in the prevalence of premarital fertility were 

statistically significant—with the exception of the Sonrai and the Tamacheck—but are of such small 

magnitude as to have little sociological importance. 

Table 3 Premarital fertility and nuptiality indicators, Mali 

Ethnolinguistic group 

Number of 

women 

surveyed 

Ppercent

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bambara 6,413 25.8 16.2 0.0 2.9 8.9 28.2 

Malinke 1,968 35.3 15.7 0.0 3.6 11.1 34.0 

Peulh 3,119 31.7 15.9 0.1 2.3 6.9 22.5 

Sarakole/Soninke 2,841 34.6 16.0 0.3 2.4 6.6 19.6 

Sonrai 1,722 50.2 17.0 0.0 3.0 7.8 25.9 

Dogon 1,472 17.9 15.8 0.0 1.5 4.6 19.0 

Tamacheck 864 49.1 15.9 0.2 2.9 7.4 18.6 

Senoufo/Minianka 1,736 25.4 16.7 0.0 3.5 10.6 32.7 

Bobo 760 29.1 16.9 0.7 1.9 7.0 27.4 

Other and unknown 1,658 43.1 16.4 0.0 3.0 8.0 25.6 

 

Total 22,553 30.8 16.2 0.1 2.7 8.1 26.0 

Source: Authors’ calculations after merging data from 1995 and 2001 DHS surveys. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Mali 

Malinke Senoufo Minianka

Sonrai

Bobo

Bambara

Dogon

Tamacheck

Sarakole Soninke Peulh

0

10

20

15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
57

MOZAMBIQUE

Mozambique conducted two DHS surveys, in 1997 and 2003. In 1997, ethnicity was defined as 

the main language spoken at home (V131), and was grouped into five large language families plus 

Portuguese speakers, which include mainly educated Africans and mixed races (assimilados). In addition, 

the mother tongue (“language learned to speak”) was also recorded (S119) and coded in 50 categories. 

The 2003 survey also provided the “language learned to speak” in 26 detailed categories (S119). The two 

surveys were compatible to a large extent, since most of the additional categories in the first survey were 

small groups. 

Table 1 Sample size and main characteristics of DHS surveys, 

Mozambique 

Mozambique 

DHS 

1997 

DHS 

2003 

No. of women interviewed 7,143 12,418 

No. of ethnic categories, African 50 26 

Percent other and unknown 1.3 3.2 

After combining the two surveys, 16 groups large enough for proper estimation of premarital 

fertility were kept for final analysis (Table 2). 

Table 2 Distribution of ethnic groups by survey, Mozambique 

Origin 

Ethnolinguistic 

group 

DHS 

1997 

DHS 

2003 Significance 

Mixed Portuguese 3.6 9.7 * 

African Emakhuwa 26.2 25.5 

 Xichangana 15.8 13.8 * 

 Elomxe 8.0 6.3 * 

 Cisena 12.4 6.4 * 

 Echuwabo 2.5 3.4 * 

 Bitonga 2.4 1.8 * 

 Chichewa 3.1 4.9 * 

 Nhungue 1.8 3.7 * 

 Chitswa 6.1 6.6 

 Naconde 0.8 1.8 * 

 Ndau 2.1 3.6 * 

 Ronga 3.6 1.6 * 

 Chitewe 1.9 1.4 * 

 Chope 3.0 1.9 * 

 Jaua 1.4 1.7 

Other and unknown 5.7 5.3 

 

Total 100.0 100.0 

Note: The spelling of names of ethnic groups varied between the two surveys; the 

spelling in the 2003 survey was used in this report. 

*p <0.05 
58

Some discrepancies in the frequency of ethnic groups could be noted between the two surveys, 

and most of the differences were statistically significant. Portuguese speakers accounted only for 3.6 

percent in the first survey, but for 9.7 percent in the second survey, indicating probably some mixture 

between mother tongue, language spoken at home or language learned in school. The Cisena had an 

abnormally high presence in the first sample and an abnormally low presence in the second; this may be a 

result of the sampling procedure. The Nhungue had an abnormally low presence in the first survey, 

whereas the Ronga and Chope were over represented. In any case, with the exception of the Portuguese 

speakers, which is a mixed category anyway, these discrepancies appear as minor. 

Premarital Fertility by Ethnicity

Mozambique has medium age at first marriage (17.4 years) and a medium level of premarital 

fertility (6.7 percent of all births, 15.3 percent of women) (Table 3). Between African groups, age at 

marriage varied from 15.7 to 19.4 years. It was higher for Portuguese speakers, who are more urbanized 

(83.1 percent). Similarly, premarital fertility varied from 5.8 to 34.1 percent among the African groups, 

and was 30.6 percent for Portuguese speakers. The prevalence of premarital intercourse, which ranged 

from 31.6 to 72.1 percent among African groups, was 80.9 percent among Portuguese speakers. 

Table 3 Premarital fertility and nuptiality indicators, Mozambique 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Portuguese 1,761 83.1 20.3 7.5 16.5 30.6 80.9 

Emakhuwa 4,051 22.1 15.7 1.2 3.7 8.4 31.6 

Xichangana 3,987 41.9 18.4 1.7 11.5 24.3 64.0 

Elomxe 725 8.3 16.9 2.4 6.4 13.9 52.8 

Cisena 1,705 26.1 17.1 0.0 4.3 10.3 34.7 

Echuwabo 473 23.9 17.7 2.7 8.0 18.0 60.7 

Bitonga 504 43.4 19.8 5.8 13.8 30.0 72.1 

Chichewa 793 4.6 17.7 1.6 3.5 10.8 50.9 

Nhungue 809 31.7 17.7 0.0 4.4 12.4 48.8 

Chitswa 1,371 24.0 18.3 4.0 12.3 22.3 60.0 

Naconde 290 20.9 16.9 0.0 6.5 14.1 49.3 

Ndau 1,076 35.9 17.3 2.8 3.0 5.8 36.6 

Ronga 726 81.7 18.7 3.2 14.9 34.1 71.7 

Chitewe 620 30.0 17.3 1.7 4.5 8.1 39.0 

Chope 556 34.0 18.3 0.8 12.6 28.6 63.8 

Jaua 540 25.2 17.2 0.0 4.3 11.8 32.8 

Other and unknown 1,210 24.4 17.1 0.8 4.3 9.2 42.8 

 

Total 21,197 31.3 17.4 1.8 6.7 15.3 49.0 

Source: Authors’ calculations after merging data from 1997 and 2003 DHS surveys. 

Correlations between premarital fertility and other factors were high: age at marriage 

(ρ = 0.975), urban residence (ρ = 0.709), and premarital intercourse (ρ = 0.919). There is little deviation 

from the linear patterns for age at marriage (Figure 1) and urban residence. 

 
59

Figure 1 Correlation between premarital fertility and age at first marriage, 

Mozambique 

Echuwabo

Emakhuwa

Xichangana

Elomxe

Portuguese sp.

Cisena

Ronga

Chope

Chitswa

Ndau

Chitwe

Chichewa

Nhungue

Bitonga

Naconde

Jaua

0

10

20

30

40

50

15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
60

NAMIBIA 

Namibia conducted two DHS surveys, in 1992 and 2000. Ethnicity was defined as the main 

language spoken at home (V131). The first DHS survey coded ten ethnolinguistic group categories: seven 

of African origin, and three of European origin (Afrikaans, English and German). The second DHS 

survey coded the same categories, though two of the European groups (German and English) were 

lumped together. 

Table 1 Sample size and main characteristics of DHS surveys, Namibia 

Namibia 

DHS 

1992 

DHS 

2000 

No. of women interviewed 5,421 6,755 

No. of ethnic categories, African 7 7 

No. of ethnic categories, European 3 2 

Percent other and unknown 10.7 0.9 

There were some minor inconsistencies in definitions of ethnolinguistic groups between the two 

surveys. For example, in the 1992 DHS, the group of “other and unknown” was much larger than in 2000 

(10.7 percent versus 0.9 percent). In fact, it included a number of smaller groups living in the northeast. 

These could be identified by referring to the main language used for the interview (SLANG), which was 

in most cases either Kwangali or Lozi. The “other and unknown” ethnicity variable in the 1992 DHS was 

therefore recoded according to the language used for the interview. After this procedure, the two 

distributions of ethnicity were comparable in the two DHS surveys, and compatible with the 2001 Census 

information (Table 2). 

Table 2 Distribution of ethnic groups by survey, Namibia 

Origin Ethnolinguistic group 

DHS 

1992 

DHS 

2000 

Census 

2001 

African Ovambo/Oshivambo 48.4 48.9 49.4 

 Kavango/Kwangali 10.6 8.9 10.1 

 Nama/Damara 14.6 14.7 9.6 

 Herero/OshiHerero 6.3 10.3 5.1 

 Caprivi/Lozi 6.0 4.1 3.8 

 San 1.0 1.3 - 

 Tswana 0.6 0.2 - 

European Afrikaans 11.4 10.1 8.2 

and mixed English 0.7 0.7 - 

 German 0.5 - - 

 Other and unknown 0.9 13.7 

 

 Total 100.0 100.0 100.0 

Note: The data for the 1992 DHS survey were analyzed after correction of “other and unknown” from language of 

interview. 

Note that since only the main language spoken at home was recorded in the survey, some 

categories are somewhat fuzzy. This is the case in Afrikaans-speaking groups in particular, which include 

people of European origin (Afrikaner), mixed races (Rohobotan/Baster), and some urbanized people of 

African origin. Of course, there are many more ethnic groups described in Namibia; some 25 

ethnolinguistic groups have been described, not counting European languages and tiny minorities of 

foreign origin (Indians, Portuguese, etc.). 
61

 Both DHS surveys were compatible in the definition of ethnicity, in the population distribution by 

ethnolinguistic groups, and in the ranking of premarital fertility. Data are therefore presented for both 

surveys combined (Table 3). 

Table 3 Premarital fertility and nuptiality indicators, Namibia 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

English/German 108 94.9 23.5 1.2 17.7 26.5 71.0 

Afrikaans 1,411 86.4 23.7 9.8 38.6 55.5 74.0 

Ovambo/Oshivambo 4,910 25.2 29.6 18.6 44.7 65.2 77.0 

Kavongo/Kwangali 1,256 16.3 18.8 0.5 13.1 27.9 57.9 

Caprivi/Lozi 966 27.5 21.0 0.9 25.6 52.4 80.7 

Damara/Nama 2,130 65.7 27.2 18.8 57.0 70.8 86.8 

Herero 1,149 52.2 30.1 30.9 60.0 76.2 91.1 

San 154 2.2 20.6 4.2 23.5 26.8 59.1 

Other and unknown 92 78.0 29.8 38.7 53.1 54.0 80.8 

 

Total 12,176 39.9 27.0 16.0 42.7 60.4 77.5 

Source: Authors’ calculations after merging data from 1992 and 2000 DHS surveys. 

Premarital Fertility by Ethnicity

 Namibia has a very high median age at first marriage (25.9 years), a high proportion of women 

who never marry (16.0 percent), and a high level of premarital fertility (42.7 percent for all births and 

60.4 percent for women). 

Differentials in premarital fertility by ethnicity are marked, varying from 13 to 60 percent for all 

births, and from 29 to 79 percent for women. Premarital fertility is closely associated with age at first 

marriage (ρ = 0.831), as seen in Figure 1, and with the prevalence of premarital intercourse (ρ = 0.900); 

however, it is not associated with urban residence (ρ = 0.195). 

 A detailed analysis of premarital fertility in Namibia was published elsewhere (Garenne and 

Zwang, 2005). Differentials in premarital fertility by ethnicity were stable after controlling for a variety of 

socioeconomic factors, including urban residence, level of education, and access to mass media. This 

highlights the major role of cultural factors in determining levels of premarital fertility. 
62

Figure 1 Correlation between premarital fertility and age at first marriage, 

Namibia 

San English, German Kavongo

Lozi, Caprivi

Afrikaans sp.

Damara, Nama

Herero

Ovambo

0

20

40

60

80

18 19 20 21 22 23 24 25 26 27 28 29 30 31

Median age at first marriage (years)

% women with premarital birth
63

NIGER 

Niger conducted two DHS surveys, in 1992 and in 1998 (Table 1). We were able to combine the 

two surveys since both provided the same distribution of ethnic groups. Ethnicity was defined as the main 

language spoken at home (V131). The DHS survey coded nine ethnolinguistic group categories of 

African origin, and proportions of “other and unknown” were small in both surveys. 

Table 1 Sample size and main characteristics of DHS surveys, Niger 

Niger 

DHS 

1992 

DHS 

1998 

No. of women interviewed 6,503 7,577 

No. of ethnic categories, African 9 9 

Percent other and unknown 2.4 1.8 

The two surveys were compatible in the distribution of ethnic groups, with some minor 

differences (Table 2). However, some groups were small in size and had to be lumped together in the 

“other and unknown” category for final analysis. 

Table 2 Distribution of ethnic groups by survey, Niger 

Origin Ethnolinguistic group 

 DHS 

1992 

DHS 

1998 P-value Significance 

African Arab 0.2 0.2 0.462 

 Djerma 22.4 21.4 0.164 

 Gourmantche 0.3 0.4 0.190 

 Hausa/Haoussa 54.5 58.4 0.000 * 

 Kanouri 5.3 4.3 0.007 * 

 Mossi 0.0 0.2 0.039 * 

 Peulh 4.6 4.9 0.460 

 Touareg 10.0 8.4 0.001 * 

 Toubou 0.3 0.1 0.000 * 

 Other and unknown 2.4 1.8 0.013 * 

 

 Total 100.0 100.0 

*p <0.05 

 

Premarital Fertility by Ethnicity

Niger has a low age at first marriage and a low level of premarital fertility (Table 3). Overall, all 

indicators of premarital fertility are on the low side in Niger: premarital births (1.0 percent), women with 

a premarital birth (2.8 percent), premarital intercourse (4.5 percent), proportion never married (0.2 percent), median age at first marriage (15.0 years), and proportion urban (19 percent). 

Niger is markedly homogenous with respect to ethnicity. There was hardly any variation among 

the variables examined. The only group that stands out is the “other and unknown,” which primarily 

includes urban residents, many originally from other countries. 
64

Table 3 Premarital fertility and nuptiality indicators, Niger 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Djerma 3,560 23.3 15.5 0.3 1.5 4.1 4.9 

Hausa 7,405 15.9 14.8 0.0 0.8 2.3 3.7 

Kanouri 565 17.1 14.8 0.0 0.8 2.1 3.4 

Peulh 734 22.6 15.3 0.0 0.9 2.2 5.2 

Touareg 1,148 12.7 15.0 0.0 0.7 2.1 5.0 

Other and unknown 668 61.5 15.5 4.0 3.6 9.7 19.8 

 

Total 14,080 19.0 15.0 0.2 1.0 2.8 4.5 

Source: Authors’ calculations after merging data from 1992 and 1998 DHS surveys. 

The level of premarital fertility among ethnic groups that extend across national borders is similar 

to that of their counterparts in the neighboring countries. Hausa, Kanouri and Fulani (Peulh) in Niger have 

patterns of behavior similar to those of related groups in Nigeria. This is also the case for the Touareg in 

Niger and Burkina Faso. 

 There is a clear relationship between premarital fertility and urban residence (ρ = 0.977). This is 

primarily because of the “other and unknown” category, although there was a small relationship among 

the five indigenous groups because of the Djerma (ρ = 0.612) (Figure 1). Correlation with age at marriage 

was also significant, despite small differentials for the same reasons (ρ = 0.761). 

Figure 1 Correlation between premarital fertility and age at first marriage, Niger 

Djerma

Peulh Kanouri

Hausa

Touareg

0

2

4

6

8

10

13 14 15 16 17 18

Median age at first marriage (years)

% women with premarital birth
65

NIGERIA 

Nigeria is a special case in Africa, both for its large population, as well its extreme ethnic 

diversity. Some 485 languages appear in the Ethnologue database. The ethnic information gained from 

DHS surveys is necessarily much more limited in scope. 

 Nigeria conducted one WFS survey in 1982 and three DHS surveys, in 1990, 1999, and in 2003 

(Table 1). All four surveys had some information on ethnicity, though coded in various ways. The WFS 

had 34 categories, including the most important groups. The 1990 DHS survey had 92 categories; 

however, labels were provided for only 25 groups and the others could not be used. The last two DHS 

surveys (1999 and 2003) had the same coding and provided basically the same information, although 

some of the ethnic groups were very small. Although more could be probably done with ethnicity in 

Nigeria, only the last two surveys were selected since both provided compatible information, and also 

provided a large enough sample for statistical inference. Adding a few groups from the other surveys 

would not have changed the main features of the analysis. Ethnicity was defined as the main language 

spoken at home (S119 and S118 respectively). The proportion of “other and unknown” was small in the 

two surveys selected. 

Table 1 Sample size and main characteristics of DHS surveys, Nigeria 

Nigeria 

WFS 

1982 

DHS 

1990 

DHS 

1999 

DHS 

2003 

No. of women interviewed 9,727 8,781 9,810 7,620 

No. of ethnic categories, African 34 92 112 95 

Percent other and unknown 15.8 2.3 8.4 10.2 

The two surveys were compatible in the distribution of ethnic groups, with some minor 

differences (Table 2). Large groups (Hausa, Fulani, Yoruba, Igbo) were always well represented, and 

these four already account for more than half (58 percent) of the total population. Many other groups had 

enough women interviewed in 1999 and 2003 to be analyzed separately. A final list of 13 groups was kept 

in addition to the four largest, nine of them with at least 250 women, and four of them with less than 250 

women. The smallest group contained 136 women (Table 2). 

Groups with smaller sample size were lumped together according to their geographic origin: other 

groups from the Northern regions (Northwest and Northeast), other groups from North-Central and 

Southwest regions, and other groups from South and Southeast regions. Regions were based on the 2003 

survey (V101). 

Premarital Fertility by Ethnicity

Nigeria is a large country with marked differences in demographic patterns and social behavior. 

Nigeria has a medium level of premarital fertility (4.5 percent for all births, and 11.0 percent for women), 

a medium age at first marriage (17.8 years), a medium prevalence of premarital intercourse (31.2 

percent), a low proportion of women who never marry (1.0 percent), and a moderate level of urban 

residence (32.4 percent). 

 
66

Table 2 Distribution of ethnic groups by survey, Nigeria 

 Difference between 

1999 and 2003 

surveys 

Ethnolinguistic group 

WFS 

1982 

DHS 

1990 

DHS 

1999 

DHS 

2003 P-value 

Significance 

Hausa 18.6 25.2 18.3 27.0 0.000 * 

Fulani 6.8 3.3 4.3 6.1 0.000 * 

Kanuri 2.8 2.4 0.7 3.0 0.000 * 

Other Northern 1.1 7.4 7.5 6.6 0.019 * 

Yoruba 14.4 16.8 19.7 11.4 0.000 * 

Tiv 1.1 2.8 1.3 2.2 0.000 * 

Nupe 1.1 1.2 0.8 0.008 * 

Igbala/Igala 1.9 0.7 2.3 3.0 0.006 * 

Idoma 0.8 1.2 1.8 0.8 0.000 * 

Ibira/Igbirra 0.3 2.0 0.6 0.000 * 

Gwari 1.5 5.8 0.6 1.1 0.000 * 

Other Central, West 1.1 0.9 2.9 1.7 0.000 * 

Igbo/Ibo 23.7 16.5 15.9 13.6 0.000 * 

Ibibio 4.1 4.8 3.8 0.003 * 

Ijaw 1.1 1.0 1.4 1.1 0.099 

Edo 0.9 0.5 2.4 0.9 0.000 * 

Annang 1.4 1.3 1.7 0.059 

Urhobo 0.8 1.1 1.0 1.1 0.237 

Ogoni/Ogori 0.0 1.0 1.6 0.002 * 

Other South and East 1.0 12.0 1.0 1.5 0.011 * 

Other and unknown 15.8 2.3 8.4 10.2 0.000 * 

 

Total 100.0 100.0 100.0 100.0 

*p <0.05 

These average values hide major differences among ethnic groups. Urban residence is low for 

small groups such as the Ogoni and the Annang, but it is high for the Yoruba, the Ibira and the Urhobo. 

Age at first marriage is low (<15 years) for the northern groups (Hausa, Fulani, Kanuri) but high 

(>20 years) for some of the southeastern groups (Igbo, Urhobo), as well as the urbanized Yoruba. 

Premarital fertility is low (<5 percent) for the Fulani and Kanuri and high (>20 percent) for the Ibibio, 

Ijaw, Urhobo, and Ogoni. Similarly, premarital intercourse is rare among the Fulani, Kanuri, and Hausa, 

but common (>50 percent) among many of the southeastern groups as well as among the Yoruba. 

Correlation with age at first marriage was relatively high (ρ = 0.762), as can be seen in Figure 1. 

The differentials show the main divisions in the country: a cluster of three northern groups with low age 

at first marriage and low level of premarital fertility (Hausa, Fulani, Kanuri); a second cluster of groups in 

central and southwest Nigeria with medium age at first marriage and level of premarital fertility; and a 

third cluster of groups primarily in southern and eastern Nigeria with high age at first marriage and level 

of premarital fertility. There are some exceptions to this overall pattern. The Yoruba live in the central 

and western parts of the country, but are included in the third cluster because they are more urbanized. 

The Annang are located in the southern region, but belong to the second cluster. The “other northern 

groups” also belong to the second cluster; they are primarily ethnic groups located in the southern parts of 

the northern provinces, and are close to the north-central groups. 
67

Table 3 Premarital fertility and nuptiality indicators, Nigeria 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Hausa 3,623 26.0 14.3 0.2 2.4 6.1 4.8 

Fulani 912 15.5 14.3 0.8 1.8 4.7 3.4 

Kanuri 253 32.8 14.3 0.0 0.9 2.4 3.0 

Other Northern 1,321 23.3 16.3 0.0 4.8 11.5 17.9 

Yoruba 2,914 61.0 20.4 0.2 6.2 14.9 55.0 

Tiv 340 19.4 17.7 0.0 3.5 8.0 29.3 

Nupe 180 34.3 17.4 0.0 4.1 13.3 13.0 

Igbala/Igala 364 18.4 17.6 0.0 9.3 16.6 46.5 

Idoma 260 19.8 18.3 2.9 6.0 13.9 32.1 

Ibira/Igbirra 260 60.4 18.4 0.0 5.4 12.5 37.7 

Gwari 136 13.3 17.9 0.0 7.4 15.4 18.3 

Other Central, West 405 16.2 17.5 2.0 7.4 11.8 21.1 

Igbo/Ibo 2,946 38.0 21.0 2.9 4.5 11.3 50.7 

Ibibio 599 19.8 19.8 6.2 7.8 22.1 62.1 

Ijaw 239 19.4 19.0 1.9 8.7 22.7 60.5 

Edo 296 48.0 19.8 0.0 5.3 15.5 56.1 

Annang 223 3.1 17.8 0.0 4.7 10.4 56.8 

Urhobo 158 59.5 20.3 0.0 8.7 20.7 61.8 

Ogoni/Ogori 158 0.0 19.5 4.6 9.8 21.0 61.8 

Other South, East 176 23.6 19.6 0.0 8.4 18.9 68.0 

Other and unknown 1,667 27.1 17.7 1.1 5.8 14.4 35.5 

 

Total 17,430 32.4 17.8 1.0 4.5 11.0 31.2 

Source: Authors’ calculations after merging data from 1999 and 2003 DHS surveys. 

Figure 1 Correlation between premarital fertility and age at first marriage, Nigeria 

Kanuri

Fulani

Hausa

Other Northern

Yoruba

Tiv

Nupe

Igbala

Idoma

Igbira

Gwari

Other Central, West Igbo

Ibibio Ijaw

Edo

Annang

Ogoni Urhobo

Other South & East

0

5

10

15

20

25

14 15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
68

RWANDA 

Rwanda is a special case in this analysis because ethnicity is linked more to social status than to 

geographical area or culture. Like Burundi, Rwanda is a small country and more homogeneous ethnically 

than other African countries. Three ethnic groups are usually distinguished in Rwanda: Hutu, Tutsi, and 

Twa. The first two groups account for 99 percent of the population, while the Twa is a small minority of 

aborigines (pygmies), most of whom live in the northwestern forests. Both Hutu and Tutsi speak the same 

language (kinyarwanda), share the same culture, and live in the same areas, although the proportion of 

Tutsis tends to be lower in the northern part of the country. The early history of relationships between the 

Hutu and Tutsi is complex and well documented. They were further complicated by political events 

around the time of independence (1960), subsequent struggles for power, and civil war and genocide in 

1994. Despite these events, Rwanda was kept in this analysis because it shows an interesting pattern. 

Rwanda conducted one WFS survey in 1983 and two DHS surveys, in 1992 and 2000 (Table 1). 

The first two surveys covered the three ethnic groups and a tiny fraction of other and unknown ethnic 

groups. After 1994, ethnicity became a politically sensitive subject in Rwanda, and it was not examined in 

the 2000 DHS survey. For this reason, we relied on the first two surveys for this analysis. 

Table 1 Sample size and main characteristics of surveys, Rwanda 

Rwanda 

WFS 

1983 

DHS 

1992 

DHS 

2000 

No. of women interviewed 5,738 6,551 10,421 

No. of ethnic categories, African 3 3 na 

Percent other and unknown 0.5 0.3 0.5 

na = Not applicable 

The two surveys were compatible with respect to the distribution of ethnic groups and could be 

combined, although fewer Tutsis were present in the second survey. The second survey also showed 

higher levels of premarital fertility for both Tutsis and Hutus, indicating an increasing trend over time. 

However, the pattern of differences with respect to premarital fertility was the same in the two surveys. 

Table 2 Distribution of ethnic groups by survey, Rwanda 

Origin Ethnolinguistic group 

WFS 

1983 

DHS 

1992 P-value Significance 

African Hutu 86.4 90.7 0.000 * 

 Tutsi 12.6 8.7 0.000 * 

 Twa 0.5 0.4 0.284 

 Other and unknown 0.5 0.3 0.070 

 

 Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

Results for the Twa should be interpreted with caution because they are based on only 48 women, 

show no cases of premarital birth, and have wide confidence intervals (Table 3). However, the premarital 

fertility of the Twa was borderline significantly different from the other groups (p = 0.054), and they were 

kept separate because of their special ethnic identity and because they matched the overall pattern of 

relationship with age at marriage. 
69

 The two other groups were quite different. Compared with the Hutu, the Tutsi are more 

urbanized, have higher age at marriage, higher premarital fertility, and higher incidence of premarital 

intercourse. The Twa, who are almost entirely rural, had lower premarital fertility despite high rates of 

premarital intercourse. This pattern is primarily the result of lower age at marriage. 

Table 3 Premarital fertility and nuptiality indicators, Rwanda 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Hutu 10,750 5.4 19.7 0.6 2.2 6.9 17.4 

Tutsi 1,416 14.5 22.0 1.3 3.2 10.0 23.2 

Twa 48 3.0 17.6 0.0 0.0 0.0 30.2 

Other and unknown 75 36.2 19.3 0.0 2.9 14.0 41.8 

 

Total 12,289 6.2 19.9 0.6 2.2 7.1 18.0 

Source: Authors’ calculations after merging data from 1983 WFS and 1992 DHS surveys. 

Correlations with age at marriage and urban residence are of little value because they are based on 

only three ethnic groups, one of which is very weak. However, the patterns resemble those seen in other 

countries (Figure 1). 

 An important feature of premarital fertility in Rwanda is its low prevalence (2.2 percent for all 

births, 7.1 percent for women) in conjunction with high age at first marriage (19.9 years). A similar 

pattern is seen in Burundi, with which Rwanda shares much of its social fabric. Despite minor differences 

relating to socioeconomic factors, and despite the special case of the Twa minority, Rwanda and Burundi 

have a unique pattern of premarital fertility in Central Africa. 
70

Figure 1 Correlation between premarital fertility and age at first marriage, 

Rwanda 

Tutsi

Twa

Hutu

0

5

10

15

16 17 18 19 20 21 22 23

Median age at first marriage (years)

% women with premarital birth
71

SENEGAL 

Senegal conducted one WFS survey in 1978, and three DHS surveys, in 1986, 1993, and 1997 

(Table 1). Another DHS survey was conducted in 1999 but the data were not available when this report 

was prepared. The first survey (WFS) included 18 specific ethnic groups, the second survey had only five 

groups, the third survey had seven groups, and the fourth survey had ten groups. The main groups were 

compatible, but many were missing in the second survey. The data in the first survey were considered 

somewhat out-of-date, and had a lower than average rate of premarital fertility. The second survey was 

limited in the number of ethnic groups, and had a higher than average rate of premarital fertility. 

Therefore, the last two surveys (1993 and 1997), which also had larger sample sizes, were used for the 

analysis. 

Table 1 Sample size and main characteristics of surveys, Senegal 

Senegal 

WFS 

1978 

DHS 

1986 

DHS 

1993 

DHS 

1997 

No. of women interviewed 3,985 4,415 6,310 8,593 

No. of ethnic categories, African 18 5 7 10 

Percent other and unknown 7.5 10.1 3.5 4.5 

The last two surveys were compatible with respect to the distribution of ethnic groups, were 

compatible with the other surveys, and could be matched (Table 2). However, the southern groups 

(Manjaak, Mancagne, and Balant) were not coded in the 1993 DHS survey, so information on these 

groups comes only from the 1997 survey. Because the sample sizes of the three groups were small and the 

groups had similar characteristics, they were merged in this analysis to form a separate ethnic category. 

This was done partly because the three groups had unusual characteristics. 

Table 2 Distribution of ethnic groups by survey, Senegal 

Difference between 

1993 and 1997 

surveys 

Ethnolinguistic group 

WFS 

1978 

DHS 

1986 

DHS 

1993 

DHS 

1997 P-value 

Significance 

Wolof/Lebou 42.7 42.1 42.5 41.0 0.063 

Poular 22.8 23.0 23.2 24.8 0.021 * 

Serer 14.2 14.5 15.4 14.3 0.074 

Mandingue/Soce/Malinké 4.5 5.0 7.6 5.0 0.000 * 

Diola 3.8 5.5 5.2 4.6 0.058 

Sarakole/Soninke 1.8 1.7 2.3 0.004 * 

Bambara 1.5 0.9 1.8 0.000 * 

Manjaak, Mancagne, Balante 1.0 1.7 na na 

Other and unknown 7.7 10.1 3.5 4.5 na na 

 

Total 100.0 100.0 100.0 100.0 

*p <0.05 

na = Not applicable 

 

 
72

Premarital Fertility by Ethnicity

 Senegal has a moderate level of premarital fertility, with an average of 3.8 percent for all births 

and 11.1 percent for women. Median age at marriage is low (16.9 years), and the level of premarital 

intercourse is low by African standards (13.8 percent), except in the southern groups, where it is much 

higher (>44 percent). 

Table 3 Premarital fertility and nuptiality indicators, Senegal 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Wolof/Lebou 5,931 48.6 16.8 0.3 3.3 10.1 10.6 

Poular 3,475 34.8 15.8 0.5 1.6 5.1 6.6 

Serer 2,388 34.6 17.6 0.1 4.0 13.1 17.2 

Mandingue/Soce/Malinké 1,012 38.6 16.6 0.8 4.3 12.2 16.7 

Diola 855 53.0 20.3 0.3 15.9 39.1 53.5 

Sarakole/Soninke 279 38.4 16.8 0.0 3.7 9.0 10.5 

Bambara 206 62.3 18.3 0.0 3.6 12.8 15.2 

Manjaak, Mancagne, 

Balante 168 49.7 19.4 0.0 13.3 38.9 44.5 

Other and unknown 589 57.3 17.0 0.0 4.4 12.1 17.8 

 

Total 14,903 43.2 16.9 0.3 3.8 11.1 13.8 

Source: Authors’ calculations after merging data from 1993 and 1997 DHS surveys. 

Differentials by ethnicity are large. Two groups, the Diola, and the Manjaak-Mancagne-Balant 

stand out as having high levels of premarital fertility (39.1 percent and 38.9 percent, respectively) and 

high age at marriage (20.3 years and 19.4 years, respectively) (Table 3). The two groups are located 

primarily in Casamance, in the southern part of the country, south of the Gambia and near Guinea Bissau 

(where the Manjaak-Mancagne-Balant originated). The behavior of these groups is quite different from 

that of the other groups in the country. At the other end of the spectrum are the Poular (Fulani), who, like 

their kin in various other West African countries, have a low age at marriage (15.8 years) and only a small 

proportion of the women have had a premarital birth (5.1 percent). Other groups are similar, with minor 

variations. The Wolof tend to have a low level of premarital fertility, despite being more urbanized, while 

the opposite is the case for the Serer. The small group of Bambara had lower levels than expected, given 

that they are the most urbanized group, and had higher age at marriage than the others. Even if 

statistically significant, the small differences between the five middle groups have little sociological 

implication, and the groups can be regarded as similar. 
73

Figure 1 Correlation between premarital fertility and age at first marriage, 

Senegal 

Sarakole, Soninke

Poular

Mandingue, Socé Serer Bambara

Wolof, Lebou

Diola

Manjaak, Mancagne, Balant

0 

10 

20 

30 

40 

14 15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
74

SOUTH AFRICA 

South Africa conducted one DHS survey in 1998 and another in 2003-04. Data for the latter 

survey have not been released. Only the 1998 DHS survey was accessible when this study was conducted 

(Table 1). The 1998 DHS survey included four racial groups (V131) and the 11 official languages of the 

country, two of which are European languages (Afrikaans and English). The two types of information 

(race and language) were merged to form 13 comprehensive ethnolinguistic groups. Three of the groups 

identify the non-African population by race (White, Asian/Indian, Colored), while nine are ethnolinguistic 

groups in the black/African population. The sample was large enough to accommodate the 13 groups. 

Very few “other and unknown” groups were left over, despite there being a large number of foreigners 

living in South Africa. However, some of these would be included in the various ethnic groups (for 

example, the Shangaan/Tsonga from Mozambique, and the Southern Sotho from Lesotho). 

Table 1 Sample size and main characteristics of 

DHS survey, South Africa 

South Africa 

DHS 

1998 

No. of women interviewed 11,735 

No. of ethnic categories, African 9 

Racial groups 4 

Percent other and unknown 0.2 

The survey is compatible with respect to the distribution of ethnic groups from other sources 

(Table 2). 

Table 2 Distribution of ethnic groups in survey, South Africa 

South Africa 

Ethnolinguistic and racial 

group 

DHS 

1998 

Others White 7.8 

 Asian/Indian 3.5 

 Coloured 10.2 

Black/African Speaking European 

languages 1.9 

 Xhosa 15.2 

 Zulu 25.0 

 Sotho 8.6 

 Tswana 11.0 

 Pedi 9.3 

 Swazi 2.0 

 Venda 1.7 

 Tsonga 2.7 

 Ndebele 0.9 

 Other and unknown 0.2 

 

 Total 100.0 
75

Premarital Fertility by Ethnicity

 Premarital fertility is high in South Africa, with an average of 38.9 percent for all births and 59.1 

percent for women. The median age at marriage is high (24.7 years) and the prevalence of premarital 

intercourse is high (81.4 percent). 

Table 3 Premarital fertility and nuptiality indicators, South Africa 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

White 755 86.7 21.3 0.6 3.2 5.2 50.4 

Asian/Indian 393 98.2 21.1 6.3 7.6 11.9 30.9 

Coloured 1,533 82.4 25.0 11.2 44.6 66.6 83.5 

Black, speaking European 

languages 257 66.9 28.3 28.9 42.5 70.6 88.4 

Xhosa 2,693 53.4 24.6 18.3 38.6 62.7 86.0 

Zulu 2,147 55.8 27.1 18.5 49.6 72.9 90.2 

Sotho 951 80.4 23.2 8.6 35.0 58.6 85.3 

Tswana 1,200 61.6 26.8 16.8 52.7 74.3 90.6 

Pedi 910 33.6 23.1 14.6 37.2 58.1 78.7 

Swazi 333 29.3 20.9 14.8 31.9 54.9 82.1 

Venda 169 10.8 19.8 0.0 16.7 38.6 63.9 

Tsonga 269 16.4 19.8 3.0 23.1 41.9 65.6 

Ndebele 125 46.5 26.7 12.0 42.3 73.2 89.6 

 

Total 11,735 60.5 24.7 13.2 38.9 59.1 81.4 

Source: Authors’ calculations from 1998 DHS survey. 

Differentials by ethnicity are large. Racial groups stand out as significant, with White and Asian 

populations having much lower premarital fertility (5.2 percent and 11.9 percent, respectively), despite 

high median age at marriage (21.3 and 21.1 years, respectively) and high urban residence (86.7 percent 

and 98.2 percent, respectively). At the other end of the spectrum, the Colored (mixed race)1

 population 

shows high premarital fertility (66.6 percent), high age at marriage (25.0 years), and higher than average 

urban residence (82.4 percent). Among the African groups, the differentials were wide as well. The 

Tsonga and Venda have lower age at marriage (19.8 years each) and lower than average premarital 

fertility (38.6 percent and 41.9 percent, respectively). The Swazi, Pedi, Sotho, and Xhosa are located on 

the age at marriage/premarital fertility axis somewhat above the regression line linking all the groups 

(Figure 1). The groups with the highest levels of premarital fertility are also the groups with the highest 

age at first marriage: Ndebele, Tswana, and Zulu. 

Correlation with age at marriage was high and positive (ρ = 0.758), but correlation with urban 

residence was curvilinear, with maximum values in the medium range (40 to 60 percent) for the Ndebele 

Zulu, Xhosa, and Tswana, and lower values for more rural groups (Venda, Tsonga, Pedi, Swazi) and other 

racial groups, which are primarily urban residents (White, Asian). 

 

1

 The Colored (mixed) population of South Africa came into existence during the early period of European (Dutch) 

contact with the indigenous population, primarily Khoisan-speaking hunters and gatherers (Bushmen and 

Hottentots). The descendants of this population are physiologically and culturally different from the descendants of 

the African farming populations that moved into the area. 
76

Figure 1 Correlation between premarital fertility and age at first marriage, 

South Africa 

White

Asian / Indian

Coloured Black, speaking 

European language

Venda

Tsonga

Swazi

Xhosa

Ndebele

Zulu

Tswana

Pedi

Sotho

0

20

40

60

80

18 19 20 21 22 23 24 25 26 27 28 29 30

Median age at first marriage (years)

% women with premarital birth
77

TANZANIA 

Tanzania conducted three DHS surveys, in 1991, 1996, and 1999, plus two KAP-HS surveys in 

1994 and 2003. The 1994 survey did not have maternity histories, and the 1999 and 2003 surveys did not 

provide information on ethnicity (Table 1). The 1991 DHS survey included 126 ethnic groups (S114), 

while the 1996 DHS survey included 112 ethnic groups (S117), with basically the same coding. The two 

surveys selected for this analysis (1991 and 1996) had large sample sizes that allowed for in-depth 

analysis of ethnicity. 

Table 1 Sample size and main characteristics of DHS surveys, Tanzania 

Tanzania 

DHS 

1991 

KAP-HS 

1994 

DHS 

1996 

DHS 

1999 

No. of women interviewed 9,238 4,225 8,120 4,029 

No. of ethnic categories, African 126 100 112 na 

Percent other and unknown 3.7 5.9 6.7 

na = Not applicable 

Tanzania has a large number of small ethnic groups that are well-documented in the 1991 and 

1996 DHS surveys. The two surveys are compatible and, after combining the data, all ethnic groups with 

at least 200 women interviewed were kept for final analysis. This resulted in 29 groups, plus a residual 

category of “other and unknown” (Table 2). Although the two surveys are largely compatible, some 

statistically significant minor differences were found. These have no importance for this study. The only 

large group in Tanzania is the Sukuma, which accounts for one-sixth of the population. The other groups 

are much smaller but have sufficient women interviewed for statistical inference. 

Table 2 Distribution of ethnic groups by survey, Tanzania 

Ethnolinguistic 

group 

DHS 

1991 

DHS 

1996 P value 

Significance 

Sukuma 15.6 15.1 0.416 

Ha 4.3 4.5 0.561 

Makonde 3.5 3.8 0.185 

Chagga 4.7 3.6 0.000 * 

Gogo 5.2 2.7 0.000 * 

Zigua 1.8 3.6 0.000 * 

Nyamwezi 2.7 2.2 0.039 * 

Fipa 1.6 1.8 0.221 

Bena 2.9 2.5 0.172 

Shirazi 1.5 0.6 0.000 * 

Iramba 1.8 2.1 0.142 

Ngoni 2.0 1.8 0.295 

Zaramo 1.5 1.7 0.197 

Hehe 1.6 2.7 0.000 * 

Pare 2.4 2.2 0.291 

Nyakyusa 2.2 2.9 0.006 * 

Luguru 1.7 2.0 0.233 

Haya 3.1 2.1 0.000 * 

Sambaa 1.7 2.0 0.161 

Jita 1.9 1.3 0.001 * 

Iragw 3.2 2.2 0.000 * 

Makua 1.1 1.2 0.477 

Simbiti 2.7 0.2 0.000 * 

Zanaki 1.7 0.5 0.000 * 

 Continued...
78

Table 2—Continued 

Ethnolinguistic 

group 

DHS 

1991 

DHS 

1996 P value 

Significance 

Pogoro 1.4 1.2 0.104 

Ndengereko 0.9 1.2 0.059 

Kaguru 1.9 1.0 0.000 * 

Mwera 1.4 1.4 0.771 

Masai 1.2 2.4 0.000 * 

Other and unknown 20.8 27.5 0.000 * 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Tanzania, with an average of 8.2 percent for all births 

and 20.0 percent for women. Age at marriage is medium (17.9 years), and the prevalence of premarital 

intercourse is high (57.1 percent). 

 One of the most interesting aspects of premarital fertility in Tanzania is the wide diversity 

observed, along with low correlation with age at marriage (ρ = 0.462) and urban residence (ρ = 0.346). 

The low correlation with age at marriage can be seen in Figure 1, where the 29 groups have a link with 

age at marriage, but are spread widely around it. 

Table 3 Premarital fertility and nuptiality indicators, Tanzania 

Ethnolinguistic 

group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Sukuma 2,033 7.8 17.7 0.0 6.4 16.6 54.3 

Ha 823 19.6 17.5 0.0 2.5 6.8 17.7 

Makonde 693 27.4 17.2 0.0 5.6 11.0 47.1 

Chagga 628 35.5 21.0 2.2 8.8 23.7 49.9 

Gogo 543 19.3 18.1 0.0 6.8 19.0 56.7 

Zigua 475 29.8 17.3 1.2 6.3 16.4 45.4 

Nyamwezi 474 25.3 17.5 0.0 8.9 22.8 55.5 

Fipa 444 18.4 17.6 0.7 6.9 18.9 39.5 

Bena 389 21.8 19.7 2.7 10.3 26.0 50.4 

Shirazi 379 28.5 15.7 0.0 1.7 3.8 2.6 

Iramba 361 14.1 18.9 0.0 15.0 40.7 66.7 

Ngoni 347 38.4 18.0 0.0 13.1 33.6 62.0 

Zaramo 340 32.6 17.2 0.0 11.6 25.1 46.4 

Hehe 327 27.9 18.7 1.9 10.0 25.4 50.7 

Pare 320 28.0 19.8 5.3 16.7 38.8 62.3 

Nyakyusa 312 41.2 17.6 2.0 8.6 17.7 32.2 

Luguru 296 46.8 17.7 2.5 12.8 26.2 47.6 

Haya 292 14.3 17.9 0.0 3.8 8.8 24.5 

Sambaa 287 31.6 18.8 0.0 6.7 18.2 37.8 

Jita 280 35.1 17.9 0.0 8.3 27.2 63.9 

Iragw 276 35.0 19.8 0.0 11.0 23.7 59.9 

Makua 271 16.0 17.3 2.3 10.1 24.2 64.2 

 Continued... 
79

Table 3—Continued 

Ethnolinguistic 

group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Simbiti 262 53.6 17.3 0.0 8.5 21.8 46.4 

Zanaki 236 19.7 17.3 0.0 11.0 27.9 56.1 

Pogoro 235 36.7 16.8 0.0 10.6 27.7 48.5 

Ndengereko 225 65.8 17.7 0.0 14.1 26.8 51.3 

Kaguru 220 26.2 19.2 4.0 15.6 35.7 64.6 

Mwera 375 24.8 17.3 2.0 9.4 22.1 58.6 

Masai 209 0.3 16.3 0.0 5.4 10.8 46.3 

Other and unknown 5,006 24.9 17.7 1.1 8.3 19.4 41.3 

 

Total 17,358 24.2 17.9 0.9 8.2 20.0 47.1 

Source: Authors’ calculations after merging data from 1991 and 1996 DHS survey. 

Differentials by ethnicity are large in Tanzania. Premarital childbearing among women ranges 

from 3.8 percent (Shirazi) to 40.7 percent (Iramba). Similar differences are seen for prevalence of 

premarital intercourse (2.6 to 66.7 percent, respectively). Age at first marriage varies widely from 15.7 

years (Shirazi) to 21 years (Chagga). The Shirazi, who live on the islands of Zanzibar and Pemba, are 

culturally conservative despite an above-average level of urban residence (28.5 percent). The Shirazi are 

Muslim and their history is quite different from that of most other ethnic groups on the continent. 

There is no clear geographical pattern for premarital fertility. Groups with low levels of 

premarital childbearing were found on the islands (Shirazi), in the northwest (Ha, Haya), in the northeast 

(Masai), and in the southeast (Makonde). Groups with high levels of premarital childbearing were found 

primarily in the central part of the country (Ngoni, Kaguru, Iramba), but also in the North (Pare) and on 

the coast (Ndengereko). Groups with middle levels of premarital childbearing were found all over the 

country. 

There is wide variation in residence among ethnic groups in Tanzania, with the Masai living 

almost entirely in rural areas (0.3 percent urban), and other groups living primarily in urban areas 

(Ndengereko, Simbiti). Among groups with average levels of urban residence (20 to 30 percent), 

premarital fertility is very low for some (Ha, Shirazi) and very high for others (Pare, Kaguru). The 

Ndengereko and Zanaki have similar levels of premarital fertility, but urban residence is high among the 

Ndengereko and low among the Zanaki (65.8 and 19.7 percent, respectively). 
80

Figure 1 Correlation between premarital fertility and age at first marriage, 

Tanzania 

Mwera Simbiti

Zaramo

Zanaki

Hehe

Gogo

Zigua

Pogoro 

Ngoni

Kaguru

Iramba

Pare

Bena

Iragw

Sambaa

Chagga 

Masai Makonde

Haya

Ha

Shirazi 

Sukuma

Nyamwezi

Makua

Jita

Ndengereko

Luguru

Nyakyusa Fipa

0 

15 

30 

45 

15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
81

TOGO 

Togo conducted two DHS surveys, in 1988 and 1998 (Table 1). The 1988 DHS included 34 

ethnic groups (RC110), and three main ethnic categories (V131). The 1998 DHS included five main 

categories (V131), with similar coding but no details on ethnicity. 

Table 1 Sample size and main characteristics of DHS surveys, Togo 

Togo 

DHS 

1988 

DHS 

1998 

No. of women interviewed 3,360 8,569 

No. of ethnic groups, African 34 na 

No. of ethnic categories 3 5 

Percent other and unknown 9.1 7.9 

To merge the two data sets, the two additional main categories present in the 1998 survey were 

added to the three main categories in the 1988 survey by recoding data from the detailed 1988 ethnic 

categories. Once the recoding was done, the two surveys were compatible, and the five categories were 

retained for the final analysis (Table 2). The two surveys showed minor differences, some statistically 

significant, however, these differences were of no importance to the study. It should be noted that for the 

1988 sample, the ethnic categories include from 4 to 10 groups, which reduces the specificity of the 

analysis. 

Table 2 Distribution of ethnic groups by survey, Togo 

Ethnolinguistic group 

DHS 

1988 

DHS 

1998 P-value Significance 

Adja-Ewe 47.6 44.2 0.001 * 

Akposso, Akebou 4.1 4.2 0.906 

Ana-Ife 1.6 3.2 0.000 * 

Kabye-Tem 21.0 25.9 0.000 * 

Para-Gourma, Akan 22.2 14.6 0.000 * 

Other and unknown 3.4 7.9 0.000 * 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Togo, with an average of 5.6 percent for all births and 

16.3 percent for women. The prevalence of premarital intercourse is high (63.6 percent), although median 

age at marriage remains at a medium level (18.6 years). 

 Level of premarital fertility is generally homogenous across the population, with little variation 

among ethnic groups (from 13.7 percent among the Para-Gourma to 14.4 percent among the AkpossoAkebou). 
82

Correlations of premarital fertility with age at marriage (ρ = -0.181) and urban residence 

(ρ = -0.244) were small and negative. The low correlation with age at marriage is illustrated in Figure 1, 

where the five ethnic groups show basically no association with age at marriage. 

Table 3 Premarital fertility and nuptiality indicators, Togo 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

births 

Percent 

premarital 

intercourse 

Adja-Ewe 4,293 43.1 19.2 0.6 6.3 17.5 70.0 

Akposso, Akebou 444 21.6 17.7 0.0 8.2 24.4 70.2 

Ana-Ife 286 38.6 18.1 1.4 5.8 20.3 64.8 

Kabye-Tem 3,320 33.6 18.6 0.0 5.6 15.4 57.5 

Para-Gourma, Akan 2,768 26.2 17.5 0.1 4.3 13.7 58.0 

Other and unknown 818 42.2 18.1 0.0 4.1 11.3 53.5 

 

Total 11,929 36.9 18.6 0.3 5.6 16.3 63.6 

Source: Authors’ calculations after merging data from 1988 and 1998 DHS surveys. 

Figure 1 Correlation between premarital fertility and age at first marriage, Togo 

Adja-Ewe

Akposso, Akebou

Ana-Ife

Kabye-Tem

Para-Gourma, Akan

0

10

20

30

16 17 18 19 20 21

Median age at first marriage (years)

% women with premarital birth
83

UGANDA 

Uganda conducted three DHS surveys, in 1988, 1995, and 2001 (Table 1). The 1988 DHS survey 

included 18 ethnic groups (V131); the 1995 DHS survey included 33 groups (V131) plus the language 

spoken by the respondent (SLANGRE); and the 2001 survey included only information on the language 

spoken in the cluster (SH053). The labels of ethnic groups were not provided in the code books for the 

first two surveys so, for this analysis, we relied on language spoken in the last two surveys. 

Table 1 Sample size and main characteristics of DHS surveys, Uganda 

Uganda 

DHS 

1988 

DHS 

1995 

DHS 

2001 

No. of women interviewed 4,730 7,070 7,246 

No. of ethnic groups, African 18 33 na 

No. of languages spoken, African 6 6 

Percent other and unknown 14.8 1.9 

Note: Ethnic group labels were not provided in the 1988 and 1995 surveys. 

Fortunately, the last two surveys were compatible with respect to language spoken, and could be 

merged (Table 2). 

Table 2 Distribution of ethnic groups by survey, Uganda 

Ethnolinguistic group 

DHS 

1988 

DHS 

1998 P value 

Significance 

Ateso-Karamojong 6.8 7.8 0.028 * 

Luganda 18.1 24.8 0.000 * 

Lugbara 7.5 7.3 0.722 

Luo 12.6 9.7 0.000 * 

Runyankole-Rukiga 19.2 16.8 0.000 * 

Runyoro-Rutoro 6.5 5.2 0.000 * 

Other and unknown 29.3 28.4 0.236 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Uganda, with an average of 6.2 percent for all births and 

17.5 percent for women. The prevalence of premarital intercourse is high (46.8 percent), although median 

age at marriage remains at a medium level (17.6 years). 

 The prevalence of premarital fertility varies by ethnicity in Uganda, with levels ranging from 11.0 

percent among the Runyankole-Rukiga to 32.7 percent among the Runyoro-Rutoro. The distribution of 

levels of premarital fertility is not continuous: four groups have rather low prevalence rates (AtesoKaramojong, Lugbara, Luo,Runyangole-Rukiga), and two groups have rather high prevalence rates 

(Luganda,Runyoro-Rutoro). 
84

The correlation of premarital fertility with age at marriage was negligible (ρ = -0.099) while the 

correlation with urban residence was average (ρ = -0.543). The low correlation with age at marriage is 

shown in Figure 1, where the six groups have basically no link with age at marriage. 

Table 3 Premarital fertility and nuptiality indicators, Uganda 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Ateso-Karamojong 925 10.5 17.7 0.0 5.4 15.7 50.8 

Luganda 3,466 38.0 18.1 1.2 10.7 27.9 59.2 

Lugbara 852 9.6 17.7 0.0 4.9 11.9 26.2 

Luo 1,388 8.7 16.9 1.8 4.4 12.1 44.7 

Runyankole-Rukiga 2,594 7.9 18.1 0.6 3.7 11.0 33.1 

Runyoro-Rutoro 821 10.7 17.4 0.0 11.7 32.7 57.8 

Other and unknown 4,270 10.8 17.2 0.3 4.7 15.3 48.6 

 

Total 14,316 15.8 17.6 0.7 6.2 17.5 46.8 

Source: Authors’ calculations after merging data from 1988 and 1998 DHS surveys 

. 

Figure 1 Correlation between premarital fertility and age at first marriage, Uganda 

Luganda

Runyoro-Rutoro

Ateso-Karamojong

Lugbara Runyankole-Rukiga

Luo

0

10

20

30

40

16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
85

ZAMBIA 

Zambia conducted three DHS surveys, in 1992, 1996, and 2001 (Table 1). All three had detailed 

information on ethnicity, and all three used the same coding. Merging the data was straightforward. 

Table 1 Sample size and main characteristics of DHS surveys, Zambia 

Zambia 

DHS 

1992 

DHS 

1996 

DHS 

2001 

No. of women interviewed 7,060 8,021 7,658 

No. of ethnic groups, African 58 50 50 

No. of ethnic categories 7 

Percent other and unknown 2.6 2.7 2.7 

Additionally, the three surveys were found to be compatible with respect to ethnicity, which, 

given the large number of groups, is unusual. After the data were merged, only groups with more than 

250 women were retained for the final analysis (Table 2). 

Table 2 Distribution of ethnic groups by survey, Zambia 

Ethnolinguistic group 

DHS 

1992 

DHS 

1996 

DHS 

2001 

Significance 

Bemba 18.8 22.6 20.4 * 

Tonga 14.4 10.9 11.6 * 

Chewa 6.8 8.1 6.4 * 

Lozi 5.1 6.0 6.3 * 

Nsenga 5.8 5.9 5.0 * 

Tumbuka 4.3 4.6 4.3 

Ngoni 4.1 3.4 4.0 * 

Lala 3.8 2.8 2.6 * 

Kaonde subgroup 2.7 2.4 2.9 

Mambwe 2.6 2.4 2.8 

Namwanga 2.0 2.6 2.9 * 

Ushi 1.8 2.6 2.7 * 

Lamba 2.1 2.1 2.2 

Luvale 1.9 2.2 2.2 

Lunda 3.5 2.5 3.7 * 

Mbunda 1.5 1.7 2.5 * 

Bisa 1.9 1.2 1.8 * 

Lenje 1.7 1.7 1.3 

Other and unknown 15.3 14.1 14.3 * 

 

Total 100.0 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Zambia, with an average of 7.1 percent for all births and 

20.0 percent for women. The prevalence of premarital intercourse is high (49.9 percent), although median 

age at marriage remains at a medium level (17.6 years). 
86

 Differentials in premarital fertility by ethnicity are wide in Zambia, varying from 11.8 percent 

among the Mambwe in the North, to 46.3 percent among the Mbunda in the southwest (Table 3). 

Table 3 Premarital fertility and nuptiality indicators, Zambia 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bemba 5,445 59.3 17.4 0.6 5.2 15.3 43.7 

Tonga 1,723 28.1 18.2 0.0 10.4 29.5 58.7 

Chewa 1,077 30.8 17.3 1.1 4.6 13.4 39.1 

Lozi 1,032 45.3 20.0 2.2 18.1 41.2 74.4 

Nsenga 779 49.9 17.3 0.8 6.8 18.4 46.0 

Tumbuka 624 52.4 18.0 0.0 4.7 15.2 42.3 

Ngoni 530 50.8 17.8 1.7 6.8 19.9 48.1 

Lala 1,292 49.5 17.2 0.5 8.7 23.7 55.1 

Kaonde subgroup 603 43.4 16.8 0.0 6.7 19.3 55.4 

Mambwe 368 45.4 17.7 0.0 4.1 11.8 41.3 

Namwanga 381 53.5 17.8 0.0 5.0 13.7 41.8 

Ushi 1,540 49.9 17.1 0.0 4.6 14.2 42.8 

Lamba 417 50.4 17.1 0.0 5.5 16.5 41.8 

Luvale 472 38.1 17.9 1.4 10.7 24.1 65.7 

Lunda 1,916 31.6 17.4 0.0 7.8 22.9 59.1 

Mbunda 401 7.1 18.6 1.4 19.5 46.3 78.1 

Bisa 794 40.9 18.0 0.0 9.6 27.0 56.0 

Lenje 256 48.7 18.8 4.4 12.6 31.8 70.7 

Other and unknown 3,089 38.3 17.5 0.5 6.0 17.7 46.8 

 

Total 22,739 45.4 17.6 0.5 7.1 20.0 49.9 

Source: Authors’ calculations after merging data from 1992, 1996, and 2001 DHS surveys. 

Correlation of premarital fertility with age at marriage is high (ρ = +0.754) and groups are spread 

along the age at marriage axis from about 17 years (Ushi, Lamba, Kaonde) to 20 years (Lozi) (Figure 1). 

Surprisingly, for a country that is relatively urbanized (45.4 percent) and industrialized (because 

of the copper mines), the correlation of premarital fertility with urban residence is strongly negative 

(ρ = -0.601). This finding is related to the heavy weight of southern groups that have low levels of urban 

residence and high levels of premarital fertility (Tonga, Mbunda) and northern groups that have high 

levels of urban residence and low levels of premarital fertility (Bemba, Tumbuka, Namwanga). 
87

Figure 1 Correlation between premarital fertility and age at first marriage, Zambia 

Mbunda

Lozi

Lenje

Kaonde SG

Bemba

Tonga

Chewa

Nsenga

Tumbuka

Ngoni

Lala

Mambwe

Ushi Namwanga

Lamba

Lunda

Bisa

Luvale

0

10

20

30

40

50

16 17 18 19 20 21

Median age at first marriage (years)

% women with premarital birth
DHS Comparative Reports Series 

1. Westoff, Charles F. 2001. Unmet Need at the End of the Century. 

2. Westoff, Charles F. and Akinrinola Bankole. 2002. Reproductive Preferences in Developing 

Countries at the Turn of the Century. 

3. Rutstein, Shea O. 2002. Fertility Levels, Trends, and Differentials 1995-1999. 

4. Mahy, Mary. 2003. Childhood Mortality in the Developing World: A Review of Evidence from 

the Demographic and Health Surveys. 

5. Westoff, Charles F. 2003. Trends in Marriage and Early Childbearing in Developing Countries. 

6. Rutstein, Shea O. and Kiersten Johnson. 2004. The DHS Wealth Index. 

7. Yoder, P. Stanley, Noureddine Abderrahim, and Arlinda Zhuzhuni. 2004. Female Genital Cutting in 

the Demographic and Health Surveys: A Critical and Comparative Analysis. 

8. Stallings, Rebecca. 2004. Child Morbidity and Treatment Patterns. 

9. Rutstein, Shea O. and Iqbal H. Shah. 2004. Infecundity, Infertility, and Childlessness in 

Developing Countries. 

10. Mukuria, Altrena, Jeanne Cushing, and Jasbir Sangha. 2005. Nutritional Status of Children: 

Results from the Demographic and Health Surveys, 1994–2001. 

11. Mukuria, Altrena, Casey Aboulafia, and Albert Themme. 2005. The Context of Women’s Health: 

Results from the Demographic and Health Surveys, 1994-2001. 

12. Yoder, P. Stanley, Noureddine Abderrahim, and Arlinda Zhuzhini. 2005. L’excision dans les 

Enquêtes Démographiques et de Santé : Une Analyse Comparative. 

13. Garenne, Michel, and Julien Zwang. 2006. Premarital Fertility and Ethnicity in Africa. 

14. Westoff, Charles F. 2006. New Estimates of Unmet Need and the Demand for Family Planning. 
The MEASURE DHS project assists countries worldwide in the collection and use of data to monitor and 

evaluate population, health, nutrition, and HIV/AIDS programs. Funded by the United States Agency for 

International Development (USAID) under Contract No. GPO-C-00-03-00002-00, MEASURE DHS is 

implemented by Macro International Inc. in Calverton, Maryland. 

The main objectives of the MEASURE DHS project are: 

• To provide decisionmakers in survey countries with information useful for informed policy choices; 

• To expand the international population and health database; 

• To advance survey methodology; and 

• To develop in participating countries the skills and resources necessary to conduct high-quality 

demographic and health surveys. 

Additional information about the MEASURE DHS project is available on the Internet at 

http://www.measuredhs.com or by contacting Macro International Inc., MEASURE DHS, 11785 Beltsville 

Drive, Suite 300, Calverton, MD 20705 USA; Telephone: 301-572-0200, Fax: 301-572-0999, E-mail: 

reports@measuredhs.com. 
DHS Comparative Reports No. 13 

Premarital Fertility and Ethnicity in Africa 

Michel Garenne 

French Institute for Research and Development (IRD) 

and Institut Pasteur, Paris 

Julien Zwang 

Institut des Cordeliers, Université de Paris VI, and 

Centre d’Etudes et de Recherches sur le Développement International (CERDI) 

Macro International Inc. 

Calverton, Maryland USA 

December 2006 

The authors’ views expressed in this publication do not necessarily reflect the views of the 

United States Agency for International Development or the United States Government.
This publication was made possible through support provided by the United States Agency for International Development (USAID) under Contract No. GPO-C-00-03-00002-00. 

Recommended citation: 

Garenne, Michel, and Julien Zwang. 2006. Premarital Fertility and Ethnicity in Africa. DHS Comparative 

Reports No. 13. Calverton, Maryland, USA: Macro International Inc. 
iii

In memory of Etienne van de Walle, 

A pioneer in the study of 

African nuptiality and fertility.
v

Contents 

Tables and Figures.............................................................................................................................................vii 

Preface................................................................................................................................................................ ix 

Acknowledgments .............................................................................................................................................. xi 

Executive Summary..........................................................................................................................................xiii 

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

2 Data and Methods........................................................................................................................................ 3 

 2.1 Datasets ..................................................................................................................................... 3 

 2.2 Ethnicity in DHS Surveys ......................................................................................................... 3 

 2.3 Sample Size and Grouping of Datasets ..................................................................................... 4

 2.4 Prevalence of Premarital Fertility.............................................................................................. 4 

 2.5 Socioeconomic Variables .......................................................................................................... 5 

 2.6 Methodology ............................................................................................................................. 6 

3 Results ......................................................................................................................................................... 7 

 3.1 Samples of Ethnic Groups......................................................................................................... 7 

 3.2 Premarital Fertility by Ethnicity................................................................................................ 8 

 3.3 Comparison with the Ethnographic Literature .......................................................................... 9 

 3.4 Demographic Factors and Socioeconomic Determinants........................................................ 10 

 3.5 Geographical Patterns.............................................................................................................. 11 

 3.6 Outliers from Demographic Variables .................................................................................... 14 

4 Conclusions ............................................................................................................................................... 15 

References ......................................................................................................................................................... 17 

Appendix ........................................................................................................................................................... 19 

vii

Tables and Figures 

Table 3.1 Ethnic groups in sub-Saharan Africa: Information from population and survey 

 data, various sources including WFS and DHS national sample surveys.............................. 7 

Table 3.2 Distribution of ethnic groups by level of premarital fertility, sub-Saharan Africa ................ 9 

Table 3.3 Norms of premarital sexual behavior in African ethnic groups in Murdock’s Atlas, 

and relationship with the prevalence of premarital fertility in DHS surveys......................... 9 

Table 3.4 Correlation of premarital fertility with demographic factors, modern contraception, 

and socioeconomic determinants, sub-Saharan Africa......................................................... 10 

Table 3.5 Correlation coefficients between socioeconomic determinants and demographic 

factors, sub-Saharan Africa (N = 263 ethnic groups)........................................................... 11 

Figure 3.1 Distribution of ethnic groups according to the prevalence of premarital fertility, 

25 countries in sub-Saharan Africa ........................................................................................ 8 

Figure 3.2 Prevalence of premarital fertility in Africa, by region ......................................................... 12 

Figure 3.3 Median age at first marriage in Africa, by region ................................................................ 13 

Figure 3.4 Relationship between prevalence of premarital fertility and median age at first 

marriage among 263 African ethnic groups......................................................................... 14 

ix

Preface 

One of the most significant contributions of the MEASURE DHS program is the creation of an 

internationally comparable body of data on the demographic and health characteristics of populations in 

developing countries. The DHS Comparative Reports series examines these data across countries in a 

comparative framework, and is primarily descriptive. The DHS Analytical Studies series focuses on 

technical analysis of specific topics. The principal objectives of both series are to provide information for 

policy formulation at the international level and to examine individual country results in an international 

context. 

DHS Comparative Reports covers a variable number of countries, depending on the availability 

of datasets. Where possible, data from previous DHS surveys are used to evaluate trends over time. Each 

report provides detailed tables and graphs organized by region. Survey-related issues such as 

questionnaire comparability, survey procedures, data quality, and methodological approaches are 

addressed as needed. 

The topics covered in the DHS Comparative Reports series are selected by MEASURE DHS staff 

in conjunction with the U.S. Agency for International Development. Some reports are updates of 

previously published reports. 

It is anticipated that the availability of comparable information for a large number of developing 

countries will enhance the understanding of important issues in the field of international population and 

health by analysts and policymakers. 

Martin Vaessen 

Project Director 

xi

Acknowledgments 

The authors would like to thank the U.S. Agency for International Development and Macro 

International Inc. for supporting this research and the Wellcome Trust for sponsoring the first part of the 

study. 

xiii

Executive Summary 

Premarital fertility, defined as giving birth before a woman’s first marriage, is prevalent in subSaharan Africa. According to DHS data from surveys in 25 countries, an average of one in five women 

has a birth before marriage. The prevalence of premarital fertility varies markedly, ranging from 2.4 to 

60.2 percent in the countries covered. The variation is even greater by ethnic group, ranging from 0.1 to 

76.2 percent. The level of premarital fertility is determined by a number of factors including age at first 

marriage, age at first intercourse, contraceptive use, and various cultural factors; and all of these factors 

vary by ethnicity. An analysis of 263 ethnic groups shows that age at first marriage is by far the most 

important factor. Variables linked to modernization—urban residence, modern education, wealth, and 

Christianity—have positive correlations with premarital fertility, whereas living in a polygynous union 

and being Muslim have negative correlations. Even taking into account demographic and socioeconomic 

factors, variations in the level of premarital fertility are substantial, indicating the strong effect of cultural 

factors. The demographic evidence presented in this analysis is consistent with the ethnographic record, 

which distinguishes between societies that are culturally conservative and societies that are more open 

and permissive. The Appendix presents detailed information on premarital fertility by ethnicity for the 

countries in the study. 
1

1 Introduction 

Premarital fertility, defined as giving birth before a woman’s first marriage, was of considerable 

interest to Europeans when they encountered African societies in the nineteenth and early twentieth 

centuries. Most Europeans came from cultures in which premarital sexual intercourse and premarital 

childbirth were highly stigmatized and repressed, and where marriage was strictly regulated, whether by 

civil law or by Christian religion. In Africa, they found a diversity of cultures that had very different 

world views about sexual intercourse and childbirth before marriage. Furthermore, marriage in Africa was 

guided by custom, with no equivalent to a marriage certificate. There was no official point in time before 

which intercourse or childbirth could be considered premarital. Marriage was a social process, an alliance 

between families or social groups. At the same time, marriage in African societies did follow clear rules, 

the rules were just different from those of European societies (Radcliffe-Brown and Forde, 1950; van de 

Walle, 1968). Observers of African cultures wrote extensively about premarital sexual relations and their 

relationship to marriage. For example, Grandidier (1913) described patterns of marriage and fertility at 

the turn of the twentieth century in Madagascar and presented numerous accounts of permissiveness 

toward premarital sexual behavior: some groups considered it normal for a woman to give birth before her 

first marriage. He further noted that permissiveness varied among ethnic groups, and also by social class. 

These patterns seem to have been resistant to change because, a century later, similar patterns were found 

in demographic survey data (Garenne and Zwang, 2005). 

Ethnographers working in Africa in the first part of the twentieth century spent considerable time 

and effort describing patterns of marriage and sexual permissiveness. There does not appear to be any 

review or synthesis of this abundant literature with regard to premarital fertility. However, in his classic 

work, Ethnographic Atlas, Murdock (1967) uses a series of characteristics taken from ethnographic 

literature to describe attitudes toward premarital sexual intercourse in different ethnic groups. Attitudes 

were categorized, ranging from very permissive to very repressive: (F) premarital sexual relations freely 

permitted and subject to no sanctions; (A) premarital sexual relations allowed, not sanctioned unless 

pregnancy results; (P) premarital sexual relations prohibited, but weakly sanctioned; (T) trial marriage; 

promiscuous relations prohibited; (E) premarital sexual relations precluded by very early age at marriage 

for females; (V) insistence on virginity; premarital sexual relations prohibited.1

 In his synthesis, Murdock 

analyzed 277 ethnic groups from sub-Saharan Africa. Only 114 (41 percent) had information on norms of 

sexual behavior. A majority of these (53 percent) were categorized as “permissive” (groups A and F); a 

smaller number (15 percent) were considered “tolerant” (group P); and the remainder (34 percent) were 

seen as “restrictive” (groups E and V). Those in the restrictive category included cultures with very early 

age at marriage for females and those with strong sanctions on premarital sexual relations. This overview 

points up the ethnographic diversity found in sub-Saharan Africa, which accounts for the diverse patterns 

of premarital fertility that emerge from demographic surveys. This diversity contrasts markedly with 

North African and European populations, for whom permissiveness has traditionally been rare. In the 

same Ethnographic Atlas, only one group in North Africa—the Tamasheq Kel Antessar in Southern 

Sahara—and only one small group in central Europe, fall into the (F) category. 

 

1

 While Murdock distinguished six categories of “norms of premarital sexual behavior,” only five pertain to Africa: 

F, A, P, E, V. 
2

The aim of this study is to examine the variations in levels of premarital fertility by ethnicity in 

sub-Saharan Africa. Much of the information on marriage, fertility, and ethnicity came from DHS 

datasets provided by the MEASURE DHS project. The main reason for emphasizing ethnicity stems from 

case studies conducted by the authors in South Africa, Namibia, and Madagascar. The research showed 

that ethnicity was the primary source of differential behavior in premarital fertility, and was much more 

important than socioeconomic factors such as urbanization, education, wealth, or religion (Garenne et al., 

2000; Garenne and Zwang, 2004; Garenne and Zwang, 2005; Zwang, 2004). This study goes beyond a 

description of the differentials in premarital fertility by analyzing the relationship between premarital 

fertility and socioeconomic determinants such as urbanization, education, wealth, and religion. From this 

perspective, it is an extension of previous research on the determinants of age at marriage in sub-Saharan 

Africa (Garenne, 2004). 
3

2 Data and Methods 

2.1 Datasets 

A11 World Fertility Surveys (WFS) and Demographic and Health Surveys (DHS) that were 

available in early 2005 were considered for this study. Surveys with samples based only on ever-married 

women and surveys without information on ethnicity were excluded. When several surveys were 

available for the same country, only those in which the coding of ethnicity was explicit and consistent 

were kept for final analysis. Information about the surveys kept for final analysis is shown by country in 

the Appendix, along with the reasons given for the choices. When several compatible surveys were 

selected in the same country, the computations regarding premarital fertility were made on the combined 

dataset. The main reason for combining datasets was to increase the sample size of ethnic groups in the 

country. Final results are provided at the country level only. The analysis covers 25 sub-Saharan 

countries, which accounts for a large proportion (about 75 percent) of the total population of the region. 

2.2 Ethnicity in DHS Surveys 

DHS surveys have been conducted in 32 African countries but several surveys did not include 

information on ethnicity. Also, while some surveys included information on ethnicity, they differed in the 

characterization of ethnic groups and in the level of detail provided. Some surveys (such as those in 

Zambia) included a comprehensive list of all of the ethnolinguistic groups while others (such as those in 

Senegal) included only a list of the largest groups, ignoring small minorities. Another group of surveys 

(such as those in Mali) included a short list of the main ethnic groups, and a large “other” category. In 

some cases, only large language families were provided (such as in Togo), and in a few surveys in 

Southern Africa, only race was included (such as in Zimbabwe). 

Information on ethnicity in DHS surveys is usually provided by the V131 variable of the 

Individual Recode file, although it appears in the S-section of country-specific variables in some surveys. 

In one case (Uganda 2001), the information was contained in the Household Recode file as the language 

in each cluster. In this case we merged the cluster with the individual file to determine the ethnicity of the 

person interviewed. 

Some countries recorded ethnicity confidentially in the questionnaires, and the labels of the ethnic 

groups were not available in the dataset code book. In some cases the labels could be retrieved from other 

information, such as language spoken, but in others the analysis had to be cancelled. 

Lastly, some surveys provided only the language usually spoken by the respondent as the sole 

information on ethnicity. This information was used in a few cases. However, information on the 

language used for the interview was not considered in this study because it may not reflect correct ethnic 

identity. Each case is detailed in the Appendix by country and survey. 

In some countries, when the necessary information was available, the ethnic distribution obtained 

from the DHS surveys was compared with the distribution obtained from the national censuses. Another 

source of information was the Ethnologue database, which provides names, locations, and population 

sizes of virtually all ethnolinguistic groups in Africa (Gordon, 2005). 

In terms of sample size, the cluster sampling method used in DHS surveys is unlikely to provide 

an accurate ethnic distribution in a country. Many clusters are likely to be ethnic-specific and, as a result, 

the ethnic distribution may show overestimates or underestimates, according to chance. It would be 

cumbersome to try to estimate the biases involved because they depend on the ethnic distribution in each 
4

enumeration area. However, since the emphasis of this study is on the specificity of ethnic groups, minor 

variations in sample size are unlikely to affect the main results. 

The spelling of ethnic groups was kept as indicated in the DHS code books. Some groups have 

English spelling; others have French or Portuguese spelling. Some ethnic group labels differ from those in 

the classical ethnographic literature, but no attempt was made to correct them. 

2.3 Sample Size and Grouping of Datasets

In many countries, more than one survey was conducted. When possible, the surveys were 

grouped together to increase the sample size of small groups and to reduce the confidence intervals 

associated with the prevalence of premarital fertility. This was done only in cases where the coding was 

consistent from survey to survey. Each case is detailed in the Appendix. 

A main limitation of the analysis of ethnicity in DHS surveys is sample size. The typical DHS 

survey has a sample of about 7,000 women. A minority group that makes up only 1 percent of the 

population will have only 70 women surveyed. This was considered too small a sample for this 

demographic analysis. Therefore, after grouping surveys in a country, ethnic groups with at least 250 

women were kept for analysis. This allowed even small groups to be included in countries where two or 

more surveys were conducted. A sample of 250 women will provide reasonable confidence intervals for 

the prevalence of premarital fertility. For example, a prevalence of 20 percent and a sample of 250 

women give a 95 percent confidence interval of 15.1 to 24.9 percent, which still allows a distinction 

between low, medium, and high levels of premarital fertility. Of course, larger sample sizes are desirable 

for finer estimation; however, because the aim of the study was to analyze ethnic diversity, it was 

preferable to include small groups with a wider confidence interval rather than ignore them. In a few 

cases, even smaller groups (such as the Twa in Rwanda) were included when they had special 

significance for ethnographic reasons. Proper testing of differences between groups is sometimes done 

after controlling for other factors. Readers who wish to do their own testing can do so using the tables in 

the Appendix, which include sample size. It is recommended to use simple testing based on sample size 

(unweighted number of women interviewed)—assuming random distribution of women within ethnic 

group—and to ignore the design effect associated with cluster sampling. This is suggested because most 

clusters in Africa are likely to be ethnic-specific. 

In the analysis of ethnicity, priority was given to specificity: well-defined groups were considered 

individually while others were lumped together in the “other and unknown” category. This was 

considered more informative than attempting to group them by language families or by geographical 

proximity. However, in cases of high ethnic diversity (such as in Nigeria and Cameroon), small ethnic 

groups were lumped together by geographical area, following the main divisions of the country. 

2.4 Prevalence of Premarital Fertility 

The DHS definition of marriage was used in this report for consistency. In DHS surveys, a 

woman is considered married if she is formally married (civil or religious union)2

 or if she is in an 

informal union (living together). For a discussion of discrepancies in African surveys regarding “married” 

and “in union,” see Garenne (2004). Terminal celibacy is defined as the probability of never marrying by 

age 50. It is approximated by the proportion of never-married women age 40-49 at the time of the survey. 

The Appendix shows two indicators of the prevalence of premarital fertility.3

 The first is the 

prevalence of premarital births, defined as the proportion of all births that occurred before the first 

 

2

 Includes customary marriages 

3

 Almost all DHS surveys interview women age 15-49 only and collect retrospective maternity histories. 
5

marriage. Dates are counted in months and years, as defined by the century month code (CMC) system of 

the DHS surveys (corresponding variables are V509 for first marriage and V211 for first birth). The 

second is the proportion of women who have had a premarital birth to all women who have ever given 

birth or who have ever been married. (Never-married women who never had a live birth were excluded 

from the calculations.)4

 The prevalence of premarital intercourse, defined as the proportion of women 

who had intercourse before their first marriage (V525 variable), was calculated wherever possible. 

Median age at first marriage was calculated by selecting all women age 25 and over and 

determining the age at which 50 percent of the women in each cohort were ever married. Because some 

women will never marry, this definition differs from the formal definition of median age at first marriage, 

which uses ever-married women as the population base. It is also different from mean age at first 

marriage, which is computed from life table analysis. In most cases the three values were found to be 

equivalent. Calculating life table estimates for each ethnic group would be cumbersome and would lead to 

erratic estimates in small ethnic groups. 

2.5 Socioeconomic Variables 

Several socioeconomic variables were considered as potential determinants of level of premarital 

fertility. Urban residence was measured by the proportion of interviewed women living in urban areas. 

This figure in DHS surveys sometimes varied substantially from the proportion urban as reported by the 

national census. Because of the cluster sampling method used in DHS surveys, some clusters for selected 

ethnic groups can end up primarily in one or the other residence categories (urban or rural). This 

introduces bias into the calculation of prevalence of premarital fertility for small ethnic groups. However, 

because this study focuses on diversity, the bias probably does not have much effect on the analysis. 

Religion was taken as reported in the DHS surveys, and grouped into three categories: Muslims, 

Christians, and “other and unknown.” First analyses revealed only minor differences among Christian 

groups (Protestants versus Catholics), although the distinction can be a major source of differentials when 

associated with other characteristics, as occurred in the case of Madagascar (Garenne and Zwang, 2004). 

Analyzing traditional religion is beyond the scope of this paper, and DHS surveys do not provide details 

on local religions, which are usually grouped under labels such as “traditional religion,” “animist,” or 

“spiritualist.” 

A wealth index was developed for this study, although it follows a model described elsewhere 

(Garenne and Hohmann, 2003). It is the sum of a group of dummy variables that count modern goods and 

amenities in the household. The wealth index was calculated the same way for all of the surveys so that it 

could be used comparatively and averaged for ethnic groups. It therefore differs from the DHS wealth 

index provided by some DHS surveys, which is based on principal components and wealth quintiles. 

Other data used for this analysis were straightforward and derived directly from the survey. Level of 

education was measured by the mean number of years of schooling (V133). Because use of a 

contraceptive method might be an important element in premarital fertility, “knowledge of any modern 

method” (V301), “ever use of any modern method” (V302), and “current use of any modern method” 

(V303) were considered separately. Use of contraception was examined only for women who had ever 

had intercourse and were never married—that is, use of contraception during the risk period for premarital 

births. Modern contraceptive methods were selected because they have the largest effect on unwanted 

pregnancies. 

 

4

 The two indicators refer to live premarital births; premarital pregnancies that resulted in miscarriage or abortion are 

not included. 
6

2.6 Methodology 

Premarital fertility is a period-specific measure of births that occur before marriage. The period of 

risk for premarital births is the interval between first intercourse and first marriage. Premarital fertility is 

the product of a series of demographic behaviors: first intercourse, first marriage, contraceptive use, and 

abstinence between first intercourse and first marriage. The prevalence of premarital births in a group is 

likely to be positively correlated with age at marriage, and negatively correlated with age at first 

intercourse and use of modern contraceptive methods. These demographic factors have a structural effect 

on premarital fertility. Other variables, labeled “socioeconomic determinants,” affect these intermediate 

variables, as well as attitudes. These include ethnicity, religion, urban-rural residence, level of education, 

polygyny, and wealth. 

This analysis aims to describe differentials in the prevalence of premarital fertility by ethnicity as 

well as by demographic and socioeconomic factors. While some of the analysis could have been done 

using individual-level data, the use of ethnic group as the unit of analysis offered the opportunity to 

include several factors that could not otherwise be included—in particular, age at first marriage and level 

of contraceptive use. These were found to be major factors determining premarital fertility at the group 

level, but were inappropriate at the individual level. For example, if a woman is never married but had a 

premarital birth, she does not have an age at marriage. 
7

3 Results 

3.1 Samples of Ethnic Groups 

Of the 51 countries in sub-Saharan Africa, 32 were covered by DHS surveys and 25 of these 

surveys had information on ethnicity (see Table 3.1). Altogether, 43 surveys were included in the 

analysis, 8 of which were WFS surveys and 35 were DHS surveys. Some 2,104 ethnic groups are 

included in the Ethnologue database for Africa, which is the most extensive count. It corresponds to an 

average of 310,600 persons per ethnic group, with populations ranging from a few individuals to several 

million. 

In the 43 surveys analyzed, 263 ethnic groups were kept for final analysis. They were usually the 

larger groups, and their average population size was more than five times that of the average group size 

for the whole set. DHS surveys primarily include large groups, whereas the ethnographic literature tends 

to emphasize small, well-defined groups with specific cultural characteristics. 

After grouping surveys, the average sample size per country was 12,915 women interviewed. The 

overall average of 1,228 women interviewed per ethnic group is an appropriate sample size for many 

demographic estimates, including premarital fertility. 

Table 3.1 Ethnic groups in sub-Saharan Africa: Information from population and survey data, 

various sources including WFS and DHS national sample surveys 

Coverage of DHS surveys 

Characteristic 

Total 

sub-Saharan

Africa Total 

Information 

on ethnicity 

Total population 

 Number of countries 51 32 25 

 Number of ethnic groups 2,104a

 1,804 1,648 

 Population covered (millions) 653.6b

 562.2 491.6 

 Mean size of ethnic groups 310,600c

 311,600 298,300 

Sample surveys (DHS, WFS) DHS and WFS surveys analyzed 

 Number of surveys analyzed 43 

 Number of ethnic groups 263 

 Mean population size per group 1,621,200 

 Average survey sample size (number of women interviewed) 12,915 

 Mean number of women interviewed per ethnic group 1,228 

a

 Ethnologue database (Gordon, 2005) 

b

 Population in year 2000 (United Nations, Population Division) c

 Mean size = population/number of ethnic groups 

 

 
8

3.2 Premarital Fertility by Ethnicity 

The prevalence of premarital fertility, defined as the proportion of women who had a premarital 

birth, varies considerably among the 263 ethnic groups examined, from 0.1 percent (Kanem-Bornou in 

Chad) to 76.2 percent (Herero in Namibia). The wide range is illustrated in Figure 3.1. The distribution of 

ethnic groups by premarital fertility is complex and does not follow a simple statistical distribution; 

instead, it shows wide heterogeneity. At one end of the range are low levels of premarital fertility, which 

could be interpreted (in repressive societies) as accidents or as deviant behavior by a small proportion of 

the population. A second group clusters between 10 and 13 percent; another group is 22 to 27 percent; 

another group is 38 to 41 percent; and a number of ethnic groups have very high levels of premarital 

fertility (50 percent and above). Such a wide range of prevalence of premarital fertility reflects the wide 

variety of behavioral norms described in the ethnographic literature, from societies that require girls to 

marry right after puberty—in which case premarital fertility is virtually impossible—to societies in which 

marriage occurs late and premarital intercourse is permitted. 

Figure 3.1 Distribution of ethnic groups according to the prevalence of 

premarital fertility, 25 countries in sub-Saharan Africa 

0 5 10 15 20 25

< 2

2-3

4-5

6-7

8-9

10-11

12-13

14-15

16-17

18-19

20-21

22-23

24-25

26-27

28-29

30-31

32-33

34-35

36-37

38-39

40-41

42-43

44-45

46-47

48-49

50-51

52-53

55-55

56-57

58-59

60+

Level of premarital fertility (%) ok

No. of ethnic groups
9

Five levels of premarital fertility can be defined: “Very Low” for levels below 9.0 percent, with 

an average of 4.7 percent; “Low” from 9.0 to 14.9 percent, with an average of 12.1 percent; “Medium” 

from 15.0 to 29.9 percent, with an average of 22.0 percent; “High” from 30.0 to 49.9 percent, with an 

average of 38.6 percent, and “Very high” above 50.0 percent, with an average of 66.5 percent (Table 3.2). 

The mean population size of ethnic groups did not indicate a linear relationship with level of premarital 

fertility; permissive and repressive behaviors were found in small and large groups alike. 

Table 3.2 Distribution of ethnic groups by level of premarital fertility, sub-Saharan Africa 

Level of premarital 

fertility 

Range 

(%) 

Number of 

ethnic groups 

Mean 

population 

per group 

Mean level of 

premarital 

fertility (%) 

Very low < 9 81 1,969,661 4.7 

Low 9-14 57 1,965,123 12.1 

Medium 15-29 73 1,160,181 22.0 

High 30-49 34 1,031,049 38.6 

Very high 50+ 18 1,949,115 66.5 

 

Total 263 1,621,245 17.9 

3.3 Comparison with the Ethnographic Literature 

Estimates of the prevalence of premarital fertility by ethnicity in DHS surveys were matched with 

ethnographic characteristics in Murdock’s Atlas (Table 3.3). Matching groups from the two sources was 

difficult because of the different ethnic categories and many missing values in the Atlas. Altogether, only 

91 ethnic groups could be matched; of these, 36 had ethnographic details on premarital norms. Despite the 

low coverage, a pattern emerged. Groups who were more repressive (V and E) had lower premarital 

fertility (9.2 percent and 12.9 percent), intermediate groups (P) had medium values (15.8 percent), and 

groups classified as permissive (A and F) had higher values (37.9 percent and 20.0 percent). Even though 

the sample of selected ethnic groups was obviously biased and the sample sizes of some groups were 

small, the average of selected groups (17.7 percent) was close to the African average, and the 

demographic classification approximately matched the ethnographic typology. 

Table 3.3 Norms of premarital sexual behavior in African ethnic groups from Murdock’s Atlas, and relationship 

between ethnicity and the prevalence of premarital fertility in DHS surveys 

Norms of premarital sexual behavior 

Number of 

groups in Atlas 

Number of 

groups found in 

DHS surveys 

Average percentage 

of women with a 

premarital birth 

A 

Premarital sexual relations allowed; no 

sanctions unless pregnancy results 12 4 37.9 

F Premarital sexual relations freely permitted; 

no sanctions 48 19 20.0 

P Premarital sexual relations prohibited; weak 

sanctions; not infrequent in fact 15 3 15.8 

E Premarital sexual relations precluded by 

early age at marriage for females 11 5 12.9 

V 

Insistence on virginity; premarital sexual 

relations prohibited; strong sanctions, rare 

in fact 

 28 5 9.2 

 Total, stated 114 36 17.7 

 Total, not stated 163 227 

 Total 277 263 17.7 

Source: Murdock Atlas (1967) and DHS surveys 
10

3.4 Demographic Factors and Socioeconomic Determinants 

Correlations of premarital fertility with demographic factors are shown in Table 3.4. Premarital 

fertility is positively correlated with age at first marriage (+0.779), age at first intercourse (+0.217), and 

terminal celibacy (+0.687). The first and third correlations are straightforward because later marriage and 

lower levels of marriage are likely to result in an increase in premarital fertility. The second correlation 

shows the results of the selection effect: women who marry later and have first intercourse at the time of 

marriage have higher age at first intercourse. In fact, if age at marriage is controlled, the net effect of age 

of first intercourse becomes negative. 

Table 3.4 Correlation of premarital fertility with demographic factors, modern 

contraception, and socioeconomic determinants, sub-Saharan Africa 

Variables 

Correlation 

coefficients P-value Significance 

Demographic factors 

Age at first marriage 0.779 6.10E-55 * 

Age at first intercourse 0.217 3.98E-04 * 

Terminal celibacy 0.687 4.46E-38 * 

Modern contraception 

Knowledge 0.319 1.30E-07 * 

Ever use 0.496 9.79E-18 * 

Current use 0.373 4.36E-10 * 

Socioeconomic determinants 

Urbanization 0.456 6.80E-15 * 

Education 0.692 9.45E-39 * 

Wealth index 0.588 7.98E-26 * 

Proportion Muslim -0.436 1.29E-13 * 

Proportion Christian 0.383 1.26E-10 * 

Polygyny -0.478 2.11E-16 * 

p = <0.05 

The effect of contraception is counterintuitive; all three variables (knowledge, ever use, and 

current use) had a positive correlation with premarital fertility, suggesting that greater use of 

contraception leads to higher fertility. Such a conclusion is the result of reverse causality because groups 

that have higher levels of premarital fertility are more likely to use contraception. So far, use of modern 

contraceptive methods before marriage has not had a large enough impact to allow women to prevent 

premarital births (assuming that this is their desire). Thus, the results in Table 3.4 imply that use of 

modern contraceptive methods is not an important factor in premarital fertility. 

Four socioeconomic variables were found to have a positive correlation with premarital fertility: 

urban residence, level of education, wealth, and Christianity. The effect of these variables is related 

primarily to higher age at first marriage, but also increased terminal celibacy (Table 3.5). 

The two remaining variables, Islam and polygyny, had negative correlations with premarital 

fertility. Here again, the effect is primarily related to nuptiality, particularly lower age at marriage, but 

also decreased terminal celibacy (Tables 3.4 and 3.5). Note that Islam and polygyny are correlated 

(0.493), and that both tend to encourage early and universal marriage for women. 

An analysis of premarital fertility shows that socioeconomic determinants explain about half 

(57 percent) of the total variance. The rest is due to ethnicity, thus emphasizing the strong role of cultural 

factors in childbearing before marriage. 
11

Table 3.5 Correlation coefficients between socioeconomic determinants and demographic factors, subSaharan Africa (N = 263 ethnic groups) 

Nuptiality Modern contraception 

Socioeconomic 

determinants 

Age at first 

marriage 

Age at first 

intercourse 

Terminal 

celibacy Knowledge 

Ever 

use 

Current 

use 

Urbanization (%) 0.358 0.112 0.270 0.290 0.338 0.173 

Education (No. of years) 0.681 0.461 0.450 0.470 0.496 0.312 

Wealth index 0.616 0.371 0.470 0.335 0.572 0.406 

Muslim (%) -0.458 -0.314 -0.265 -0.297 -0.328 -0.187 

Christian (%) 0.422 0.339 0.220 0.382 0.322 0.158 

Polygyny (%) -0.523 -0.338 -0.430 -0.329 -0.304 -0.247 

3.5 Geographical Patterns 

All these factors interact to shape geographical patterns of premarital fertility. Details at the 

country level are provided in the Appendix and show great diversity in countries with complex social 

systems and numerous ethnic groups. Some regional patterns emerge. Prevalence of premarital fertility is 

low in the West African Sahelian areas, medium in coastal West Africa and in Eastern Africa, and high to 

very high in Southern Africa (Figure 3.2). In Sahelian West Africa, there is a gradient from the most 

conservative area in the central part of the region, primarily rural and Muslim, to the more urbanized 

West, with the exception of Mandinka and Poular areas in Northern Guinea, which appear to be very 

Figure 3.2 Prevalence of premarital fertility in Africa, by region 
12

conservative. On the West African coast, Liberia and southern areas of Côte d’Ivoire appear as 

exceptions. In Central Africa, a pocket of high levels of premarital fertility ranges from southern 

Cameroon to Gabon. In Eastern Africa, pockets of higher premarital fertility are seen in southern Uganda, 

central Kenya and southern Tanzania. The highest levels of premarital fertility are found in Southern 

Africa; this includes Namibia, South Africa and Botswana, up to southern Zambia. In Madagascar, 

premarital fertility is more prevalent on the northeast coast and less prevalent in the central highlands. 

The geographical patterns for the prevalence of premarital fertility in sub-Saharan Africa are 

related to the patterns for age at first marriage (Figure 3.3). However, some exceptions can be noted. 

Premarital fertility is low in Rwanda, Burundi, and central Madagascar at the same time that age at first 

marriage is high. In these countries contraceptive use is low and there is strong social control of young 

women. 

Figure 3.3 Median age at first marriage in Africa, by region 
13

A better illustration of the relationship between premarital fertility and age at first marriage is 

seen in Figure 3.4. This figure reveals three situations: 

• Very low age at marriage (<15 years), which correlates with very low premarital fertility 

(<10 percent). 

• Very high age at marriage (≥22 years), which correlates with very high premarital fertility 

(≥50 percent). 

• Intermediate levels of age at first marriage (15-21 years) with a wide range of levels of premarital 

fertility. For instance, around age 18, premarital fertility ranges from virtually 0 to 40 percent or 

more. 

 This case highlights the importance of cultural factors that are not explained by the 

socioeconomic variables examined in this study, and which reveal the different norms regarding 

premarital fertility that are associated with the various ethnic groups. 

Figure 3.4 Relationship between prevalence of premarital fertility and 

median age at first marriage among 263 African ethnic groups 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

14 16 18 20 22 24 26 28 30 32

Median age at first marriage

% premarital women

3.6 Outliers from Demographic Variables 

Another way of showing how cultural factors shape the distribution of premarital fertility—beyond 

the effect of demographic factors—is looking at the outliers, groups that differ significantly from 

expected values based on median age at first marriage and median age at first intercourse. 

The negative outliers are groups with lower-than-expected premarital fertility, which indicates a 

more repressive attitude toward women who give birth before marriage. Groups differing by more than 10 

percent were found in several countries throughout Africa: many groups in Ghana (Akwapim, Asante, 

Ga-Adangbe, Fante, other Akan, Ewe, Guan, Mole-Dagbani, Grussi); several groups in southeastern 

Nigeria (Igbo, Ibibio, Annang, Ijaw, Urhobo) and the Yoruba; many groups in Malawi (Yao, Lomwe, 
14

Chewa, Sena, Anyanja); several groups in the Central African Republic (Yakoma-Sango, Mandjia, 

Banda, Zande-Nzakara, Gbaya); several groups in Benin (Yoa and Lokpa, Adja, Fon, Betamaribe, 

Yoruba); and two groups in Tanzania (Makonde, Sukuma). The average prevalence of premarital fertility 

for these groups was 11 percent, which is half of what was expected (22 percent) based on age at first 

marriage and age at first intercourse. 

The positive outliers are groups with higher-than-expected premarital fertility, which indicates a 

more permissive attitude toward women who give birth before marriage. Here again, groups differing by 

more than 10 percent were found throughout Africa: many groups in Liberia (Grebo, Vai, Krahn, 

Krou/Sapo, Gola, Bassa, Mano, Lorma); many groups in Gabon (Okande-Tsogho, Kota-Kele, NzabiDuma, Mbede-Teke, Shira-Punu/Vili, Fang); several groups in Tanzania (Pare, Ngoni, Iramba, Pogoro, 

Ndengereko); several groups in South Africa (Tsonga, Venda, Swazi), as well as in nearby Zimbabwe 

(Ndebele), Namibia (Caprivi/Lozi) and Southern Zambia (Mbunda, Bisa, Tonga); several groups in 

Cameroon (Boulou-Fang, other Adamaoua, Wimbum-Yamba, Bamoun, Gbaya); and small groups in 

southern Senegal (Diola, Manjaak/Mancagne/Balant). The average prevalence of premarital fertility for 

these groups was 43 percent, which is well above what was expected (30 percent) based on age at first 

marriage and age at first intercourse. 

4 Conclusions 

This study of the prevalence of premarital fertility by ethnicity shows wide variation throughout 

sub-Saharan Africa. A woman giving birth before marriage ranges from being a rare event to being 

almost universal. Such a broad range of behavior is unusual when compared with other demographic and 

social indicators. While problems of definition and sample size must be taken into consideration, the 

overall diversity of the results of this study are apparent from the data, and matches the diversity of 

behavior documented in the ethnographic literature. DHS surveys facilitate this kind of comparative 

analysis because they utilize consistent questions on age at first marriage, age at first intercourse, and age 

at first birth. 

The prevalence of premarital fertility has a structural component; it is bounded by the window of 

opportunity (for a birth to occur) between a woman’s first intercourse and her first marriage, assuming 

nonuse of contraception during this period. In the study, the correlation between age at marriage and 

premarital fertility was strong. Age at marriage, which varied widely among groups, was found to be the 

most important factor in premarital fertility. Age at first intercourse had varied less and had less impact on 

premarital fertility. However, age at first marriage and age at first intercourse do not explain everything. 

The study found that while attitudes and behaviors have considerable influence, contraceptive use has 

little impact. A number of ethnic groups were found to be particularly repressive in terms of premarital 

intercourse whereas others were generally permissive. These behaviors are ethnicity-specific even though 

other factors such as religion have an impact. 

Cultural change in the twentieth century has influenced patterns of premarital fertility in Africa. 

First, the spread of monotheistic religions has had a strong negative effect on premarital fertility. At the 

same time, increases in modern education and wage-based income have had a positive effect, with women 

delaying childbirth until after marriage. These contrasting forces explain to a large extent the higher levels 

of premarital fertility found in urban areas and in wealthier countries. The balance between positive and 

negative effects may explain the intermediate situation in some countries, while other countries have been 

more influenced by one set of factors than another. Here again, the variation within and between groups is 

substantial in sub-Saharan Africa, and modernization has further complicated an already diverse situation. 
15

This overview has several limitations. Above all, we regret the lack of details on ethnicity and its 

coding in many countries. However, now that a list of ethnic groups is available with standardized coding, 

we encourage the use of the list in demographic surveys. This will allow further analysis and, in some 

instances, the grouping of cases by language family or geographical proximity. Such activities promoting 

standardization would improve the quality of analyses. Some countries have chosen to ignore ethnicity in 

their demographic surveys for political reasons. However, failing to record this important information, 

which is needed for adequate program planning at national and regional levels, misses a valuable 

opportunity for analysis and deeper understanding of African societies. 

Ethnicity has long been neglected in demographic research, partly because of its complexity and 

its lack of standardization, but also because of lack of interest among those studying basic topics such as 

fertility and mortality. However, for topics such as nuptiality and migration, or the spread of HIV/AIDS, 

ethnicity may be one of the key factors in differentials by country or region. This study has shown the 

important effect of ethnicity on premarital fertility. The correlation of data on premarital fertility in subSaharan Africa by ethnic group has yielded new information that could not have been obtained using 

standard socioeconomic determinants alone. 
17

References 

Garenne, M. 2004. Age at marriage and modernization in sub-Saharan Africa. Southern African Journal 

of Demography 9(2):57-77. 

Garenne, M., and S. Hohmann. 2003. A wealth index to screen high risk families: Application to 

Morocco. Journal of Health, Population and Nutrition 21(3):235-242. 

Garenne, M., and J. Zwang. 2004. Social change and premarital fertility in Madagascar. Southern African 

Journal of Demography 9(1):27-48. 

Garenne, M., and J. Zwang, 2005. Premarital fertility in Namibia: Levels, trends and factors. Journal of 

Biosocial Science 37(1):1-23. 

Garenne, M., S. Tollman, and K. Kahn. 2000. Marital and premarital fertility in a rural area of South 

Africa: A challenge to existing population policy. Studies in Family Planning 31(1):47-54. 

Gordon, R.G., Jr. (ed.). 2005. Ethnologue: Languages of the world, Fifteenth edition. Dallas, Texas: SIL 

International. Available at http://www.ethnologue.com/. 

Grandidier, G. 1913. Le mariage à Madagascar. Bulletins et mémoires de la Société d'anthropologie de 

Paris, séance du 16 janvier 1913. 

Murdock, G.P. 1967. Ethnographic atlas: A summary. Ethnology 1:109-236. Pittsburgh: University of 

Pittsburgh Press. 

Radcliffe-Brown, A.R., and D. Forde. 1950. African systems of kinship and marriage. London: Routledge 

and Kegan. 

van de Walle, E. 1968. Marriage in African censuses and inquiries. In The demography of tropical Africa,

ed. W. Brass et al., 183-238. Princeton: Princeton University Press. 

Zwang, J. 2004. Perceptions and attitudes towards late marriage and premarital fertility in rural South 

Africa. Cahiers de l’IFAS, No. 4. Available at http://www.ifas.org.za 
Appendix 

Premarital Fertility and Ethnicity 

in Africa: 

Country Analysis
21

Overview of the Country Analysis 

This section presents estimates of premarital fertility by ethnicity for 25 countries in sub-Saharan 

Africa. A description of the methodology is presented in the main part of this report. The Appendix is 

organized by country with the data presented in the same format for each country: description of the 

available surveys, distribution of selected ethnic groups, and estimates of premarital fertility and its main 

correlates (median age at first marriage, percentage living in urban areas, and percentage that had sexual 

intercourse before marriage). 

A figure for each country illustrates the relationship between age at first marriage and premarital 

fertility, which is defined as the proportion of women who gave birth before marriage. Usually, the 

relationship is linear; that is, premarital fertility increases as age at marriage increases. However, in some 

countries the relationship is either absent (homogeneous countries) or complex (curvilinear relationship). 

A straight line is shown in each figure to guide the reader. 

The country analyses presented here are limited in scope. The aim was to explain how ethnic 

groups were selected for analysis and to describe the main relationships between premarital fertility, age 

at first marriage, and ethnicity, at the national level. All estimates were calculated using weighted samples 

(V005 in DHS files). 

Definitions 

Definitions for the indicators presented in Table 3 for each country are the following: 

Percent urban is the proportion of interviewed women living in urban areas. For some ethnic groups the 

percentage urban may differ from that cited in the national census. Because of the cluster sampling 

method used in DHS surveys, some clusters for selected ethnic groups can end up primarily in urban or 

rural areas. 

Median age at first marriage was obtained by selecting women age 25 and over and calculating for each 

cohort the age at which 50 percent of the women were ever married. This definition is different from life 

table estimates for median age at marriage. 

Percent never married is the proportion of women age 40-49 at the time of the survey who were never 

married. 

Percent premarital births is the proportion of births that occurred prior to the woman’s first marriage, 

dates being counted by month and year. 

Percent women with premarital birth is the proportion of women who had at least one premarital birth, 

among those who are either ever married or ever fertile. Never-married women who never had a live birth 

are excluded. 

Percent premarital intercourse is the proportion of women who had sexual intercourse prior to their 

first marriage, among those who ever had intercourse. 
22

BENIN 

Benin conducted one WFS survey in 1982 and two DHS surveys, in 1996 and 2001. The WFS 

survey code book did not provide the codes for ethnicity (V707), and it was not possible to recover the 

labels from the “language spoken at home” variable (S727), except for a few obvious cases. It was 

decided that only the data from the two DHS surveys would be used. The 1982 WFS survey included the 

42 official ethnic groups of Benin. The DHS surveys included only the eight main linguistic groups. 

These groups appear to have remained stable over the years and were also used in the census. 

Table 1 Sample size and main characteristics of surveys, Benin 

Benin WFS 

1982 

DHS 

1996 

DHS 

2001 

No. of women interviewed 4,018 5,491 6,219 

No. of ethnic categories, local 42 

No. of families of ethnic groups 8 8 

No. of ethnic categories, foreign 1 1 1 

Percent other and unknown 6.7 4.8 4.6 

The two DHS surveys were compatible, with coding of the ethnicity variable (V131) basically the 

same in both surveys (Table 2). There were, however, some minor differences, the most important being 

the higher proportion of Fon, the largest ethnic group in the country, in the second DHS survey, and a 

corresponding gap among the Bariba, Yoa and Lopka, Betamaribe, and Peulh. This pattern is related to 

the higher number of women who answered the questionnaire in Fon in the second survey (49.7 percent), 

compared with 1996 (35.3 percent) and 1982 (28.9 percent). 

 

Table 2 Distribution of ethnic groups by survey, Benin 

Difference 

between the two 

DHS surveys 

Ethnic group 

Census 

1992 

DHS 

1996 

DHS 

2001 P-value 

Significance 

Adja 15.6 14.6 15.1 0.438 

Bariba 8.6 9.5 8.2 0.014 * 

Dendi 2.8 2.5 2.7 0.548 

Fon 42.2 39.9 45.0 0.000 * 

Yoa and Lokpa 3.8 5.7 3.7 0.000 * 

Betamaribe 6.1 6.4 5.1 0.004 * 

Peulh 6.1 6.0 3.8 0.000 * 

Yoruba 12.1 10.7 11.9 0.042 * 

Other and unknown 2.7 4.8 4.6 0.642 

 

Total 100.0 100.0 100.0 7.37E-48 * 

*p <0.05 

It was decided that this minor difference between the two surveys would not seriously bias the 

estimates. In fact, it probably functioned to minimize differences between the Fon and the other groups 

because, increasingly, people in the other groups tended to assimilate themselves into the dominant group. 

In addition, the distribution of the population in the second DHS survey was similar to that of the 1992 

census, with some minor differences. The 1996 and 2001 DHS surveys were therefore combined for the 

final estimates. 
23

Premarital Fertility

 Premarital fertility is low in Benin compared with other African countries. The proportion of 

women with a premarital birth ranges from 4.9 percent among the Peulh to 13.6 percent among the 

Yoruba. The Yoruba are among the more urbanized groups and have a somewhat higher age at first 

marriage, whereas the Peulh are the least urbanized group and have a lower than average age at marriage. 

Overall, premarital fertility is low given the relatively high prevalence of premarital intercourse (55.0 

percent). 

Table 3 Premarital fertility and nuptiality indicators, Benin 

Ethnic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

 never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Adja 1,941 36.6 19.0 0.0 2.8 7.8 44.2 

Bariba 1,037 39.0 17.2 0.0 3.0 9.1 36.5 

Dendi 292 64.8 17.7 0.0 2.2 6.5 35.9 

Fon 4,761 40.5 18.8 0.7 3.4 9.2 58.2 

Yoa and Lokpa 590 30.2 18.1 0.8 1.6 5.6 31.9 

Betamaribe 751 28.1 16.8 1.7 4.3 9.8 37.2 

Peulh 589 14.9 17.5 0.0 1.8 4.9 20.1 

Yoruba 1,211 52.7 19.2 2.0 5.2 13.6 55.9 

Other and unknown 538 58.1 19.0 1.4 5.2 12.2 54.8 

 

Total 11,710 40.2 18.5 0.7 3.4 9.1 55.0 

Source: Authors’ calculations after merging data from 1996 and 2001 DHS surveys. 

 Correlation with age at marriage was low (ρ = 0.35). Figure 1 shows three groups: a group in the 

middle with expected values of medium age at marriage and low premarital fertility (Peulh, Dendi, Yoa 

and Lokpa); a group with low age at marriage and higher premarital fertility (Bariba, Betamaribe); and a 

group with higher age at marriage and higher premarital fertility (Yoruba, Fon, Adja). 

The correlation with urban residence was more straightforward, although it remained moderate 

(ρ = 0.40). The more urbanized groups also had higher premarital fertility. The only exception was the 

Dendi, who had lower than average premarital fertility despite the highest proportion of urban residence. 

 
24

Figure 1 Correlation between premarital fertility and age at first marriage, Benin % women with premarital birth

Betamaribe

Yoa & Lokpa Peulh

Yorouba

Adja

Fon

Dendi

Bariba

0

5

10

15

20

15 16 17 18 19 20

Median age at first marriage (years)
25

BURKINA FASO 

Burkina Faso conducted three DHS surveys, in 1993, 1996, and 2003. The second DHS survey 

included more ethnic groups (Bissa, Dafing, Dagara, Samo) than the first, although these disappeared in 

the last survey, with the exception of the Bissa. There are about 50 ethnolinguistic groups reported in 

Burkina Faso. Grouping them into 10 categories is a simplification, however the largest groups are well 

defined in the DHS surveys. 

Table 1 Sample size and main characteristics of DHS surveys, Burkina Faso 

Burkina Faso 

DHS 

1993 

DHS 

1996 

DHS 

2003 

No. of women interviewed 6,354 5,445 12,477 

No. of ethnic categories, local 9 13 10 

No. of ethnic categories, foreign 1 6 1 

Percent other and unknown 7.2 12.2 8.7 

Overall, the three DHS surveys were compatible with respect to ethnic distribution (Table 2), 

however there were several notable differences. The Dioula group almost disappeared in 1996 (0.5 

percent compared with 7.5 percent in 1993) then reappeared in the last survey (5.7 percent in 2003). 

According to census sources, however, Dioula speakers are assumed to make up about 9.3 percent of the 

population. 

 

Table 2 Distribution of ethnic groups by survey, Burkina Faso 

Difference between 

the first two 

DHS surveys 

Ethnic group 

DHS 

1993 

DHS 

1996 

DHS 

2003 P-value 

Significance 

Bobo 6.9 4.7 2.5 0.245 

Dioula 7.5 0.5 5.7 0.001 * 

Fulfude (Peulh) 5.3 6.5 6.3 0.561 

Gourmantche 4.2 8.2 6.9 0.056 

Gourounsi 5.8 5.3 3.4 0.796 

Lobi 4.4 1.3 5.2 0.016 * 

Mossi 56.1 58.8 56.5 0.519 

Senoufo 1.1 2.3 3.8 0.313 

Touareg 1.5 0.4 1.1 0.150 

Other and unknown 7.2 12.2 8.7 0.054 

 

Total 100.0 100.0 100.0 <E-99 * 

*p <0.05

The questions about ethnicity were the same in the three DHS surveys (Q117, Q119, and Q118 

respectively: Quelle est votre ethnie?). There was no evidence of a major bias in the sampling in 1999, 

and the provinces where Dioula are normally counted (Houet, Kadiago, Kenedougou, Kossi, Mouhoun, 

Sourou) were well represented in 1999, although somewhat less so than in 1993. Some of the Dioula 

could have been counted among the new categories in 1999, but these were not in the same provinces. It 

seems more likely that there was some confusion in 1999 between ethnic category, language of the 

interview, and language spoken at home, or some other unknown factor. Other smaller biases were 

identified in 1999; more people were counted as Gourmantche and fewer as Lobi. Other differences could 

be attributed to sample biases. 
26

Despite these small discrepancies, the three surveys were merged for the final analysis. It is likely 

that the Dioula category is underestimated. This might reduce the specificity of some of the other groups 

because some of the Dioula were probably merged with them. 

Premarital Fertility

 Premarital fertility in Burkina Faso is low compared with other African countries and marriage is 

virtually universal for women. The proportion of women with a premarital birth ranges from 2.6 percent 

among the Touareg to 12.4 percent among the Senoufo. 

Table 3 Premarital fertility and nuptiality indicators, Burkina Faso 

Ethnic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bobo 1,155 28.8 17.2 0.3 3.1 10.0 32.4 

Dioula 1,310 32.1 17.3 0.0 3.0 9.4 29.9 

Fulfulde (Peulh) 1,392 9.8 15.8 0.0 2.1 5.6 13.3 

Gourmantche 1,373 3.0 17.0 0.0 3.2 8.0 7.7 

Gourounsi 1,262 22.4 17.8 0.8 3.3 9.3 27.0 

Lobi 1,435 14.3 17.2 0.3 3.3 10.5 21.0 

Mossi 14,048 21.5 17.7 0.1 2.5 7.4 29.1 

Senoufo 922 28.8 16.8 0.0 4.3 12.4 34.3 

Touareg 243 3.4 15.1 0.0 1.1 2.6 5.5 

Bissa 758 17.1 17.8 0.0 2.9 8.3 20.0 

Other and unknown 1,378 22.9 17.4 0.0 3.9 10.6 30.8 

 

Total 25,276 20.1 17.4 0.1 2.8 8.1 26.1 

Source: Authors’ calculations after merging data from 1993, 1999, and 2003 DHS surveys. 

The main difference by ethnicity was between the pastoral groups (Fulfulde, Touareg) with low 

age at marriage, low urban residence, and low levels of premarital fertility, and the more urbanized 

groups (Dioula, Bobo, Senoufo) for whom the average age at first marriage is about 17 years. The 

Gourmantche and the Lobi had higher levels of premarital fertility than would be expected by their level 

of urban residence or age at marriage, whereas the Mossi and Gourounsi were well below the regression 

lines linking premarital fertility to urban residence or age at marriage. 

The correlation with urban residence was low (r = 0.26), as it is for the country in general. The 

correlation with age at first marriage was much higher (0.71), pointing up the gap of almost three years in 

median age at marriage between the Touareg and the Bissa (Figure 1). Differences in age at marriage are 

a major factor in the varying levels of premarital fertility in Burkina Faso. The main division is between 

the northern pastoral groups (Touareg, Peulh), which have very low age at first marriage, and all the other 

groups. 
27

Figure 1 Correlation between premarital fertility and age at first marriage, 

Burkina Faso 

Dioula

Peulh

Gourmantche

Bobo

Senoufo

Mossi

Gourounsi

Lobi

Touareg

Bissa

0

5

10

15

14 15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
28

CAMEROON 

Cameroon conducted one WFS survey in 1978 and three DHS surveys, in 1991, 1998, and 2004. 

Coding of ethnicity was very different in 1978 and not compatible with that of later DHS surveys. 

Ethnicity was not available in 1991. Coding of ethnicity was identical in the 1998 and 2004 surveys, 

therefore these two were combined for analysis. 

Table 1 Sample size and main characteristics of surveys, Cameroon 

Cameroon 

WFS 

1978 

DHS 

1991 

DHS 

1998 

DHS 

2004 

No. of women interviewed 8,219 3,871 5,501 10,656 

No. of ethnic categories, local 33 0 46 46 

No. of ethnic categories, foreign 1 1 1 1 

Percent other and unknown 4.8 0.2 1.4 3.9 

The 1998 and 2004 DHS surveys were largely compatible (Table 2). With the exception of the 

Bamileke, frequencies for ethnic groups were not significantly different in the two surveys. Because of 

the large number of ethnic groups in Cameroon—some 240 have been reported in the ethnographic 

literature—and the small sample size of some groups, only larger groups with at least 250 women were 

retained and merged according to regional residence. This resulted in 24 groups: 19 were well defined 

ethnically, 4 were regional groupings, and one comprised the category “other and unknown.” Because of 

the large sample size of the second survey and the merging of the two surveys, the differences in 

demographic behavior between groups were marked and most were significant. 

 

Table 2 Distribution of ethnic groups by survey, Cameroon 

Difference 

between the two 

DHS surveys 

V131 Ethnic group 

DHS 

1998 

DHS 

2004 P-value 

Significance 

1 Arabe Choa 0.9 0.9 0.965 

2 Peulh 4.5 5.6 0.479 

3 Haoussa 0.6 0.8 0.944 

4 Kanuri 0.3 1.0 0.690 

5 Bata 1.3 0.2 0.480 

6 Daba 0.1 0.7 0.678 

7 Guidar 1.2 1.3 0.919 

8 Kotoko 0.7 0.8 0.955 

9 Kwang/Kera 0.0 0.0 0.990 

10 Mafa 6.6 3.9 0.104 

11 Margui 1.0 0.3 0.657 

12 Massa 1.8 1.7 0.949 

14 Mousgoum 1.1 0.1 0.551 

15 Sara 0.9 0.6 0.872 

16 Wandala/Mandara 0.8 1.3 0.776 

17 Dourou 1.2 0.3 0.579 

18 Fali 2.6 1.2 0.400 

19 Gbaya 1.3 1.6 0.818 

21 Mambila 0.4 1.1 0.662 

22 Mboum 3.4 6.5 0.060 

23 Samba 0.1 0.2 0.948 

24 Banyang 1.2 0.8 0.820 

25 Bendi 0.1 0.1 0.997 

26 Efik-Korop 0.2 0.1 0.951 

27 Ejagham 0.1 0.2 0.960 

28 Mbembe 0.0 0.8 0.648 

29 Tiv 0.0 1.3 0.431 

 Continued... 
29

Table 2—Continued

Difference 

between the two 

DHS surveys 

V131 Ethnic group 

DHS 

1998 

DHS 

2004 P-value 

Significance 

30 Bebe 0.8 0.4 0.855 

31 Menchum 0.6 0.3 0.828 

32 Momo 3.0 2.0 0.542 

33 Ngemba 3.4 3.1 0.840 

34 Ring 4.3 3.4 0.572 

35 Wimbum-Yamba 1.8 1.6 0.894 

36 Bamoun 4.3 3.7 0.730 

37 Bamilike-Central 15.4 21.0 0.000 * 

38 Cotier 2.1 1.3 0.590 

39 Ngoe-Oroko 2.2 3.0 0.586 

40 Bafia 0.6 1.1 0.751 

41 Banen-Bandem 0.9 0.3 0.745 

42 Yambassa 1.4 1.1 0.828 

43 Bassa-Bakoko 4.7 4.8 0.962 

44 Beti 12.0 9.4 0.101 

45 Boulou-Fang 3.0 3.6 0.744 

46 Kako 1.1 0.8 0.834 

47 Meka 4.3 1.8 0.122 

48 Pygmee 0.5 0.1 0.809 

 Other and unknown 1.4 3.9 0.618 

 

 Total 100.0 100.0 

*p <0.05

The variation in demographic behavior by ethnicity is marked (Table 3). Age at first marriage 

ranged from 14.7 to 20.8 years; the proportion of women who had premarital intercourse was 4.8 to 79.2 

percent; the proportion of premarital births was 0.2 to 26.2 percent; and the proportion of women with a 

premarital birth was 1.0 to 49.1 percent. The diversity of behaviors associated with premarital fertility in 

Cameroon is almost as great as that of the entire African continent. 

Table 3 Premarital fertility and nuptiality indicators, Cameroon 

Ethnic group 

Number 

of women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

 never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Peulh 835 48.6 14.8 0.0 1.6 5.0 10.4 

Guidar 201 29.9 15.4 0.0 1.1 3.2 10.6 

Mafa 605 21.1 15.3 0.0 1.7 4.6 10.2 

Massa 215 29.9 15.1 0.0 0.9 2.5 11.0 

Other Northern 920 31.7 15.0 0.0 1.2 3.5 7.4 

Fali 233 15.1 14.7 0.0 0.2 1.0 4.8 

Gbaya 344 35.9 16.1 0.0 6.8 16.0 41.9 

Mboum 741 24.0 15.6 0.0 1.3 3.6 13.0 

Other Adamaoua 257 40.2 15.6 0.0 8.0 13.3 32.8 

Momo 332 36.5 18.2 0.0 10.7 27.6 61.7 

Ngemba 484 38.9 19.3 4.0 12.3 25.4 69.3 

Ring 511 39.7 19.3 8.8 15.4 32.6 64.5 

Wimbum/Yamba 244 30.9 18.3 15.8 15.5 30.2 59.1 

Other Western 516 46.5 17.9 0.0 13.6 29.1 61.9 

Bamoun 599 53.7 16.6 0.0 5.6 15.1 36.4 

Bamilike 3,275 75.4 18.8 1.3 7.0 16.4 58.4 

 Continued... 
30

Table 3—Continued 

Ethnic group 

Number 

of women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

 never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Cotier/Douala 284 73.1 20.8 2.9 19.8 37.2 76.9 

Ngoe-Oroko 491 40.7 19.1 3.5 17.4 34.4 68.0 

Bassa-Bakoko 899 67.8 19.9 1.4 18.7 38.4 75.2 

Beti 1,784 51.0 19.4 2.1 18.7 38.2 74.3 

Other Central Coast 466 58.3 19.7 7.4 17.7 34.4 67.4 

Boulou/Fang 733 44.3 20.3 0.0 26.2 49.1 79.2 

Meka 484 30.0 19.2 0.0 16.2 36.1 74.5 

Other South, East 219 24.6 17.1 0.0 8.6 19.5 59.3 

Other and unknown 485 52.7 16.5 0.0 5.6 14.8 39.0 

 

Total 16,157 48.1 17.8 1.4 8.9 20.4 48.3 

Source: Authors’ calculations after merging data from 1998 and 2004 DHS surveys. 

Correlations of the prevalence of premarital fertility with age at marriage (p = 0.942) and 

premarital sex (p = 0.955) were high, and the distribution of ethnic groups according to median age at 

marriage was basically linear (Figure 1). Correlation with urban residence was much lower (ρ = 0.488), 

and most of the differences could be attributed to differences in cultural patterns. 

Figure 1 Correlation between premarital fertility and age at first marriage, 

Cameroon

 

Guidar

Mafa Mboum

Massa

Other N

Fali

Peulh

Other Adamaoua

Gbaya Bamoun

Other S,E

Momo

Wimbum Yamba Other, WH

Bamileke

Beti

Bassa Bakoko

Cotier

Boulou Fang

Other W,C,C

Meka

Ngoe Oroko

Ngemba

Ring

0

10

20

30

40

50

14 15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
31

CENTRAL AFRICAN REPUBLIC 

The Central African Republic (CAR) conducted only one DHS survey, in 1994. Ethnicity was 

defined as the main language spoken at home (V131). The DHS survey coded nine ethnolinguistic group 

categories of African origin. 

Table 1 Sample size and main characteristics of DHS 

surveys, CAR 

CAR 

DHS 

1994 

No. of women interviewed 5,884 

No. of ethnic categories, African 9 

Percent other and unknown 2.1 

The distribution of ethnic groups is marked by two dominant groups (Gbaya, Banda) who account 

for more than half of the population, plus several groups common to Cameroon (Table 2). 

Table 2 Distribution of ethnic groups in survey, CAR 

Origin Ethnolinguistic group 

DHS 

1994 

African Hausa/Haoussa 4.9 

 Sara 6.1 

 Mboum 6.9 

 Gbaya 28.4 

 Mandjia 8.7 

 Banda 27.4 

 Ngbaka-Bantou 6.6 

 Yakoma-Sango 5.7 

 Zande-Nzakara 3.2 

Other Other and unknown 2.1 

 

Total 100.0 

Premarital Fertility by Ethnicity 

CAR has a medium age at first marriage (17.2 years), a low proportion of women who never 

marry (1.8 percent), and a moderate level of premarital fertility (5.9 percent for all births, 11.1 percent for 

women). Differentials in premarital fertility by ethnicity vary from 3.4 to 8.0 percent for all births, and 

from 6.6 to 16.8 percent for women. 

Correlation was negative with urban residence (-0.815), but positive with age at first marriage 

(+0.847). As in Cameroon, the relationship between age at marriage and the proportion of women with a 

premarital birth was straightforward, with the exception of the Hausa (Figure 1). However, premarital 

fertility and age at marriage were higher for the Mboum and Gbaya in CAR compared with their 

counterparts in Cameroon. 
32

 

Table 3 Premarital fertility and nuptiality indicators, CAR 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Hausa 290 60.1 15.6 0.0 3.4 6.6 26.8 

Sara 361 40.5 18.0 4.4 7.7 14.9 47.8 

Mboum 405 27.7 18.0 0.0 7.9 16.8 51.7 

Gbaya 1,673 35.5 17.3 3.1 7.2 13.4 53.7 

Mandjia 513 49.5 17.6 1.0 6.9 12.2 49.1 

Banda 1,610 40.8 17.0 1.5 4.1 8.3 44.6 

Ngbaka-Bantou 389 50.8 17.0 0.0 4.1 8.9 47.3 

Yakoma-Sango 335 64.3 17.1 0.0 4.4 8.0 42.0 

Zande-Nzakara 191 44.0 17.3 6.4 8.0 12.7 47.3 

Other and unknown 117 57.6 17.5 0.0 3.5 4.7 34.1 

 

Total 5,884 42.6 17.2 1.8 5.9 11.1 47.5 

Source: Authors’ calculations from 1994 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, 

Central African Republic 

Mboum

Sara

Mandjia

Zande Nzakara

Gbaya

Yakoma Sango

Ngbaka Bantou

Banda

Hausa

0

2

4

6

8

10

12

14

16

18

15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
33

CHAD 

Chad conducted only one DHS survey, in 1997. Ethnicity was defined as the main language 

spoken at home (V131). The DHS survey coded 12 ethnolinguistic group categories of African origin. 

Table 1 Sample size and main characteristics of DHS 

survey, Chad 

Chad 

DHS 

1997 

No. of women interviewed 7,454 

No. of ethnic categories, African 12 

Percent other and unknown 2.1 

 All groups were kept for final analysis, after grouping “other and unknown” (Table 2). 

Table 2 Distribution of ethnic groups in DHS survey, Chad 

Origin Ethnolinguistic group 

DHS 

1997 

African Gorane 5.2 

 Arab 10.4 

 Ouaddai 12.1 

 Baguirmien 1.5 

 Kanem-Bornou 9.5 

 Fitri-Batha 6.0 

 Hadjarai 5.4 

 Lac Iro 1.0 

 Sara 29.1 

 Tandjile 6.0 

 Peulh 1.9 

 Kebbi 9.7 

Others Other and unknown 2.1 

 

 Total 100.0 

Premarital Fertility by Ethnicity

Chad is a relatively homogenous country with a low age at first marriage (15.8 years), a low 

proportion of women who never marry (<0.1 percent), and a low level of premarital fertility (0.8 percent 

for all births, 2.4 percent for women). Differentials in premarital fertility by ethnicity do not vary much 

(from 0.1 to 1.7 percent for all births, and from 0.2 to 4.7 percent for women). The prevalence of 

premarital intercourse was somewhat higher (17.2 percent), though still low by African standards. 

Correlation of premarital fertility with age at first marriage was low (ρ = +0.197), and correlation with 

urban residence was negative (ρ = -0.431). 
34

Table 3 Premarital fertility and nuptiality indicators, Chad 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Gorane 453 41.4 15.8 0.0 0.3 0.9 12.7 

Arab 831 29.6 15.2 0.0 0.4 0.8 12.6 

Ouaddai 819 14.2 16.0 0.0 1.6 4.7 18.9 

Baguirmien 131 37.0 16.3 0.0 0.2 0.6 17.4 

Kanem-Bornou 698 20.4 15.0 0.0 0.1 0.2 6.7 

Fitri-Batha 455 22.7 16.3 0.0 0.6 1.3 15.3 

Hadjarai 433 29.3 15.3 0.0 0.5 2.0 19.0 

Lac Iro 66 11.4 15.1 0.0 1.7 4.7 42.1 

Sara 2,180 24.1 16.3 0.0 1.3 4.3 24.2 

Tandjile 416 16.4 15.5 0.0 0.5 1.9 18.5 

Peulh 142 25.1 14.8 0.0 0.2 1.0 12.5 

Kebbi 641 11.7 15.8 0.0 0.1 0.4 11.4 

Other and unknown 189 43.9 15.2 2.7 0.9 2.0 14.1 

 

Total 7,454 23.1 15.8 0.1 0.8 2.4 17.2 

Source: Authors’ calculations from 1997 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Chad 

Lac Iro Ouaddai

Sara

Hadjarai

Tandjile

Fitri Batha

Barguimien

Gorane Arab

Kanem Bornou Kebbi

Peulh

0

2

4

6

8

10

14 15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
35

CÔTE D’IVOIRE

Côte d’Ivoire conducted a WFS survey in 1980 and two DHS surveys in 1994 and 1999 (Table 1). 

The WFS survey included 16 ethnic groups and five larger language families. The 1994 DHS survey 

included 50 detailed ethnic groups plus many categories for foreigners by country of origin. 

Unfortunately, labels for these 50 detailed ethnic groups were not provided in the codebook, rendering 

them unusable. The 1999 survey, which was based on a small sample, provided only the five larger 

language families, which, fortunately, happened to be the same as in the 1980 survey. We therefore 

combined the 1980 and the 1999 surveys for final analysis. Côte d’Ivoire being a country of in-migration, 

the proportion of foreigners was high. 

Table 1 Sample size and main characteristics of surveys, Côte d’Ivoire 

Côte d’Ivoire 

WFS 

1980 

DHS 

1994 

DHS 

1999 

No. of women interviewed 5,764 8,099 3,040 

No. of ethnic categories, local 16 50 -- 

No. of ethnic categories, foreign 1 13 1 

Large ethnolinguistic families 5 -- 5 

Percent foreigner 24.4 22.2 22.2 

Percent other and unknown 0.3 0.2 0 

Differences in the distribution of large ethnolinguistic families between the two surveys were 

minor, though three of them were statistically significant (Table 2). However, these minor differences 

could not impact the final estimates based on the combined data sets. 

Table 2 Distribution of ethnic groups by survey, Côte d’Ivoire 

Difference between 

the two surveys 

Ethnic group 

WFS 

1980 

DHS 

1999 P-value 

Significance 

Akan 29.1 29.8 0.495 

Krou 13.3 11.0 0.002 * 

Mande North 12.0 12.1 0.932 

Mande South 9.7 10.3 0.395 

Voltaic 11.1 14.6 0.000 * 

Other and unknown 24.8 22.2 0.008 * 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

In Côte d’Ivoire, the level of urban residence is average, and age at marriage is medium, around 

17.7 years. However, premarital fertility varies markedly, between 5.0 and 18.7 percent for all births and 

between 14.6 and 40.5 percent for women. A majority of first sexual encounters are premarital, ranging 

from 48.2 to 80.1 percent by ethnic group. Correlation of premarital fertility with urban residence was 

small (0.295), but was much higher with age at first marriage (0.856). However, most of the correlation 

was due to the special situation of the Akan group, which has much higher age at marriage and higher 

premarital fertility than the other groups (Figure 1). 
36

Table 3 Premarital fertility and nuptiality indicators, Côte d’Ivoire 

Ethnolinguistic group 

(large family) 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Akan 2,626 45.6 18.8 0.5 18.7 40.5 79.6 

Krou 1,123 50.7 17.2 0.9 10.9 28.3 80.1 

Mande North 1,095 49.5 17.0 0.0 5.0 14.6 46.9 

Mande South 811 24.0 17.2 0.0 8.1 21.9 68.0 

Voltaic 1,029 30.3 17.4 0.0 6.0 17.5 48.2 

Other and unknown 2,120 44.5 17.3 1.0 4.9 11.8 39.1 

 

Total 8,804 41.9 17.7 0.5 10.2 23.9 61.1 

Source: Authors’ calculations after merging data from 1980 and 1999 surveys. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, 

Côte d’Ivoire 

Akan

Krou

Mande, North

Mande, South

Voltaic

0

10

20

30

40

50

15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
37

ETHIOPIA 

Ethiopia conducted a single DHS survey in 2000 (Table 1). The survey included 50 ethnic groups 

(V131), with virtually no unknowns, which covers a large proportion of the 79 languages ever recorded in 

the country. Unfortunately, the labels of the ethnic groups were not provided in the DHS codebook. 

Table 1 Sample size and main characteristics of 

DHS survey, Ethiopia 

Ethiopia 

DHS 

2000 

No. of women interviewed 15,367 

No. of ethnic categories, local 50 

Language of respondent 8 

Percent other and unknown 0.1 

However, the language of the respondent was recorded (SRESP), and could be matched with the 

ethnic group variable, which allowed the identification of main ethnic groups. The final list therefore 

included 12 ethnic groups, which accounted for some 90 percent of the population (Table 2). 

 

Table 2 Distribution of ethnic 

groups in survey, Ethiopia 

Ethnic group 

DHS 

2000 

Amara 31.8 

Oromo 34.6 

Tigraway 6.7 

Somali 1.2 

Gedeo 5.4 

Afar 0.8 

Anuak 0.1 

Sidama 3.9 

Weleyta 2.2 

Hadayya 0.2 

Gurage 1.8 

Kafa 1.4 

Other and unknown 10.0 

 

Total 100.0 

Premarital Fertility by Ethnicity

 Premarital fertility is low in Ethiopia, with a prevalence of 0.9 percent for all births and 2.7 

percent for women (Table 3). This is because of a variety of factors, including low median age at first 

marriage (16.1 years), low prevalence of premarital intercourse (10.9 percent), and low urban residence 

(18.2 percent). 
38

Table 3 Premarital fertility and nuptiality indicators, Ethiopia 

Ethnolinguistic group 

(large family) 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Amara 4,431 26.0 14.9 0.1 1.2 3.8 16.9 

Oromo 4,161 13.3 16.3 0.4 0.9 2.4 6.3 

Tigraway 1,483 29.5 15.6 1.0 1.0 3.2 20.0 

Somali 785 28.9 17.3 0.0 0.5 1.3 1.6 

Gedeo 862 26.1 18.3 0.2 1.1 2.9 9.3 

Afar 585 6.4 15.7 0.0 1.6 2.8 2.3 

Anuak 363 20.0 15.8 0.0 3.2 8.7 23.8 

Sidama 355 0.7 16.6 0.0 0.1 0.3 5.3 

Weleyta 230 13.4 16.8 0.0 0.8 2.6 5.9 

Hadayya 211 13.8 16.1 0.0 0.8 2.4 9.6 

Gurage 209 15.3 19.0 0.0 0.2 1.0 5.8 

Kafa 207 7.3 17.2 0.0 0.5 2.2 13.4 

Other and unknown 1,485 7.7 17.3 0.0 0.3 1.0 5.3 

 

Total 15,367 18.2 16.1 0.2 0.9 2.7 10.9 

Source: Authors’ calculations from 2000 DHS survey. 

Differences between ethnic groups were small given the low level of premarital fertility. In 

virtually all groups, premarital fertility was very low (<4 percent). The exception was the Anuak, a small 

group living in the marshland area of Gambela province. The province has a marginal position in the 

country and has recently been subject to discrimination and violence. The Anuak had somewhat higher 

premarital fertility despite low age at marriage (15.8 years). This is probably because of the higher 

prevalence of premarital intercourse (23.8 percent versus 10.9 percent for the country as a whole). 

 Correlation with age at first marriage was slightly negative (ρ = -0.339), which is unusual and is 

found in only a few countries. Correlation with urban residence was virtually nil (ρ = -0.067). 

 
39

Figure 1 Correlation between premarital fertility and age at first marriage, 

Ethiopia 

Anuak

Amara

Afar

Tigraway

Sidama

Weleyta

Somali

Gurage

Gedeo

Hadayya Oromo

Kafa

0

2

4

6

8

10

14 15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
40

GABON 

Gabon conducted only one DHS survey, in 2000. Ethnicity was defined as the main language 

spoken at home (V131). The DHS survey coded eight ethnolinguistic group categories of African origin. 

The large proportion of other and unknown is due to a large group of foreigners (17.9 percent of the 

sample). 

Table 1 Sample size and main characteristics 

of DHS survey, Gabon 

Gabon 

DHS 

2000 

No. of women interviewed 6,183 

No. of ethnic categories, African 8 

Percent other and unknown 19.6 

Although the ethnic groups were of unequal size, seven of them were large enough to be counted 

(Table 2). The Pygmy group was too small to be analyzed separately, and was merged with the “other and 

unknown” category in the final analysis. 

Table 2 Distribution of ethnic groups in survey, Gabon 

Origin Ethnolinguistic group 

DHS 

2000 

African Fang 25.2 

 Kota-Kele 6.5 

 Mbede-Teke 8.3 

 Myene 4.7 

 Nzabi-Duma 10.6 

 Okande-Tsogho 2.9 

 Shira-Punu/Vili 22.2 

 Pygmy 0.1 

Foreign 17.9 

 Other and unknown 1.7 

 

 Total 100.0 

Premarital Fertility by Ethnicity

 Gabon has a high level of urban residence, high age at first marriage, and high level of premarital 

fertility, with little variation by ethnic group. Differentials in premarital fertility by ethnicity vary from 

17.6 to 37.9 percent for all births, and from 41.0 to 55.2 percent for women. Although urban residence 

was high for all groups, the more urbanized groups had higher premarital fertility, with a positive 

correlation of 0.682. Age at first marriage is universally high, with a positive correlation of 0.735. A large 

majority of first intercourse is premarital (74.0), with minor differences by ethnic group. 
41

Table 3 Premarital fertility and nuptiality indicators, Gabon 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Fang 1,372 82.9 19.8 3.6 31.0 54.1 78.6 

Kota-Kele 491 60.3 19.1 3.9 27.6 53.0 78.9 

Mbede-Teke 642 82.1 19.3 5.9 30.2 51.8 78.4 

Myene 190 96.9 23.9 4.2 37.9 55.2 80.1 

Nzabi-Duma 783 74.5 18.2 0.0 21.7 42.4 73.0 

Okande-Tsogho 266 43.4 17.2 0.0 17.6 41.0 66.2 

Shira-Punu/Vili 1,428 78.7 19.3 3.4 26.8 51.1 74.9 

Other and unknown 1,011 88.6 20.3 2.7 19.6 30.3 64.2 

 

Total 6,183 80.2 19.6 3.1 26.4 46.7 74.0 

Source: Authors’ calculations from 2000 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Gabon 

Myene Fang

Kota Kele

Shira Punu Vili

Mbede Teke

Nzabi Duma

Okande Tsogho

0

10

20

30

40

50

60

15 16 17 18 19 20 21 22 23 24 25

Median age at first marriage (years)

% women with premarital birth
42

GHANA 

Ghana conducted one WFS survey in 1979 and four DHS surveys, in 1988, 1993, 1999 and 2003 

(Table 1). The WFS survey and the 1988 DHS survey each coded the same 7 ethnic groups; the 1993 

DHS survey coded 11 groups; the 1999 DHS survey coded 12 groups, 11 of which were identical to the 

previous survey; and the 2003 DHS survey coded 8 groups. The proportion of “other and unknown” was 

lowest in 1993 and 1999, due to the more detailed categories. 

Table 1 Sample size and main characteristics of surveys, Ghana 

Ghana 

WFS 

1979 

DHS 

1988 

DHS 

1993 

DHS 

1999 

DHS 

2003 

No. of women interviewed 6,125 4,488 4,562 4,843 5,691 

No. of ethnic categories, African 7 7 11 11 8 

Percent other and unknown 10.1 8.9 3.2 2.1 6.5 

For final analysis, the 1993 and the 1999 DHS surveys were combined since they offered the 

greatest number of groups and the smallest number of “other and unknown.” Overall, the distribution of 

ethnic groups was similar in the two surveys, though not identical (Table 2). 

 

Table 2 Distribution of ethnic groups by survey, Ghana 

Difference between 

the two DHS surveys 

Ethnic group 

DHS 

1993 

DHS 

1999 P-value 

Significance 

Asante 16.2 15.9 0.676 

Akwapim 3.2 4.1 0.025 * 

Fante 12.1 14.1 0.004 * 

Other Akan 18.1 19.5 0.083 

Ga-Adangbe 8.0 8.3 0.606 

Ewe 14.9 15.8 0.207 

Guan 2.2 1.5 0.015 * 

Mole-Dagbani 15.6 6.8 0.000 * 

Grussi 3.5 2.5 0.003 * 

Gruma 2.3 5.4 0.000 * 

Hausa/Haoussa 0.7 1.4 0.001 * 

Dagarti 2.5 na na 

Other and unknown 3.2 2.1 na na 

Total 100.0 100.0 9.0E-115 * 

*p <0.05

na = Not applicable

The Mole Dagbani group was lower in the second survey, partly because a new group emerged 

(Dagarti), with which it was probably combined in 1993. For final analysis, the Hausa group was dropped 

because it was too small (less than 100 women in the two surveys combined), but the Dagarti group was 

kept, because it was large enough, and had the lowest premarital fertility. 
43

Premarital Fertility by Ethnicity

 Premarital fertility in Ghana is low by African standards, with a prevalence of 4.0 percent for all 

births and 9.4 percent for women. This is despite a medium age at first marriage (18.9 years) and a high 

prevalence of premarital intercourse (57.4 percent) (Table 3). 

 

Table 3 Premarital fertility and nuptiality indicators, Ghana 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Asante 1,412 39.8 18.6 0.0 4.7 10.1 60.2 

Akwapim 319 46.0 20.3 0.0 6.9 14.2 66.5 

Fante 1,127 48.8 19.2 0.0 4.7 10.7 61.0 

Other Akan 1,650 33.7 18.7 0.8 5.7 12.7 65.5 

Ga-Adangbe 708 60.5 19.5 3.6 4.9 10.6 67.0 

Ewe 1,325 33.6 19.3 0.0 3.6 8.4 65.0 

Guan 170 34.5 18.8 0.0 3.5 9.2 51.3 

Mole-Dagbani 1,220 21.3 18.5 0.0 1.6 4.5 33.6 

Grussi 363 20.9 18.6 0.0 1.9 5.7 43.4 

Gruma 480 12.2 18.7 0.0 1.8 5.3 38.4 

Dagarti 288 15.3 18.6 0.0 1.0 3.4 23.3 

Other and unknown 343 42.5 18.6 0.0 3.1 7.4 51.8 

 

Total 9,405 36.8 18.9 0.4 4.0 9.4 57.4 

Source: Authors’ calculations after merging data from 1993 and 1999 DHS surveys. 

 

Differentials in premarital fertility by ethnicity were moderate, ranging from 3.4 percent (Dagarti) 

to 14.2 percent (Akwapim). Correlation with age at first marriage was high (0.669); the prevalence of 

premarital intercourse was high (0.911); and correlation with urban residence was high (0.795). The 

ethnic groups in northern Ghana (Mole-Dagbani, Grussi, Gruma, Dagarti) had lower age at marriage, 

lower prevalence of premarital intercourse, lower premarital fertility, and lower urban residence compared with those in the south. The Akwapim stand out with the highest level of premarital fertility and the 

highest age at marriage. They also have high prevalence of premarital intercourse, although they are not 

the most urbanized ethnic group. 
44

Figure 1 Correlation between premarital fertility and age at first marriage, Ghana 

Akwapim

Other Akan

Fante Ga-Adangbe

Ewe

Asante

Guan

Gruma Grussi

Dagarti

Mole-Dagbani

0

10

20

17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
45

GUINEA 

Guinea conducted two DHS surveys, in 1992 and 1999. However, access to the 1992 survey was 

restricted. In 1999, ethnicity was defined as the main language spoken at home (V131). The DHS survey 

coded six ethnolinguistic group categories of African origin (Table 1). 

Table 1 Sample size and main characteristics of DHS surveys, Guinea 

Guinea DHS 

1992 

DHS 

1999 

No. of women interviewed 6,065 7,143 

No. of ethnic categories, African na 6 

Percent other and unknown na 1.6 

na = Not applicable 

Three groups were dominant in the country: the Peulh, the Soussou and the Malinke. The other 

three were much smaller, although they still had enough cases of women interviewed to be analyzed 

separately (Table 2). 

Table 2 Distribution of ethnic groups in survey, Guinea 

Origin Ethnolinguistic group 

DHS 

1999 

African Sousou 19.8 

 Peulh 35.9 

 Malinke 27.8 

 Kissi 5.0 

 Toma 2.6 

 Guerze 7.3 

Other Other and unknown 1.6 

 

 Total 100.0 

Premarital Fertility by Ethnicity

Guinea has a low median age at first marriage (16.4 years), a low proportion of women who never 

marry (0.1 percent), and a low level of premarital fertility (3.3 percent for all births, 8.1 percent for 

women). Differentials in premarital fertility by ethnicity vary from 1.3 to 7.2 percent for all births, and 

from 4.3 to 18.1 percent for women. The prevalence of premarital intercourse is low, varying from 12 to 

37 percent. The only group that stands out is the Soussou, which have the highest level of urban 

residence. Correlation of premarital fertility with urban residence is high (0.871), whereas correlation 

with age at marriage is low. This is because the Soussou marry at about the same age as other groups 

(Malinke, Guerze) that have much lower premarital fertility. 
46

Table 3 Premarital fertility and nuptiality indicators, Guinea 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Sousou 1,389 50.4 17.1 0.0 7.2 18.1 37.1 

Peulh 2,222 25.2 15.8 0.0 2.4 5.6 11.7 

Malinke 1,985 34.2 16.8 0.3 2.5 6.2 24.8 

Kissi 353 21.8 15.6 0.0 2.9 6.4 22.1 

Toma 180 8.0 15.8 0.0 1.3 4.3 23.9 

Guerze 511 19.9 17.1 0.0 1.8 4.5 37.9 

Other and unknown 113 53.3 16.3 0.0 4.1 11.0 36.4 

 

Total 6,753 32.2 16.4 0.1 3.3 8.1 23.5 

Source: Authors’ calculations from 1999 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Guinea 

Soussou

Guerze

Malinke

Toma

Kissi

Peulh

0

10

20

14 15 16 17 18 19

Median age at first marriage (years)

% women with premarital birth
47

KENYA 

Kenya has a great wealth of high-quality demographic data: a WFS survey in 1978 and four DHS 

surveys, in 1988, 1993, 1998, and 2003, all of about the same sample size (Table 1). The WFS survey 

contained more details on ethnic groups with 42 distinct categories, but did not include what became one 

of the leading groups later on, the Kalenjin. However, the other categories were compatible with those of 

the DHS surveys. 

 

Table 1 Sample size and main characteristics of surveys, Kenya 

Kenya 

WFS 

1978 

DHS 

1988 

DHS 

1993 

DHS 

1998 

DHS 

2003 

No. of women interviewed 8,093 7,150 7,540 7,881 8,195 

No. of ethnic categories, African 42 9 10 11 14 

Percent other and unknown 1.0 6.7 4.8 2.9 1.4 

The four DHS surveys were quite compatible, with basically the same groups. We chose to 

combine the last three surveys (1993, 1998, and 2003), because this provided the opportunity to include 

three small but important groups: the Masai, the Somali, and the Taita/Taveta. The Masai and the 

Taita/Taveta were not detailed in the 1988 survey. Cumulating the three surveys gave more than 250 

women for these small groups. Note that the Masai were not detailed in 1993, but were in a large enough 

number in the last two surveys combined. 

Table 2 Distribution of ethnic groups by survey, Kenya 

Origin Ethnolinguistic group 

DHS 

1993 

DHS 

1998 

DHS 

2003 

African Kalenjin 11.7 12.6 10.1 

 Kamba 13.5 12.8 11.4 

 Kikuyu 20.6 17.9 23.0 

 Kisii 7.2 10.9 5.7 

 Luhya 16.1 14.5 15.0 

 Luo 11.4 13.6 12.0 

 Masai na 1.4 2.3 

 Meru/Embu 6.9 7.2 7.2 

 Mijikenda/Swahili 6.5 5.0 5.0 

 Somali 0.3 0.2 3.6 

 Taita/Taveta 1.1 1.0 1.2 

Other Other and unknown 4.8 2.9 3.4 

 

 Total 100.0 100.0 100.0 

na = Not applicable 

 

The consistency of ethnicity data was remarkable, and most likely the five surveys could have 

been combined if necessary (Table 2). Ethnicity was defined as the main language spoken at home 

(V131). The distribution of women 15-49 by main ethnolinguistic groups was similar in the three selected 

surveys. Only a few differences were statistically significant, but without consequence. Kalenjin and Kisii 

were somewhat over-represented and Kikuyu somewhat underrepresented in 1998, while none of the 

other groups were significantly different from the average in 1993 and 2003. 
48

Premarital Fertility by Ethnicity

Kenya is a country with relatively high age at first marriage (19.1 years), a low proportion of 

women who never marry (2.7 percent), and a high level of premarital fertility (11.2 percent for all births, 

30.7 percent for women). Differentials in premarital fertility by ethnicity were marked for all births (2.3 

to 16.6 percent), and for women (7.7 to 40.5 percent). The prevalence of premarital intercourse was high 

(65.7 percent), with marked differences among the ethnic groups, from 6.7 percent to 77.8 percent. 

Table 3 Premarital fertility and nuptiality indicators, Kenya 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Kalenjin 3,055 5.6 18.5 2.0 11.1 29.5 54.3 

Kamba 2,402 20.9 19.7 2.4 15.0 40.5 77.8 

Kikuyu 4,738 30.7 20.8 6.3 16.6 38.1 73.6 

Kisii 1,648 11.6 18.8 1.3 10.7 32.9 67.7 

Luhya 3,498 21.9 18.9 1.1 9.0 28.1 66.1 

Luo 2,745 29.8 17.2 0.3 8.6 27.9 74.9 

Masai 232 4.0 16.9 0.8 4.0 12.1 53.3 

Meru/Embu 1,428 13.7 20.6 3.9 14.3 36.3 75.3 

Mijikenda/Swahili 1,726 27.7 17.0 2.1 4.9 10.6 25.3 

Somali 638 38.0 18.2 1.3 2.3 7.7 6.7 

Taita/Taveta 702 30.0 20.3 8.8 9.0 22.9 51.8 

Other and unknown 804 33.7 19.2 0.1 6.1 15.0 47.7 

 

Total 23,616 22.1 19.1 2.7 11.2 30.7 65.7 

Source: Authors’ calculations after merging data from 1993, 1998, and 2003 DHS surveys. 

 

Surprisingly, correlation of premarital fertility with urban residence was not significant, and even 

somewhat negative (-0.209), whereas correlation with age at first marriage was positive (0.692), a value 

comparable with other countries. Note that Kenya is primarily rural (78 percent in the samples). 
49

Figure 1 Correlation between premarital fertility and age at first marriage, Kenya 

Meru Embu

Kikuyu

Kamba

Kisii

Luhya

Kalenjin Luo

Masai

Mijikenda Swahili

Taita Taveta

Somali

0

10

20

30

40

50

16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
50

LIBERIA 

Liberia has conducted only one DHS survey, in 1986, with details on 16 ethnic groups and using 

a reasonable sample size (Table 1). Liberia is one of the rare African countries in which high premarital 

fertility has been documented, the highest in West Africa. We therefore pushed our analysis to its limits, 

including some ethnic groups with less than 250 women. 

Table 1 Sample size and main characteristics of 

DHS survey, Liberia 

Liberia 

DHS 

1986 

No. of women interviewed 5,239 

No. of ethnic categories, African 16 

Percent other and unknown 4.3 

Among the small groups, all were kept except the Belle (14 women), the Dey (23 women), and 

the Mande (35 women). 

Table 2 Distribution of ethnic groups in survey, Liberia 

Origin Ethnolinguistic group 

DHS 

1986 

African Bassa 12.7 

 Gbandi 2.8 

 Gio 7.7 

 Gola 4.6 

 Grebo 7.3 

 Kissi 3.6 

 Kpelle 16.3 

 Krahn 4.2 

 Krou/Sapo 10.6 

 Lorma 6.0 

 Mandingue 6.1 

 Mano 7.9 

 Vai 3.8 

Other Other and unknown 6.6 

 

 Total 100.0 

 

Premarital Fertility by Ethnicity

Liberia has a medium age at first marriage (17.2 years), a low proportion of women who never 

marry (1.1 percent), and a high level of premarital fertility (13.0 percent for all births, 29.6 percent for 

women). Differentials in premarital fertility by ethnicity were small, from 8.0 to 16.8 percent for all 

births, and from 14.6 to 41.1 percent for women. The prevalence of premarital intercourse was high (68.4 

percent on average, ranging from 53.1 to 77.9 percent), with only minor differences among ethnic groups. 
51

Table 3 Premarital fertility and nuptiality indicators, Liberia 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bassa 490 43.4 17.0 1.5 14.1 28.4 65.8 

Gbandi 109 19.4 18.3 0.0 11.9 23.5 65.8 

Gio 294 26.5 15.9 0.0 11.7 24.6 60.0 

Gola 177 36.7 16.4 0.0 11.2 29.0 68.2 

Grebo 570 51.7 16.8 0.0 15.4 41.0 71.7 

Kissi 137 55.8 18.0 0.0 12.3 28.3 68.5 

Kpelle 661 31.4 18.3 2.4 12.6 31.9 77.9 

Krahn 521 34.4 16.7 1.8 13.3 32.4 67.9 

Krou/Sapo 1,039 60.1 17.7 3.0 16.8 41.1 76.6 

Lorma 230 50.6 17.4 0.0 12.6 30.6 73.6 

Mandingue 262 60.1 16.9 0.0 8.0 14.6 53.1 

Mano 301 15.3 15.3 0.0 8.1 19.8 55.3 

Vai 145 53.2 15.9 0.0 12.9 29.7 70.6 

Other and unknown 303 73.6 18.9 0.0 16.0 30.8 68.2 

 

Total 5,239 43.2 17.2 1.1 13.0 29.6 68.4 

Source: Authors’ calculations from 1986 DHS survey. 

 

Correlation of premarital fertility with urban residence was small but positive, (p = +0.343), as 

was the correlation with age at first marriage (p = +0.252). Both values are much lower than those of 

other countries. Note that overall, Liberia is almost half urban (43.2 percent in the samples). 

 Two groups stand out with higher than expected premarital fertility: the Grebo and the 

Krou/Sapo. Urban residence is also higher for these groups. In contrast, two groups stand out with lower 

than expected premarital fertility: the Mandingue (Mandinka), who are primarily urban, and the Mano, 

who are primarily rural. 
52

Figure 1 Correlation between premarital fertility and age at first marriage, Liberia 

Bassa

Krahn Lorma

Gola Kissi Vai

Gio

Mano

Mandingue

Gbandi

Kpelle

Grebo Krou Sapo

0

10

20

30

40

50

14 15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
53

MALAWI 

 Malawi has conducted two DHS surveys, in 1992 and 2000. The first survey did not provide 

ethnicity, but the second provided nine ethnic groups with a large sample size (Table 1). 

Table 1 Sample size and main characteristics of DHS surveys, Malawi 

Malawi 

DHS 

1992 

DHS 

2000 

No. of women interviewed 4,849 13,220 

No. of ethnic categories, African 0 9 

Percent other and unknown - 2.7 

Since the sample size was large enough in the 2000 survey, all ethnic groups were kept for final 

analysis (Table 2). 

Table 2 Distribution of ethnic groups in survey, Malawi 

Origin Ethnolinguistic group 

DHS 

2000 

African Chewa 32.3 

 Tumbuka 7.9 

 Lomwe 18.2 

 Tonga 1.8 

 Yao 13.8 

 Sena 4.0 

 Nkonde 1.3 

 Ngoni 12.6 

 Amanganja/Anyanja 5.5 

Other Other and unknown 2.7 

 

 Total 100.0 

 

Premarital Fertility by Ethnicity

Malawi is a homogenous country with respect to nuptiality and fertility indicators. Age at first 

marriage ranges from 17.2 to 18.3 years, (average of 17.8 years) and the proportion of women who never 

marry is negligible (0.2 percent). Premarital fertility ranges from 2.3 to 5.1 percent for all births (average 

of 3.7 percent) and from 5.8 to 14.0 percent for women (average of 9.9 percent). The prevalence of 

premarital intercourse ranges from 32.1 to 47.0 percent (average of 39.4 percent). 

 Unlike most African countries, premarital fertility in Malawi is not related to age at first marriage, 

and has only a moderate correlation with urban residence (ρ = 0.518). Two groups stand out from the 

others: the Ngoni, with higher premarital fertility (14.0 percent), and the Sena, who are primarily rural 

and have a lower level of premarital fertility (5.8 percent). 
54

Table 3 Premarital fertility and nuptiality indicators, Malawi. 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

Percent 

premarital 

intercourse 

Chewa 3,536 13.6 18.3 0.0 3.7 8.8 35.8 

Tumbuka 1,291 27.5 17.8 0.0 2.8 8.3 32.1 

Lomwe 2,589 13.2 17.2 0.4 3.7 10.1 45.7 

Tonga 286 30.9 17.5 2.1 5.1 12.1 45.1 

Yao 1,928 14.6 17.8 0.4 4.5 10.7 47.0 

Sena 455 8.5 17.8 0.0 2.3 5.8 32.4 

Nkonde 437 34.4 17.6 0.0 3.3 10.9 35.7 

Ngoni 1,462 21.6 17.9 0.5 4.4 14.0 38.0 

Amanganja/Anyanja 745 10.8 17.2 0.2 3.4 8.6 42.4 

Other and unknown 491 11.4 17.3 0.0 3.2 8.8 29.4 

 

Total 13,220 15.9 17.8 0.2 3.7 9.9 39.4 

Source: Authors’ calculations from 2000 DHS survey. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Malawi 

Ngoni

Sena

Tonga

Yao

Tumbuka Amanganja

Lomwe

Chewa

Nkonde

0

10

20

15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
55

MALI 

 

Mali has conducted three DHS surveys, in 1987, 1995, and 2001. The first survey provided six 

ethnic groups, while the two others provided nine groups with the same coding and larger sample sizes 

(Table 1). Furthermore the first survey gave higher than expected levels of premarital fertility. Therefore, 

the surveys of 1995 and 2001 were lumped together for final analysis. 

 

Table 1 Sample size and main characteristics of DHS surveys, Mali 

Mali 

DHS 

1987 

DHS 

1995 

DHS 

2001 

No. of women interviewed 3,200 9,740 12,849 

No. of ethnic categories, African 6 9 9 

Percent other and unknown 11.3 11.1 5.5 

The distribution of women age 15-49 by main ethnic group was basically the same in the two 

surveys. There were fewer “other and unknown” in the 2001 survey despite having the same ethnic 

groups. There were more Bambara, Sonrai, and Tamacheck, but fewer Dogon. These small differences do 

not matter for this study. 

Table 2 Distribution of ethnic groups by survey, Mali 

Ethnolinguistic group 

DHS 

1995 

DHS 

2001 P-value Significance 

Bambara 29.0 33.0 0.000 * 

Malinke 7.6 9.2 0.000 * 

Peulh 14.5 14.0 0.301 

Sarakole/Soninke 12.7 12.3 0.456 

Sonrai 3.3 5.9 0.000 * 

Dogon 8.8 7.3 0.000 * 

Tamacheck 0.8 2.0 0.000 * 

Senoufo/Minianka 8.9 8.3 0.127 

Bobo 3.3 3.8 0.066 

Other and unknown 11.1 4.2 0.000 * 

 

Total 100.0 100.0 

*p <0.05 

 

Premarital Fertility by Ethnicity

Mali is a homogenous country with respect to nuptiality and fertility indicators. Early marriage is 

common and the level of premarital fertility is low (Table 2). Age at first marriage ranges from 15.7 to 

17.0 years (average of 16.2 years), and the proportion of women who never marry is negligible (0.1 

percent). Premarital fertility estimates range from 1.5 to 3.6 percent for all births (average of 2.7 percent) 

and from 4.6 to 11.1 percent for women (average of 8.1 percent). The prevalence of premarital intercourse 

ranges from 18.6 to 34.0 percent (average of 26.0 percent). 

Unlike many African countries, premarital fertility is not related to age at first marriage 

(ρ = 0.088), and has no correlation with urban residence (ρ = 0.126). 
56

 Because of the large sample size, most differences in the prevalence of premarital fertility were 

statistically significant—with the exception of the Sonrai and the Tamacheck—but are of such small 

magnitude as to have little sociological importance. 

Table 3 Premarital fertility and nuptiality indicators, Mali 

Ethnolinguistic group 

Number of 

women 

surveyed 

Ppercent

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bambara 6,413 25.8 16.2 0.0 2.9 8.9 28.2 

Malinke 1,968 35.3 15.7 0.0 3.6 11.1 34.0 

Peulh 3,119 31.7 15.9 0.1 2.3 6.9 22.5 

Sarakole/Soninke 2,841 34.6 16.0 0.3 2.4 6.6 19.6 

Sonrai 1,722 50.2 17.0 0.0 3.0 7.8 25.9 

Dogon 1,472 17.9 15.8 0.0 1.5 4.6 19.0 

Tamacheck 864 49.1 15.9 0.2 2.9 7.4 18.6 

Senoufo/Minianka 1,736 25.4 16.7 0.0 3.5 10.6 32.7 

Bobo 760 29.1 16.9 0.7 1.9 7.0 27.4 

Other and unknown 1,658 43.1 16.4 0.0 3.0 8.0 25.6 

 

Total 22,553 30.8 16.2 0.1 2.7 8.1 26.0 

Source: Authors’ calculations after merging data from 1995 and 2001 DHS surveys. 

 

Figure 1 Correlation between premarital fertility and age at first marriage, Mali 

Malinke Senoufo Minianka

Sonrai

Bobo

Bambara

Dogon

Tamacheck

Sarakole Soninke Peulh

0

10

20

15 16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
57

MOZAMBIQUE

Mozambique conducted two DHS surveys, in 1997 and 2003. In 1997, ethnicity was defined as 

the main language spoken at home (V131), and was grouped into five large language families plus 

Portuguese speakers, which include mainly educated Africans and mixed races (assimilados). In addition, 

the mother tongue (“language learned to speak”) was also recorded (S119) and coded in 50 categories. 

The 2003 survey also provided the “language learned to speak” in 26 detailed categories (S119). The two 

surveys were compatible to a large extent, since most of the additional categories in the first survey were 

small groups. 

Table 1 Sample size and main characteristics of DHS surveys, 

Mozambique 

Mozambique 

DHS 

1997 

DHS 

2003 

No. of women interviewed 7,143 12,418 

No. of ethnic categories, African 50 26 

Percent other and unknown 1.3 3.2 

After combining the two surveys, 16 groups large enough for proper estimation of premarital 

fertility were kept for final analysis (Table 2). 

Table 2 Distribution of ethnic groups by survey, Mozambique 

Origin 

Ethnolinguistic 

group 

DHS 

1997 

DHS 

2003 Significance 

Mixed Portuguese 3.6 9.7 * 

African Emakhuwa 26.2 25.5 

 Xichangana 15.8 13.8 * 

 Elomxe 8.0 6.3 * 

 Cisena 12.4 6.4 * 

 Echuwabo 2.5 3.4 * 

 Bitonga 2.4 1.8 * 

 Chichewa 3.1 4.9 * 

 Nhungue 1.8 3.7 * 

 Chitswa 6.1 6.6 

 Naconde 0.8 1.8 * 

 Ndau 2.1 3.6 * 

 Ronga 3.6 1.6 * 

 Chitewe 1.9 1.4 * 

 Chope 3.0 1.9 * 

 Jaua 1.4 1.7 

Other and unknown 5.7 5.3 

 

Total 100.0 100.0 

Note: The spelling of names of ethnic groups varied between the two surveys; the 

spelling in the 2003 survey was used in this report. 

*p <0.05 
58

Some discrepancies in the frequency of ethnic groups could be noted between the two surveys, 

and most of the differences were statistically significant. Portuguese speakers accounted only for 3.6 

percent in the first survey, but for 9.7 percent in the second survey, indicating probably some mixture 

between mother tongue, language spoken at home or language learned in school. The Cisena had an 

abnormally high presence in the first sample and an abnormally low presence in the second; this may be a 

result of the sampling procedure. The Nhungue had an abnormally low presence in the first survey, 

whereas the Ronga and Chope were over represented. In any case, with the exception of the Portuguese 

speakers, which is a mixed category anyway, these discrepancies appear as minor. 

Premarital Fertility by Ethnicity

Mozambique has medium age at first marriage (17.4 years) and a medium level of premarital 

fertility (6.7 percent of all births, 15.3 percent of women) (Table 3). Between African groups, age at 

marriage varied from 15.7 to 19.4 years. It was higher for Portuguese speakers, who are more urbanized 

(83.1 percent). Similarly, premarital fertility varied from 5.8 to 34.1 percent among the African groups, 

and was 30.6 percent for Portuguese speakers. The prevalence of premarital intercourse, which ranged 

from 31.6 to 72.1 percent among African groups, was 80.9 percent among Portuguese speakers. 

Table 3 Premarital fertility and nuptiality indicators, Mozambique 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Portuguese 1,761 83.1 20.3 7.5 16.5 30.6 80.9 

Emakhuwa 4,051 22.1 15.7 1.2 3.7 8.4 31.6 

Xichangana 3,987 41.9 18.4 1.7 11.5 24.3 64.0 

Elomxe 725 8.3 16.9 2.4 6.4 13.9 52.8 

Cisena 1,705 26.1 17.1 0.0 4.3 10.3 34.7 

Echuwabo 473 23.9 17.7 2.7 8.0 18.0 60.7 

Bitonga 504 43.4 19.8 5.8 13.8 30.0 72.1 

Chichewa 793 4.6 17.7 1.6 3.5 10.8 50.9 

Nhungue 809 31.7 17.7 0.0 4.4 12.4 48.8 

Chitswa 1,371 24.0 18.3 4.0 12.3 22.3 60.0 

Naconde 290 20.9 16.9 0.0 6.5 14.1 49.3 

Ndau 1,076 35.9 17.3 2.8 3.0 5.8 36.6 

Ronga 726 81.7 18.7 3.2 14.9 34.1 71.7 

Chitewe 620 30.0 17.3 1.7 4.5 8.1 39.0 

Chope 556 34.0 18.3 0.8 12.6 28.6 63.8 

Jaua 540 25.2 17.2 0.0 4.3 11.8 32.8 

Other and unknown 1,210 24.4 17.1 0.8 4.3 9.2 42.8 

 

Total 21,197 31.3 17.4 1.8 6.7 15.3 49.0 

Source: Authors’ calculations after merging data from 1997 and 2003 DHS surveys. 

Correlations between premarital fertility and other factors were high: age at marriage 

(ρ = 0.975), urban residence (ρ = 0.709), and premarital intercourse (ρ = 0.919). There is little deviation 

from the linear patterns for age at marriage (Figure 1) and urban residence. 

 
59

Figure 1 Correlation between premarital fertility and age at first marriage, 

Mozambique 

Echuwabo

Emakhuwa

Xichangana

Elomxe

Portuguese sp.

Cisena

Ronga

Chope

Chitswa

Ndau

Chitwe

Chichewa

Nhungue

Bitonga

Naconde

Jaua

0

10

20

30

40

50

15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
60

NAMIBIA 

Namibia conducted two DHS surveys, in 1992 and 2000. Ethnicity was defined as the main 

language spoken at home (V131). The first DHS survey coded ten ethnolinguistic group categories: seven 

of African origin, and three of European origin (Afrikaans, English and German). The second DHS 

survey coded the same categories, though two of the European groups (German and English) were 

lumped together. 

Table 1 Sample size and main characteristics of DHS surveys, Namibia 

Namibia 

DHS 

1992 

DHS 

2000 

No. of women interviewed 5,421 6,755 

No. of ethnic categories, African 7 7 

No. of ethnic categories, European 3 2 

Percent other and unknown 10.7 0.9 

There were some minor inconsistencies in definitions of ethnolinguistic groups between the two 

surveys. For example, in the 1992 DHS, the group of “other and unknown” was much larger than in 2000 

(10.7 percent versus 0.9 percent). In fact, it included a number of smaller groups living in the northeast. 

These could be identified by referring to the main language used for the interview (SLANG), which was 

in most cases either Kwangali or Lozi. The “other and unknown” ethnicity variable in the 1992 DHS was 

therefore recoded according to the language used for the interview. After this procedure, the two 

distributions of ethnicity were comparable in the two DHS surveys, and compatible with the 2001 Census 

information (Table 2). 

Table 2 Distribution of ethnic groups by survey, Namibia 

Origin Ethnolinguistic group 

DHS 

1992 

DHS 

2000 

Census 

2001 

African Ovambo/Oshivambo 48.4 48.9 49.4 

 Kavango/Kwangali 10.6 8.9 10.1 

 Nama/Damara 14.6 14.7 9.6 

 Herero/OshiHerero 6.3 10.3 5.1 

 Caprivi/Lozi 6.0 4.1 3.8 

 San 1.0 1.3 - 

 Tswana 0.6 0.2 - 

European Afrikaans 11.4 10.1 8.2 

and mixed English 0.7 0.7 - 

 German 0.5 - - 

 Other and unknown 0.9 13.7 

 

 Total 100.0 100.0 100.0 

Note: The data for the 1992 DHS survey were analyzed after correction of “other and unknown” from language of 

interview. 

Note that since only the main language spoken at home was recorded in the survey, some 

categories are somewhat fuzzy. This is the case in Afrikaans-speaking groups in particular, which include 

people of European origin (Afrikaner), mixed races (Rohobotan/Baster), and some urbanized people of 

African origin. Of course, there are many more ethnic groups described in Namibia; some 25 

ethnolinguistic groups have been described, not counting European languages and tiny minorities of 

foreign origin (Indians, Portuguese, etc.). 
61

 Both DHS surveys were compatible in the definition of ethnicity, in the population distribution by 

ethnolinguistic groups, and in the ranking of premarital fertility. Data are therefore presented for both 

surveys combined (Table 3). 

Table 3 Premarital fertility and nuptiality indicators, Namibia 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

English/German 108 94.9 23.5 1.2 17.7 26.5 71.0 

Afrikaans 1,411 86.4 23.7 9.8 38.6 55.5 74.0 

Ovambo/Oshivambo 4,910 25.2 29.6 18.6 44.7 65.2 77.0 

Kavongo/Kwangali 1,256 16.3 18.8 0.5 13.1 27.9 57.9 

Caprivi/Lozi 966 27.5 21.0 0.9 25.6 52.4 80.7 

Damara/Nama 2,130 65.7 27.2 18.8 57.0 70.8 86.8 

Herero 1,149 52.2 30.1 30.9 60.0 76.2 91.1 

San 154 2.2 20.6 4.2 23.5 26.8 59.1 

Other and unknown 92 78.0 29.8 38.7 53.1 54.0 80.8 

 

Total 12,176 39.9 27.0 16.0 42.7 60.4 77.5 

Source: Authors’ calculations after merging data from 1992 and 2000 DHS surveys. 

Premarital Fertility by Ethnicity

 Namibia has a very high median age at first marriage (25.9 years), a high proportion of women 

who never marry (16.0 percent), and a high level of premarital fertility (42.7 percent for all births and 

60.4 percent for women). 

Differentials in premarital fertility by ethnicity are marked, varying from 13 to 60 percent for all 

births, and from 29 to 79 percent for women. Premarital fertility is closely associated with age at first 

marriage (ρ = 0.831), as seen in Figure 1, and with the prevalence of premarital intercourse (ρ = 0.900); 

however, it is not associated with urban residence (ρ = 0.195). 

 A detailed analysis of premarital fertility in Namibia was published elsewhere (Garenne and 

Zwang, 2005). Differentials in premarital fertility by ethnicity were stable after controlling for a variety of 

socioeconomic factors, including urban residence, level of education, and access to mass media. This 

highlights the major role of cultural factors in determining levels of premarital fertility. 
62

Figure 1 Correlation between premarital fertility and age at first marriage, 

Namibia 

San English, German Kavongo

Lozi, Caprivi

Afrikaans sp.

Damara, Nama

Herero

Ovambo

0

20

40

60

80

18 19 20 21 22 23 24 25 26 27 28 29 30 31

Median age at first marriage (years)

% women with premarital birth
63

NIGER 

Niger conducted two DHS surveys, in 1992 and in 1998 (Table 1). We were able to combine the 

two surveys since both provided the same distribution of ethnic groups. Ethnicity was defined as the main 

language spoken at home (V131). The DHS survey coded nine ethnolinguistic group categories of 

African origin, and proportions of “other and unknown” were small in both surveys. 

Table 1 Sample size and main characteristics of DHS surveys, Niger 

Niger 

DHS 

1992 

DHS 

1998 

No. of women interviewed 6,503 7,577 

No. of ethnic categories, African 9 9 

Percent other and unknown 2.4 1.8 

The two surveys were compatible in the distribution of ethnic groups, with some minor 

differences (Table 2). However, some groups were small in size and had to be lumped together in the 

“other and unknown” category for final analysis. 

Table 2 Distribution of ethnic groups by survey, Niger 

Origin Ethnolinguistic group 

 DHS 

1992 

DHS 

1998 P-value Significance 

African Arab 0.2 0.2 0.462 

 Djerma 22.4 21.4 0.164 

 Gourmantche 0.3 0.4 0.190 

 Hausa/Haoussa 54.5 58.4 0.000 * 

 Kanouri 5.3 4.3 0.007 * 

 Mossi 0.0 0.2 0.039 * 

 Peulh 4.6 4.9 0.460 

 Touareg 10.0 8.4 0.001 * 

 Toubou 0.3 0.1 0.000 * 

 Other and unknown 2.4 1.8 0.013 * 

 

 Total 100.0 100.0 

*p <0.05 

 

Premarital Fertility by Ethnicity

Niger has a low age at first marriage and a low level of premarital fertility (Table 3). Overall, all 

indicators of premarital fertility are on the low side in Niger: premarital births (1.0 percent), women with 

a premarital birth (2.8 percent), premarital intercourse (4.5 percent), proportion never married (0.2 percent), median age at first marriage (15.0 years), and proportion urban (19 percent). 

Niger is markedly homogenous with respect to ethnicity. There was hardly any variation among 

the variables examined. The only group that stands out is the “other and unknown,” which primarily 

includes urban residents, many originally from other countries. 
64

Table 3 Premarital fertility and nuptiality indicators, Niger 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Djerma 3,560 23.3 15.5 0.3 1.5 4.1 4.9 

Hausa 7,405 15.9 14.8 0.0 0.8 2.3 3.7 

Kanouri 565 17.1 14.8 0.0 0.8 2.1 3.4 

Peulh 734 22.6 15.3 0.0 0.9 2.2 5.2 

Touareg 1,148 12.7 15.0 0.0 0.7 2.1 5.0 

Other and unknown 668 61.5 15.5 4.0 3.6 9.7 19.8 

 

Total 14,080 19.0 15.0 0.2 1.0 2.8 4.5 

Source: Authors’ calculations after merging data from 1992 and 1998 DHS surveys. 

The level of premarital fertility among ethnic groups that extend across national borders is similar 

to that of their counterparts in the neighboring countries. Hausa, Kanouri and Fulani (Peulh) in Niger have 

patterns of behavior similar to those of related groups in Nigeria. This is also the case for the Touareg in 

Niger and Burkina Faso. 

 There is a clear relationship between premarital fertility and urban residence (ρ = 0.977). This is 

primarily because of the “other and unknown” category, although there was a small relationship among 

the five indigenous groups because of the Djerma (ρ = 0.612) (Figure 1). Correlation with age at marriage 

was also significant, despite small differentials for the same reasons (ρ = 0.761). 

Figure 1 Correlation between premarital fertility and age at first marriage, Niger 

Djerma

Peulh Kanouri

Hausa

Touareg

0

2

4

6

8

10

13 14 15 16 17 18

Median age at first marriage (years)

% women with premarital birth
65

NIGERIA 

Nigeria is a special case in Africa, both for its large population, as well its extreme ethnic 

diversity. Some 485 languages appear in the Ethnologue database. The ethnic information gained from 

DHS surveys is necessarily much more limited in scope. 

 Nigeria conducted one WFS survey in 1982 and three DHS surveys, in 1990, 1999, and in 2003 

(Table 1). All four surveys had some information on ethnicity, though coded in various ways. The WFS 

had 34 categories, including the most important groups. The 1990 DHS survey had 92 categories; 

however, labels were provided for only 25 groups and the others could not be used. The last two DHS 

surveys (1999 and 2003) had the same coding and provided basically the same information, although 

some of the ethnic groups were very small. Although more could be probably done with ethnicity in 

Nigeria, only the last two surveys were selected since both provided compatible information, and also 

provided a large enough sample for statistical inference. Adding a few groups from the other surveys 

would not have changed the main features of the analysis. Ethnicity was defined as the main language 

spoken at home (S119 and S118 respectively). The proportion of “other and unknown” was small in the 

two surveys selected. 

Table 1 Sample size and main characteristics of DHS surveys, Nigeria 

Nigeria 

WFS 

1982 

DHS 

1990 

DHS 

1999 

DHS 

2003 

No. of women interviewed 9,727 8,781 9,810 7,620 

No. of ethnic categories, African 34 92 112 95 

Percent other and unknown 15.8 2.3 8.4 10.2 

The two surveys were compatible in the distribution of ethnic groups, with some minor 

differences (Table 2). Large groups (Hausa, Fulani, Yoruba, Igbo) were always well represented, and 

these four already account for more than half (58 percent) of the total population. Many other groups had 

enough women interviewed in 1999 and 2003 to be analyzed separately. A final list of 13 groups was kept 

in addition to the four largest, nine of them with at least 250 women, and four of them with less than 250 

women. The smallest group contained 136 women (Table 2). 

Groups with smaller sample size were lumped together according to their geographic origin: other 

groups from the Northern regions (Northwest and Northeast), other groups from North-Central and 

Southwest regions, and other groups from South and Southeast regions. Regions were based on the 2003 

survey (V101). 

Premarital Fertility by Ethnicity

Nigeria is a large country with marked differences in demographic patterns and social behavior. 

Nigeria has a medium level of premarital fertility (4.5 percent for all births, and 11.0 percent for women), 

a medium age at first marriage (17.8 years), a medium prevalence of premarital intercourse (31.2 

percent), a low proportion of women who never marry (1.0 percent), and a moderate level of urban 

residence (32.4 percent). 

 
66

Table 2 Distribution of ethnic groups by survey, Nigeria 

 Difference between 

1999 and 2003 

surveys 

Ethnolinguistic group 

WFS 

1982 

DHS 

1990 

DHS 

1999 

DHS 

2003 P-value 

Significance 

Hausa 18.6 25.2 18.3 27.0 0.000 * 

Fulani 6.8 3.3 4.3 6.1 0.000 * 

Kanuri 2.8 2.4 0.7 3.0 0.000 * 

Other Northern 1.1 7.4 7.5 6.6 0.019 * 

Yoruba 14.4 16.8 19.7 11.4 0.000 * 

Tiv 1.1 2.8 1.3 2.2 0.000 * 

Nupe 1.1 1.2 0.8 0.008 * 

Igbala/Igala 1.9 0.7 2.3 3.0 0.006 * 

Idoma 0.8 1.2 1.8 0.8 0.000 * 

Ibira/Igbirra 0.3 2.0 0.6 0.000 * 

Gwari 1.5 5.8 0.6 1.1 0.000 * 

Other Central, West 1.1 0.9 2.9 1.7 0.000 * 

Igbo/Ibo 23.7 16.5 15.9 13.6 0.000 * 

Ibibio 4.1 4.8 3.8 0.003 * 

Ijaw 1.1 1.0 1.4 1.1 0.099 

Edo 0.9 0.5 2.4 0.9 0.000 * 

Annang 1.4 1.3 1.7 0.059 

Urhobo 0.8 1.1 1.0 1.1 0.237 

Ogoni/Ogori 0.0 1.0 1.6 0.002 * 

Other South and East 1.0 12.0 1.0 1.5 0.011 * 

Other and unknown 15.8 2.3 8.4 10.2 0.000 * 

 

Total 100.0 100.0 100.0 100.0 

*p <0.05 

These average values hide major differences among ethnic groups. Urban residence is low for 

small groups such as the Ogoni and the Annang, but it is high for the Yoruba, the Ibira and the Urhobo. 

Age at first marriage is low (<15 years) for the northern groups (Hausa, Fulani, Kanuri) but high 

(>20 years) for some of the southeastern groups (Igbo, Urhobo), as well as the urbanized Yoruba. 

Premarital fertility is low (<5 percent) for the Fulani and Kanuri and high (>20 percent) for the Ibibio, 

Ijaw, Urhobo, and Ogoni. Similarly, premarital intercourse is rare among the Fulani, Kanuri, and Hausa, 

but common (>50 percent) among many of the southeastern groups as well as among the Yoruba. 

Correlation with age at first marriage was relatively high (ρ = 0.762), as can be seen in Figure 1. 

The differentials show the main divisions in the country: a cluster of three northern groups with low age 

at first marriage and low level of premarital fertility (Hausa, Fulani, Kanuri); a second cluster of groups in 

central and southwest Nigeria with medium age at first marriage and level of premarital fertility; and a 

third cluster of groups primarily in southern and eastern Nigeria with high age at first marriage and level 

of premarital fertility. There are some exceptions to this overall pattern. The Yoruba live in the central 

and western parts of the country, but are included in the third cluster because they are more urbanized. 

The Annang are located in the southern region, but belong to the second cluster. The “other northern 

groups” also belong to the second cluster; they are primarily ethnic groups located in the southern parts of 

the northern provinces, and are close to the north-central groups. 
67

Table 3 Premarital fertility and nuptiality indicators, Nigeria 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Hausa 3,623 26.0 14.3 0.2 2.4 6.1 4.8 

Fulani 912 15.5 14.3 0.8 1.8 4.7 3.4 

Kanuri 253 32.8 14.3 0.0 0.9 2.4 3.0 

Other Northern 1,321 23.3 16.3 0.0 4.8 11.5 17.9 

Yoruba 2,914 61.0 20.4 0.2 6.2 14.9 55.0 

Tiv 340 19.4 17.7 0.0 3.5 8.0 29.3 

Nupe 180 34.3 17.4 0.0 4.1 13.3 13.0 

Igbala/Igala 364 18.4 17.6 0.0 9.3 16.6 46.5 

Idoma 260 19.8 18.3 2.9 6.0 13.9 32.1 

Ibira/Igbirra 260 60.4 18.4 0.0 5.4 12.5 37.7 

Gwari 136 13.3 17.9 0.0 7.4 15.4 18.3 

Other Central, West 405 16.2 17.5 2.0 7.4 11.8 21.1 

Igbo/Ibo 2,946 38.0 21.0 2.9 4.5 11.3 50.7 

Ibibio 599 19.8 19.8 6.2 7.8 22.1 62.1 

Ijaw 239 19.4 19.0 1.9 8.7 22.7 60.5 

Edo 296 48.0 19.8 0.0 5.3 15.5 56.1 

Annang 223 3.1 17.8 0.0 4.7 10.4 56.8 

Urhobo 158 59.5 20.3 0.0 8.7 20.7 61.8 

Ogoni/Ogori 158 0.0 19.5 4.6 9.8 21.0 61.8 

Other South, East 176 23.6 19.6 0.0 8.4 18.9 68.0 

Other and unknown 1,667 27.1 17.7 1.1 5.8 14.4 35.5 

 

Total 17,430 32.4 17.8 1.0 4.5 11.0 31.2 

Source: Authors’ calculations after merging data from 1999 and 2003 DHS surveys. 

Figure 1 Correlation between premarital fertility and age at first marriage, Nigeria 

Kanuri

Fulani

Hausa

Other Northern

Yoruba

Tiv

Nupe

Igbala

Idoma

Igbira

Gwari

Other Central, West Igbo

Ibibio Ijaw

Edo

Annang

Ogoni Urhobo

Other South & East

0

5

10

15

20

25

14 15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
68

RWANDA 

Rwanda is a special case in this analysis because ethnicity is linked more to social status than to 

geographical area or culture. Like Burundi, Rwanda is a small country and more homogeneous ethnically 

than other African countries. Three ethnic groups are usually distinguished in Rwanda: Hutu, Tutsi, and 

Twa. The first two groups account for 99 percent of the population, while the Twa is a small minority of 

aborigines (pygmies), most of whom live in the northwestern forests. Both Hutu and Tutsi speak the same 

language (kinyarwanda), share the same culture, and live in the same areas, although the proportion of 

Tutsis tends to be lower in the northern part of the country. The early history of relationships between the 

Hutu and Tutsi is complex and well documented. They were further complicated by political events 

around the time of independence (1960), subsequent struggles for power, and civil war and genocide in 

1994. Despite these events, Rwanda was kept in this analysis because it shows an interesting pattern. 

Rwanda conducted one WFS survey in 1983 and two DHS surveys, in 1992 and 2000 (Table 1). 

The first two surveys covered the three ethnic groups and a tiny fraction of other and unknown ethnic 

groups. After 1994, ethnicity became a politically sensitive subject in Rwanda, and it was not examined in 

the 2000 DHS survey. For this reason, we relied on the first two surveys for this analysis. 

Table 1 Sample size and main characteristics of surveys, Rwanda 

Rwanda 

WFS 

1983 

DHS 

1992 

DHS 

2000 

No. of women interviewed 5,738 6,551 10,421 

No. of ethnic categories, African 3 3 na 

Percent other and unknown 0.5 0.3 0.5 

na = Not applicable 

The two surveys were compatible with respect to the distribution of ethnic groups and could be 

combined, although fewer Tutsis were present in the second survey. The second survey also showed 

higher levels of premarital fertility for both Tutsis and Hutus, indicating an increasing trend over time. 

However, the pattern of differences with respect to premarital fertility was the same in the two surveys. 

Table 2 Distribution of ethnic groups by survey, Rwanda 

Origin Ethnolinguistic group 

WFS 

1983 

DHS 

1992 P-value Significance 

African Hutu 86.4 90.7 0.000 * 

 Tutsi 12.6 8.7 0.000 * 

 Twa 0.5 0.4 0.284 

 Other and unknown 0.5 0.3 0.070 

 

 Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

Results for the Twa should be interpreted with caution because they are based on only 48 women, 

show no cases of premarital birth, and have wide confidence intervals (Table 3). However, the premarital 

fertility of the Twa was borderline significantly different from the other groups (p = 0.054), and they were 

kept separate because of their special ethnic identity and because they matched the overall pattern of 

relationship with age at marriage. 
69

 The two other groups were quite different. Compared with the Hutu, the Tutsi are more 

urbanized, have higher age at marriage, higher premarital fertility, and higher incidence of premarital 

intercourse. The Twa, who are almost entirely rural, had lower premarital fertility despite high rates of 

premarital intercourse. This pattern is primarily the result of lower age at marriage. 

Table 3 Premarital fertility and nuptiality indicators, Rwanda 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Hutu 10,750 5.4 19.7 0.6 2.2 6.9 17.4 

Tutsi 1,416 14.5 22.0 1.3 3.2 10.0 23.2 

Twa 48 3.0 17.6 0.0 0.0 0.0 30.2 

Other and unknown 75 36.2 19.3 0.0 2.9 14.0 41.8 

 

Total 12,289 6.2 19.9 0.6 2.2 7.1 18.0 

Source: Authors’ calculations after merging data from 1983 WFS and 1992 DHS surveys. 

Correlations with age at marriage and urban residence are of little value because they are based on 

only three ethnic groups, one of which is very weak. However, the patterns resemble those seen in other 

countries (Figure 1). 

 An important feature of premarital fertility in Rwanda is its low prevalence (2.2 percent for all 

births, 7.1 percent for women) in conjunction with high age at first marriage (19.9 years). A similar 

pattern is seen in Burundi, with which Rwanda shares much of its social fabric. Despite minor differences 

relating to socioeconomic factors, and despite the special case of the Twa minority, Rwanda and Burundi 

have a unique pattern of premarital fertility in Central Africa. 
70

Figure 1 Correlation between premarital fertility and age at first marriage, 

Rwanda 

Tutsi

Twa

Hutu

0

5

10

15

16 17 18 19 20 21 22 23

Median age at first marriage (years)

% women with premarital birth
71

SENEGAL 

Senegal conducted one WFS survey in 1978, and three DHS surveys, in 1986, 1993, and 1997 

(Table 1). Another DHS survey was conducted in 1999 but the data were not available when this report 

was prepared. The first survey (WFS) included 18 specific ethnic groups, the second survey had only five 

groups, the third survey had seven groups, and the fourth survey had ten groups. The main groups were 

compatible, but many were missing in the second survey. The data in the first survey were considered 

somewhat out-of-date, and had a lower than average rate of premarital fertility. The second survey was 

limited in the number of ethnic groups, and had a higher than average rate of premarital fertility. 

Therefore, the last two surveys (1993 and 1997), which also had larger sample sizes, were used for the 

analysis. 

Table 1 Sample size and main characteristics of surveys, Senegal 

Senegal 

WFS 

1978 

DHS 

1986 

DHS 

1993 

DHS 

1997 

No. of women interviewed 3,985 4,415 6,310 8,593 

No. of ethnic categories, African 18 5 7 10 

Percent other and unknown 7.5 10.1 3.5 4.5 

The last two surveys were compatible with respect to the distribution of ethnic groups, were 

compatible with the other surveys, and could be matched (Table 2). However, the southern groups 

(Manjaak, Mancagne, and Balant) were not coded in the 1993 DHS survey, so information on these 

groups comes only from the 1997 survey. Because the sample sizes of the three groups were small and the 

groups had similar characteristics, they were merged in this analysis to form a separate ethnic category. 

This was done partly because the three groups had unusual characteristics. 

Table 2 Distribution of ethnic groups by survey, Senegal 

Difference between 

1993 and 1997 

surveys 

Ethnolinguistic group 

WFS 

1978 

DHS 

1986 

DHS 

1993 

DHS 

1997 P-value 

Significance 

Wolof/Lebou 42.7 42.1 42.5 41.0 0.063 

Poular 22.8 23.0 23.2 24.8 0.021 * 

Serer 14.2 14.5 15.4 14.3 0.074 

Mandingue/Soce/Malinké 4.5 5.0 7.6 5.0 0.000 * 

Diola 3.8 5.5 5.2 4.6 0.058 

Sarakole/Soninke 1.8 1.7 2.3 0.004 * 

Bambara 1.5 0.9 1.8 0.000 * 

Manjaak, Mancagne, Balante 1.0 1.7 na na 

Other and unknown 7.7 10.1 3.5 4.5 na na 

 

Total 100.0 100.0 100.0 100.0 

*p <0.05 

na = Not applicable 

 

 
72

Premarital Fertility by Ethnicity

 Senegal has a moderate level of premarital fertility, with an average of 3.8 percent for all births 

and 11.1 percent for women. Median age at marriage is low (16.9 years), and the level of premarital 

intercourse is low by African standards (13.8 percent), except in the southern groups, where it is much 

higher (>44 percent). 

Table 3 Premarital fertility and nuptiality indicators, Senegal 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Wolof/Lebou 5,931 48.6 16.8 0.3 3.3 10.1 10.6 

Poular 3,475 34.8 15.8 0.5 1.6 5.1 6.6 

Serer 2,388 34.6 17.6 0.1 4.0 13.1 17.2 

Mandingue/Soce/Malinké 1,012 38.6 16.6 0.8 4.3 12.2 16.7 

Diola 855 53.0 20.3 0.3 15.9 39.1 53.5 

Sarakole/Soninke 279 38.4 16.8 0.0 3.7 9.0 10.5 

Bambara 206 62.3 18.3 0.0 3.6 12.8 15.2 

Manjaak, Mancagne, 

Balante 168 49.7 19.4 0.0 13.3 38.9 44.5 

Other and unknown 589 57.3 17.0 0.0 4.4 12.1 17.8 

 

Total 14,903 43.2 16.9 0.3 3.8 11.1 13.8 

Source: Authors’ calculations after merging data from 1993 and 1997 DHS surveys. 

Differentials by ethnicity are large. Two groups, the Diola, and the Manjaak-Mancagne-Balant 

stand out as having high levels of premarital fertility (39.1 percent and 38.9 percent, respectively) and 

high age at marriage (20.3 years and 19.4 years, respectively) (Table 3). The two groups are located 

primarily in Casamance, in the southern part of the country, south of the Gambia and near Guinea Bissau 

(where the Manjaak-Mancagne-Balant originated). The behavior of these groups is quite different from 

that of the other groups in the country. At the other end of the spectrum are the Poular (Fulani), who, like 

their kin in various other West African countries, have a low age at marriage (15.8 years) and only a small 

proportion of the women have had a premarital birth (5.1 percent). Other groups are similar, with minor 

variations. The Wolof tend to have a low level of premarital fertility, despite being more urbanized, while 

the opposite is the case for the Serer. The small group of Bambara had lower levels than expected, given 

that they are the most urbanized group, and had higher age at marriage than the others. Even if 

statistically significant, the small differences between the five middle groups have little sociological 

implication, and the groups can be regarded as similar. 
73

Figure 1 Correlation between premarital fertility and age at first marriage, 

Senegal 

Sarakole, Soninke

Poular

Mandingue, Socé Serer Bambara

Wolof, Lebou

Diola

Manjaak, Mancagne, Balant

0 

10 

20 

30 

40 

14 15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
74

SOUTH AFRICA 

South Africa conducted one DHS survey in 1998 and another in 2003-04. Data for the latter 

survey have not been released. Only the 1998 DHS survey was accessible when this study was conducted 

(Table 1). The 1998 DHS survey included four racial groups (V131) and the 11 official languages of the 

country, two of which are European languages (Afrikaans and English). The two types of information 

(race and language) were merged to form 13 comprehensive ethnolinguistic groups. Three of the groups 

identify the non-African population by race (White, Asian/Indian, Colored), while nine are ethnolinguistic 

groups in the black/African population. The sample was large enough to accommodate the 13 groups. 

Very few “other and unknown” groups were left over, despite there being a large number of foreigners 

living in South Africa. However, some of these would be included in the various ethnic groups (for 

example, the Shangaan/Tsonga from Mozambique, and the Southern Sotho from Lesotho). 

Table 1 Sample size and main characteristics of 

DHS survey, South Africa 

South Africa 

DHS 

1998 

No. of women interviewed 11,735 

No. of ethnic categories, African 9 

Racial groups 4 

Percent other and unknown 0.2 

The survey is compatible with respect to the distribution of ethnic groups from other sources 

(Table 2). 

Table 2 Distribution of ethnic groups in survey, South Africa 

South Africa 

Ethnolinguistic and racial 

group 

DHS 

1998 

Others White 7.8 

 Asian/Indian 3.5 

 Coloured 10.2 

Black/African Speaking European 

languages 1.9 

 Xhosa 15.2 

 Zulu 25.0 

 Sotho 8.6 

 Tswana 11.0 

 Pedi 9.3 

 Swazi 2.0 

 Venda 1.7 

 Tsonga 2.7 

 Ndebele 0.9 

 Other and unknown 0.2 

 

 Total 100.0 
75

Premarital Fertility by Ethnicity

 Premarital fertility is high in South Africa, with an average of 38.9 percent for all births and 59.1 

percent for women. The median age at marriage is high (24.7 years) and the prevalence of premarital 

intercourse is high (81.4 percent). 

Table 3 Premarital fertility and nuptiality indicators, South Africa 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

White 755 86.7 21.3 0.6 3.2 5.2 50.4 

Asian/Indian 393 98.2 21.1 6.3 7.6 11.9 30.9 

Coloured 1,533 82.4 25.0 11.2 44.6 66.6 83.5 

Black, speaking European 

languages 257 66.9 28.3 28.9 42.5 70.6 88.4 

Xhosa 2,693 53.4 24.6 18.3 38.6 62.7 86.0 

Zulu 2,147 55.8 27.1 18.5 49.6 72.9 90.2 

Sotho 951 80.4 23.2 8.6 35.0 58.6 85.3 

Tswana 1,200 61.6 26.8 16.8 52.7 74.3 90.6 

Pedi 910 33.6 23.1 14.6 37.2 58.1 78.7 

Swazi 333 29.3 20.9 14.8 31.9 54.9 82.1 

Venda 169 10.8 19.8 0.0 16.7 38.6 63.9 

Tsonga 269 16.4 19.8 3.0 23.1 41.9 65.6 

Ndebele 125 46.5 26.7 12.0 42.3 73.2 89.6 

 

Total 11,735 60.5 24.7 13.2 38.9 59.1 81.4 

Source: Authors’ calculations from 1998 DHS survey. 

Differentials by ethnicity are large. Racial groups stand out as significant, with White and Asian 

populations having much lower premarital fertility (5.2 percent and 11.9 percent, respectively), despite 

high median age at marriage (21.3 and 21.1 years, respectively) and high urban residence (86.7 percent 

and 98.2 percent, respectively). At the other end of the spectrum, the Colored (mixed race)1

 population 

shows high premarital fertility (66.6 percent), high age at marriage (25.0 years), and higher than average 

urban residence (82.4 percent). Among the African groups, the differentials were wide as well. The 

Tsonga and Venda have lower age at marriage (19.8 years each) and lower than average premarital 

fertility (38.6 percent and 41.9 percent, respectively). The Swazi, Pedi, Sotho, and Xhosa are located on 

the age at marriage/premarital fertility axis somewhat above the regression line linking all the groups 

(Figure 1). The groups with the highest levels of premarital fertility are also the groups with the highest 

age at first marriage: Ndebele, Tswana, and Zulu. 

Correlation with age at marriage was high and positive (ρ = 0.758), but correlation with urban 

residence was curvilinear, with maximum values in the medium range (40 to 60 percent) for the Ndebele 

Zulu, Xhosa, and Tswana, and lower values for more rural groups (Venda, Tsonga, Pedi, Swazi) and other 

racial groups, which are primarily urban residents (White, Asian). 

 

1

 The Colored (mixed) population of South Africa came into existence during the early period of European (Dutch) 

contact with the indigenous population, primarily Khoisan-speaking hunters and gatherers (Bushmen and 

Hottentots). The descendants of this population are physiologically and culturally different from the descendants of 

the African farming populations that moved into the area. 
76

Figure 1 Correlation between premarital fertility and age at first marriage, 

South Africa 

White

Asian / Indian

Coloured Black, speaking 

European language

Venda

Tsonga

Swazi

Xhosa

Ndebele

Zulu

Tswana

Pedi

Sotho

0

20

40

60

80

18 19 20 21 22 23 24 25 26 27 28 29 30

Median age at first marriage (years)

% women with premarital birth
77

TANZANIA 

Tanzania conducted three DHS surveys, in 1991, 1996, and 1999, plus two KAP-HS surveys in 

1994 and 2003. The 1994 survey did not have maternity histories, and the 1999 and 2003 surveys did not 

provide information on ethnicity (Table 1). The 1991 DHS survey included 126 ethnic groups (S114), 

while the 1996 DHS survey included 112 ethnic groups (S117), with basically the same coding. The two 

surveys selected for this analysis (1991 and 1996) had large sample sizes that allowed for in-depth 

analysis of ethnicity. 

Table 1 Sample size and main characteristics of DHS surveys, Tanzania 

Tanzania 

DHS 

1991 

KAP-HS 

1994 

DHS 

1996 

DHS 

1999 

No. of women interviewed 9,238 4,225 8,120 4,029 

No. of ethnic categories, African 126 100 112 na 

Percent other and unknown 3.7 5.9 6.7 

na = Not applicable 

Tanzania has a large number of small ethnic groups that are well-documented in the 1991 and 

1996 DHS surveys. The two surveys are compatible and, after combining the data, all ethnic groups with 

at least 200 women interviewed were kept for final analysis. This resulted in 29 groups, plus a residual 

category of “other and unknown” (Table 2). Although the two surveys are largely compatible, some 

statistically significant minor differences were found. These have no importance for this study. The only 

large group in Tanzania is the Sukuma, which accounts for one-sixth of the population. The other groups 

are much smaller but have sufficient women interviewed for statistical inference. 

Table 2 Distribution of ethnic groups by survey, Tanzania 

Ethnolinguistic 

group 

DHS 

1991 

DHS 

1996 P value 

Significance 

Sukuma 15.6 15.1 0.416 

Ha 4.3 4.5 0.561 

Makonde 3.5 3.8 0.185 

Chagga 4.7 3.6 0.000 * 

Gogo 5.2 2.7 0.000 * 

Zigua 1.8 3.6 0.000 * 

Nyamwezi 2.7 2.2 0.039 * 

Fipa 1.6 1.8 0.221 

Bena 2.9 2.5 0.172 

Shirazi 1.5 0.6 0.000 * 

Iramba 1.8 2.1 0.142 

Ngoni 2.0 1.8 0.295 

Zaramo 1.5 1.7 0.197 

Hehe 1.6 2.7 0.000 * 

Pare 2.4 2.2 0.291 

Nyakyusa 2.2 2.9 0.006 * 

Luguru 1.7 2.0 0.233 

Haya 3.1 2.1 0.000 * 

Sambaa 1.7 2.0 0.161 

Jita 1.9 1.3 0.001 * 

Iragw 3.2 2.2 0.000 * 

Makua 1.1 1.2 0.477 

Simbiti 2.7 0.2 0.000 * 

Zanaki 1.7 0.5 0.000 * 

 Continued...
78

Table 2—Continued 

Ethnolinguistic 

group 

DHS 

1991 

DHS 

1996 P value 

Significance 

Pogoro 1.4 1.2 0.104 

Ndengereko 0.9 1.2 0.059 

Kaguru 1.9 1.0 0.000 * 

Mwera 1.4 1.4 0.771 

Masai 1.2 2.4 0.000 * 

Other and unknown 20.8 27.5 0.000 * 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Tanzania, with an average of 8.2 percent for all births 

and 20.0 percent for women. Age at marriage is medium (17.9 years), and the prevalence of premarital 

intercourse is high (57.1 percent). 

 One of the most interesting aspects of premarital fertility in Tanzania is the wide diversity 

observed, along with low correlation with age at marriage (ρ = 0.462) and urban residence (ρ = 0.346). 

The low correlation with age at marriage can be seen in Figure 1, where the 29 groups have a link with 

age at marriage, but are spread widely around it. 

Table 3 Premarital fertility and nuptiality indicators, Tanzania 

Ethnolinguistic 

group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Sukuma 2,033 7.8 17.7 0.0 6.4 16.6 54.3 

Ha 823 19.6 17.5 0.0 2.5 6.8 17.7 

Makonde 693 27.4 17.2 0.0 5.6 11.0 47.1 

Chagga 628 35.5 21.0 2.2 8.8 23.7 49.9 

Gogo 543 19.3 18.1 0.0 6.8 19.0 56.7 

Zigua 475 29.8 17.3 1.2 6.3 16.4 45.4 

Nyamwezi 474 25.3 17.5 0.0 8.9 22.8 55.5 

Fipa 444 18.4 17.6 0.7 6.9 18.9 39.5 

Bena 389 21.8 19.7 2.7 10.3 26.0 50.4 

Shirazi 379 28.5 15.7 0.0 1.7 3.8 2.6 

Iramba 361 14.1 18.9 0.0 15.0 40.7 66.7 

Ngoni 347 38.4 18.0 0.0 13.1 33.6 62.0 

Zaramo 340 32.6 17.2 0.0 11.6 25.1 46.4 

Hehe 327 27.9 18.7 1.9 10.0 25.4 50.7 

Pare 320 28.0 19.8 5.3 16.7 38.8 62.3 

Nyakyusa 312 41.2 17.6 2.0 8.6 17.7 32.2 

Luguru 296 46.8 17.7 2.5 12.8 26.2 47.6 

Haya 292 14.3 17.9 0.0 3.8 8.8 24.5 

Sambaa 287 31.6 18.8 0.0 6.7 18.2 37.8 

Jita 280 35.1 17.9 0.0 8.3 27.2 63.9 

Iragw 276 35.0 19.8 0.0 11.0 23.7 59.9 

Makua 271 16.0 17.3 2.3 10.1 24.2 64.2 

 Continued... 
79

Table 3—Continued 

Ethnolinguistic 

group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Simbiti 262 53.6 17.3 0.0 8.5 21.8 46.4 

Zanaki 236 19.7 17.3 0.0 11.0 27.9 56.1 

Pogoro 235 36.7 16.8 0.0 10.6 27.7 48.5 

Ndengereko 225 65.8 17.7 0.0 14.1 26.8 51.3 

Kaguru 220 26.2 19.2 4.0 15.6 35.7 64.6 

Mwera 375 24.8 17.3 2.0 9.4 22.1 58.6 

Masai 209 0.3 16.3 0.0 5.4 10.8 46.3 

Other and unknown 5,006 24.9 17.7 1.1 8.3 19.4 41.3 

 

Total 17,358 24.2 17.9 0.9 8.2 20.0 47.1 

Source: Authors’ calculations after merging data from 1991 and 1996 DHS survey. 

Differentials by ethnicity are large in Tanzania. Premarital childbearing among women ranges 

from 3.8 percent (Shirazi) to 40.7 percent (Iramba). Similar differences are seen for prevalence of 

premarital intercourse (2.6 to 66.7 percent, respectively). Age at first marriage varies widely from 15.7 

years (Shirazi) to 21 years (Chagga). The Shirazi, who live on the islands of Zanzibar and Pemba, are 

culturally conservative despite an above-average level of urban residence (28.5 percent). The Shirazi are 

Muslim and their history is quite different from that of most other ethnic groups on the continent. 

There is no clear geographical pattern for premarital fertility. Groups with low levels of 

premarital childbearing were found on the islands (Shirazi), in the northwest (Ha, Haya), in the northeast 

(Masai), and in the southeast (Makonde). Groups with high levels of premarital childbearing were found 

primarily in the central part of the country (Ngoni, Kaguru, Iramba), but also in the North (Pare) and on 

the coast (Ndengereko). Groups with middle levels of premarital childbearing were found all over the 

country. 

There is wide variation in residence among ethnic groups in Tanzania, with the Masai living 

almost entirely in rural areas (0.3 percent urban), and other groups living primarily in urban areas 

(Ndengereko, Simbiti). Among groups with average levels of urban residence (20 to 30 percent), 

premarital fertility is very low for some (Ha, Shirazi) and very high for others (Pare, Kaguru). The 

Ndengereko and Zanaki have similar levels of premarital fertility, but urban residence is high among the 

Ndengereko and low among the Zanaki (65.8 and 19.7 percent, respectively). 
80

Figure 1 Correlation between premarital fertility and age at first marriage, 

Tanzania 

Mwera Simbiti

Zaramo

Zanaki

Hehe

Gogo

Zigua

Pogoro 

Ngoni

Kaguru

Iramba

Pare

Bena

Iragw

Sambaa

Chagga 

Masai Makonde

Haya

Ha

Shirazi 

Sukuma

Nyamwezi

Makua

Jita

Ndengereko

Luguru

Nyakyusa Fipa

0 

15 

30 

45 

15 16 17 18 19 20 21 22

Median age at first marriage (years)

% women with premarital birth
81

TOGO 

Togo conducted two DHS surveys, in 1988 and 1998 (Table 1). The 1988 DHS included 34 

ethnic groups (RC110), and three main ethnic categories (V131). The 1998 DHS included five main 

categories (V131), with similar coding but no details on ethnicity. 

Table 1 Sample size and main characteristics of DHS surveys, Togo 

Togo 

DHS 

1988 

DHS 

1998 

No. of women interviewed 3,360 8,569 

No. of ethnic groups, African 34 na 

No. of ethnic categories 3 5 

Percent other and unknown 9.1 7.9 

To merge the two data sets, the two additional main categories present in the 1998 survey were 

added to the three main categories in the 1988 survey by recoding data from the detailed 1988 ethnic 

categories. Once the recoding was done, the two surveys were compatible, and the five categories were 

retained for the final analysis (Table 2). The two surveys showed minor differences, some statistically 

significant, however, these differences were of no importance to the study. It should be noted that for the 

1988 sample, the ethnic categories include from 4 to 10 groups, which reduces the specificity of the 

analysis. 

Table 2 Distribution of ethnic groups by survey, Togo 

Ethnolinguistic group 

DHS 

1988 

DHS 

1998 P-value Significance 

Adja-Ewe 47.6 44.2 0.001 * 

Akposso, Akebou 4.1 4.2 0.906 

Ana-Ife 1.6 3.2 0.000 * 

Kabye-Tem 21.0 25.9 0.000 * 

Para-Gourma, Akan 22.2 14.6 0.000 * 

Other and unknown 3.4 7.9 0.000 * 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Togo, with an average of 5.6 percent for all births and 

16.3 percent for women. The prevalence of premarital intercourse is high (63.6 percent), although median 

age at marriage remains at a medium level (18.6 years). 

 Level of premarital fertility is generally homogenous across the population, with little variation 

among ethnic groups (from 13.7 percent among the Para-Gourma to 14.4 percent among the AkpossoAkebou). 
82

Correlations of premarital fertility with age at marriage (ρ = -0.181) and urban residence 

(ρ = -0.244) were small and negative. The low correlation with age at marriage is illustrated in Figure 1, 

where the five ethnic groups show basically no association with age at marriage. 

Table 3 Premarital fertility and nuptiality indicators, Togo 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

births 

Percent 

premarital 

intercourse 

Adja-Ewe 4,293 43.1 19.2 0.6 6.3 17.5 70.0 

Akposso, Akebou 444 21.6 17.7 0.0 8.2 24.4 70.2 

Ana-Ife 286 38.6 18.1 1.4 5.8 20.3 64.8 

Kabye-Tem 3,320 33.6 18.6 0.0 5.6 15.4 57.5 

Para-Gourma, Akan 2,768 26.2 17.5 0.1 4.3 13.7 58.0 

Other and unknown 818 42.2 18.1 0.0 4.1 11.3 53.5 

 

Total 11,929 36.9 18.6 0.3 5.6 16.3 63.6 

Source: Authors’ calculations after merging data from 1988 and 1998 DHS surveys. 

Figure 1 Correlation between premarital fertility and age at first marriage, Togo 

Adja-Ewe

Akposso, Akebou

Ana-Ife

Kabye-Tem

Para-Gourma, Akan

0

10

20

30

16 17 18 19 20 21

Median age at first marriage (years)

% women with premarital birth
83

UGANDA 

Uganda conducted three DHS surveys, in 1988, 1995, and 2001 (Table 1). The 1988 DHS survey 

included 18 ethnic groups (V131); the 1995 DHS survey included 33 groups (V131) plus the language 

spoken by the respondent (SLANGRE); and the 2001 survey included only information on the language 

spoken in the cluster (SH053). The labels of ethnic groups were not provided in the code books for the 

first two surveys so, for this analysis, we relied on language spoken in the last two surveys. 

Table 1 Sample size and main characteristics of DHS surveys, Uganda 

Uganda 

DHS 

1988 

DHS 

1995 

DHS 

2001 

No. of women interviewed 4,730 7,070 7,246 

No. of ethnic groups, African 18 33 na 

No. of languages spoken, African 6 6 

Percent other and unknown 14.8 1.9 

Note: Ethnic group labels were not provided in the 1988 and 1995 surveys. 

Fortunately, the last two surveys were compatible with respect to language spoken, and could be 

merged (Table 2). 

Table 2 Distribution of ethnic groups by survey, Uganda 

Ethnolinguistic group 

DHS 

1988 

DHS 

1998 P value 

Significance 

Ateso-Karamojong 6.8 7.8 0.028 * 

Luganda 18.1 24.8 0.000 * 

Lugbara 7.5 7.3 0.722 

Luo 12.6 9.7 0.000 * 

Runyankole-Rukiga 19.2 16.8 0.000 * 

Runyoro-Rutoro 6.5 5.2 0.000 * 

Other and unknown 29.3 28.4 0.236 

 

Total 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Uganda, with an average of 6.2 percent for all births and 

17.5 percent for women. The prevalence of premarital intercourse is high (46.8 percent), although median 

age at marriage remains at a medium level (17.6 years). 

 The prevalence of premarital fertility varies by ethnicity in Uganda, with levels ranging from 11.0 

percent among the Runyankole-Rukiga to 32.7 percent among the Runyoro-Rutoro. The distribution of 

levels of premarital fertility is not continuous: four groups have rather low prevalence rates (AtesoKaramojong, Lugbara, Luo,Runyangole-Rukiga), and two groups have rather high prevalence rates 

(Luganda,Runyoro-Rutoro). 
84

The correlation of premarital fertility with age at marriage was negligible (ρ = -0.099) while the 

correlation with urban residence was average (ρ = -0.543). The low correlation with age at marriage is 

shown in Figure 1, where the six groups have basically no link with age at marriage. 

Table 3 Premarital fertility and nuptiality indicators, Uganda 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Ateso-Karamojong 925 10.5 17.7 0.0 5.4 15.7 50.8 

Luganda 3,466 38.0 18.1 1.2 10.7 27.9 59.2 

Lugbara 852 9.6 17.7 0.0 4.9 11.9 26.2 

Luo 1,388 8.7 16.9 1.8 4.4 12.1 44.7 

Runyankole-Rukiga 2,594 7.9 18.1 0.6 3.7 11.0 33.1 

Runyoro-Rutoro 821 10.7 17.4 0.0 11.7 32.7 57.8 

Other and unknown 4,270 10.8 17.2 0.3 4.7 15.3 48.6 

 

Total 14,316 15.8 17.6 0.7 6.2 17.5 46.8 

Source: Authors’ calculations after merging data from 1988 and 1998 DHS surveys 

. 

Figure 1 Correlation between premarital fertility and age at first marriage, Uganda 

Luganda

Runyoro-Rutoro

Ateso-Karamojong

Lugbara Runyankole-Rukiga

Luo

0

10

20

30

40

16 17 18 19 20

Median age at first marriage (years)

% women with premarital birth
85

ZAMBIA 

Zambia conducted three DHS surveys, in 1992, 1996, and 2001 (Table 1). All three had detailed 

information on ethnicity, and all three used the same coding. Merging the data was straightforward. 

Table 1 Sample size and main characteristics of DHS surveys, Zambia 

Zambia 

DHS 

1992 

DHS 

1996 

DHS 

2001 

No. of women interviewed 7,060 8,021 7,658 

No. of ethnic groups, African 58 50 50 

No. of ethnic categories 7 

Percent other and unknown 2.6 2.7 2.7 

Additionally, the three surveys were found to be compatible with respect to ethnicity, which, 

given the large number of groups, is unusual. After the data were merged, only groups with more than 

250 women were retained for the final analysis (Table 2). 

Table 2 Distribution of ethnic groups by survey, Zambia 

Ethnolinguistic group 

DHS 

1992 

DHS 

1996 

DHS 

2001 

Significance 

Bemba 18.8 22.6 20.4 * 

Tonga 14.4 10.9 11.6 * 

Chewa 6.8 8.1 6.4 * 

Lozi 5.1 6.0 6.3 * 

Nsenga 5.8 5.9 5.0 * 

Tumbuka 4.3 4.6 4.3 

Ngoni 4.1 3.4 4.0 * 

Lala 3.8 2.8 2.6 * 

Kaonde subgroup 2.7 2.4 2.9 

Mambwe 2.6 2.4 2.8 

Namwanga 2.0 2.6 2.9 * 

Ushi 1.8 2.6 2.7 * 

Lamba 2.1 2.1 2.2 

Luvale 1.9 2.2 2.2 

Lunda 3.5 2.5 3.7 * 

Mbunda 1.5 1.7 2.5 * 

Bisa 1.9 1.2 1.8 * 

Lenje 1.7 1.7 1.3 

Other and unknown 15.3 14.1 14.3 * 

 

Total 100.0 100.0 100.0 

*p <0.05 

Premarital Fertility by Ethnicity

 Premarital fertility is moderately high in Zambia, with an average of 7.1 percent for all births and 

20.0 percent for women. The prevalence of premarital intercourse is high (49.9 percent), although median 

age at marriage remains at a medium level (17.6 years). 
86

 Differentials in premarital fertility by ethnicity are wide in Zambia, varying from 11.8 percent 

among the Mambwe in the North, to 46.3 percent among the Mbunda in the southwest (Table 3). 

Table 3 Premarital fertility and nuptiality indicators, Zambia 

Ethnolinguistic group 

Number of 

women 

surveyed 

Percent 

urban 

Median 

age at 

first 

marriage 

(years) 

Percent 

age 40-49 

never 

married 

Percent 

premarital 

births 

Percent 

women 

with 

premarital 

birth 

Percent 

premarital 

intercourse 

Bemba 5,445 59.3 17.4 0.6 5.2 15.3 43.7 

Tonga 1,723 28.1 18.2 0.0 10.4 29.5 58.7 

Chewa 1,077 30.8 17.3 1.1 4.6 13.4 39.1 

Lozi 1,032 45.3 20.0 2.2 18.1 41.2 74.4 

Nsenga 779 49.9 17.3 0.8 6.8 18.4 46.0 

Tumbuka 624 52.4 18.0 0.0 4.7 15.2 42.3 

Ngoni 530 50.8 17.8 1.7 6.8 19.9 48.1 

Lala 1,292 49.5 17.2 0.5 8.7 23.7 55.1 

Kaonde subgroup 603 43.4 16.8 0.0 6.7 19.3 55.4 

Mambwe 368 45.4 17.7 0.0 4.1 11.8 41.3 

Namwanga 381 53.5 17.8 0.0 5.0 13.7 41.8 

Ushi 1,540 49.9 17.1 0.0 4.6 14.2 42.8 

Lamba 417 50.4 17.1 0.0 5.5 16.5 41.8 

Luvale 472 38.1 17.9 1.4 10.7 24.1 65.7 

Lunda 1,916 31.6 17.4 0.0 7.8 22.9 59.1 

Mbunda 401 7.1 18.6 1.4 19.5 46.3 78.1 

Bisa 794 40.9 18.0 0.0 9.6 27.0 56.0 

Lenje 256 48.7 18.8 4.4 12.6 31.8 70.7 

Other and unknown 3,089 38.3 17.5 0.5 6.0 17.7 46.8 

 

Total 22,739 45.4 17.6 0.5 7.1 20.0 49.9 

Source: Authors’ calculations after merging data from 1992, 1996, and 2001 DHS surveys. 

Correlation of premarital fertility with age at marriage is high (ρ = +0.754) and groups are spread 

along the age at marriage axis from about 17 years (Ushi, Lamba, Kaonde) to 20 years (Lozi) (Figure 1). 

Surprisingly, for a country that is relatively urbanized (45.4 percent) and industrialized (because 

of the copper mines), the correlation of premarital fertility with urban residence is strongly negative 

(ρ = -0.601). This finding is related to the heavy weight of southern groups that have low levels of urban 

residence and high levels of premarital fertility (Tonga, Mbunda) and northern groups that have high 

levels of urban residence and low levels of premarital fertility (Bemba, Tumbuka, Namwanga). 
87

Figure 1 Correlation between premarital fertility and age at first marriage, Zambia 

Mbunda

Lozi

Lenje

Kaonde SG

Bemba

Tonga

Chewa

Nsenga

Tumbuka

Ngoni

Lala

Mambwe

Ushi Namwanga

Lamba

Lunda

Bisa

Luvale

0

10

20

30

40

50

16 17 18 19 20 21

Median age at first marriage (years)

% women with premarital birth
DHS Comparative Reports Series 

1. Westoff, Charles F. 2001. Unmet Need at the End of the Century. 

2. Westoff, Charles F. and Akinrinola Bankole. 2002. Reproductive Preferences in Developing 

Countries at the Turn of the Century. 

3. Rutstein, Shea O. 2002. Fertility Levels, Trends, and Differentials 1995-1999. 

4. Mahy, Mary. 2003. Childhood Mortality in the Developing World: A Review of Evidence from 

the Demographic and Health Surveys. 

5. Westoff, Charles F. 2003. Trends in Marriage and Early Childbearing in Developing Countries. 

6. Rutstein, Shea O. and Kiersten Johnson. 2004. The DHS Wealth Index. 

7. Yoder, P. Stanley, Noureddine Abderrahim, and Arlinda Zhuzhuni. 2004. Female Genital Cutting in 

the Demographic and Health Surveys: A Critical and Comparative Analysis. 

8. Stallings, Rebecca. 2004. Child Morbidity and Treatment Patterns. 

9. Rutstein, Shea O. and Iqbal H. Shah. 2004. Infecundity, Infertility, and Childlessness in 

Developing Countries. 

10. Mukuria, Altrena, Jeanne Cushing, and Jasbir Sangha. 2005. Nutritional Status of Children: 

Results from the Demographic and Health Surveys, 1994–2001. 

11. Mukuria, Altrena, Casey Aboulafia, and Albert Themme. 2005. The Context of Women’s Health: 

Results from the Demographic and Health Surveys, 1994-2001. 

12. Yoder, P. Stanley, Noureddine Abderrahim, and Arlinda Zhuzhini. 2005. L’excision dans les 

Enquêtes Démographiques et de Santé : Une Analyse Comparative. 

13. Garenne, Michel, and Julien Zwang. 2006. Premarital Fertility and Ethnicity in Africa. 

14. Westoff, Charles F. 2006. New Estimates of Unmet Need and the Demand for Family Planning.