Demographic Change in Sub-Saharan Africa (1993) / Chapter Skim
Currently Skimming:
4 Recent Trends in Marriage Ages
4 Recent Trends in Marriage Ages
Pages 117-152
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 117... ...
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)
|
From page 118... ...
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.
|
From page 119... ...
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)
|
From page 120... ...
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.
|
From page 121... ...
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.
|
From page 122... ...
. 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.
|
From page 123... ...
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
|
From page 124... ...
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., 1988:171; in Mali (Traore 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)
|
From page 125... ...
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)
|
From page 126... ...
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)
|
From page 127... ...
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.
|
From page 128... ...
The Sudanese surveys are also almost 10 years apart. Table 4-4 compares the percentages of cohorts married before age 15, at 1517, at 18-19, and the published medians.l° 9WFS and DHS data for Sudan refer only to northern Sudan.
|
From page 129... ...
, 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.
|
From page 130... ...
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.
|
From page 131... ...
bDHS data for Sudan refer only to northern Sudan. 131 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.
|
From page 132... ...
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)
|
From page 133... ...
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.
|
From page 134... ...
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.
|
From page 135... ...
RECENT TRENDS IN MARRIAGE AGES TABLE 4-7 Singulate Mean Age at Marriage, Women Data Source 135 Region and Country Date Type SMAM Differencea Sourceb Western Benin 1961 Survey 16.9 UN 1982 WFS 18.3 no UN Burkina Faso 1975 Census 17.4 UN Cole d'Ivoire 1975 Census 18.4 UN 1978 WFS 18.9 no UN Ghana 1960 Census 17.8 UN 1971 Census 19.4 (1960-1971)
|
From page 136... ...
136 TABLE 4-7 (continued DEMOGRAPHIC CHANGE IN SUB-SAHARAN AFRICA 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 no UN Ethiopia 1978 Survey 17.5 YB 1981 Survey 17.7 UN 1984 Survey 17.1 (1978-1984)
|
From page 137... ...
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. O ~ 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)
|
From page 138... ...
Among the subSaharan 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.
|
From page 139... ...
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.
|
From page 140... ...
aDHS data for Sudan refer only to northern Sudan. SOURCES: Lesetedi et al.
|
From page 141... ...
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.
|
From page 142... ...
U) A, 35 .,, cat 3025 20 o o o o o oo o o o o o 0 10 20 30 40 50 60 70 Never Married, 20-24: % FIGURE 4-2 Percentage married and childless for women aged 20-24 (DHS data)
|
From page 143... ...
o 24 ~ 20 4J Q ~ 17 z m 23- / `,, 21- / 20 c / 0 Hi: 19- / ~~ _ 16 - / o/ a/ o o , o Ax.' / o o o 16 17 18 19 20 21 22 23 24 inn~,l~te Mean Age at First Marriage In ~ 1 l ytJ ~ t ~ ~ ~ ~ FIGURE 4-4 Singulate mean age at first marriage and nulliparate mean age at first birth (DHS data)
|
From page 144... ...
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)
|
From page 145... ...
, 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.
|
From page 146... ...
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
|
From page 147... ...
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.
|
From page 148... ...
148 o 3 o Ct 50 Ct Cal sly .~ Lie 4 Ct ¢ Ct ¢ 1 ¢ EM .
|
From page 149... ...
Botswana 1985 Botswana Family Health Survey 1984. Gaborone: Family Health Division, Minis try of Health; Columbia, Md.: Westinghouse Public Applied Systems.
|
From page 150... ...
Rutenberg 1989 Family Health Survey II, 1988. Gaborone: Central Statistics Office, Ministry of Finance and Development Planning, Family Health Division, Ministry of Health; Columbia, Md.: Institute for Resource Development/Macro Systems, Inc.
|
From page 151... ...
Meekers 1988 Marriage drinks and kola nuts. Paper presented at the International Union for the Scientific Study of Population Seminar on Nuptiality in Sub-Saharan Africa: Current Changes and Impact on Fertility.
|
From page 152... ...
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.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.