MEASURE DHS+ assists countries worldwide in the collection and use of data to monitor and evaluate

population, health, and nutrition programs. Funded by the U.S. Agency for International Development

(USAID), MEASURE DHS+ is implemented by ORC Macro in Calverton, Maryland.

The main objectives of the MEASURE DHS+ project are: 

1) to provide decisionmakers in survey countries with information useful for informed policy choices, 

2) to expand the international population and health database, 

3) to advance survey methodology, and 

4) to develop in participating countries the skills and resources necessary to conduct high-quality

demographic and health surveys.

Information about the MEASURE DHS+ project or the status of MEASURE DHS+ surveys is available on the

Internet at http://www.measuredhs.com or by contacting: 

ORC Macro

11785 Beltsville Drive, 

Suite 300

Calverton, MD 20705 USA

Telephone: 301-572-0200

Fax: 301-572-0999

E-mail: reports@macroint.com
DHS Analytical Studies No. 3

Trends and Differentials in Adolescent

Reproductive Behavior in Sub-Saharan Africa

Mary Mahy

Neeru Gupta

July 2002

ORC Macro

Calverton, Maryland USA
Recommended citation:

Mahy, Mary and Neeru Gupta. 2002. Trends and Differentials in Adolescent

Reproductive Behavior in Sub-Saharan Africa. DHS Analytical Studies No. 3.

Calverton, Maryland: ORC Macro.
iii

Contents

Page

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

1 Introduction and Background .................................1

2 Conceptual Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Operationalizing the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

3 Data and Methods ..........................................7

3.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.2 Data Quality ....................................7

3.3 Statistical Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4 Levels and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4.1 Sociodemographic Characteristics . . . . . . . . . . . . . . . . . . 12

4.2 Reproductive Health Knowledge . . . . . . . . . . . . . . . . . . . 14

4.3 Reproductive Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.4 Differentials in Reproductive Health Knowledge

and Behavior by Sociodemographic Characteristics . . . . . 18

Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Urban-rural Residence . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Exposure to Mass Media . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Contextual Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

5 Determinants of Changes in Adolescent Reproductive Behavior . . . . . 27

5.1 Age at First Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

5.2 Age at First Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

5.3 Age at First Union . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

6 Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
v

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

Analytical Studies series and the DHS Comparative Reports series examine these

data, focusing on 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. Whereas Comparative Reports

are primarily descriptive, Analytical Studies take a more analytical approach. 

The Analytical Studies series comprises in-depth, focused studies on a

variety of substantive topics. The studies are based on a variable number of data

sets, depending on the topic under study. A range of methodologies is used,

including multivariate statistical techniques. The topics covered are selected by

MEASURE DHS+ staff in conjunction with the MEASURE DHS+ Scientific

Advisory Committee and USAID.

It is anticipated that the Analytical Studies will enhance the understanding

of significant issues in the fields of international population and health for analysts

and policymakers.

Martin Vaessen

Project Director
vi

Acknowledgments

The authors wish to thank Darrin Helsel for assistance in preparing a

literature review, and Charles Westoff and Ties Boerma for useful comments toward

the final drafting of this report.
vii

Executive Summary

Fertility levels in sub-Saharan Africa are among the highest in the world.

Much of the high fertility can be attributed to young age at first sex, young age at

first union, and young age at first birth. At the same time, there is wide variation in

early initiation of reproductive behavior across countries and between subgroups in

the same country. This paper examines the trends and differentials in age at first sex,

age at first union, and age at first birth in the adolescent populations in selected subSaharan countries.

The study draws on data from Demographic and Health Surveys carried out

in eight countries—Burkina Faso, Côte d’Ivoire, Ghana, Kenya, Mali, Senegal,

Tanzania, and Zimbabwe. These countries had at least two surveys conducted

approximately five years apart, with questionnaires for women and men of

reproductive age.

The main analytical tool used to carry out the study is a multivariate logistic

model that uses a generalized estimating equation to consider the probability of a

young woman having a birth, sex, or union before age 18. The study also considers

the probability of a young man engaging in first sex or union before age 20.

The results suggest that certain sociodemographic characteristics of

adolescents, particularly education, have a strong influence on early reproductive

outcomes. However, the direction of the relationship is not always the same for

young women as for young men. The effects of community characteristics are

inconclusive. While these results may be useful for identifying target groups for

reproductive health services and outreach programs, further research is needed to

find more appropriate community-level measures for assessing adolescent

reproductive behavior.
1

 Among the documented health consequences of early childbearing are higher than average levels of toxemia, anemia,

bleeding, cervical trauma, prolonged and difficult labor, premature delivery, and death. Children born to teenage

mothers are susceptible to higher incidence of low birth weight (which can lead to neurological problems, retardation,

and death), prematurity, stillbirth, and perinatal mortality (Senderowitz and Paxman, 1985).

1

1 Introduction

Over the past four decades the developing world has seen important changes in reproductive behavior

in both adult and adolescent populations. Fertility has declined rapidly in the face of higher levels of

schooling, better health care, increased urbanization, and greater exposure to modern forms of mass

communication. In developing countries in particular, estimates indicate that fertility has dropped by about

one-third, from an average of six lifetime children per woman in the 1960s to about four today. However,

wide variations in reproductive behavior persist at the national and subnational levels, and across social

groups. While much research has been carried out on the causes and consequences of differential behavior

among adults, until recently adolescents have received relatively little attention. The factors that influence

adolescents to behave similar to, or different from, adults remain less understood.

In conjunction with an increasing body of literature on adolescent reproductive behavior produced

in the past decade, concerns are increasing over the health, social, and economic consequences of early sexual

activity, pregnancy, and childbearing. A review of the literature reveals a number of potentially adverse

impacts of early sex, including unplanned pregnancy and exposure to sexually transmitted infections (STIs)

through unprotected sex. Early childbearing has been linked to higher rates of maternal and child morbidity

and mortality,1

 truncated educational opportunities, and lower family income. Larger completed family size

is one of the long-term demographic effects of adolescent fertility because the timing of the first birth is

usually an indicator of future fertility patterns (see Menken, 1980; Senderowitz and Paxman, 1985;

Voydanoff and Donnelly, 1990; Wulf and Singh, 1991).

The Program of Action of the International Conference for Population and Development, recently

reaffirmed the priority of providing reproductive health services for youth (United Nations, 1999). To achieve

this objective, policymakers need a better understanding of the causes and consequences of initiation of

reproductive behavior among adolescents. The purpose of this report is to present a comparative perspective

on determinants and trends in the timing of sexual activity, union formation, and childbearing during

adolescence. The analysis draws on data collected by Demographic and Health Surveys (DHS) in eight subSaharan countries in which at least two surveys were conducted, each with questionnaires for women and men

of reproductive age.

The report is divided into six sections. Following the introduction, section 2 outlines a conceptual

framework for the analysis of adolescent reproductive behavior. Section 3 details the data and statistical

methods being used. Section 4 presents descriptive analyses of the trends in sociodemographic characteristics,

reproductive health knowledge, and reproductive practices of the adolescent populations in each country.

Section 5 focuses on multivariate analyses of changes in reproductive behavior among the target groups.

Section 6 summarizes results and explores the policy and programmatic implications.
2

 It is likely that the duration of the fertile period varies across societies in sub-Saharan Africa but is increasing over time

as the average age at menarche declines under conditions of improved nutritional status (Meekers, 1994). Different

levels of sterility might also exist due to sexually transmitted infections.

2

Table 2.1 Summary of DHS surveys used in this

analysis, 1987-1999

________________________________________

Year of fieldwork _________________________

Country Earlier survey Later survey

________________________________________

Burkina Faso 1993 1998/99

Côte d’Ivoire 1994 1998

Ghana 1993 1998

Kenya 1993 1998

Mali 1987 1995/96

Senegal 1992/93 1997

Tanzania 1991/92 1996

Zimbabwe 1994 1999

2 Conceptual Framework

Sub-Saharan Africa has some of the highest levels of adult and adolescent childbearing in the world.

Since the 1980s, several countries in the region have begun a transition to lower fertility. This has generally

been accompanied by an upward trend in the age at first birth, although wide variations remain across

countries and social groups.

The present study examines trends in age at first birth among women in eight countries in subSaharan Africa (Burkina Faso, Côte d’Ivoire, Ghana, Kenya, Mali, Senegal, Tanzania, and Zimbabwe),

drawing on information from successive DHS surveys conducted between 1987 and 1999 (see Table 2.1).

The goal is to evaluate the risk of a young woman having a first birth before age 18. Because of the strong

associations between fertility and sexual activity and union formation, our analysis also focuses on changes

in age at first sex and age at first union. Trends in male reproductive behavior are explored where data permit.

We systematically look at changes over time for any evidence of patterns at the individual and contextual

levels that could help explain early initiation of reproductive behavior. Understanding the sociodemographic

causes of changes in behavior will assist program planners and policymakers in creating programs aimed at

improving reproductive health care for adolescents.

The framework for this analysis is based on the Bongaarts model of proximate determinants which

measures the effects of behavioral and biological variables on fertility (Bongaarts, 1978). These intermediate

variables are the pathways through which sociodemographic variables directly influence fertility outcomes.

They pertain to the three stages of the reproductive process: intercourse, conception, and gestation and

parturition. The intermediate variables are: proportion of reproductive age who are married or in union,

frequency of sex, contraceptive use, lactational infecundability, duration of the fertile period, sterility,

spontaneous abortion, and induced abortion. These variables are considered to most directly influence

fertility in any society.

Borrowing from this framework, we can consider only those variables that affect the probability of

early first birth. Because lactational infecundability only applies to women who have a previous child, it is

dropped for this model. Given the lack of consistent, reliable data, such variables as duration of the fertile

period,2

 sterility, and abortion (induced or spontaneous) are not considered here. Age at entry into union, age

at first sex, and contraceptive use remain as intermediate variables that affect the timing of the first birth.
3

 It has been noted elsewhere (Westoff, Blanc, and Nyblade, 1994) that in some sub-Saharan societies a considerable

amount of childbearing goes on outside of cohabiting relationships. The two countries where this is most common are

Botswana and Namibia, neither of which is included in this analysis.

3

Intermediate fertility variables Intermediate variables for early first birth ________________________________________________________________________

Proportion married or in union Age at first union

Frequency of sex Age at first sex

Contraceptive use Contraceptive use

Lactational infecundability Lactational infecundability (not applicable)

Duration of fertile period Age at menarche (not considered here)

Sterility Sterility (not considered here)

Induced abortion Induced abortion (not considered here)

Spontaneous abortion Spontaneous abortion (not considered here)

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 2.1 Percentage of women age 15-19 

who had their first birth before age 18 and out 

of union, by relative date of survey

%

Early initiation of sexual activity warrants particular attention among both males and females given

the risk of contracting or transmitting a sexually transmitted infection such as HIV/AIDS. The risk of

contracting a disease is affected by the age of sexual debut. An individual who initiates sexual activity at age

15, for example, will have more exposure to STIs over the reproductive period than one who initiates sex at

age 20. Also, sexual activity at a younger age is often associated with greater likelihood of unprotected

intercourse and multiple partners, which can leave the adolescent at greater risk of STIs (Blanc and Way,

1998).

Early entry into union is considered to be strongly associated with early childbearing. Assuming that

living with a partner exposes individuals to regular sexual activity, union formation will increase the

probability of conception. For most countries in sub-Saharan Africa, the majority of childbearing occurs in

union,3

 but in both Côte d’Ivoire and Kenya about half of first births among women under age 18 occurred

out of union (Figure 2.1). In some societies an early birth is seen as securing the marriage because it

demonstrates the woman’s fecundity to the man’s family and increases her social standing. In such a case,

union formation is not a determinant of the first birth, rather the first birth is a determinant of union formation.

The effects of early union formation on risk of STIs are mixed. If the couple remain faithful to each

other, the risk of infection is reduced for both partners. However, if a young woman marries an older man

who is more sexually experienced, she may have increased exposure to STIs.
4

 Modern contraceptive methods include male and female sterilization, the pill, the IUD, injectables, implants, condoms,

and vaginal methods (foam, jelly, or diaphragm).

5

 While the intervals between surveys may be somewhat short, collection of information from male respondents is a

relatively recent practice in the Demographic and Health Surveys. Future implementation of male surveys should

improve researchers’ ability to conduct gender-specific, trend analyses.

4

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 2.2.2 Percentage of men age 15-19 who 

had first sex before age 18 and reported ever 

use of modern contraceptive methods,

% by relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 2.2.1 Percentage of women age 15-19 

who had first sex before age 18 and reported 

ever use of modern contraceptive methods,

% by relative date of survey

DHS surveys provide information about ever use and current use of contraceptive methods. As seen

in Figures 2.2.1 and 2.2.2, ever use of modern methods4

 among adolescent populations varies by sex.

Contraceptive use tends to be higher among men than women largely due to greater use of condoms. In most

countries, contraceptive use is increasing over time for both sexes. It should be noted that ever use of

contraceptive methods does not necessarily imply continual use since sexual debut or consistent use with

every, or even any, partner. The direction of the causality between contraceptive use and sexual initiation and

union formation among adolescents may be difficult to trace. Many health delivery systems in sub-Saharan

Africa provide contraceptives only to married women. However, unmarried adolescents, who may be more

likely to have multiple partners, face greater risk of unplanned pregnancy or STI infection. Given the general

lack of data in these countries on duration of contraceptive use and level of accessibility to reproductive

health services among adolescents, contraceptive practice is measured indirectly in our multivariate models

through the community-level family planning environment (described below).

Operationalizing the Model

DHS surveys collect data on age of first birth, age of first sex, and age of first union for female

respondents. Age of first sex and age of first union are generally collected for male respondents. All the

countries analyzed in this report had surveys at least four years apart5

 so it is possible to use young adult data

from two points in time to conduct trend analyses. This allows the assumption of similar recall biases and

background variables that best reflect the situation at the time of the event.

Our analysis first examines the probability of a woman having a first birth before age 18. The trends

and differentials of this event then lead us to seek a better understanding of what influenced the observed

changes in adolescent fertility. Two intermediate variables, age at first sex and age at first union, are

considered here as outcomes. Because the histories of women under age 18 are incomplete, we only include

in our multivariate models women age 18-24 at the time of each survey. Trends and differentials in the

probability of a man having first sex and first union before age 20 are also considered. The different age

groups for men and women were chosen primarily because of data constraints (some surveys only collected

data for men 20 years and older) and to ensure sufficient sample sizes. Only men age 20-29 are included in

the multivariate analyses to avoid problems of censored observations.
5

Intermediate variables

Age at first union

Age at first sex

Individual characteristics

Education

Urban-rural residence

Mass media exposure Outcomes

Early first birth

Risk of STIs

There are large differences in reproductive behavior between young men and women. In many

African societies men start sexual behavior and marry at a later age than women. The repercussions of early

fertility are also different for both sexes. For this reason it is important to evaluate both adolescent women’s

and adolescent men’s reproductive health needs. The following analysis considers both female and male

models of adolescent reproductive behavior to emphasize the differences between the two sexes.

Figure 2.3 diagrams how individual and community characteristics affect intermediate variables,

which in turn influence reproductive health outcomes. Risk of STIs (including HIV/AIDS), as well as early

fatherhood among men, are evaluated through observation of the intermediate variables.

Figure 2.3

Framework for assessing adolescent reproductive outcomes

Several characteristics related to individuals and their communities have been linked in the literature

to changes in reproductive behavior. Theories of fertility transition suggest that modernization dissolves

traditional tendencies toward large families and replaces those tendencies with individualism marked by

material aspirations. Based on early research and observation in pre-modern populations and contemporary

industrial countries, the theory claims that, with sufficient modernization, fertility (and mortality) will

inevitably fall (see Caldwell, 1976; Coale, 1973; Farooq and DeGraff, 1988; Simmons, 1985).

Four widely recognized, empirically identifiable aspects of modernization are identified in Easterlin

(1983) as follows: innovations in formal schooling; innovations in public health and medical care;

urbanization; and the introduction of new goods. We will attempt to model these basic social influences and

examine how changes in reproductive outcomes occur in different subgroups among the adolescent

populations of the eight countries.

A strong correlation between education and reproductive outcomes consistently emerges from

empirical applications throughout the developing world. Evidence of correlations exist between education

and reduced fertility, increased contraceptive use, and delayed union formation (see, for example, Ainsworth,

1994; Martin and Juarez, 1995; Robey et al., 1992). Mboup and Saha (1998) found that in many sub-Saharan

countries, including Burkina Faso, Ghana, and Senegal, women with no schooling have two or three children

more than women with secondary or higher education.

Among adolescents, while we expect more education to be associated with a lower probability of

early first birth, the direction of causality is unclear. Young women may decide to delay childbearing in order

to complete their formal education. On the other hand, some teenage mothers may be forced to leave school

early after having a child. For example, according to the 1996 DHS survey in Mali, 12 percent of adolescent

women (age 15-19) who were no longer attending school indicated a pregnancy or marriage as the main

reason they left. We have elected to limit the category for high educational attainment in our multivariate

models to eight or more years of schooling, in hopes of reducing the likelihood of biases in terms of the

Community characteristics

Family planning environment

Socioeconomic development
6

number of young respondents who might not have finished their education at the time of the survey, or who

may have been obliged to leave school early due to an event related to pregnancy or marriage.

Urban-rural residence is another variable considered to influence reproductive outcomes. The

distinction between urban and rural residence is important because of differences in access to health facilities,

cultural beliefs, and living situations. According to transition theory, modern urban-commercial life produces

special motivational constraints on childbearing. Costs of children are highest in urban areas, where nearly

everything must be bought.

Access to modern goods and ideas can also affect an individual’s reproductive decisions. Cleland and

Wilson (1987) suggest that the spread of new knowledge and technology can help explain observed patterns

of fertility decline in many low-income countries, independent of economic circumstances. Research has

found that exposure to modern forms of mass communication in particular has a strong effect on reproductive

outcomes, especially on contraceptive use and age at marriage (Adamchak and Mbvizo, 1991; Westoff and

Bankole, 1997). We consider in this analysis radio listenership as representative of access to the mass media

and new ideas. Listening to the radio can occur outside the respondents’ home and, therefore, may be less

strongly associated with economic status as compared with radio ownership. Radio is the medium selected

here because of the diversity of development levels among the countries studied. This variable needs to be

interpreted carefully since television and newspapers may be more popular among young respondents in some

countries.

At the contextual level, indirect variables include access (physical, financial, and sociocultural) to

reproductive health care, which affects the risk of early childbearing or STIs. For example, a strong

reproductive health program in the community could influence an individual’s familiarity with contraception

and knowledge of how to avoid contracting STIs. While improving knowledge and practices is an important

component of many reproductive health programs, modeling impacts based on individual-level survey

responses poses statistical problems. Attempts to include indicators of reproductive health knowledge and

service use among youth may fail to completely overcome problems of endogeneity.

Ideally, the contextual variable on health care in the multivariate analyses would be measured

independently from health facility data on outreach programs and on the use of services by adolescents. The

availability of such data is limited in the DHS program. Alternatively, the strength of local health programs

can be measured through proxy indicators of whether a large proportion of the population of reproductive age

in the community has practiced family planning. As will be described in detail in the next section, this

proportion can be measured through cluster-level aggregates of the number of adults who have reported ever

using modern contraceptives.

Lastly, there is increasing evidence that adolescents are strongly influenced by their environment,

suggesting that community characteristics might influence reproductive behaviors. Lloyd, Kaufman, and

Hewett (2000) suggest that in areas that have not yet achieved mass schooling, development will be slow

because of the slower pace of social interaction and diffusion, resulting in a lagging fertility decline. In our

models we use cluster-level aggregates of educational attainment among adults as proxy for the local

socioeconomic development context.
6

 Women age 15-49. Men age 15-54 in most countries; age groups 20-54 in the earlier Kenya survey, 20-55 in the earlier

Mali, and 20 and over in both Senegal surveys.

7

3 Data and Methods

3.1 Data

The DHS program has been producing cross-national and comparative quantitative data on fertility

in developing countries since 1985. The bulk of the information is collected from personal interviews with

a representative sample of women of reproductive age (although in certain countries coverage is limited to

ever-married women). The standard DHS questionnaire addresses fertility, family planning, and maternal and

child health. In some cases additional questionnaires are included for husbands/males and on community-level

service availability.

Repeat surveys, usually conducted around five years apart, allow researchers to evaluate national

trends. Over time the standard questionnaire has expanded to collect more in-depth data on a broader range

of reproductive-related behavior and health topics such as knowledge and practices related to STIs and

HIV/AIDS or the prevalence of anemia.

The surveys are carried out in a standardized manner, although questionnaires may be adapted to the

needs and conditions of a specific country. Survey samples are designed using scientific sampling probability.

Most samples use two-stage stratified designs: selection of area units or clusters in a single stage, normally

with probability proportional to size, followed by selection of households.

The present study draws on information collected from samples of women and men regardless of

marital status from surveys conducted at least four years apart to allow for trend analysis in particular age

groups. Each survey included separate women’s and men’s questionnaires for examining gender differentials.

The DHS countries retained are Burkina Faso, Côte d’Ivoire, Ghana, Kenya, Mali, Senegal, Tanzania, and

Zimbabwe. The surveys generally cover six to eight thousand women and two to three thousand men of

reproductive age.6

3.2 Data Quality

Our analysis focuses on the probability of early initiation of reproductive behavior, using

retrospective data compiled from young women and (where available) from young men on age at first birth,

age at first sex, and age at first union. Because the study is heavily dependent on information pertaining to

the timing of events, an assessment of the quality of age-related responses is important.

As with all survey data based on individuals, responses in the DHS surveys are not immune to errors

such as recall errors due to memory lapses, duration heaping, and event omission (both deliberate and

accidental). Previous studies have examined the quality of information on current age reported at the time of

interview (Rutstein and Bicego, 1990), age at initiation of reproductive behavior (Blanc and Rutenberg, 1990;

Gage, 1995), and other demographic measures (Marckwardt and Rutstein, 1996). In general, the quality of

age reporting can be considered better among the youngest age groups and improving across survey rounds.

In the DHS individual questionnaire, the respondent’s age is obtained by asking both the birth date and age

in completed years. While there is no record of how age was recorded under circumstances when the

respondent could report neither current age nor year of birth, interviewers are considered likely to have placed

respondents at about the middle of the age range, usually between 30 and 40 years (Rutstein and Bicego,

1990).
8

Figure 3.1.1 Percentage of women with

current age/year of birth reported,

by age group and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 15-24 25-49

Earlier Later

Figure 3.1.2 Percentage of men with

current age/year of birth reported,

by age group and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 15-29 30-54

Earlier Later

As seen in Figures 3.1.1 and 3.1.2, the expected trend toward better current age information among

women and men in the youngest age groups and over time can be noted for the eight sub-Saharan countries.

In most countries, at least 90 percent of young respondents of either sex could provide current age or year

of birth information in the latest survey. However some problems remain. Changes in questionnaire design,

training of interviewers, fieldwork implementation, and data processing across survey phases can affect the

quality of the information obtained. In Mali in particular, only a third of female respondents provided age or

year information in the earlier survey, but in the later survey the information was recorded as complete. This

difference is probably due to a change in survey implementation and training as opposed to an increase in

respondents’ knowledge of their age.

Information on the timing of the first birth is only collected from women in DHS surveys. A detailed

birth history is obtained from female respondents. It includes all live births in the woman’s lifetime, along

with the age, birth date, sex, survival status, and living arrangements of each child. Age at first birth is

calculated as the difference between the date of birth of the woman and the date of birth of her first child.

While the accuracy of information on age at first birth is dependent on that of the date of birth of the first

child, the probability of recall errors is less among younger women.

With regard to the timing of first sex, the DHS questionnaires collect information on age at first sex

from male and female respondents in most countries. Because only age (and not year) information is

collected, comparable analysis on the completeness of date reporting is not possible. Some researchers have

voiced concern that respondents, especially teenagers, might be uncomfortable with the topic of sexual

activity. However, low levels of nonresponse or inconsistency in reporting of age at first sex in the DHS

surveys indicate willingness of the target populations to answer such questions. Tabulations of consistency

of reported age at first sex by current age group among women and men are presented in Figures 3.2.1 and

3.2.2. In most of the countries (and where data were available), age at first sex was missing or inconsistent

in less than 10 percent of cases.

In the DHS program, unions are generally defined as encompassing both formal marriage and

consensual union. The DHS questionnaires ask respondents whether they have ever been married or have

lived with a member of the opposite sex, and if so the age at which and date when they first entered into

union. Collecting both age at first union and date of first union allows for checks on the consistency of

information on first union formation.
9

Figure 3.2.1 Percentage of sexually experienced 

women with consistent age at first sex reported,

by age group and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 15-24 25-49

Earlier Later

Figure 3.2.2 Percentage of sexually experienced 

men with consistent age at first sex reported,

by age group and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 15-29 30-54

Earlier Later

Figure 3.3.1 Percentage of women ever in union with 

age/year at first union information reported,

by age group and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 15-24 25-49

Earlier Later

Figure 3.3.2 Percentage of men ever in union with 

age/year at first union information reported,

by age group and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 15-29 30-54

Earlier Later

In general, fewer problems of incompleteness or inconsistency for age at first union and date of first

union are noted among younger male and female respondents and over time (Figures 3.3.1 and 3.3.2). While

date displacement or omission may be less of an issue with younger respondents, a potentially greater

problem of data quality is the failure to report certain unions because they were of short duration, not socially

recognized, or were followed by more stable unions.

In sum, while caution must be exercised when using survey data, particularly in countries in subSaharan Africa that have poor documentation and knowledge of dates, improvements in quality of age

reporting can be noted over the course of the DHS program. The impact of such improvements on the

direction of timing of first reproductive events remains unknown. But by limiting our focus to respondents

in the youngest age groups, we may minimize the bias of recall errors, which tend to be more frequent among

older respondents, whose first experience with reproductive behavior generally took place several years

earlier. For this reason there is a distinct advantage in analyzing trends within a given age group from

successive surveys instead of using selected cohorts from one cross-sectional database in a retrospective

study.
7 In most countries, adult education was obtained from the number of women and men age 25 or over with 8 or

more years of schooling as reported in the household schedule. In the later Côte d’Ivoire, later Senegal, and both

Mali surveys, the level of adult schooling was compiled by pooling responses from the individual women’s and

men’s datasets.

10

3.3 Statistical Methods

Our analysis uses multivariate regression models to evaluate trends and determinants of adolescent

reproductive outcomes. The focus is on the probability of a young woman having first birth, first sex, and first

union before age 18, and the probability of a young man having first sex and first union before age 20. A

logistic link is used to model the dichotomous outcomes.

We use a generalized estimating equation to avoid the inefficient estimation of coefficients that result

from the cluster-based DHS sampling structure. The standard logistic model assumes that the distribution of

the error term follows a binomial distribution and the outcomes are random and independent. However,

respondents in the same community or cluster are likely to demonstrate similar characteristics and behaviors

(due to a number of unmeasured and unmeasurable factors), implying that the outcomes are not independent

within clusters. General estimating equations allow us to estimate the model parameters while controlling for

intracluster correlation (Liang and Zeger, 1993).

Included in the regressions are a number of variables related to individuals’ sociodemographic

characteristics (education, urban-rural residence, and exposure to mass media) as well as contextual variables

(community development and family planning environment). Community characteristics are captured through

aggregating men and women’s individual-level responses within a cluster. Clusters in the DHS surveys are

made up of roughly 200 households in a defined geographical area, from which approximately 30 households

are randomly selected in each area to be interviewed. A proxy for community development is measured

through the proportion of adult women and men (age 25 or over) in the cluster who have eight or more years

of schooling.7

 Communities where at least 20 percent of all adults have achieved this level of schooling are

considered to have a higher socioeconomic development. An exception was made for Mali: because of the

small number of educated adults, the cutoff for higher status was set at 10 percent.

Family planning environment is evaluated through the pooled responses for ever use of modern

contraceptive methods among adult women and men in the cluster. For most countries, communities where

at least 50 percent of adults had ever used contraception are considered to have a better reproductive health

care environment. For Mali the cutoff for stronger family planning environment was set to at least 10 percent

of adults who have ever used contraception, while for Zimbabwe it was set to at least 80 percent. It should

be noted that, in order to capture the community-level characteristics, each cluster must have a sufficient

number of respondents to make a valid assessment of the situation. In cases where we are only interested in

a specific age group, it is unlikely that there will be enough individuals per cluster that match the criteria.

Thus cluster-level estimates for the proportion of adolescents who have ever used modern contraception are

not deemed reliable.

The key hypothesis being tested is that changes in sociodemographic and contextual variables

associated with a process of modernization influence adolescents’ risk of early first birth, first sex, and first

union. Given the important differences in the underlying social and biological processes shaping reproductive

behaviors among women and men, each sex is treated distinctly. Separate models are run for each country

to take account of unobserved variables not captured here. Trends in the effects of sociodemographic and

community variables are analyzed through interaction terms of the characteristic on the survey period. These

interaction terms are used to specify how the influences on the outcomes have changed between surveys.
11

The coefficients in the regression outputs can be described as the log of the odds for a given category

of a variable over the odds for the base category of the same variable. To ease interpretation, our results will

be expressed in terms of odds ratios, which are calculated by exponentiating the parameters. A ratio greater

than unity implies that an individual in the given category would be more likely to have a first birth, first sex,

or first union before age 18 (or 20 for males) compared with a counterpart in the base category. A ratio lower

than unity signals that an individual in the given category is less likely to experience the event during

adolescence compared with a counterpart in the base category.
8

 Characteristics refer to those reported at the time of the survey. For the earlier Kenya and Mali surveys and both

Senegal surveys, the male sample considers those age 20-24 years.

12

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.1.1 Percentage of women age 15-19 

with 8 or more years of schooling,

by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.1.2 Percentage of men age 15-19 with 

8 or more years of schooling,

by relative date of survey

4 Levels and Trends

This section first looks at trends in the sociodemographic characteristics, reproductive health

knowledge, and reproductive behavior among the adolescent populations in selected countries of sub-Saharan

Africa. We then identify some of the interrelationships between these traits as a prelude to modeling the

possible determinants of reproductive outcomes in the target groups.

4.1 Sociodemographic Characteristics

Evidence from the DHS surveys points to large disparities in the sociodemographic status of

adolescent populations8

 across sub-Saharan Africa. In most countries, levels of schooling are substantially

lower for women (Figure 4.1.1) than for men (Figure 4.1.2). Only in Tanzania, where education levels are

very low for both sexes, and in Zimbabwe, where education levels are relatively high, are the levels similar

for young women and young men.

Fewer than 10 percent of young women have eight or more years of schooling in Burkina Faso, Mali,

and Tanzania. On the other hand, the majority of young women had attained this level of schooling in

Zimbabwe (66 percent) and Ghana (51 percent) according to the most recent survey findings. A majority of

young men have eight or more years of schooling in Kenya (72 percent), Zimbabwe (65 percent), Ghana (59

percent), and Côte d’Ivoire (58 percent). Rapid improvements in schooling between surveys can be noted in

a few countries: Kenya, Senegal, and Zimbabwe for women; and Côte d’Ivoire, Mali, Senegal, and Zimbabwe

for men. In Burkina Faso, the proportion of better-educated adolescents decreased among both sexes.

As seen in Figures 4.2.1 and 4.2.2, all eight countries are predominantly rural. Only in Senegal are

a majority of young men (55 percent) living in urban areas. Burkina Faso is the least urban society. Kenya

and Senegal are characterized by a somewhat more urban male population than female population, but in all

countries the differences by sex remain under 10 percentage points.
9

 In the earlier surveys for Burkina Faso, Côte d’Ivoire, Ghana, and Kenya, and in both surveys for Mali, Senegal, and

Tanzania, respondents were asked whether or not they usually listen to the radio once a week. In the later surveys for

Burkina Faso, Côte d’Ivoire, Ghana, and Kenya, and for both surveys in Zimbabwe, respondents were asked whether

or not they usually listen to the radio every day.

13

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.2.2 Percentage of men age 15-19 

living in urban areas, by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.2.1 Percentage of women age 15-19 

living in urban areas, by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.3.1 Percentage of women age 15-19 

who listen to the radio regularly,

by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.3.2 Percentage of men age 15-19 who 

listen to the radio regularly,

by relative date of survey

Exposure to radio varies across the countries in the region. The majority of adolescents of both sexes

listen to the radio regularly9

 in Ghana, Kenya, Mali, and Senegal (Figures 4.3.1 and 4.3.2). In contrast, at most

one-quarter of adolescent women reported listening to the radio in the latest survey in Burkina Faso and in

Côte d’Ivoire, where listenership has fallen over time. In most countries, exposure to radio is higher among

young men than among young women.

Such characteristics of the adolescent populations suggest general modernizing trends across the

region. There remain strong differentials across countries, however, and even across subgroups within each

country. The implications of such disparities would undoubtedly affect other aspects of individuals’ lives,

in particular reproductive health knowledge and behaviors.

4.2 Reproductive Health Knowledge
10 The age group 15-19 was chosen for this analysis because it most closely approximates the level of young women

and men’s knowledge of reproductive health when they enter their reproductive years. (For the earlier Kenya and Mali

and both Senegal surveys, the male sample considers those age 20-24 years.)

14

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100 Earlier

 Later

Figure 4.4.1 Percentage of women age 15-19 

with knowledge of modern contraception,

by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100 Earlier

 Later

Figure 4.4.2 Percentage of men age 15-19

with knowledge of modern contraception,

by relative date of survey

%

Behavior change communication (BCC) campaigns are an important component of most successful

reproductive health interventions. Data from the DHS surveys allow a descriptive portrait to be drawn on the

levels and trends of knowledge of reproductive health issues among young women and men in the countries

being studied10. Individuals who are adequately informed about reproductive health may be better able to

exercise options favoring improved health status.

As seen in Figures 4.4.1 and 4.4.2, knowledge of modern contraceptive methods varies across

countries and generally increases over time. Knowledge tends to be higher among males. According to the

most recent survey findings, at least 90 percent of young men in Côte d’Ivoire, Ghana, Kenya, Senegal, and

Zimbabwe know of one or more modern contraceptive methods. The lowest levels of knowledge are found

in Tanzania (65 percent) and Mali (75 percent). Among women, the proportion with knowledge of modern

contraception reaches at least 90 percent in Côte d’Ivoire, Kenya, and Zimbabwe. Only two-thirds have

knowledge in Burkina Faso, Mali, and Tanzania. The greatest intersurvey increase was observed in Mali,

where knowledge of modern methods was lowest among the earlier surveys.

The DHS program collects information from women on their knowledge of the ovulatory cycle.

Knowledge of basic reproductive physiology remains poor across the region. Fewer than 10 percent of young

women could correctly identify the fertile period in the latest surveys in Burkina Faso, Mali, Senegal,

Tanzania, and Zimbabwe (Figure 4.5). Even in Côte d’Ivoire where knowledge is highest barely a third of

women age 15-19 know when the fertile period occurs. There was little sign of improvement in any country.

Figures 4.6.1 and 4.6.2 present data on young women’s and men’s knowledge of ways to avoid

getting HIV/AIDS. Although awareness of AIDS is widespread, methods of AIDS prevention are less well

known. Most AIDS-prevention programs focus on using condoms, limiting the number of sexual partners,

staying faithful to one partner, and abstaining from sexual intercourse as ways to prevent transmission of

HIV. According to information from the most recent DHS surveys, knowledge of condoms as a barrier

method is highest in Côte d’Ivoire and Zimbabwe, where about half of young women and two-thirds of young

men reported knowledge. Ways to avoid HIV/AIDS related to the level of sexual activity (abstaining from

sex, limiting sex to one faithful partner, avoiding multiple partners, avoiding prostitutes) were reported by

at least 60 percent of young women in Côte d’Ivoire, Ghana, and Zimbabwe, and by at least 60 percent of

young men in Senegal and Zimbabwe. In most of the countries studied, knowledge of these latter ways to
15

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.5 Percentage of women age 15-19

with knowledge of the fertile period in the 

ovulatory cycle, by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100 Condom use

Abstinence/limit partners

No misconceptions

Figure 4.6.1 Percentage of women age 15-19

with knowledge of ways to avoid HIV/AIDS

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100 Condom use

Abstinence/limit partners

No misconceptions

Figure 4.6.2 Percentage of men age 15-19

with knowledge of ways to avoid HIV/AIDS

%

avoid HIV/AIDS was as great or greater among women than among men, in contrast to knowledge of

condoms, which was substantially lower among women across all countries.

At the same time, misconceptions about HIV/AIDS transmission are common. Fewer than half of

young women in Burkina Faso, Mali, and Senegal indicated correct knowledge of ways to prevent

HIV/AIDS; the majority reported no means or gave erroneous responses not associated with changes in sexual

behavior (among them, avoiding kissing, avoiding mosquito bites, or seeking protection from a traditional

healer). Less than two-thirds of men in Burkina Faso, Ghana, and Mali reported only correct ways to avoid

HIV/AIDS. In all countries except Ghana young women were less likely to be properly informed about AIDS

prevention than their male counterparts.

Many important differences are seen across young women’s and men’s knowledge of reproductive

health issues, and only small improvements were noted between surveys. While awareness of modern

contraception is generally widespread, other aspects remain less well known. Such differentials in the range

of reproductive health knowledge could hold important implications for adolescents’ decisionmaking

processes.

4.3 Reproductive Behavior
11 Data on age at first birth, first sex, and first union among women refer to retrospective information collected from

respondents age 18-24 at the time of the survey. Among men, data on age at first sex and age at first union are compiled

from respondents currently age 20-29.

16

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.7 Percentage of women age 18-24 

who had first birth by age 18, by relative date 

of survey

%

Most of the sub-Saharan countries being studied experienced a decline in adolescent fertility between

the surveys, though important differentials emerge. Figure 4.7 presents the trends in the proportion of young

women11 who had a first birth before age 18 for each survey. The proportion is seen to have declined for all

countries in the study except for Burkina Faso. The highest level of adolescent childbearing was observed

in Mali (45 percent). In contrast, less than a quarter of young women had had an early first birth in Ghana,

Kenya, and Zimbabwe. Côte d’Ivoire witnessed the largest intersurvey reduction in the proportion of first

births occurring to women under the age of 18 (from 41 to 28 percent). In Mali, the difference was only

marginal. This is noteworthy given that Mali also had the largest interval between surveys (in most countries

the time between surveys averaged about five years; however, in Mali the surveys were eight years apart).

Similar trends are observed in terms of the proportion of young women who had first sex and first

union before age 18 (Figures 4.8.1 and 4.8.2). Most countries showed declines over time in the level of

adolescent sex. Only in Kenya is a slight increase noted. The highest level of adolescent sexual activity is

found in Mali (81 percent) while the lowest is in Zimbabwe (40 percent). Likewise, Mali has the highest

proportion of young women who entered into union before age 18 (66 percent) and Zimbabwe has the lowest

(23 percent). In every country, union formation among adolescent women has declined across surveys. The

largest declines were observed in Côte d’Ivoire and in Mali, where the differences were more than

10 percentage points.

Figures 4.9.1 and 4.9.2 show the trends in the proportion of young men who had first sex and first

union before age 20. In countries where information from two surveys is available, declines over time are

observed in the proportion of men who had first sex before age 20. However, there is no consistent trend with

regard to the proportion in first union before age 20. Overall levels of early union formation are much lower

among young men than young women in every country.
17

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.8.1 Percentage of women age 18-24 

who reported having had first sex before 

age 18, by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.9.1 Percentage of men age 20-29 who 

reported having had first sex before age 20, by 

relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.8.2 Percentage of women age 18-24 

who reported having had first union before

age 18, by relative date of survey

%

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Earlier

 Later

Figure 4.9.2 Percentage of men age 20-29 who 

reported having had first union before age 20, 

by relative date of survey

%

Levels of male sexual experience and union formation during adolescence remain lowest in Senegal.

Early sexual initiation is most common in Kenya, Côte d’Ivoire, and Tanzania, where some 80 percent of

young men had first sex before age 20. However, there was no country in which more than 20 percent of men

reported having had first union before age 20, suggesting widespread premarital sexual activity across the

region.

Given the general trend toward lower adolescent fertility, later sexual initiation, and later union

formation, which are occurring alongside strong differentials across countries and population subgroups, we

need to consider which background variables are associated with these differences.
18

Figure 4.10.2 Percentage of men age 20-29 with 

knowledge of modern contraceptive methods,

by place of residence and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Rural Urban

Earlier Later

Figure 4.10.1 Percentage of women age 18-24 with 

knowledge of modern contraceptive methods,

by place of residence and relative date of survey

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

 Rural Urban

Earlier Later

4.4 Differentials in Reproductive Health Knowledge and Behavior by Sociodemographic

Characteristics

Evidence from the DHS program points to differences in reproductive health knowledge and

behaviors among adolescents according to their sociodemographic background characteristics. For example,

as seen in Figures 4.10.1 and 4.10.2, the proportion of adolescent women and men with knowledge of modern

family planning methods is substantially higher among those who live in urban areas compared with their

rural counterparts. This trend remains universal across countries and time periods. Differences by urban-rural

residence tend to be greater in countries where overall levels of knowledge are poorer, such as in Mali, where

the gap reaches 20 percentage points or more.

Differences can also be observed in terms of age at initiation of reproductive behaviors by

sociodemographic subgroup. The levels and trends in early first birth, first sex, and first union are affected

by young women’s and men’s background characteristics. Following is a brief descriptive analysis of these

trends according to selected individual and contextual variables.

Education

Figures 4.11.1 and 4.11.2 show the trends in the percentage of young women and men with early first

birth, first sex, and first union by educational attainment (no formal schooling, one to seven years, eight or

more years). As was previously described, overall the propensity for early reproductive outcomes has changed

between survey periods. The direction and pace of change for each education category can be seen by the

distinct angle of the line between the earlier and later surveys. (Note that this representation is simply for

illustrative purposes and does not necessarily imply a linear trend across the intersurvey period.)

Although in general the trends seem quite parallel between education groups, there is a definite

association between education and the proportion of women who have given birth before age 18. Bettereducated women are consistently less likely to have had an early first birth than their less educated

counterparts. Most countries experienced a similar decrease across education categories in the percentage of

women with an early birth; but in Côte d’Ivoire and Mali, the pace of change was faster among the most

educated women compared with those who were less educated. Burkina Faso saw slightly increasing

proportions of early births between the two surveys for each education level and Zimbabwe saw an increase

among those women with no schooling.
19

No data on age

at first birth

for men

Figure 4.11.1 Trends in percentage of women age Figure 4.11.2 Trends in percentage of men age

18-24 who had first birth, first sex, and first 20-29 who had first sex and first union

union before age 18, by education level: before age 20, by education level:

earlier survey versus later survey earlier survey versus later survey

First birth before age 18

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

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40

60

80

100

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Ghana

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Senegal

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% 100

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Burkina Faso

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

First sex before age 18

%

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& &

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

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60

80

100

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

First sex before age 20

%

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

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100

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

First union before age 18

%

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&

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&

& )' )' & &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

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Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

100

First union before age 20

%

No schooling 1-7 years 8+ years
20

Burkina Faso and Mali are good examples of how different education levels have different effects

on levels and trends of early sex among young women. Educated women are less likely to have first sex

before age 18 than women with no schooling. The higher the level of educational attainment the stronger the

declining trend: the fastest decline in early sex occurred among the most educated women (eight or more

years of schooling). Thus both the level and the pace of change are correlated with education category.

We also see from Figure 4.11.1 that in some countries, the proportion of more educated women who

had early sex increased while that for less educated women decreased. This discordant trend occurred in

Kenya, Senegal, and Tanzania. In Côte d’Ivoire and Kenya, the proportion of women with no schooling who

had early sex decreased over time to below the rate observed for women with primary education.

Education and early union appear to have a more consistent relationship than education and early sex.

Better-educated women are least likely to have had an early union, while women with no schooling are most

likely to have had an early union. Many of the countries showed roughly parallel trends between the

subgroups, notably Côte d’Ivoire, Kenya, and Zimbabwe. On the other hand, Mali had the widest differences

in trends between education and early union formation: women with no schooling had a small decline in the

proportion in union before age 18 while the most educated women had a large decline (2 and 55 percentage

points, respectively).

Among young men the findings are often quite different (Figure 4.11.2). Although trend data are not

available for all countries, we can still see some important differences across education level and reproductive

behavior. There are a number of cases where trends in reproductive outcomes are discordant between

education categories. In some instances the survey sample sizes for men are small, rendering estimates for

subgroups unstable. The trends in risk of early first sex and early first union by education level are much less

consistent for men than for women.

The likelihood of early sexual initiation is remarkably different for males than for females. In most

of the countries, higher proportions of men who reported having had first sex before age 20 were found

among the better-educated groups (except in Tanzania and Zimbabwe). In Zimbabwe, for the educated men

(the majority of the population) there has been a decrease in the percent having early sex; however, for men

with no schooling there has been a sharp rise. This could be due in part to the small numbers of men that fall

into the latter category.

Union formation by education level is more difficult to interpret for the male data. In most cases the

better-educated men were the least likely to have formed an early union, but the trends suggest this could be

changing over time. In Ghana, Mali, and Zimbabwe there have been increases in the proportions in early first

union among the more educated men, resulting in higher rates by the later survey period than their noneducated counterparts. Tanzania had a large variation in the trend by education group. The men with no

education had the largest decline while the men with the most education had a minimal decline in likelihood

of early first union.

The situation among young men in Ghana shows some interesting trends. The proportion of educated

men having early sex is decreasing over time while that same group is showing an increasing proportion in

early union. Conversely, the percent of men with no schooling who had sex early is decreasing and the

percent who were in union early is increasing.
21

Urban-rural Residence

For each of the reproductive behaviors, urban women are less likely to experience the outcome before

age 18 than rural women, across all countries and survey periods (Figure 4.12.1). In most cases the levels of

early first birth, first sex, and first union are decreasing over time at a fairly uniform pace according to urbanrural residence.

In particular, the stratification of adolescent first births shows that most of the decline between

surveys has not been affected by urban-rural differences (i.e. most of the trends lines are relatively parallel

indicating steady decline). Only in Burkina Faso do we find discordant trends: the proportion of women

having a first birth by age 18 increases in rural areas and decreases in urban areas.

Some distinctions emerge in terms of the trends in early first sex by urban-rural residence. In

Tanzania and Zimbabwe, despite an overall decline between periods in the proportion of women who had first

sex by age 18, there was an increase in urban areas. In Kenya there were increases in the percentage of

women having early sex in both urban and rural settings. In Mali the proportion increased over time in rural

areas but decreased in urban areas.

The pace of decline in levels of early first union among women was somewhat faster in urban areas

for Burkina Faso, Côte d’Ivoire, and Mali. In Senegal a large part of the overall decrease is due to changes

in behavior among women in rural areas. In Zimbabwe, despite a decrease nationally in the proportion in first

union by age 18, in urban areas the proportion actually increased.

As was seen for trends by level of education, the male figures are often different from the female

figures by urban-rural residence. For the earlier period, men in urban areas were more likely to have had first

sex before age 20 than rural males in all countries where data were available except Kenya and Zimbabwe

(Figure 4.12.2). This tendency has changed over time in Ghana, where the decline in the proportion having

early sex was faster for urban males than rural males. Declines were observed regardless of urban-rural

residence in all countries except Kenya.

In most instances, levels of early union formation are lower for urban men than rural men. In five of

the seven countries for which trend data are available, overall increases are observed in the proportion having

first union before age 20. However, no consistent trend by residence is apparent; increases are found among

urban men in some countries, and among rural men in others.
22

No data on age

at first birth

for men

Figure 4.12.1 Trends in percentage of women age Figure 4.12.2 Trends in percentage of men age

18-24 who had first birth, first sex, and first 20-29 who had first sex and first union

union before age 18, by residence: before age 20, by residence:

earlier survey versus later survey earlier survey versus later survey

First birth before age 18

' '

& & ' '

& &

'

'

&

& ' '

& &

' '

& &

' '

&

&

'

'

&

&

'

'

& &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First sex before age 18

' '

& &

' '

& &

'

'

&

&

' '

& &

' ' ' & &

'

&

&

' '

&

&

'

'

& &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First sex before age 20

' '

&

&

'

'

&

&

'

&

'

&

' ' & &

'

'

& &

'

&

&'

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First union before age 18

' '

& &

' '

& &

'

'

&

&

'

'

& &

' '

& ' & '

& &

'

'

&

' &

'

& &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First union before age 20

' &

' &' & &' ' ' ' & & & &' ' &' ' & &'

&

' ' & & '

&

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

Rural Urban
23

Exposure to Mass Media

Exposure to mass media, as measured by regular listening to the radio, tends to have a negative

correlation with likelihood of early reproductive behavior. As seen in Figure 4.13.1, in most cases higher

proportions of young women who do not listen to the radio regularly reported having first birth, first sex, and

first union before age 18 compared with women who listen regularly.

Declines over time in the proportion of women having an early first birth are generally uniform by

exposure to radio. Only in Mali do discordant differences exist, but they are minor. Côte d’Ivoire had the

fastest decline in probability of early first birth among women with little or no exposure to radio. Although

we had previously found that Burkina Faso was the only country where the proportion having an early first

birth rose nationally, this trend disappeared when the analysis was by media exposure. Caution is warranted

in interpreting the data, because a small number of cases were missing information on exposure to radio.

In most countries, the trend toward early first sex is similar for both women who have been exposed

to radio and those who have not. However, Mali and Zimbabwe show differences for the two subgroups. In

Zimbabwe women who listen to radio regularly were increasingly likely to have early sex, while in Mali

increases in early sex were seen among women who were not exposed to radio.

In addition, exposure to radio appears to have affected the proportion of young women having formed

a first union before age 18 differently between surveys in Mali. The proportion in early first union dropped

by 20 percentage points among women who listened to the radio regularly, whereas the decline was only one

percentage point among those who were not regular listeners. Only in Zimbabwe was the trend different for

the two subgroups: the likelihood of having an early union increased for women with exposure to radio but

decreased for those without.

We find a smaller correlation between exposure to radio and early initiation of sex for males (Figure

4.13.2). In many countries little difference is observed in the proportion of young men who had first sex

before age 20 by exposure to radio. Only in Mali was there a large difference; men who listen regularly were

more likely to have early first sex than those who did not.

There was also no appreciable correlation with exposure to radio and early union formation for men.

In general it appears that young men who listened to radio regularly are less likely to form a first union before

age 20, but the differences are small.
24

No data on age

at first birth

for men

Figure 4.13.1 Trends in percentage of women age Figure 4.13.2 Trends in percentage of men age

18-24 who had first birth, first sex, and first 20-29 who had first sex and first union

union before age 18, by mass media exposure: before age 20, by mass media exposure:

earlier survey versus later survey earlier survey versus later survey

First birth before age 18

' '

&

& ' '

& ' &

'

&

&

' '

& &

' '

&

& ' '

&

&

' '

&

&

' '

& &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First sex before age 18

' '

&

&

' '

& &

'

'

&

&

' ' & &

' '

& & '

'

&

&

' '

&

&

'

'

& &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First sex before age 20

' '

&

&

'

& '

&

'

&

&' &'

'

' &

&

'

&

'

&

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First union before age 18

' '

& ' & '

& ' &

'

&

&

'

'

& &

' '

&

& ' '

& & ' '

&

&

'

'

& &

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

First union before age 20

' ' ' ' & & ' & & ' ' & & ' & ' &

&

'

& &'

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

0

20

40

60

80

% 100

Does not listen to radio regularly Listens to radio regularly
25

Women: Did not have first sex before age 18 Women: Had first sex before age 18

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Figure 4.14 Distribution of cluster-level variable for proportion of adults with eight or 

more years of schooling, by whether women (age 18-24) or men (age 20-29) had first 

sex during adolescence

Men: Did not have first sex before age 20 Men: Had first sex before age 20

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Contextual Variables

A comparison was made of the different reproductive outcome variables among young women and

men according to their community characteristics. Two aspects were considered: the degree of community

development and the family planning environment. The first was measured by the proportion of adults in the

sampling cluster who had completed eight or more years of schooling. The family planning environment was

evaluated though the proportion of adults who had ever used a modern method of contraception. For the

multivariate models that follow, the cluster-level aggregates were transformed into dichotomous variables

for higher or lower community status. We will comment here only on the general relationships, focusing on

trends in early first sex (Figures 4.14 and 4.15). The trends for early first birth and early first union are similar

(not shown).
26

Figure 4.15 Distribution of cluster-level variable for proportion of adults who have ever 

used modern contraception, by whether women (age 18-24) and men (age 20-29) had first 

sex during adolescence

Women: Did not have first sex before age 18 Women: Had first sex before age 18

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Men: Did not have first sex before age 20 Men: Had first sex before age 20

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Burkina Faso

Côte d’Ivoire

Ghana

Kenya

Mali

Senegal

Tanzania

Zimbabwe

Young women who had early first sex are less likely to live in communities with lower development

status. In every country, the median proportion of well-educated adults in a cluster is higher for women who

did not have sex before age 18 compared with those who did. For males the relationship is the opposite: men

who did not have sex during adolescence tend to live in less-developed communities (except in Zimbabwe

and perhaps Tanzania). Interestingly, for Kenya the median proportion of well-educated adults in the clusters

for men who had early sex was very similar to the median proportion for men who did not have early sex.

Because this trend exists in Tanzania and Zimbabwe, it might suggest that there is a regional effect based on

higher HIV/AIDS awareness in the East African countries. The trend could also be a result of small male

sample sizes, and should be verified with larger data sets.

Considering the local family planning environment, young women who had early first sex tend to

reside in communities characterized by a smaller proportion of adults who have ever used a modern

contraceptive method. Males, however, show a different pattern. In the majority of the countries studied,

young men who had early first sex live in communities that have a strong family planning environment.

Overall, little change in patterns can be noted over time.
27

5 Determinants of Changes in Adolescent Reproductive Behavior

As described in section four, similar trends in early reproductive behavior across background

characteristics suggest that similar social influences are at play. To control for the potentially confounding

influences, and to see if variables have their own significance, we have included them in a multivariate model.

This section describes the results of the multivariate analyses of the three outcome variables: first birth, first

union, and first sex during adolescence.

Analysis of how trends are affected by sociodemographic and community-level variables is captured

through interaction terms of the characteristic on the year of the survey. The interaction terms are included

to specify how the effects of the dependent variables on the outcome variables have changed between surveys.

Although stratification of the regressions by survey could help simplify the analyses, in a stratified form we

are unable to see if the difference between the coefficients is statistically significant. In some cases we have

run the stratified regressions to explain the findings of the interaction term more clearly; however, we do not

display those results here.

We refer to the category of one to seven years of schooling as primary education and that of eight

or more years as secondary education. Although the educational systems vary by country, these levels of

schooling have been chosen to maintain comparability.

5.1 Age at First Birth

As seen in Table 5.1, the decline between the earlier and later surveys in the risk of first birth before

age 18 for women was statistically significant in Côte d’Ivoire and in Senegal. As expected, overall young

women in the region who were less educated were more likely to have an early birth. Women with secondary

schooling were consistently at least 50 percent less likely to have had a first birth before their 18th birthday

than were those with no education, all else being equal (Table 5.1). In Côte d’Ivoire there was a significant

interaction effect for education and survey period. The interaction term was less than one, suggesting that the

difference in the probability of early childbearing for a woman with secondary education versus a woman

with no education was greater in 1994 than in 1998.

In many countries, effects of other sociodemographic and contextual variables were not statistically

significant once effects of education were considered. The association between residence and probability of

early childbearing was significant only in Côte d’Ivoire, Ghana, and Senegal. Women in these countries who

lived in urban areas were over 30 percent less likely to have a first birth before age 18 as compared with rural

women.

In Côte d’Ivoire and Zimbabwe, exposure to radio was inversely associated with the probability of

an adolescent birth. Both countries also experienced changes in the effects between surveys; the negative

association that was observed in the earlier survey was no longer significant by the later survey as suggested

by the significant interaction term.

There was no significant effect of the community development variable for the probability of a first

birth before age 18 in any of the countries. The family planning environment proved to be significantly

associated with probability of an early birth among young women in Ghana and Senegal, but the direction

of the association was not consistent. In Ghana, an adolescent was more likely to have had an early birth in

communities with a strong family planning environment, while in Senegal the opposite was true. The

interaction term for Ghana was also significant; it appears that the positive association in the early survey was

no longer significant in the later survey.
28

Table 5.1 Odds ratios for having first birth before age 18, among women age 18-24

First birth before age 18

Country

Burkina

Faso

Côte

d’Ivoire Ghana Kenya Mali Senegal Tanzania Zimbabwe

Relative date of survey

Reference category: Earlier survey

Later survey 1.08 0.65 ** 0.64 1.21 1.11 0.70 * 0.85 0.75 

Education

Reference category: None1

1-7 years of schooling 0.57 ** 0.85 0.75 0.76 1.16 0.60 ** 0.49 *** 0.64 

8+ years of schooling 0.16 *** 0.47 *** 0.27 *** 0.23 *** 0.41 * 0.09 *** 0.15 *** 0.19 ***

Interaction education-survey

1-7 years of schooling × Later 1.29 1.11 0.91 0.90 0.61 0.87 1.01 0.84 

8+ years of schooling × Later 2.43 0.47 * 1.38 1.11 0.54 1.80 0.95 0.66 

Residence

Reference category: Rural

Urban 1.37 0.70 ** 0.57 ** 0.90 0.67 0.59 ** 1.02 0.85 

Interaction residence-survey

Urban × Later 0.49 * 0.82 1.14 1.10 1.01 0.93 1.19 0.75 

Exposure to radio

Reference category: Does not listen

Listens to radio regularly 0.92 0.74 ** 0.99 0.86 0.96 0.85 1.01 0.70 **

Interaction exposure to radio–survey

Listens to radio × Later 0.98 1.68 ** 1.11 1.03 0.96 1.03 1.01 1.71 **

Community development

Reference category: Lower

Higher 0.65 0.77 1.05 0.97 0.90 0.93 0.71 0.94 

Interaction community development–survey

Higher × Later 0.82 1.25 1.19 0.76 0.85 0.93 0.72 1.45 

Community family planning environment 

Reference category: Lower

Higher 0.82 0.87 1.73 ** 0.95 1.16 0.49 * 0.72 1.05 

Interaction community FP environment–survey

Higher × Later 1.54 0.98 0.55 * 0.75 0.94 2.14 1.33 1.16 

Sample size 3,513 3,299 2,415 4,630 3,185 4,137 5,166 3,549

1

 The reference category for education is no schooling in all countries except Zimbabwe where 1-7 years of schooling is reference.

* p<0.05 ; ** p<0.01 ; *** p<0.001

5.2 Age at First Sex

Between the surveys in Côte d’Ivoire, Ghana, and Senegal, there was a significant reduction in the

proportion of women who had early sex (Table 5.2.1). This was not the case in Mali, where adolescents were

somewhat more likely to have engaged in early sex at the time of the later survey, after controlling for effects

of the background variables.

In each country, women with at least secondary education were significantly less likely to have had

sex before age 18 than were women with no education. Effects of primary education were less consistent. In

Kenya and Tanzania there were significant interaction terms for education. After stratifying to investigate the

interaction term for Kenya, we find that in 1998 the direction of the association changed and adolescents were

more likely to have early sex if they had primary education than if they had no education.
29

In five countries, urban-rural residence had an independent effect on a woman’s probability of having

sex before age 18. Urban residence reduced the probability of early sexual debut by some 40 to 50 percent

in Côte d’Ivoire, Ghana, Mali, Senegal, and Zimbabwe. No interaction effects were found, suggesting that

this association did not change between the two surveys.

Exposure to radio was associated with early sexual debut only in Senegal and Zimbabwe. In both

countries the odds ratios were in the expected direction: women listening regularly to the radio had about a

25 percent lower probability of engaging in early sex. In Zimbabwe, moreover, there was an interaction

effect. After stratifying the analysis by survey, we find that the effect of exposure to radio was negative at

the time of the earlier survey and insignificant at the time of the later survey. Thus in Zimbabwe, exposure

to radio in 1994 was significantly associated with the probability of early sexual debut among women, while

in 1999 there was no noticeable effect.

The community effects were less important and less consistent in most countries. In Ghana, women

in communities of higher development had a higher chance of early sex, while in Tanzania the opposite was

true. In neither of these two countries did the effect vary across surveys. There was no consistent effect of

family planning environment on the probability of adolescent sexual initiation.

Among young men, Zimbabwe was the only country that showed a significant change in the

probability of early sex between the two surveys (Table 5.2.2). While controlling for other variables, men

were 71 percent less likely to have had first sex before age 20 at the later survey compared with the earlier

survey.

The male data suggest that education is related to age at first sex; however, the relationship is often

in the opposite direction of the female models. This is similar to what had been found in the bivariate analysis.

In Côte d’Ivoire, Mali, and Senegal we find that men with education are more likely to have early sexual

debut compared with men with no education. In Zimbabwe and Tanzania, however, men with education were

less likely to have early sexual experience compared with men with no education.

Moreover, in Zimbabwe there was a significant interaction effect between education and survey.

Further stratification showed a significant negative effect of no education on early sex at the earlier survey

and no effect at the later survey. (Note that the Zimbabwe male sample had few cases in the no schooling

category, so the findings should be interpreted with caution.) Tanzania also experienced a significant

interaction effect: at the time of the earlier survey there was a significant negative association between

secondary education and sex before age 20 while at the time of the later survey there was no association.

In Zimbabwe and Tanzania there was an association between exposure to radio and early sex but the

effect changed between the two surveys. In Tanzania the earlier survey showed a significant positive

association and the later survey showed a nonsignificant negative association. The opposite was true for

Zimbabwe. In Mali exposure to radio was associated with the probability of early sex in the later survey

(questions on media exposure were not asked to men in the earlier survey).

There were few significant community effects on the probability of men having first sex before age

20.
30

Table 5.2.1 Odds ratios for having first sex before age 18, among women age 18-24

First sex before age 18

Country

Burkina

Faso

Côte

d’Ivoire Ghana Kenya Mali Senegal Tanzania Zimbabwe

Relative date of survey

Reference category: Earlier survey

Later survey 1.04 0.49 *** 0.6 * 0.78 1.61 * 0.56 *** 0.80 1.10 

Education

Reference category: None1

1-7 years of schooling 0.64 ** 1.00 0.84 0.76 1.07 0.54 *** 0.59 *** 0.68 

8+ years of schooling 0.33 *** 0.53 *** 0.44 *** 0.30 *** 0.44 * 0.22 *** 0.13 *** 0.21 ***

Interaction education-survey

1-7 years of schooling × Later 1.15 1.11 1.1 2.19 * 0.67 1.14 1.06 0.73 

8+ years of schooling × Later 1.01 0.91 1.21 1.82 0.68 1.33 1.80 * 0.68 

Residence

Reference category: Rural

Urban 0.83 0.58 ** 0.54 *** 0.88 0.50 * 0.52 *** 1.15 0.60 **

Interaction residence-survey

Urban × Later 0.57 1.44 0.96 1.31 1.10 0.77 1.20 1.33 

Exposure to radio

Reference category: Does not listen

Listens to radio regularly 1.12 0.95 1.20 0.94 0.90 0.75 * 0.87 0.72 **

Interaction exposure to radio–survey

Listens to radio × Later 0.74 1.27 0.66 * 0.98 0.78 1.37 1.03 1.57 **

Community development

Reference category: Lower

Higher 0.75 0.82 1.77 ** 1.02 1.05 0.71 0.51 ** 1.00 

Interaction community development–survey

Higher × Later 1.32 1.08 1.21 0.71 0.99 1.23 1.25 1.01 

Community family planning environment 

Reference category: Lower

Higher 0.89 0.83 1.13 0.85 2.27 * 0.59 0.84 0.97 

Interaction community FP environment–survey

Higher × Later 1.14 1.29 0.89 0.94 0.43 * 1.57 1.11 0.97 

Sample size 3,368 3,276 2,388 4,489 3,083 3,941 4,919 3,452

1

 The reference category for education is no schooling in all countries except Zimbabwe where 1-7 years of schooling is reference.

* p<0.05 ; ** p<0.01 ; *** p<0.001
31

Table 5.2.2 Odds ratios for having first sex before age 20, among men age 20-29

First sex before age 20

Country

Burkina

Faso

Côte

d’Ivoire Ghana Kenya Mali Senegal Tanzania Zimbabwe

Survey period 

Reference category: Earlier

Later survey 0.66 1.98 0.65 0.29 ***

Education 

Reference category: None1

1-7 years of schooling 0.84 2.92 ** 1.53 2.02 1.58 * 1.60 ** 0.59 0.12 *

8+ years of schooling 1.16 3.22 ** 1.84 2.27 2.01 * 1.54 * 0.21 ** 0.67

Interaction education-survey

1-7 years of schooling × Later 1.28 0.34 2.21 15.11 *

8+ years of schooling × Later 0.79 0.27 5.33 * 1.05 

Residence 

Reference category: Rural

Urban 0.92 1.63 1.14 1.18 1.57 1.33 1.17 0.70 

Interaction residence-survey

Urban × Later 0.44 * 1.15 0.69 1.22

Exposure to radio 

Reference category: Does not listen

Listens to radio regularly 1.14 0.55 1.41 1.05 2.16 ** 2.34 ** 0.63 *

Interaction exposure to radio–survey

Listens to radio × Later 0.73 1.35 0.38 * 2.06 **

Community development 

Reference category: Lower

Higher 0.91 0.99 1.02 0.79 1.23 0.88 0.38 * 1.56

Interaction community development–survey

Higher × Later 1.80 0.93 1.96 0.76 

Community family planning environment 

Reference category: Lower

Higher 1.36 1.09 0.80 0.93 1.06 1.13 1.60 0.86 

Interaction community FP environment–survey

Higher × Later 1.19 1.12 1.12 1.87 *

Sample size 744 306 821 1,901 606 1,177 1,227 1,551

1

 The reference category for education is no schooling in all countries except Zimbabwe where 1-7 years of schooling is reference.

* p<0.05 ; ** p<0.01 ; *** p<0.001

5.3 Age at First Union

After taking into account changes in background variables, trends in the percentage of women in a

union before age 18 were mixed (Table 5.3.1). In some countries, such as Ghana and Senegal, the probability

of early union formation decreased by about 40 percent during the intersurvey period. However, in Mali the

probability increased by over 50 percent.

Education is significantly associated with early union for females. In every country except Mali,

women with secondary or higher education were 70 to 95 percent less likely to enter into union by age 18.

Similarly, in most cases women who had some primary education were 25 to 65 percent less likely to be in

first union during adolescence than their counterparts with no education.
32

Table 5.3.1 Odds ratios for having first union before age 18, among women age 18-24

First union before age 18

Country

Burkina

Faso

Côte

d’Ivoire Ghana Kenya Mali Senegal Tanzania Zimbabwe

Relative date of survey

Reference category: Earlier survey

Later survey 1.00 0.79 0.54 * 1.02 1.53 * 0.60 ** 0.81 0.80 

Education

Reference category: None1

1-7 years of schooling 0.57 *** 0.63 *** 0.74 0.55 ** 1.10 0.38 *** 0.40 *** 0.33 **

8+ years of schooling 0.28 *** 0.27 *** 0.26 *** 0.15 *** 0.54 0.08 *** 0.07 *** 0.09 ***

Interaction education-survey

1-7 years of schooling × Later 0.89 0.82 1.44 1.24 0.38 ** 1.29 1.27 0.89 

8+ years of schooling × Later 0.46 * 0.39 * 2.39 ** 1.58 0.23 ** 2.08 1.65 0.80 

Residence 

Reference category: Rural

Urban 0.68 0.8 0.55 *** 1.19 0.69 0.38 *** 0.90 0.62 *

Interaction residence-survey

Urban × Later 0.6 0.83 0.91 1.12 0.81 0.83 1.03 1.15 

Exposure to radio

Reference category: Does not listen

Listens to radio regularly 1.03 0.72 ** 1.15 0.92 0.9 0.82 0.98 0.77 *

Interaction exposure to radio–survey

Listens to radio × Later 0.94 1.57 * 0.84 1.11 0.69 1.20 1.24 1.74 **

Community development

Reference category: Lower

Higher 0.91 0.63 ** 0.78 0.95 0.84 0.83 0.85 0.94 

Interaction community development–survey

Higher × Later 0.86 1.18 1.48 0.70 0.78 0.70 0.66 1.13 

Community family planning environment 

Reference category: Lower

Higher 0.76 0.68 1.46 * 0.68 ** 2.3 * 0.47 * 0.47 ** 1.10 

Interaction community FP environment–survey

Higher × Later 1.45 1.36 0.63 * 0.82 0.36 * 2.21 1.5 1.10 

Sample size 3,513 3,299 2,415 4,630 3,185 4,137 5,166 3,549

1

 The reference category for education is no schooling in all countries except Zimbabwe where 1-7 years of schooling is reference.

* p<0.05 ; ** p<0.01 ; *** p<0.001

Although the overall effects of education were not significant in Mali, the significance of the

interaction terms suggests that education had a different effect on early first union between the two surveys.

After stratifying the analysis we note that in the earlier survey primary education had no association with

adolescent union formation; however, in the later period there was a significant negative association. The

same was found with regard to the secondary education category. Thus in 1995 lack of schooling was

associated with early first union, an association that did not exist in 1987.

Burkina Faso, Côte d’Ivoire, and Ghana also had significant interactions between the survey and

secondary education variables. In Burkina Faso and Côte d’Ivoire the interaction suggested that more

education resulted in a higher probability of first union before age 18 at the earlier survey; however, this was

reversed in the later survey. In Ghana, secondary education was associated with less probability of early union

in both surveys; however, the odds ratio was closer to one in the later survey.
33

Urban-rural residence affected age at first union in three countries. In Ghana, Senegal, and Zimbabwe

women were less likely (45, 62, and 37 percent, respectively) to enter into union before age 18 if they lived

in an urban area compared with their rural counterparts. These associations remained stable over time while

controlling for other background variables.

Regular exposure to radio is associated with early union in only two of the eight countries in the

analysis. In Côte d’Ivoire and Zimbabwe, women who listen to the radio regularly were about 25 percent less

likely to have first union before age 18 than those who do not listen. Interaction effects between exposure to

radio and survey are in the positive direction, suggesting that, for both countries, the effect was greater in the

later survey compared with the earlier survey.

There were few significant associations with the community variables. Côte d’Ivoire was the only

country in which there was a development effect on women’s probability of early union. Women living in

a more developed community were 37 percent less likely to be in union by age 18. This influence did not vary

between the two surveys.

The effect of family planning environment was mixed. In Kenya, Senegal, and Tanzania, women who

lived in a community with a strong family planning environment were 30 to 50 percent less likely to enter

into a union before age 18. However, in Ghana and Mali, women in such types of communities were more

likely to enter into union. The latter two countries also exhibited significant interactions: in both cases a

significant positive effect of family planning effort was found for the earlier survey but was no longer evident

at the later survey.

Among men, the proportion in first union by age 20 was low across the region (Table 5.3.2); this

makes it unlikely that many significant results can be derived from these data. In fact, in Senegal there were

too few cases of male union formation during adolescence for the multivariate model to converge; thus the

results presented here are from the later survey only. Tanzania was the only country to demonstrate significant

change in the probability of early union formation, with a decreasing trend over time.

Male education had a negative association with early union in Kenya, Tanzania, and Zimbabwe. In

Kenya and Tanzania, we found differences in the effect between the first and second surveys. In both cases

the education-survey interaction term was greater than one suggesting an upward shift in the effect. After

running the models stratified, we found a significant negative association of primary school with early union

formation in the earlier survey that dissipated in the later survey.

Controlling for education, there were few significant associations of other sociodemographic or

contextual variables with men’s probability of first union before age 20. Residence was significantly

associated with early union formation only in Côte d’Ivoire: men who lived in an urban area were 64 percent

less likely to have an early union than men in a rural area. This trend was stable over time.

Neither exposure to radio nor indicators of community context (development level and family

planning effort) were significantly associated with men’s probability of early union for any of the countries.

To summarize, education had the most significant effect for most of the countries and on most of the

outcomes. Exposure to radio and residence had effects in a few of the countries and, for females, consistently

had a negative association with early reproductive behavior.

The community variables had little overall effect. This suggests that any trends at the bivariate level

would be better captured by individual-level sociodemographic characteristics.
34

Table 5.3.2 Odds ratios for having first union before age 20, among men age 20-29

First union before age 20

Country

Burkina

Faso

Côte

d’Ivoire Ghana Kenya Mali Senegal Tanzania Zimbabwe

Survey period

Reference category: Earlier survey

Later survey 0.96 0.65 0.70 1.36 0.29 * 0.80 

Education 

Reference category: None1

1-7 years of schooling 0.52 1.00 2.00 0.31 * 1.34 0.11 ** 0.22 *** 2.52 

8+ years of schooling 0.45 1.00 1.25 0.07 *** 0.99 0.18 0.08 *** 0.39 *

Interaction education-survey

1-7 years of schooling × Later 0.76 1.73 3.08 0.88 5.08 ** 0.38 

8+ years of schooling × Later 1.08 1.58 5.86 * 1.31 3.02 0.93 

Residence

Reference category: Rural

Urban 0.55 0.36 * 0.55 1.04 1.04 0.42 0.94 0.68 

Interaction residence-survey

Urban × Later 1.62 0.59 1.33 0.40 0.67 1.32 

Exposure to radio 

Reference category: Does not listen

Listens to radio regularly 0.79 0.72 1.35 1.65 1.18 

Interaction exposure to radio–survey

Listens to radio × Later 0.79 0.65 0.60 1.59 

Community development 

Reference category: Lower

Higher 0.78 0.72 0.49 0.55 0.38 0.25 0.19 0.77 

Interaction community development–survey

Higher × Later 0.36 2.43 1.50 2.54 5.81 0.88 

Community family planning environment 

Reference category: Lower

Higher 0.74 2.08 1.12 0.62 0.23 0.36 0.21 0.81 

Interaction community FP environment–survey

Higher × Later 1.18 1.02 0.99 5.15 4.01 2.36 

Sample size 794 1,124 822 1,974 916 1,352 1,232 1,551

1

 The reference category for education is no schooling in all countries except Zimbabwe where 1-7 years of schooling is reference.

 * p<0.05 ; ** p<0.01 ; *** p<0.001
35

6 Discussion and Conclusion

This report has investigated trends and differentials in reproductive behavior among adolescents in

eight sub-Saharan countries, drawing on data from successive DHS surveys. The key questions we set out

to answer were: what are the levels and trends of adolescent reproductive behavior, what characteristics are

associated with these trends, and in what contexts do the trends occur.

The data presented in section 4.3 suggest that, despite the shortness of the time between surveys, in

most countries, there was a decline in the levels of first birth, first sex, and first union among adolescent

women and men. Exceptions included a slight increase in early first birth among women in Burkina Faso, of

first sex among women in Kenya, and of first union among men in Ghana, Kenya, Mali, and Zimbabwe

(though overall levels of union formation among young men remained low). Subsequently, multivariate

models were used to determine the independent impact of selected sociodemographic and contextual variables

on those trends (section 5).

As previous research has found, modernization is a key determinant of reductions in fertility. In our

models we proxy modernization through a series of characteristics related to individuals and their

environment: education, urbanization, exposure to mass media, community development, and family planning

environment. Strong disparities are observed with regard to these characteristics from country to country,

suggesting that the pace of modernization has not been consistent across the region.

The findings suggest that adolescent women’s sociodemographic characteristics (education,

residence, and exposure to mass media) had greater influence on early reproductive outcomes while the

contextual variables had weaker influence. In particular, secondary schooling had among the strongest and

most consistent negative effects.

Modernization had a negative effect on probability of early sex for males, but was associated with

delayed union formation. While DHS surveys do not collect data on age at first birth for men, in the absence

of increased contraceptive use, increased probability of early first sex and early first union will affect the

probability of early first birth. Community development and family planning environment did not appear to

be significant factors in determining probabilities among males for early first sex or first union. The definition

of these variables was inconsistent and may need to be considered further.

Important gender differentials were observed. In the majority of the countries studied, young men

who were more educated, more urbanized, had greater exposure to the media, and lived in more developed

settings were more likely to have had early sex. However, these same men were more likely to enter into

union later. Women, on the other hand, tended to be less likely to have had early birth, early sex, or early

union if they were more educated, more urbanized, had more exposure to the media, and lived in a more

developed setting. These distinct associations suggest that program planners and policymakers need to plan

separate activities (but with equal emphasis) for young men and women.

This research suggests that modernization is associated with fewer early births for women but not

necessarily delayed sexual debut, and not associated with later fatherhood for men. Modernization, especially

as measured by educational attainment, may increase the chances of men initiating reproductive behavior

during adolescence, but decreases the chances for women. However, the benefits of schooling outweigh any

negative effects on early male sexual activity and imply that as modernization occurs, programs directed at

young men should be distinct from those directed at young women.

There are differences between what women and men know about reproductive health, with only small

improvements occurring between surveys. Men had more knowledge of modern contraceptive methods than
36

women. This is partially due to greater knowledge of condoms. There was very little knowledge of the

ovulatory cycle among adolescent women and virtually no improvement between the surveys. There was an

interesting gender disparity between HIV/AIDS prevention knowledge. Women were more likely to know

that abstaining from sex or limiting the number of partners help prevent HIV transmission, but were also more

likely to report misinformation about how HIV is transmitted than were men. Men were much more likely

to know that condoms prevent transmission. Solid reproductive health knowledge is essential for adolescents

making decisions about reproductive behavior.

While the ability to conduct quality research in the area of adolescent reproductive health and

behavior has been improved in recent years, in part due to the data collected through the DHS program, in

many ways empirical analyses are limited by survey design. The present results are useful for identifying

target groups for reproductive health services and outreach programs; however, the need for more contextual

and qualitative information is evident.

For example, while the health consequences of early reproductive behavior have been well

documented elsewhere, less is known about the social context in which it occurs. Little information is

available about the partner, familial, and community reactions to adolescent childbearing, sexual activity, and

union formation. Researchers have suggested the timing of first union may affect young women, especially

in terms of autonomy in choosing their spouse and in the way they are viewed by their parents, in-laws, and

society. However, quantitative indicators of personal autonomy are difficult to measure. Moreover, in many

African cultures union formation is a process and not necessarily a single definitive event. The standard DHS

questions on age at first union do not necessarily refer to timing of marriage in a religious or legal ceremony,

or consummation of the union.

In addition, it has been suggested that financial transactions following intercourse are frequent among

adolescents in many sub-Saharan societies, and characterize a majority of early sexual encounters in some

areas. While the standard DHS questionnaire includes a question on payment for sex, there is no clear

distinction between those paying formal prostitutes and those reimbursing girlfriends or more regular

partners. Nor does it measure reciprocity of giving and receiving between unmarried adolescents and their

partners (Castle and Konate, 1999).

An area of weakness of the DHS sampling scheme is the age distribution of respondents, in particular

the often small sample sizes in the youngest groups and exclusion of teens under 15 years (sometimes even

under 19 years for males). In a sense, the age intervals chosen here to represent adolescence have been

arbitrary, reflecting DHS convention and sample sizes more than the real experiences of African youth.

Our analyses have helped to identify areas for further investigation related to adolescent reproductive

health and behavior. Among these are the following:

• Biological effects of differential fertility levels early in the reproductive years (age at menarche,

sterility due to STI infection)

• Information on community-level reproductive health behavior change communication programs, and

accessibility of contraceptive methods for adolescents regardless of marital status

• Information on reproductive behaviors among young men

• Context of first birth for teenage mothers and fathers, such as familial support systems

• Context of first sexual experience (age of partner, nature of the relationship)

• Context of first union formation (age of spouse, familial influences)

The findings on differentials and determinants in adolescent reproductive health and behavior are

useful for policy and program development for the region. Consideration of contextual variables enhances

understanding of the factors that influence adolescent reproductive decisions, which in turn affect adolescent
37

health. Understanding the factors that influence adolescents’ decisions allows for interventions affecting

overall health (including HIV transmission), fertility, population growth, and population momentum for the

region.

39

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