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Demographic Change in Sub-Saharan Africa (1993)

Chapter: 4 Recent Trends in Marriage Ages

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Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

4
Recent Trends in Marriage Ages

Etienne van de Walle

INTRODUCTION

The aim of this chapter is to review recent data on nuptiality in sub-Saharan Africa (Africa in short) and assess the demographic evidence of changes over time in the proportions married and the age at marriage. Demographers have been interested in nuptiality mostly because of its possible implications for fertility. In a classic article, Davis and Blake (1956) included the factors governing the formation and dissolution of unions in the reproductive period among the intermediate variables affecting exposure to intercourse. In their review of the proximate determinants of fertility, Bongaarts and Potter (1983:4) defined marriages as “relatively stable sexual unions” to which “socially sanctioned childbearing” is limited in most societies. As a consequence, fertility surveys that have featured so prominently in recent demographic research in Africa, particularly the World Fertility Surveys (WFS) and the Demographic and Health Surveys (DHS), have included questions on marriage. But the nature of the data sources and the actuality of the concern about fertility in Africa should not lead us to forget that marriage has long played a major role in the studies of anthropologists and

Etienne van de Walle is a professor at the Population Studies Center, University of Pennsylvania.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

sociologists because of its role in shaping descent systems and social organization.1

Much of the qualitative information collected by anthropologists, with its rich institutional and cultural context, is overlooked in the statistical studies pursued by the demographer. Marriage patterns in their own right nonetheless constitute an important topic of study for the student of population because they associate many socioeconomic, cultural, and demographic variables at the individual and societal levels. The evidence on nuptiality change could further the understanding of other social change. For example, the changing frequency of the types of unions that occur in a society (customary or civil marriages with full social recognition versus informal or temporary unions) may influence the prevalence of female-headed households and the economic environment of children. Even from the narrow perspective of the demographer, the type of union or the active involvement of a man in a household may affect infant mortality; a plausible mechanism is through the lesser access to resources by single mothers or wives of polygynists.2 Moreover, mating patterns play a major role in the transmission of the human immunodeficiency virus (HIV), a major killer that will influence the size, growth, and distribution of African populations.

For better or worse, the nature of the sources will affect the analysis of these issues, and hence understanding of them. The vast body of ethnographic descriptions of African marriage presents a complexity of peoples, perspectives, and time periods, making interpretation difficult in a comparative context. Nuptiality data are most rich, detailed, and useful when they are provided on one particular subpopulation of a country—for example, the Yoruba of Nigeria, the Mbeere of Kenya, or even the Creoles of Freetown. Recent fertility surveys, however, have stressed international comparability and reduced the concepts to the simplest common denominator. Censuses, which represent a major source of information on marriage because of their wide coverage, have also used simple definitions (but not necessarily the same ones as the surveys).

The task, then, is to look at the available material for the purpose of ascertaining the evolution of simple indices of nuptiality in recent times. The fertility perspective will dominate, but cannot be exclusive of other concerns. For example, when one examines the fertility implications of recorded changes in nuptiality, the conclusion is that age at marriage has risen in many countries of sub-Saharan Africa, but that this trend appears to

1  

The comparative insignificance of childbearing in the eyes of most anthropologists is obvious in a recent publication on the evolution of marriage in Africa by Parkin and Nyamwaya (1987).

2  

Adegbola (1987) has raised the issue of the relationship between premarital fertility and infant mortality; see also Lesthaeghe et al. (1989:329–330).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

have little relationship to any change in fertility; the proportions single increase sharply in the age group 15–19, but the number of children ever born at the same ages often changes little, if at all. It is likely that the proportion of unmarried mothers is increasing—a change that may have important demographic and social consequences—but not in relation to total fertility. Excessive concentration on the fertility aspects of age at marriage would lead us to lose sight of the overall picture.

Before reviewing the empirical evidence on nuptiality, it is important to understand some problems concerning the use of these data. The first section of this chapter deals with the consideration of three crucial issues, without which it would be impossible to proceed. These are (1) the definition of marriage, (2) problems of recall and of age reporting encountered in retrospective reports, and (3) the measurement of age at first marriage. These problems are conceptually distinct, but their effects on available data may be difficult to disentangle. The second section is devoted to a look at data sources and findings. The topic of marriage has received a great deal of attention in recent publications (e.g., Lesthaeghe, 1989; United Nations, 1990). Because the results of the 1990 round of censuses have not yet appeared fully, the main new data sets consist of results from the DHS. The section discusses the extent to which retrospective evidence from surveys on the date and age at which individuals report they were married (as contrasted with information on the current marital status of individuals) can be used to evaluate trends in nuptiality. In the third section, I consider the effects of nuptiality changes on fertility.

It may be in order to list some of the topics that are not considered here. The discussion is limited to the marital status of women for two reasons. First, the issues raised by the nuptiality of men are even less well understood than those of women. Men marry later and spend a sizable portion of their adult life in the single state, although they probably lead in most cases a complex sexual life that does not appear in the statistical record. Moreover, in Africa, polygyny is a typical feature of men’s married life, which dilutes the connection between their nuptiality and reproduction.3 Second, the new sources on nuptiality (the WFS and DHS, discussed below) pay little attention to the marriage of men. Census data have provided the available information on men, and I have not tried to go beyond the available monographs on the subject (United Nations, 1988, 1990).

3  

For what a detailed investigation of male nuptiality would entail, see a suggestive study of South-Benin by Donadjè and Tabutin (1991). With an average age at marriage of 28 (compared to less than 20 for women), men are reported to have a total fertility of 11 children (compared to between 6 and 7 for women) because more than half end up in polygynous unions.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

The next topic to which I cannot do justice, despite its interest, is the topic of premarital sexual activities of women. Informal unions may be fruitful and may also represent an early stage in the contracting of a marriage. They complicate the retrospective definition of unions in demographic surveys, as I point out, but to study them in depth, the anthropological approach is essential. It may be that informal unions and premarital or even illegitimate births4 have become more frequent, but in the absence of reliable information, one confronts “the interpretive problem of sensing that marriage may be more informal than in the past without having any clear ‘data’ or clear chronology to support such a conclusion” (Guyer, 1988:1).

Finally, in the absence of new data from the last round of censuses, there is little information that would allow review of the conclusions made in the authoritative review of Lesthaeghe et al. (1989) on the subject of polygyny.5 The institution remains alive and well, although its multiple forms, which owe some of their complexity to the ambiguity of the definition of what a stable union is, challenge the analyst.

CONCEPTUAL AND MEASUREMENT ISSUES

Definitions

The subject of nuptiality is complex and is governed by different rules and practices in different countries. It has long been accepted that the description of marital status in censuses can be kept simple because people are reasonably certain about their own present status when an interviewer asks questions; being “married” corresponds to a social reality recognizable in almost any culture, so that there is no need for elaborate definitions. There are clearly diminishing returns to adding questions or attempting to narrow concepts. However, the particular reality that people recognize as the married state is by no means uniform across societies. A corollary is that one does not always know what reality is covered by conventional census categories (single, married, widowed, and divorced), and it is always possible that the changes apparent over time from the comparison of several surveys and censuses taken at different dates are more changes of implicit (the population’s) or explicit (the census taker’s) definitions than changes

4  

By illegitimate births, we mean those births that have no socially recognized legitimacy. The term illegitimate is controversial (see Adegbola, 1987), but legitimacy of offspring is a recognized goal of marital unions.

5  

Their observations spanned a period roughly between 1960 and 1980.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

in the underlying reality. Also of concern is the inverse danger that an apparent stability of some indicators of nuptiality in fact hides deep changes in the sociological reality. Lesthaeghe et al. (1989:244) remark that

…“outside wives” are more akin to concubines than to women in a polygynous union since they are external and often illicit. But demographically they are of significance as an alternative mode of reproduction in societies undergoing socioeconomic change.

How they are defined in a census or survey will affect measures of trends and the impact of economic change on these trends.

Ever since censuses have been taken in sub-Saharan Africa, they have included a simple typology of marital status (single, married, widowed, or divorced), based on self-definition by the respondents. In this rather coarse net, a variety of people are caught as “married,” including some who have not performed any ceremony of marriage or whose unions have not been formally recognized by society. It is likely, however, that what pass for marriages in a census are relatively stable unions, benefiting from a degree of public recognition; in many instances, cohabitation is also involved, although there are forms of marriages in Africa, particularly among matrilineal groups, in which cohabitation is not essential (see, for example, van de Walle and Meekers (1988) for Côte d’Ivoire). Generally, marriage in Africa is “a process,” and therefore there is some ambiguity in determining exactly when a couple is married.

The ambiguity is less critical in a census than in a fertility survey where retrospective questions are asked about age at, or date of, marriage. A retrospective question of the type—At what age were you first married? —is different in nature from the assessment of the current marital status of an individual at the time of a survey or census. Even if perfect recall by the respondent is assumed, identification of the date (by month and year) when a woman’s first conjugal union started is conceptually difficult. A number of unions that have some features of marriage, and might have been reported as such at the time they were still extant, may retrospectively appear never to have taken place; also, some unions that turned out to be successful would not have been reported as “marriages” in their early stages, but with the benefit of hindsight appear to have started in earnest at a time when their status was actually quite uncertain. Such systematic misreporting introduces biases in the a posteriori reporting of age at marriage in surveys.

The WFS and DHS surveys have introduced new concepts in the description and measurement of African marriage. Designed as fertility surveys, they have focused on one aspect of the marital state—exposure to sexual intercourse. For female respondents in surveys, being married was held by the designers of the WFS and the DHS to be synonymous with “living in union” or “living with a man”; the fact of cohabitation was the

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

single most important criterion distinguishing a marriage for these surveys.6 The concept is not exactly comparable with the commonly accepted (but somewhat imprecise) category of married in a census, and comparisons of these surveys with censuses taken at the same time usually reveal differences that must be due to the definitions used. Moreover, differential coverage may account for some of the difference between census and survey results; censuses may be better at capturing young adults than surveys. Yet, because censuses and surveys are usually not taken exactly in the same year, the differences between the two sources in the same countries have sometimes been attributed to changes in nuptiality. Table 4–1 presents the comparison of the percentage ever married at ages 15–19, 20–24, and 40–44 in the two kinds of sources.

The expectation is that surveys should find more women living in union than there are married women in the census, and typically fewer widows and divorcees. Blanc and Rutenberg (1990:53) give the following rationale:

It is expected that the retrospective estimates of the proportion of women ever married calculated from DHS data will be higher than the estimates from previous censuses or surveys for three reasons. First,…censuses often use a less inclusive definition of marriage than that of the DHS surveys…Second, information on marital status and date of marriage in DHS surveys usually comes from the individual questionnaire, for which the respondent is a woman, rather than from the household questionnaire, for which the respondent is often a male head of household. A third factor which might act to improve the validity of estimates from DHS surveys, relative to earlier censuses and surveys, is that the quality of reporting of …marriage dates may have improved in recent years…

Surprisingly, Table 4–1 does not conform to these expectations when one compares direct estimates based on DHS and census data for each country. At age 15–19 (and where available, age 20–24), the proportions ever married were higher in the census than in the DHS for Botswana, Burundi, Kenya, Togo, Uganda, and Zimbabwe; it is only at 40–44 that the DHS always finds a higher proportion of ever-married women. Because all the DHS surveys in Table 4–1 have a later date than the census, part of the difference could be explained by a time trend, either in the age at marriage or in the accuracy

6  

According to the DHS Interviewer’s Manual (Institute for Resource Development, 1987:59):

“Lived with a man” means that they stayed together for some time, intending to have a lasting relationship, regardless of the formal status of the union…. For example, if a woman went to live with her boyfriend and his family, and stayed for several years, she would be considered as “living together”, whether or not the couple had any children. On the other hand, if a woman had a boyfriend for a year but never lived with him, she would not be considered as ever having married or lived with him.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–1 Comparison of Women Ever Married (percent)

 

Age

Country

Source

Date

15–19

20–24

40–44

Botswana

DHS, Ra

1981

13.1

42.2

82.8

 

Census

1981

7.3

31.2

78.9

DHS

1988

6.1

30.3

81.5

Burundi

DHS, Ra

1979

21.7

76.3

98.7

 

Census

1979

19.2

72.6

97.4

DHS

1987

6.8

66.7

99.1

Kenya

Census

1979

28.8

97.9b

 

DHS

1989

20.1

68.2

98.5

Liberia

DHS, Ra

1984

38.1

77.0

98.4

 

Census

1984

35.7

70.9

96.4

DHS

1986

36.0

75.3

98.3

Mali

DHS, Ra

1976

66.2

95.9

100.0

 

Census

1976

51.1

88.0

98.0

DHS

1987

75.4

98.0

99.7

Senegal

DHS, Ra

1976

52.5

87.1

100.0

 

Census

1976

38.6

76.1

97.5

DHS

1986

43.5

77.4

100.0

Togo

DHS, Ra

1981

40.1

81.8

100.0

 

Census

1981

43.3

81.8

97.2

DHS

1988

27.2

75.8

99.6

Uganda

Census

1969

49.9

86.5

93.9b

 

DHS

1988–1989

40.8

83.0

99.0

Zimbabwe

DHS, Ra

1982

29.9

80.7

98.7

 

Census

1982

26.1

76.5

97.0

DHS

1988

19.8

71.5

99.1

NOTE: Data are from national-level census and DHS.

aR: Reconstruction for census date.

bAt age 50.

SOURCE: Data from Blanc and Rutenberg (1990: Table 2.5) for reconstruction and census proportions; United Nations (1990) for census data on Kenya in 1979 and Uganda in 1969; otherwise, Lesetedi et al. (1989); Segamba et al. (1988); Kenya (1989); Chieh-Johnson et al. (1988); Traore et al. (1989); Ndiaye et al. (1988); Agouke et al. (1989); Kaijuka et al. (1989); and Zimbabwe (1989).

of reporting. Blanc and Rutenberg tried to remove the effect of the change over time by reconstructing from DHS data the proportion ever married at the date of the previous census; in doing so, they had to rely heavily on the retrospective reporting of dates of union, which I argue here is incompatible with current status data. I show the results of their reconstruction in Table

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

4–1 (labeled DHS, R). The reconstructed proportions ever married are usually substantially higher than those recorded in the census, but they are also much higher than those at the actual time of the survey. This disparity suggests a severe bias in the proposed reconstruction.

A likely explanation of the difference between current marital status as measured at the times of surveys and censuses is that the criterion of cohabitation, which is part of the DHS definition of a union (as of the time of the interview), excludes many people who would have defined themselves to a census taker as married. It is true that surveys also may include people living in unions who are not viewed as married by the census, but their number is smaller than that of the noncohabiting married who are excluded. Other reporting biases in the retrospective reporting of dates or ages at the onset of the first union vitiate their use in the comparison by Rutenberg and Blanc.

Despite the general principle of looking at unions (defined by the criterion of cohabitation) rather than at formalized marriages, there was a remarkable diversity in the phrasing of the WFS questions, and sometimes they were different enough to yield quite different results in neighboring countries with similar populations, such as Ghana and Côte d’Ivoire. Additional diversity must have resulted from the use of local languages in the interviewing. The DHS has standardized questions to a greater extent than the WFS, but here too, there is some variety in the phrasing, which may reflect diversity in the legal definition of marriage in particular countries, or even in the ideologies of survey takers. It is interesting, for example, that all the DHS surveys in French-speaking countries (with the exception of Togo) have more or less denied the existence of consensual unions, whereas all the English-speaking countries (with the exception of Zimbabwe and Sudan) recognized their importance by giving them a separate column (headed “living together”) in the published survey reports.7 Among the DHS reports for French-speaking countries, the one for Senegal stated explicitly that “marriage remains the only socially accepted framework for sexual links” (Ndiaye et al., 1988:13); in Burundi, “cases of concubinages are rarely declared as being marriages” (Segamba et al., 1988:17); in Mali (Traoré et al., 1989), the survey categories appeared “very ambiguous” to the authors of the report, and married women were classified in the report with women “living with someone.” In contrast, among English-speaking countries, the Liberia (Chieh-Johnson, et al., 1988) DHS seems to have elicited an extraordinary proportion of responses qualifying the union as consensual: 38 percent of women between 15 and 49 “lived together,” whereas only 29

7  

Zimbabwe and Togo adopt a similar solution toward consensual unions: they classify them with marriage, not because they are unimportant but because they are difficult to distinguish.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–2 Never-Married Females in Botswana by Age (percent) —Successive Censuses and Surveys

 

Census

Family Health Survey

Age

1971

1981

1984

1988

15–19

87

93

47

94

20–24

56

69

4

70

25–29

37

47

0.5

43

30–34

27

32

0.4

30

35–39

20

25

0.1

25

40–44

17

21

0.0

19

45–49

13

17

0.0

20

 

SOURCES: Botswana (1985); Lesetedi et al. (1989).

percent were “married”; in Botswana, the report stated that “a union is not prerequisite to childbearing” and “current marital status…does not take into account the large proportion of women in stable relationships that do not involve cohabitation” (Lesetedi et al., 1989:11).

Rather small differences in phrasing of the survey or census questions can yield extraordinary differences in the proportions ever married. For Botswana, there are two censuses and two Family Health Surveys (FHS) in the 1970s and 1980s, providing an opportunity to examine trends in the proportion married over time. From the 1971 and 1981 censuses, and the 1988 FHS (taken under the DHS program), the age at marriage seems to be relatively late in Botswana, the proportions who never marry are high for an African country, and there is a trend toward later marriage. However, the 1984 FHS breaks the trend, giving an opposite impression of early and universal marriage (see Table 4–2).

In comparing the two FHS surveys, the main difference appears to be between those “in a consensual union” in 1984 (52.3 percent of women aged 15–49) and those “living together” in 1988 (10.8 percent). In 1984, the operative survey question on consensual unions was, Have you ever had a partner? In 1988, the criterion of cohabitation was introduced: Have you ever been married or lived with a man? Marriage in Botswana still involves the payment of bridewealth (Timæus and Graham, 1989:373), a prolonged and cumbersome process. Heads of cattle that are part of the bridewealth are an important factor of production in Tswana agriculture (Peters, 1986), and marriage is an index of the economic viability of a household. On the other hand, living with a man in a country where half of the women currently in union reported that their partner was not living with them at the time of the 1984 survey (Botswana, 1985:48) is probably not a good indication of the stability of a relationship or of its likelihood to bring forth

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

offspring. If the aim is to provide a denominator of “women in union” for the study of fertility, it could be argued that the census definition (or its 1988 FHS extension) is unduly restrictive. A convincing case could probably also be made that the 1984 FHS definition was too inclusive.

Marriage, as contrasted with temporary and unstable free unions, remains an important concept in Botswana. Timæus and Graham argued that late marriage was an important feature of the demography of Botswana, and one that had been established for some time. They acknowledged, however, that the effect of late marriage on fertility was “less than one might expect” (Timæus and Graham, 1989:381). It is probable that marriage has important social consequences for women and men, and that the permanence of the institution of the bridewealth is connected more to some aspects of social organization than to the biological reproduction that keeps demographers busy and conditions survey design. A classic article by Comaroff and Roberts (1977; see also Caldwell et al., 1991) has examined some of the conflictual aspects of marriage in Botswana, and the different interests served for men and women. Informal relationships may be exploitative of women (Timæus and Graham, 1989:381), and their consequences for the welfare of children and the structure of society are worthy subjects of study. It is possible, however, that historical changes in the timing and prevalence of marriage had little influence on fertility.

Botswana may appear to be an extreme case in the demography of marriage in Africa, and the very high proportions of never-married women recorded by the 1988 Family Health Survey (see Table 4–2) are not replicated elsewhere. But there are many indications from other countries that the criterion of cohabitation may not be the sine qua non identifier of a union. In Lomé, Togo, for example, the APEL (Arrivée du Prochain Enfant à Lomé) survey of 1983–1984 found that 31 percent of women in union were living in a different residence than their mates (Ekouevi, 1992). A preliminary conclusion should be that the haziness of the concepts will make comparisons over time and space hazardous.

Problems of Recall and of Age Reporting

In addition to the problem of definition discussed in the previous section, retrospective questions of the kind included in the WFS or the DHS— In what month and year did you start living with your first husband? — suffer from a fundamental weakness when asked in societies where people do not know their ages; moreover, it is possible that older women tend to “forget” the existence of earlier unions or to edit them out in their reports. The question continues to be asked in surveys, and in particular was asked in both the WFS and the DHS; it is therefore worthwhile to look at the

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

results. Taken at face value, the information may provide interesting information about trends (inferred from differences in the ages at first marriage reported by successive cohorts) and about differentials between ethnic or social groups.

The raw material used here is drawn from the DHS.8 All of the country reports (except for Botswana) contain a table that presents reported age at first marriage or union, classified by age of the respondent at the time of the survey. Several of the DHS reports comment on the reliability of the evidence. The report for Burundi notes that women appear to have a relatively precise knowledge of their date of marriage: in the survey, 58 percent gave the month and year of occurrence. Similarly, in Zimbabwe, 77 percent of the women were able to do so; the report notes, however, “a tendency on the part of some women to report the date (age) when the marriage was officially registered rather than the date (age) when the couple first began living together” (Zimbabwe, 1989:18). In Ghana, only 29 percent of ever-married women reported both a month and a year of first marriage; the report notes: “In addition to the difficulty in correct dating of events, the formalization of marriage itself may span a number of years” (Ghana, 1989:11). These problems are akin to problems of definition addressed in the previous section. If reported dates indeed correspond to a stage of formalization or to a date of registration, the reporting of age at marriage might be biased upward.

The staff of the DHS has addressed the issue of the quality of data on age at first marriage (Blanc and Rutenberg, 1990). Table 4–3 gives the percentage of ever-married women by age who reported their date of first union by year and month, and for whom no imputation was necessary. The information is particularly deficient in West African countries but has been improving in recent cohorts. In Mali, for example, less than 10 percent of women were able to provide month and year of first union, and it is hard to place too much reliance on the precision of the ages given and the reliability of trends. In Burundi, Uganda, and Zimbabwe, the percentages of unions with precise dates are much higher, perhaps because these correspond to recorded Christian ceremonies. Incidentally, the quality of reporting is related to the level of education of the respondents, which raises the question of whether apparent trends in age at marriage that characterize cohorts or educational groups are genuine or are at least partly the result of better reporting.

The evidence on reported age at marriage in the DHS is most interest-

8  

For a review of this evidence in the WFS, see Lesthaeghe et al. (1989:245). They express skepticism about the apparent trends in cohort comparisons based on a single retrospective survey.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–3 Ever-Married Women Who Reported Month and Year of First Union (percent)

 

Age of Women

 

Country, Date

20–24

30–34

45–49

All Women

Botswana, 1988

76.2

64.6

60.6

65.7

Burundi, 1987

78.6

53.2

38.8

57.7

Ghana, 1988

35.8

28.1

19.1

29.3

Liberia, 1986

37.2

28.2

14.9

29.0

Mali, 1987

9.3

6.4

0.2

5.9

Senegal, 1986

19.0

14.3

8.5

16.6

Togo, 1988

31.1

15.6

4.5

19.6

Uganda, 1988–1989

91.4

86.0

69.5

86.0

Zimbabwe, 1988–1989

88.0

76.5

58.4

76.9

NOTE: Data are national-level DHS.

SOURCE: Blanc and Rutenberg (1990: Table 2.1).

ing when it can be compared with similar information collected in the WFS at an earlier date (because the two surveys used a similar definition of union based on the criterion of cohabitation) and when the same cohorts of women can be compared in both surveys. Blanc and Rutenberg concluded from their comparisons (which involved only two sub-Saharan countries, Ghana and Senegal) that the median ages at first marriage “match reasonably well”; according to these authors (Blanc and Rutenberg, 1990:49), “The median ages reported in the two surveys are usually within one-half year of each other and trends across cohorts are generally similar [i.e., indicating an age at marriage rising with time].” The fit is indeed satisfactory for Ghana and Senegal, two countries that have accuracies of reporting of ages at union that are, respectively, in the middle and at the lower end of the range in Table 4–3. Comparisons can also be attempted for Kenya and the Sudan.9

In Kenya, for example, the two surveys were not exactly 10 years apart, but the timing is close enough to attempt a comparison between those aged 20–24 in 1977–1978 and those aged 30–34 in 1989, and similarly for other cohorts as well. The Sudanese surveys are also almost 10 years apart. Table 4–4 compares the percentages of cohorts married before age 15, at 15– 17, at 18–19, and the published medians.10

9  

WFS and DHS data for Sudan refer only to northern Sudan.

10  

The medians in the WFS are computed from single-year distributions of ages at marriage and in the DHS from grouped data.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–4 Comparison of Reported Ages at First Union, Kenya and Sudan

 

Age at First Union (%)

Age at Time of Survey

<15

15–17

18–19

Median

WFS

DHS

WFS

DHS

WFS

DHS

WFS

DHS

WFS

DHS

Kenya (WFS 1977–1978), DHS (1989)

20–24

30–34

13

23

31

28

21

17

18.1

17.9

25–29

35–39

16

20

34

31

21

20

17.5

17.9

30–34

40–44

21

25

34

30

23

20

17.1

17.3

35–39

45–49

22

18

32

28

21

21

17.1

18.5

Sudan (WFS 1978–1979), DHS (1989–1990)

20–24

30–34

26

26

21

24

10

10

18.6

18.1

25–29

35–39

31

33

28

28

16

12

17.0

16.4

30–34

40–44

42

37

27

31

11

10

15.7

15.8

35–39

45–49

38

34

27

31

12

12

16.2

16.3

NOTE: WFS and DHS data for Sudan refer only to northern Sudan; data are national-level for Kenya.

SOURCES: Data from Kenya (1980, 1989); Sudan (1982, 1991).

Lesthaeghe et al. (1989:245) noted in their examination of the WFS data that overreporting of the age at first marriage was typical for older women, and they attributed the tendency of the median to rise as one goes back in time to “advancing age and decreasing literacy of respondents.” The difference in the medians for most cohorts (but not for the oldest one, consisting of women aged 45–49 in 1989) between the two surveys in Kenya appears to be within the expected random range of imprecision. In Sudan, the match is good, and the difference exceeds half a year for only one cohort. However, the reporting of ages at marriage in both countries as either “before 15,” “from 15 to 17,” or “from 18 to 19” is rather different in the two surveys and cannot be explained by lapses of recall. The robustness of the median hides some diversity in the actual reporting of ages. These results do not generally give the impression of a problem that would be restricted largely to older women. The differences between reported proportions vary, in some cases, more between surveys than they do between cohorts in the same survey.

It is difficult to draw any conclusions about the adequacy of retrospective reports on age at union for inferring trends. The consistency of the evidence on the median age at marriage from two surveys that use similar

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

methodologies is reassuring for Ghana, Kenya, Senegal, and Sudan. In three of the countries, both surveys indicate a rise in the median age at first marriage; for Kenya, however, the apparent trend in the cohort medians for the WFS had disappeared in the DHS medians.

Measurement

The DHS reports have systematically presented median reported ages at first marriage by current age of women; age is a proxy for birth cohort, and the tabulation of these data is designed to show trends, if such trends exist. The median is the interpolated age at which 50 percent of all women are married. As computed in the WFS or the DHS, the median age at marriage does not take into account those women who will never marry. In most African countries, most women eventually go on to marry, and the effect of this assumption is relatively minor. (I explore this point more at length in the appendix to this chapter, but it has no direct bearing on the argument of this section.)

It has been convenient to use current status measures of demographic phenomena where recollection of exact dates is deemed unreliable. One of the oldest and most widely accepted estimates based on current status is the singulate mean age at marriage (SMAM).11 SMAM is vulnerable to misstatement of ages and has the further drawback of assuming, in principle, a closed population with unchanging behavior. In general, however, it has proved a robust measure of the age at first marriage.

It is interesting to compare estimates obtained retrospectively for the youngest cohorts and the singulate mean age at marriage based on data from the same surveys, as in Table 4–5. The result is by now well established: SMAM is always higher than either the median or the mean age at first marriage or union computed on the basis of retrospective records. This result is not an issue of survey-imposed definitions, because the current reports of marital status use the same criteria of union as the retrospective ones.

There are several possible explanations for the differences:

  1. Time trends: SMAM assumes stable proportions single over time. If changes had taken place, SMAM would likely reflect an earlier period when marriage was earlier. The observed difference, however, goes in the wrong direction.

  2. Particular properties of the measurement techniques: For example,

11  

The singulate mean age at marriage is an estimate of the mean age at first marriage of those who ever marry, computed from the proportions of people who are single. For details of the computation, see United Nations (1983: Annex I).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–5 Summary of Various Estimates of Age at First Union

 

Age at Time of Survey

 

Country

20–24

25–29

30–34

35–39

40–44

45–49

SMAM

Burundi

a

19.5

19.5

19.6

19.4

19.7

21.5

Ghana

18.7

18.5

18.1

18.1

17.6

17.8

20.2

Kenya

19.8

18.6

17.9

17.9

17.3

18.5

20.5

Liberia

18.2

17.9

17.2

17.2

16.0

16.6

20.1

Mali

15.9

15.9

15.6

15.6

15.6

15.8

16.4

Nigeria

17.8

17.2

16.3

17.3

16.8

17.3

19.6

Senegal

17.2

16.7

16.5

16.2

16.1

15.9

19.5

Sudanb

a

20.5

18.1

16.4

15.8

16.3

23.8

Togo

18.6

18.4

17.7

18.5

18.0

18.7

20.3

Uganda

17.8

17.5

17.0

16.8

16.6

16.7

18.9

Zimbabwe

19.7

18.8

18.5

19.0

18.1

18.6

20.4

NOTE: Data are national-level DHS.

aMajority of women in age group have not yet married.

bDHS data for Sudan refer only to northern Sudan.

SOURCES: Data on median ages based on retrospective declarations of women and SMAM computed from the proportions never married at the time of the survey, as reported in Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agouké et al. (1989); Kaijuka et al. (1989); and Zimbabwe (1989).

the median tends to be younger than the mean because of the skewness of the distribution of marriages; the weight of such effects should be light in most instances (for a detailed discussion, see appendix to this chapter).

  1. The processual nature of marriage: As discussed above, current reports of marital status may tend to underestimate the prevalence of unions that, with the benefit of hindsight, will turn out to have been the beginning of a marriage that withstood the test of time; conversely, retrospective reports may trace the beginnings of a union to its earliest signs of viability.

  2. Problems of recall: Women who do not know their ages do not know their ages at marriage either. Instead of reporting their true ages at the time of union, they may report (or the interviewer may write in) the age at which it is believed that girls should be married in a particular society. The existence of such normative ages has been reported in various contexts.12

12  

In Bamako and Bobo-Dioulasso, van de Walle and van de Walle (1988) recorded a strong feeling among women that a girl ought to be married at age 17.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×
  1. Fabrication: Short of outright lying, informants may glamorize their earlier informal unions, particularly if they have produced children. As Bleek (1987:319) warns, “Embarrassing questions in a survey produce unreliable answers.” (Bleek uses the misreporting of marriage as an example.)

There are potential causes of retrospective bias that could work in the opposite direction. Women may fail to report past periods of cohabitation that had no lasting consequences. Moreover, as noted above, the formalization of marriage may take several years in Ghana and in Zimbabwe, there is a tendency to report formal registration dates instead of dates of first cohabitation. The net effect of these influences, however, is to bias the retrospectively reported age at first marriage downwards.

I conclude this section, then, with the hypothesis that the retrospective measure of age at union and the singulate mean age at marriage measure different and irreducible dimensions of nuptiality. Of the two, SMAM conforms better to the definition of a union at the time of the survey. The SMAMs computed from current status reports in the WFS and the DHS take into account the criterion of cohabitation, which defines a union for these surveys. In retrospective reports, however, a number of other criteria are introduced, and the overall tendency may be to relax the definition and produce earlier ages at first union.

ASCERTAINING TIME TRENDS IN AGE AT MARRIAGE

Retrospective Evidence from Surveys

The distribution of median ages at first union in the DHS has been used routinely to chart the temporal evolution of age at marriage and has been interpreted as reflecting the experience of successive cohorts. For example, according to the Uganda survey report (Kaijuka et al., 1989:14), “The median age at marriage suggests that there has been recently a slight rise in the age at first union, since women aged 20–24 and 25–29 entered their first union later (age 18) than women aged 30 and above (age 17).”

Table 4–5 presents the evidence from median ages at first union classified by age at time of survey. In several countries (Kenya, Nigeria, Senegal, Zimbabwe) there is a dramatic increase in the age reported by the very last cohort, aged 20–24 at the time of the survey, which seems too large to be plausible; in Burundi and the Sudan, moreover, 50 percent of the women in the age group had not yet married. I believe that medians based on the age group 20–24 tend to be higher than the other medians. A plausible interpretation is that the downward biases inherent in the retrospective reporting of age at marriage (which were discussed in the previous section) operate less strongly in that age group than in later ones. There are still many women aged 20–24 who are regarded as single at the time of the interview on the

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

basis of their current status, who would later report an earlier age at marriage. Several countries, however, have taken the change in the proportions married at that age at face value.13

If one disregards the age group 20–24, the evidence of a clear trend in age at marriage is very inconclusive. Only in Sudan and Liberia is there a sizable increase; elsewhere, either the trend line is flat (Burundi, Mali, Nigeria, Togo, Zimbabwe), or the change is less than one year (Ghana, Kenya, Senegal, Uganda). Over a period of 20 years (the difference between the cohorts aged 25–29 and 45–49), this change is very small. The margin of uncertainty inherent in the techniques of measurement and the concepts used exceeds the measured differences.

Evidence from Current Status Data

The time taken to publish census results is so long that there are few new readings on the evolution of nuptiality over time. Writing in the late 1980s, Lesthaeghe et al. (1989:324) summarized the evidence:

In countries with two or more censuses, all proportions single, irrespective of sex and age group, tend to show an increase over time. In Angola, Kenya, and Tanzania the proportions single women 15–19 rise by approximately 0.080 per decade, implying an increase in SMAM of almost half a year. In Liberia and Ghana, the increment is of the order of 0.110 and 0.200 respectively for the decade of the 1960s, implying a SMAM increase of 8 and 13 months.

Lesthaeghe et al. believed that the increase was spent by 1975, but they thought that census returns from the 1980s would shed additional light on the trend. Unfortunately, most of this information is not yet available at this writing. I repeat that information from the WFS or the DHS on current marital status is not strictly comparable to census data. As shown in Table 4–1, in seven out of nine DHS where the comparison could be made, the singulate mean age at marriage computed from DHS proportions ever married was greater than that computed from census data.

I have obtained preliminary data for 14 regions from the 1988 census of Tanzania and have compared them to data from the census of 1978, 10 years earlier. This evidence is presented in Table 4–6. In that country at least, the tendency toward higher proportions single has continued into the most recent intercensal period and may be accelerating. For females, the

13  

The report for Nigeria states: “On a national scale, age at marriage has not changed appreciably over time. Only among the youngest women (15–24) has there been a shift from marrying during the mid-teen years to the later teen years” (Nigeria, 1992:60).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–6 Singulate Mean Age at Marriage and Proportions Married, Women: Selected Regions of Tanzania

 

Percentage Single

 

SMAM

15–19

20–24

Region

1978

1988

1978

1988

1978

1988

Dodoma

19.15

20.55

62.45

70.07

16.22

25.86

Arusha

19.14

20.95

62.48

75.55

17.09

28.70

Kilimanjaro

21.78

24.05

86.69

90.42

36.91

51.30

Tanga

19.58

20.74

71.36

74.01

18.36

27.97

Morogoro

19.52

21.47

64.75

71.55

19.25

33.08

Dar es Salaam

19.38

22.09

57.81

78.48

19.57

41.99

Lindi

18.73

20.12

57.67

66.52

12.74

22.84

Mtwara

18.82

19.64

60.57

66.96

12.04

19.45

Ruvuma

19.81

20.44

72.30

69.59

17.98

24.72

Iringa

20.45

22.17

77.02

84.90

25.67

36.29

Mbeya

18.63

19.79

58.17

65.35

11.78

20.15

Kigoma

19.16

20.01

67.10

73.18

13.43

19.05

Shinyanga

18.48

19.17

54.56

59.32

10.08

16.87

Kagera

18.47

19.31

58.90

67.95

8.03

14.39

 

SOURCES: Data from Tanzania (1982) and unpublished tabulations from the 1988 Tanzania census.

differences in singulate mean age at marriage between 1978 and 1988 averaged 1.4 years, a very large increase. (Increase for males—not shown—is not as spectacular and averages only 0.9 year.) The change in the proportion single in the age group 15–19 is not as large for 1968–1978, but it is larger in subsequent age groups up to and including 30–34; the proportions married in the older cohorts, now in their forties, remain unchanged. The picture may be interpreted as evidence that the proportion never marrying is moving progressively up the age distribution, and that the cohorts that have entered the marriage market since the 1960s will not partake in the universal marriage that used to prevail in Tanzania. Instead of a change in the age at marriage, the data would then reflect a change in the prevalence of permanent celibacy. The extent to which this is the result of a change in the definition of marriage or of a genuine change in the proportions in union is a moot point. I presume that the proportions at risk of childbearing have not changed very much and that the importance of the change in nuptiality lies elsewhere. This point receives further discussion in the next section.

Table 4–7 presents the available estimates of the singulate mean age at marriage in African countries, compiled from various sources. This material is very disparate in nature, and it is hard to compare the various cen-

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–7 Singulate Mean Age at Marriage, Women

 

Data Source

Region and Country

Date

Type

SMAM

Differencea

Sourceb

Western

 

Benin

1961

Survey

16.9

 

UN

 

1982

WFS

18.3

nc

UN

Burkina Faso

1975

Census

17.4

 

UN

Côte d’Ivoire

1975

Census

18.4

UN

 

1978

WFS

18.9

nc

UN

Ghana

1960

Census

17.8

 

UN

 

1971

Census

19.4

(1960–1971) 1.6

UN

1979–1980

WFS

19.4

 

WFS

1988

DHS

20.2

(1980–1988) 0.8

DHS

Guinea

1955

Survey

16.0

 

UN

Guinea-Bissau

1950

Survey

18.3

UN

Liberia

1962

Census

18.0

UN

 

1970

Survey

18.7

UN

1974

Census

19.4

(1962–1974) 0.7

UN

1984

Census

19.7

(1974–1984) 0.3

DHS

1986

DHS

20.1

nc

DHS

Mali

1960

Survey

16.2

 

UN

 

1976

Census

18.0

UN

1987

DHS

16.4

nc

UN

Mauritania

1977

Census

19.5

 

UN

Nigeria

1981–1982

WFS

18.7

UN

 

1990

DHS

19.6

(1981–1990) 0.9

DHS

Senegal

1960

Survey

17.4

 

UN

 

1976

Census

19.0

nc

UN

1978

WFS

18.3

 

UN

1986

DHS

19.5

(1978–1986)

DHS

Togo

1958

Census

17.6

 

UN

 

1971

Census

18.5

(1958–1971) 0.9

UN

1988

DHS

20.3

nc

DHS

Middle

 

Cameroon

1976

Census

18.8

 

UN

 

1978

WFS

18.8

nc

UN

Central African

1959

Survey

17.3

 

UN

Republic

1975

Census

18.4

(1959–1975) 1.1

UN

Chad

1963

Survey

16.5

 

UN

Congo

1960

Survey

17.6

UN

 

1974

Census

19.6

(1960–1974) 2.0

UN

1984

Census

21.9

(1974–1984) 2.3

UN

Gabon

1960

Survey

17.7

 

UN

Zaire

1955

Survey

18.3

DTA

Western Zaire

1975–1976

Survey

20.1

nc

UN

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

 

Data Source

Region and Country

Date

Type

SMAM

Differencea

Sourceb

Eastern

 

Burundi

1965

Survey

20.8

 

UN

 

1970–1971

Census

21.5

UN

1979

Survey

20.8

UN

1985

Survey

20.7

(1965–1985) –0.1

YB

1987

DHS

21.9

nc

UN

Ethiopia

1978

Survey

17.5

 

YB

 

1981

Survey

17.7

UN

1984

Survey

17.1

(1978–1984) 0.4

UN

Kenya

1962

Census

18.4

 

UN

 

1969

Census

18.5

DHS

1977–1978

WFS

20.0

DHS

1979

Census

20.3

(1962–1979) 1.9

UN

1989

DHS

20.5

(1978–1989) 0.5

DHS

Madagascar

1975

Census

20.3

 

UN

Malawi

1977

Census

17.8

UN

Mozambique

1950

Census

19.4

UN

 

1980

Census

17.6

nc

UN

Rwanda

1970

Survey

20.1

 

UN

 

1978

Census

21.0

UN

1983

WFS

21.2

nc

UN

Somalia

1980–1981

Survey

20.1

 

UN

Uganda

1969

Census

17.7

UN

 

1988–1989

DHS

18.9

nc

DHS

Tanzania

1967c

Census

17.9

 

UN

 

1978c

Census

19.1

(1967–1978) 1.2

UN

1978c

Survey

19.2

 

YB

1978

Census

19.1

YB

1988d

Census

20.8

(1978–1988)

1.4

Zambia

1969

Census

18.2

 

UN

 

1980

Census

19.4

(1969–1980) 1.2

UN

Zimbabwe

1982

Census

20.4

 

UN

 

1988–1989

DHS

20.4

nc

DHS

Southern

 

Botswana

1971

Census

24.8

 

UN

 

1981

Census

26.4

(1971–1981) 1.6

UN

1984

Survey

17.6

 

FHS

1988

DHS

17.4

nc

DHS

Lesotho

1966

Census

20.3

 

UN

 

1977

WFS

20.5

nc

UN

South Africa

1951

Census

22.8

 

UN

 

1960

Census

22.8

(1951–1960) 0.0

UN

1980

Census

25.7

(1960–1980) 2.9

UN

1985

Census

26.1

(1980–1985) 0.4

YB

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

 

Data Source

Region and Country

Date

Type

SMAM

Differencea

Sourceb

Northern

 

Sudan

1973

Census

18.7

 

UN

 

1979

WFSe

21.5

UN

1989–1990

DHSe

23.8

(1979–1989) 2.3

DHS

anc: not comparable.

bDHS, computed from percentage never married given in First Country Reports, for survey or earlier comparison; DTA=Brass et al. (1968: Table 5.7); FHS=Botswana (1985); UN= United Nations (1990: Annex Table A.1); WFS=Ghana (1983), YB=United Nations Yearbooks (passim).

cMainland only.

dTotal for 12 provinces. SMAM for same provinces in 1978 was 19.4, and difference is calculated on that basis.

eRefers only to northern Sudan.

suses and surveys over time. I have calculated change over time for sources that appear to use the same definition of marriage, but have avoided matching census or earlier survey data with the WFS and DHS, for reasons explained earlier.

For all its imperfect nature, the evidence in Table 4–7 appears to suggest that the age at marriage has been increasing since the beginning of data collection. Eastern and southern Africa appear to be breaking the average age of 20 years; age at marriage appears to remain lower in western and middle Africa. The extent to which the increasing age at first marriage hides changes in the proportions that will ever marry is not clear. If young cohorts behave differently from their elders, in terms of the proportion ultimately marrying, the SMAM ceases to be a reliable estimate of the age at marriage in a period.

AGE AT MARRIAGE AND FERTILITY

This section looks at three distinct subjects: first, the relationship between age at marriage and age at first birth in retrospective reports of women in fertility surveys; second, the relation between age at marriage (as indexed by the proportions ever married in age groups 15–19 and 20–24) and the children ever born to women in those age groups; and third, the evidence that a decline in the proportions married over time has resulted in a decline in the number of children ever born.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

Evidence from Retrospective Reports

Recently, Westoff (1992) examined WFS and DHS data on age at first marriage and age at first birth, reported retrospectively by women in successive age groups; he treated those as indications of cohort changes. Westoff (1992:3) distinguished three types of countries: “the first category in which there are clear and strong indications of increases in age at marriage and age at first birth; a second group in which there may be some recent changes underway, and a third group that shows little or no evidence of any change.”

Countries in northern Africa, which do not concern us here except for the Sudan, make up the first category that generally shows clear increases in ages both at marriage and at first birth. The second category includes some countries for which the increases in ages at marriage are quite sustained over four age groups (women aged 20–24, 25–29, 30–34, and 35–39 in the same survey) or over six age groups (when information from WFS and DHS can be spliced together). The countries in this second category are Kenya, Mauritania, Nigeria, Senegal, Togo, Uganda, and Zimbabwe, although the change in Togo is less than half a year. None of these countries has an equally clear trend in the age at first birth. The third group— Cameroon, Côte d’Ivoire, Lesotho, Liberia, and Mali—shows no clear trends. There is an apparent sustained rise in the age at marriage in Liberia, but it is coupled with a trend downward in the age at first birth. Table 4–8 presents the data on median age at first birth from the DHS in sub-Saharan Africa used by Westoff. (For the evidence on median age at first union, see Table 4–5 above.) The impression is hard to resist that age at first birth is fairly constant, whatever the age at marriage.

Westoff (1992:18) also looked at the correlates of changes in total fertility over time, between the WFS and the DHS. He found that the decline in the proportion married by age 20 was one of two proximate determinants that influenced the decrease in total fertility (the other one being the increase in the proportion of women using contraception, which had the greater effect). There was, however, a strong northern African bias in the data set, since four countries out of the seven having both a DHS and a WFS are North African: Egypt, Morocco, Sudan, and Tunisia. Among the sub-Saharan African countries—Ghana, Kenya, and Senegal—there is no suggestion that reported changes in age at marriage by successive cohorts have resulted in a measurable change in fertility, contrary to Westoff’s overall conclusion.

It is hard to draw conclusions about “sub-Saharan Africa” on the basis of the evidence used by Westoff, for countries having either two surveys or only one. About Mali, Liberia, Cameroon, Côte d’Ivoire, and Lesotho, Westoff (1992:19) himself grants that there is no evidence of increase (a

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–8 Median Age at First Birth by Cohort Based on Retrospective Reports from DHS

Country

20–24

25–29

30–34

35–39

Burundi

21.9

20.9

21.1

21.1

Ghana

19.9

20.0

19.2

19.8

Kenya

19.3

18.6

18.3

18.7

Liberia

18.5

19.0

19.4

19.8

Mali

18.4

19.0

18.6

19.1

Nigeria

19.7

19.6

19.0

19.0

Senegal

19.0

19.0

19.0

18.7

Sudana

24.4

22.8

20.8

19.4

Togo

19.5

19.2

18.8

19.5

Uganda

18.6

18.3

18.0

18.0

Zimbabwe

20.1

19.5

19.4

19.8

aDHS data for Sudan refer only to northern Sudan.

SOURCE: Westoff (1992: Figure 2).

conclusion qualified by noting that the data for the last three countries are “more than a decade out of date”):

The remaining countries all show some suggestion, weak or strong, for the recent emergence of a trend toward increasing age at marriage and [sic: should be “or”] age at first birth. These include Kenya, Mauritania, Nigeria, Senegal, Togo, Uganda, Zimbabwe, and possibly Ghana.

He goes on to say that in Nigeria and Senegal, increases in the age at marriage and first birth “have been chiefly responsible for the recent declines in fertility that have become evident in the DHS.” Westoff’s citing age at marriage and age at first birth together, as if they were strongly linked, is puzzling, as is his assessment that there is “recent emergence of a trend toward increasing…age at first birth” (Westoff, 1992:19–20).

My own assessment of the evidence is that there is no clear evidence in the WFS or the DHS that a rise in age at marriage is causing a decline of fertility in sub-Saharan Africa. One should not forget that the indices used are very weak. To a large extent, the information about age at first birth and age at marriage comes from women who do not know their own ages; sometimes a frightening proportion of the answers are provided by imputation. On the basis of retrospective reports from one survey, it is extremely difficult to estimate time trends, either in age at marriage or in age at first birth. If the DHS results are taken at face value, there has not been much of a change in recent years—but the data are flawed and could hide real change. One must, therefore, look at other evidence.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–9 Proportions Never Married, Children Ever Born (CEB) and Proportions Childless, Women Aged 15–19 and 20–24

 

Never Married (%)

CEB

Childless (%)

Country

15–19

20–24

15–19

20–24

15–19

20–24

Botswana

93.9

69.7

0.3

1.2

76.5

25.4

Burundi

93.2

33.3

0.0

0.9

96.8

44.8

Ghana

75.6

22.6

0.2

1.3

80.7

27.9

Kenya

79.9

31.8

0.3

1.6

78.6

21.5

Liberia

64.0

24.7

0.5

1.8

62.8

19.3

Mali

24.6

2.0

0.6

1.9

55.5

17.6

Nigeria

61.4

21.7

0.3

1.4

76.5

32.3

Senegal

56.5

22.6

0.3

1.6

73.9

26.4

Sudana

72.8

24.2

0.1

0.8

91.3

62.9

Togo

72.8

24.2

0.3

1.4

78.6

26.0

Uganda

59.2

17.0

0.4

1.9

69.7

16.7

Zimbabwe

80.2

28.5

0.2

1.3

83.7

28.8

NOTE: Data are national-level DHS.

aDHS data for Sudan refer only to northern Sudan.

SOURCES: Lesetedi et al. (1989); Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agouké et al. (1989); Kajuka et al. (1989); and Zimbabwe (1989).

Proportions Ever Married and Children Ever Born

Table 4–9 presents data from DHS surveys on the proportions never married, the number of children ever born, and the proportions of childless women aged 15–19 and 20–24. On the basis of the proportion childless enumerated by age of mother, and by using a technique similar to the one that is used to compute the singulate mean age at marriage, it is possible to compute what one might call (by analogy to Hajnal’s neologism “singulate”) the “nulliparate mean age at first birth” (or NMAFB).14 This information appears in Table 4–10.

There is not a strong relation between the numbers of children ever born and the proportions never married in the DHS data, which are shown graphically in Figure 4–1 for ages 20–24. Lesthaeghe et al. (1989:330; Figure 6.14) looked at the relationship in the WFS data and concluded that

14  

For the logic behind the computation of the singulate mean age at marriage, see Hajnal (1953). The term singulate refers to the fact that mean age at first marriage is equal to the number of years spent single by those who eventually marry; by analogy, the mean age at first birth is equal to the number of years spent childless by those who eventually have a child.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–10 Synthetic Measures of Ages at First Marriage and at First Birth

Country

SMAM

NMAFB

Difference

Botswana

17.4

19.5

2.1

Burundi

21.5

22.2

0.7

Ghana

20.2

20.4

0.2

Kenya

20.5

19.3

–1.2

Liberia

20.1

18.8

–1.3

Mali

16.4

18.0

1.6

Nigeria

19.6

19.8

0.2

Senegal

19.5

18.6

–0.9

Sudana

23.8

23.9

0.1

Togo

20.3

19.6

–0.7

Uganda

18.9

17.7

–1.2

Zimbabwe

20.4

19.8

–0.6

NOTE: Data are national-level DHS.

aDHS data for Sudan refer only to northern Sudan.

SOURCES: Computed from proportions single and childless in Lesetedi et al. (1989); Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agouké et al. (1989); Kaijuka et al. (1989); and Zimbabwe (1989).

“a rise in ages at first marriage for women may not necessarily be converted into a shortening of the reproductive age span.” I would prefer to avoid any conclusion about the effect of a change in age of marriage and instead speculate that what is recorded as “in union” in the DHS and the WFS is not clearly an index of exposure to the risk of childbearing. If the married state were the context of socially sanctioned childbearing, one would expect to find a strong positive relationship between the proportions single and the proportions childless; as can be seen for women aged 20–24 in Figure 4–2, however, this relationship is not strong. The outliers are the Sudan, where late marriage appears to have had a genuine effect on the proportion childless, and Botswana, where it has very little effect. Admittedly, the relationship is much stronger for ages 15–19 (see Figure 4–3). The proportion single at ages 15–19 for females is a good proxy for age at marriage, and age at marriage is closely related to the proportion having a child; yet the proportion single is larger than the proportion childless at 15–19 in Botswana, Kenya, and Liberia.

Figure 4–4 shows the relationship between age at marriage (SMAM) and age at first birth (NMAFB). Here the relationship is also clear, but

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 4–1 Percentage married and children ever born (CEB) for women aged 20– 24 (DHS data). SOURCES: Botswana (1985); Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agounké et al. (1989); Kaijuka et al. (1989); Zimbabwe (1989).

FIGURE 4–2 Percentage married and childless for women aged 20–24 (DHS data). SOURCES: Botswana (1985); Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agounké et al. (1989); Kaijuka et al. (1989); Zimbabwe (1989).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 4–3 Never-married and childless women, ages 15–19 (in percent). SOURCES: Botswana (1985); Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agounké et al. (1989); Kaijuka et al. (1989); Zimbabwe (1989).

FIGURE 4–4 Singulate mean age at first marriage and nulliparate mean age at first birth (DHS data). SOURCES: Botswana (1985); Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Nigeria (1992); Ndiaye et al. (1988); Sudan (1991); Agounké et al. (1989); Kaijuka et al. (1989); Zimbabwe (1989).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

approximately equal numbers of countries are found on either side of the 45-degree line that would describe the relationship if age at first marriage and age at first birth were the same; one would expect marriage to precede the first birth by a number of months if it truly marked the start of exposure. However, births occur in the absence of marriage, and marriages are not always followed immediately by births.

Changes in Proportions Married and Children Ever Born

A test of changes would be the comparison of proportions ever married and children ever born over time. If age at marriage reflected the beginning of exposure to the risk of childbearing, its changes should be related to those recorded in the number of children ever born (CEB) at young ages. Kenya offers the longest series, with a steady increase in the proportion single at the youngest ages, but little change in the number of children ever born (Table 4–11). Over time, the age at marriage has been going up in Kenya, but the exposure to the risk of childbearing appears to have remained almost constant (it is too early to say whether the drop in CEB in 1989 is a real change).

CONCLUSION

Several conclusions emerge from this review of recent data on age at marriage and the proportions married. The first is that the tools of investigation remain inadequate. Recent surveys have collected detailed and sophisticated information on nuptiality with the clear rationale of using it in a

TABLE 4–11 Proportions Single and Children Ever Born, Kenya

 

Proportion Single (%)

Children Ever Born

Data Source

15–19

20–24

15–19

20–24

1962 census

55

13

0.4

1.7

1969 census

64

18

0.4

1.9

1977 National Demographic Survey

71

22

0.3

1.8

1977–1978 Kenya Fertility Survey

72

21

0.4

1.8

1979 census

71

25

0.3

1.9

1984 Kenya Contraceptive Prevalence Survey

74

24

0.4

2.0

1989 Kenya Demographic and Health Survey

80

32

0.3

1.6

 

SOURCE: Kenya (1989:10, 25).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

subordinate position in the study of fertility. But the links between fertility and nuptiality have proved tenuous and variable in sub-Saharan Africa.

There are tantalizing suggestions that nuptiality has changed in recent years. Whether the change is purely structural, because more women live in cities and have gained schooling (factors that tend to delay marriage), or whether the changes represent a profound transformation of the patterns of early and universal marriage that affect the entire population is a question that cannot be settled easily with the data at hand. The changes are certainly linked with deep transformations in the African family and are accompanied by, or perhaps in part caused by, increasing female independence inside and outside of unions. (The extensive literature on this subject includes Little, 1973; Burnham, 1987; Guyer, 1988; Locoh, 1988; Obbo, 1981; and many others.)

Various authors have discussed the recent evolution of African marriage in negative terms in sharp contrast with earlier interpretations based on convergence and modernization theory (Goode, 1970). Thus, Caldwell et al. (1991) talk about the “destabilization of the traditional sexual system”; Frank and McNicoll (1987) discuss the “caribbeanization” of African nuptiality. The same authors advance the hypothesis that new types of female-headed households that are emerging may offer promising opportunities for the deliberate control of reproduction. The debate on African nuptiality is likely to be increasingly cast in terms either of resilient adaptation by the African family to the forces of socioeconomic change or of social pathology; the HIV epidemic will feature prominently in this debate.

There have been speculations on the possible consequences of the new nuptiality patterns for fertility through variables other than exposure to the risk of pregnancy. Although the direct effect of a later age at marriage on total fertility by curtailing the period of exposure is probably at work in such countries as Burundi or the Sudan, where rules against premarital sex have remained strong, the effect of a delay in age at marriage on fertility may be more subtle in most other countries, including Kenya, Botswana, and Togo. Van de Walle and Foster (1990) suggested that premarital sexual relations may constitute a training ground for the use of birth control, because young women want to avoid the pregnancies that would jeopardize their prospects of education and jobs. The acquired knowledge of techniques of contraception and abortion would later be carried over to marriage. Other mechanisms may link the types of sexual unions to the duration of sexual abstinence or breastfeeding, to infecundability and male sterility, and to the prevalence of sexually transmitted diseases.

This chapter opens by stressing the fact that there are demographic topics other than fertility for which nuptiality patterns and intrahousehold relationships may be crucial: Infant mortality and the transmission of AIDS are obvious examples. There are good reasons to continue to investigate

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

nuptiality in surveys in view of its epidemiologic and social importance. More reflection will be needed on the best ways to ask questions about nuptiality and to interpret the answers. The next task will be to continue to analyze the nuptiality data from fertility surveys and see how they can be improved in future data collection efforts. Moreover, the publication of censuses from the 1990 round will provide fresh information to help document the changes that are thought to be taking place. It has been noted that the Tanzanian data suggest the old norm of universal female marriage may be changing. This finding will have to be confirmed in subsequent research, and its meaning ascertained.

The simple questions used in conventional censuses (the “Are you married?” type) and the more sophisticated questions in fertility surveys (Have you ever been married or lived with a man?) cannot go very far when one tries to ascertain changes over time or to capture the qualitative diversity of the types of unions or sexual relationships that exist. The statistical record is weak or void when one attempts a typology of types of union or tries to distinguish free unions and informal relations from more durable marriages. To make sense of the evolution here, there is a need to resort to other methodologies or to the descriptions of other social scientists. Their observations do not range as wide as the representative samples characterizing the sociological survey; what they gain in depth, they also lose in breadth. More work on linking anthropological or ethnographic study findings with statistical data collection in large sample surveys could greatly enhance knowledge of marriage patterns and their consequences in sub-Saharan Africa.

APPENDIX: MEDIAN AND MEAN AGE AT FIRST MARRIAGE

Computation of the median age at marriage may, or may not, take into account those women who will never marry, or, for practical purposes, have not married before a given age, such as 50, after which very few marry for the first time. In the estimates published by the WFS or the DHS, the median is the age at which half of the women in a cohort are married. The difference is illustrated by considering Kenya and Botswana. In Kenya, almost all women go on to get married; such is not the case, however, in Botswana. The comparison between the two countries appears in Table 4– A.1, which uses the proportions of currently never-married women in the DHS.

If one treats these proportions as a cohort of women aging through an unchanging nuptiality schedule, the respective median ages at marriage for Kenya and Botswana, obtained by interpolation of the proportions in Table 4–A.1, would be 20.6 and 26.2 years. If one limits the computation of the median, however, to those women who will ultimately marry (98.5 percent

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–A.1 Proportions Never Married Women, Kenya and Botswana (percent)

Age

Kenya, 1989

Botswana, 1988

15–19

79.8

93.9

20–24

31.8

69.7

25–29

10.7

43.3

30–34

5.4

30.4

35–39

3.2

25.1

40–44

1.5

18.5

45–49

2.4

20.2

NOTE: Data are national-level DHS.

SOURCES: Data from Lesetedi et al. (1989); Kenya (1989).

in Kenya and 81.5 percent in Botswana), the question becomes: When would half of the 98.5 percent of Kenyans who ever get married (or 49.3 percent) and half of the 81.5 percent of those in Botswana (or 40.8 percent) be married? The medians become 20.5 years for Kenya and 24.5 for Botswana. This seems a more legitimate computation of the median (see Shryock and Siegel, 1976:166). It cannot be used, however, before one knows the proportion of women who are likely ever to marry in a cohort and is, therefore, not always practical for estimation of the age at first union of young women reporting in a survey.

Limiting the discussion to Kenya, where most women marry, note that the two computations of the median yield very similar results and that these results in turn are close to the singulate mean age at marriage, 20.5, which is also computed on the basis of current marital status of women at the time of enumeration.

The published WFS and DHS estimates of the median age of marriage by cohort are based on retrospective reporting of the ages at which women were first married, not on current marital status as in the previous comparison. In Table 4–A.2, I have systematically computed the mean age at marriage by cohort for the DHS, by assuming that women were all married in the middle of the age group at which they reported their marriage. The computation uses all the information available and is likely to be less affected than the median by the concentration of marriages at the younger ages; its value should therefore, on the whole, tend to be a bit higher. It is obvious, however, that estimates of the means are generally close to estimates of the median based on the same retrospective data. This exercise suggests that medians and means based on the same type of data tend to be similar, but that retrospective and current status reports differ systematically.

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 4–A.2 Mean Age at First Marriage of Women

Age

Burundi

Ghana

Kenya

Liberia

Mali

Senegal

Togo

Zimbabwe

20–24

19.1

17.9

18.3

17.3

16.5

16.9

17.7

18.3

25–29

19.5

18.6

18.3

18.1

16.8

17.4

18.4

18.8

30–34

19.5

18.5

18.1

17.9

16.4

17.6

18.3

18.7

35–39

20.1

18.4

18.1

19.8

16.4

17.3

18.8

19.8

40–44

19.8

18.1

17.8

17.3

16.6

17.2

18.5

18.4

45–49

19.9

18.6

18.7

18.3

16.9

17.0

19.0

19.0

Mean of the means

19.7

18.5

18.2

18.2

16.6

17.4

18.5

18.8

Mediana

19.5

18.1

18.2

17.2

15.7

16.4

18.5

18.7

NOTE: Data are national-level DHS.

aMedian value of the medians for each group computed from Table 4–5.

SOURCES: Data from Segamba et al. (1988); Ghana (1989); Kenya (1989); Chieh-Johnson et al. (1988); Traoré et al. (1989); Ndiaye et al. (1988); Agounké et al. (1989); and Zimbabwe (1989).

Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

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Suggested Citation:"4 Recent Trends in Marriage Ages." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

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Zimbabwe 1989 Zimbabwe Demographic and Health Survey 1988. Harare: Central Statistical Office, Ministry of Finance, Economic Planning, and Development; Columbia, Md.: Institute for Resource Development/Macro Systems, Inc.

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This overview includes chapters on child mortality, adult mortality, fertility, proximate determinants, marriage, internal migration, international migration, and the demographic impact of AIDS.

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