Printer Friendly

Premarital births and union formation in rural South Africa.

CONTEXT: In rural South Africa, women often delay union formation until they are in their late 20s, though premarital first births are common.

METHODS: Longitudinal data from the Agincourt Health and Socio-Demographic Surveillance System in rural South Africa were used to examine the relationship between premarital birth and union entry among 55,158 nonmigrant women aged 10-35 who took part in at least one annual census from 1993 to 2012. Discrete-time event history models were used to determine whether the likelihood of union formation differed between women who had had a premarital first birth and those who had not. Associations between single motherhood and union type (marriages or nonmarital partnerships) were identified using logistic regression.

RESULTS: Forty-five percent of women had had a premarital first birth and 25% had entered a first union. Women who had had a premarital first birth were less likely than other women to have entered a first union (odds ratio, 0.6). Women who had had a premarital birth in the past year were more likely than those without a premarital birth to have entered a union (1.5), but women had reduced odds of union formation if they had had a birth 1-2 years earlier (0.9) or at least five years earlier (0.8). Unions formed within two years of a premarital birth had an elevated likelihood of being nonmarital partnerships (1.2-1.4).

CONCLUSIONS: Single motherhood is common in the Agincourt HDSS, and women with a premarital first birth face challenges in establishing committed unions with partners.

International Perspectives on Sexual and Reproductive Health, 2016, 42(4): 187-196.

In South Africa, premarital first births, often unplanned, frequently occur during the teenage years (1-6) and women's median age at first marriage is 29. (*)(7) Despite the late age at marriage, young people usually begin sexual relationships during their teenage years; however, levels of consistent contraceptive use are low among sexually active unmarried women. (1,2,8) Together, these phenomena have helped to create high rates of premarital birth and single motherhood in South Africa. (1,2) In fact, in the regions monitored by the Agincourt Health and Socio-Demographic Surveillance System (HDSS)--the source of the data used in this article--21% of all births and 47% of births to women during adolescence and early adulthood (ages 12-26) in the 1990s were to never-married women. (1,2)

Single motherhood is viewed as an important social problem in South Africa, especially when it results from premarital births to teenagers. (9,10) A growing body of research suggests that premarital births can lead to detrimental social and health consequences for women and their children. For example, studies from South Africa have found that premarital births often precipitate young women's leaving school. (11-13) In other African settings, research has tied single motherhood to a wide array of disadvantages, including reduced earnings for women (14) and elevated risks of poor health (15) and death (16) for children. Ethnographic evidence suggests that young South Africans are well aware of the social, educational and economic consequences of premarital pregnancy. (17-19) For example, a study from KwaZulu-Natal found that although young men and women regarded premarital pregnancies with serious unmarried partners as "mistakes," they deemed those with more casual partners "disastrous." (17)

Despite growing evidence of the often-negative consequences of single motherhood for women and children, few studies from Sub-Saharan Africa--and none, to our knowledge, from South Africa--have examined whether having a premarital birth influences a young mother's prospects for establishing a stable, committed relationship. Given the potentially adverse consequences of single motherhood, we consider a premarital first birth to be a "vital conjuncture" (20,21) that may fundamentally alter a woman's future, especially the transition to a first union. (14,22,23) In this study, we investigate union patterns in the rural Agincourt HDSS site, using longitudinal data from 1993 to 2012 to analyze the relationship between premarital first birth and a woman's likelihood of entering a first union by age 36. We also examine the type of union a woman enters; in accordance with the terminology of Hosegood and colleagues, (24) we differentiate between marriages and nonmarital partnerships and refer collectively to these relationships as unions.

Understanding the marriage prospects of single mothers is important for a number of reasons. To start, receiving the economic support of both parents greatly enhances children's long-term well-being. (25,26) Children whose mothers are married or cohabit with a partner are significantly less likely to be living in poverty than are those whose mothers are unmarried and whose fathers are absent from the household. (27) Unmarried young fathers in rural South Africa often do not provide economic support for children born before marriage, (17,18) creating challenging economic circumstances for single mothers and their children. The low rates of school completion (11) and high rates of unemployment (28,29) among single mothers in rural South Africa mean that these women often must rely on their natal families (especially their mothers) and the Child Support Grant to support their children. (*) Stable, committed relationships with children's fathers could lessen the economic burden on single mothers and their families, while potentially also providing companionship, help with child care and emotional and social support. Although marriage is becoming less common, (24,30) young South Africans still regard it as a central aspiration in life. (17,18,27)

Single Motherhood and Union Formation

Evidence from Africa suggests that single mothers may face barriers to forming stable relationships. Research from Cameroon (22) and Tanzania's Moshi district (23) found that compared with unmarried childless women, single mothers were significantly less likely to marry in the long term. However, the duration of single motherhood mattered: Women whose child was less than a year old were more likely to marry than were single women without children, whereas single mothers with older children (age four or older in Cameroon and age five or older in Moshi) were less likely than childless women to marry. However, both of these studies reported that single motherhood was relatively uncommon: Seventeen percent of the women in the most recent cohort in each study had had premarital first births, (22,23) compared with 47% of young women in rural South Africa. (1,2) Moreover, although age at first marriage has increased in both Cameroon and Tanzania (to 18.6 and 18.9, respectively, among women born between 1975 and 1979), (31) it remains considerably lower than in South Africa. (7,24) These differences prompt us to ask whether single mothers are less likely than their childless peers to marry in a context wherein premarital births are much more common.

Although the studies from Cameroon and Tanzania suggest that single mothers may have a "marriage market" advantage soon after giving birth--most likely because they typically are marrying the child's father--in general, women who have premarital births may be less likely than other women to marry. One reason is that the stigma attached to premarital births (18,19,32) may harm an existing relationship or limit a woman's prospects for future relationships. Single mothers may be particularly disadvantaged in highly competitive marriage markets, such as that in rural South Africa, where men frequently migrate for work (33,34) and AIDS deaths among prime-age adults are common. (35) In the Agincourt HDSS, grandmothers often take on care-taking responsibilities for children whose mothers marry a new partner. (36) This suggests that bringing stepchildren into a marriage may be viewed as problematic and serve as a hurdle to marriage, particularly for economically disadvantaged mothers.

Marriages and Nonmarital Partnerships

In South Africa, marriage has often been described as a process that unfolds over time and is typically formalized through the payment of lobola (bridewealth) by the husband to the wife's family. Traditionally, this economic exchange signified that the husband's family had acquired the wife's reproductive capacity, and through this process the couple's children became part of the husband's family lineage. (37,38) Scholars have argued that this practice limits women's agency in relationships (39,40) and lowers their autonomy in reproductive decision making once they are married. (39) However, the custom also solidifies the bond between partners and families, and it provides women with symbolic capital in the form of dignity, respect and status in their household and community. (41) In addition, men's readiness to pay lobola is often seen as a sign of their love, commitment to the relationship and sense of responsibility to their partner. (42,43) Thus, the custom continues to be viewed as a critical step in cementing a couple's relationship and remains widely supported among both men and women in South Africa. (27,41,44)

However, the commodification of bridewealth over the past few decades has resulted in high costs that are often prohibitive to young couples. Historically paid in cattle, lobola costs typically now range from R10,000 to R25,000 (approximately US$ 1,100-2,750) and often surpass men's annual income in rural areas. (34,44,45) Despite this economic barrier, most black South Africans aspire to marriage, believe that marriage is economically beneficial and are less accepting of nonmarital partnerships than are their white counterparts. (27)

If a man cannot afford lobola when the couple moves in together, payments may proceed over months or even years; in such cases, nonmarital partnerships may eventually make the transition to marriages. Thus, the main difference between couples in nonmarital partnerships and those in marriages may revolve around a man's ability or willingness to pay lobola. That is, nonmarital partnerships may reflect economic disadvantage, such that couples in these relationships have access to fewer economic resources than couples in which the man pays lobola up front. (27) This disadvantage may be especially consequential for single mothers with children to support. Moreover, nonmarital partnerships might lead to longer-term economic disadvantage for women if they dissolve more frequently than marriages.


The Agincourt HDSS site was established in 1992 to provide reliable population-based data to aid in improving district-level health systems. (46,47) Data are collected annually from the complete population of the area, including, at the time of this study, approximately 90,000 individuals in 26 villages in the Agincourt subdistrict of the Ehlanzeni district in Mpumalanga province, northeastern South Africa. The population of the area is primarily of Shangaan heritage, an ethnic group that lives in this area and across the border in Mozambique, though about one-third of the site's population consists of refugees of the Mozambican civil war and their descendants.

As in many rural South African communities, infrastructure is limited: residents lack reliable access to piped water and electricity, and there is no formal sanitation system. (48) More than a third of women aged 15-34 are HIV-positive, (49) and access to treatment for eligible adults was restricted until 2010, when it was rolled out in local public facilities. Treatment for the prevention of mother-to-child transmission has been widely available since 2004.

Union patterns in South Africa are in flux. Nationally, the age at first marriage has steadily increased, and South Africans now typically postpone marriage until at least their mid-20s. (7,31) In addition, marriage rates have declined among all age-groups, while nonmarital partnerships have become more common. (24) These trends provide the backdrop for our analysis.



The Agincourt HDSS collects and updates information each year on all vital events, including births, deaths, unions and moves into and out of the study site. Fertility has been monitored prospectively since the census began in 1992; the HDSS collects detailed information on all pregnancies and births that occur between census rounds, and obtains retrospective birth history data from women who migrate into the area. Retrospective union histories were obtained in 2005 from all women who lived in Agincourt at the time and are obtained from all women who move into the area.

Our analyses used data collected in 1993-2012 on 55,158 women who had been aged 10-35 and had never been in a union when they were first observed in the study site. (*) These women contributed a total of 323,274 person-years of data to our analyses. (9) Three hundred ninety women who were otherwise eligible for the sample (0.7%) were excluded because of missing data on nationality (972 person-years).

Prospective fertility data were available for 21,904 women aged 10-35 who had had their first child in Agincourt between 1993 and 2012. In addition, retrospective data were available for 5,629 women who had had their first birth either before 1993 (these data were collected at the baseline census) or before moving into the study site (these data were collected at the first census after women moved into the study area).

We used prospective data on 7,502 unions that began in 2005 or later (54% of unions) and retrospective data on 6,357 unions that began before 2005 (46% of unions). Analyses of union type were limited to the 5,864 women who had entered a first union during the study period and reported whether the union had been a marriage or a nonmarital partnership when it began. We categorized unions on the basis of women's reports of union type, rather than on whether the partners resided together, because temporary or permanent migration (often for work) is common in the study area (33) and forces many couples of both union types to live apart temporarily. Union formation is frequently associated with migration out of the area. The Agincourt HDSS queries respondents who leave their household in the site about the reason for their departure; "marriage" is one of the response options. These data allowed us to analyze union formation among the 7,995 women who reported on out-migration forms that they were moving for marriage (58% of all unions). However, these unions were not included in analyses of union type, because the out-migration form did not collect information on whether the union had begun as a nonmarital partnership.

Migration out of the study site was the main cause of attrition from the sample. During the study period, 19,574 women (35%) left their households for reasons other than marriage and thus were censored at the time of migration in all analyses. Therefore, our results are primarily representative of the experiences of nonmigrant women who remained residents of the Agincourt HDSS until age 36 or were censored for a reason other than migration (i.e., death). We reflect on the implications of this for our results in the Discussion section. ([dagger])


* Dependent variables. We focused on two outcomes. First, we assessed union formation (entry into a nonmarital partnership or marriage) versus remaining single. Second, we analyzed union type, differentiating between unions that began as a nonmarital partnership and those that began as a marriage. A union was coded as a marriage if lobola had been paid (N=3,426), the marriage had been registered at the magistrate (N=5), the couple had had a religious ceremony (N=6) or all three (N=257). A union was coded as a nonmarital partnership if the woman reported that the relationship had begun as an "informal union" (instead of a marriage) and none of the union formalization processes (lobola, registration, religious ceremony) had occurred. All analyses were limited to first unions.

* Independent variables. Two independent variables were used to assess premarital births. For the first variable, we classified a birth as premarital if a woman reported having given birth at least one calendar year prior to entering a first union. For prospective data, this means that a woman reported a first birth on one census and did not report a first union until a later census, if at all. Using this definition, we compared women who had had a premarital birth with those who had not had a premarital birth. This time-varying variable was coded zero until the year in which a woman reported having had a premarital birth, and a woman who reported having given birth and having entered a first union in the same year was not coded as a single mother. (*) Because much of our data on unions was retrospective, we used a discrete-time format in our analyses, which is the most conservative approach for ensuring that premarital births occurred prior to union formation.

Because single mothers may have a union formation advantage when they marry within a year of their child's birth, (22,23) our second independent variable captured the time elapsed since a woman's premarital birth, providing nuance to our first approach. This variable was coded categorically: no premarital birth, less than one year since birth, ([dagger]) 1-2 years since birth, 3-4 years since birth and 5 or more years since birth. For the 9,361 single mothers who had had more than one premarital birth, this variable measures the time since their most recent premarital birth.

We controlled for several sociodemographic variables that are associated with both premarital childbearing and union formation: age, educational attainment and nationality. We also accounted for time by including a measure of calendar year grouped into four five-year periods: 1993-1997, 1998-2002, 2003-2007 and 2008-2012. Age was a time-varying variable and was classified into five-or six-year age intervals: 10-14, 15-19, 20-24, 25-29 and 30-35; women aged 20-24 served as the reference category because the proportion of women entering a first union during the study was highest in this age-group. Information about education was obtained in 1992, 1997, 2002 and 2006; we imputed values for intervening years using the highest previously observed value. This time-varying variable was coded categorically as none, primary (1-7 years), some secondary (8-11 years) or completed secondary ([greater than or equal to]12 years). We also included a "missing" category to retain the 12% of women who did not provide information on education in all years. To adjust for nationality, we included a dummy variable indicating whether a respondent was of Mozambican or South African origin.

Analytic Strategy

We first calculated descriptive statistics of our sample. Statistically significant differences were identified using Pearson's chi-square tests. We then employed discrete-time event history models to examine whether the likelihood of entering a first union differed between women who had had a premarital birth and those who had not. As noted above, a nonmarital partnership may serve as a precursor to marriage or be considered an early step in the marriage process; women in such partnerships are not simply dating their partners, but are in relatively committed relationships that, in many cases, will make the transition to marriage once economic circumstances improve and a man is able to pay lobola. In the long term, then, the experiences of many women who enter nonmarital partnerships may parallel those of women who marry. For these reasons, and because we cannot account for the transition from nonmarital partnership to marriage, we analyzed the likelihood of any union formation by combining the two types of union into one outcome. In a second discrete-time logistic regression model, we investigated whether the likelihood of union formation differed according to the time elapsed since a woman's premarital birth.

The discrete-time hazard modeling strategy allowed us to model time appropriately and to address the fact that some of our data were censored. Thus, the data were transformed into person-years, representing the years wherein women were at risk of union formation. Person-years of observation began when women were aged 10 (or the age at which they entered the study, if they were 10 or older at the time) and continued until the year of union formation (which was the year of migration for women who moved out of the site for marriage)[double dagger] or until they left the study site for reasons other than marriage, age (reaching age 36) or death. A total of 960 respondents (1.7%) contributed the maximum of 20 person-years of data; the mean number of years contributed was six and the median was nine. We adjusted standard errors for dependence in reports from the same individual over time and present model results as odds ratios.

The second analysis used logistic regression to investigate whether the likelihood that a first union was a nonmarital partnership differed according to whether the woman had had a premarital birth and, if so, the time elapsed since the birth. In this analysis, each woman who entered a union during the study period and provided information about union type contributed one observation to the model.


A total of 24,746 women (45%) had had a premarital first birth. (*) Twenty-five percent of women had entered a first union; among those who reported a union type, 64% were in nonmarital partnerships (Table l). ([dagger]) The mean age of respondents during the study period was 20, and almost one-third were of Mozambican origin. Among women who were age 20 or older, and thus were old enough to have finished a secondary education, 53% had attended and 25% completed secondary school.

Several differences were evident between women who had had a premarital birth and those who had not. Women who had had a premarital birth were slightly less likely to have entered a union than were women who had not had a premarital birth (24% vs. 26%). Although nonmarital partnerships were more common than marriages among women in the study who had entered a first union and reported union type, those who had not had a premarital birth were more likely than single mothers to enter an informal first union (66% vs. 60%). Moreover, compared with women whose first birth occurred after they entered a union, those who had had a premarital birth had been younger at the time of their first birth (20 vs. 22 years) and were more likely to be South African (70% vs. 67%) and to have no more than a primary education (37% vs. 31%).

Premarital Births and Union Formation

After adjustment for age, nationality, education and time period of observation, women who had had a premarital birth were less likely than those who had not had such a birth to have entered a first union during the study (odds ratio, 0.6--Table 2). ([double dagger]) All of the control variables were also associated with union formation in the expected direction. Teenagers and women aged 30 or older were less likely than women aged 20-24 to have entered a first union (0.02-0.6); Mozambicans were more likely to have entered a first union than were South Africans (1.3); and the odds of entering a union increased with women's educational attainment. Finally, the likelihood of union formation increased through 2007, after which it declined but remained higher than it had been in the 1990s. ([section])

We next disaggregated women who had had a premarital birth by the amount of time that had elapsed since the birth to test whether they had a short-term advantage in the likelihood of entering a union (Table 3). Indeed, regression models showed that the odds of entering a union were higher among women who had had a premarital birth in the past year than among those who had not had a premarital birth (odds ratio, 1.5). If a year or more had elapsed since a woman had had a premarital birth, she had no advantage or had a disadvantage in the likelihood of union formation compared with women who had not had a premarital birth. Associations between control variables and union formation were similar to those in the previous model (Table 2).

Nonmarital Partnerships Versus Marriages

In analyzing the likelihood of entering a nonmarital partnership versus a marriage, we again disaggregated women who had had a premarital birth by the time elapsed since birth. The results show that the odds of entering a nonmarital partnership were highest among women who had had a premarital birth and entered a union within two years. More specifically, the odds of entering a nonmarital partnership were elevated by 20% among women who entered a union in the same year as a first birth and 35% among women who entered a union 1-2 years after giving birth, relative to the odds among women who had not had a premarital birth (Table 4). These findings suggest that single mothers who entered a union relatively soon after birth may have had a union formation advantage (as shown in Table 3) because they were entering a nonmarital partnership as opposed to a marriage. Several of the control variables were associated with union type in the expected direction. The odds that a new union would be a nonmarital partnership were elevated among teenagers and Mozambican women, and reduced among those with completed secondary education, consistent with the argument that nonmarital partnerships are associated with economic disadvantage. (27,45) Moreover, the association between union type and period increased over time, a finding that mirrors union patterns elsewhere in South Africa and is consistent with research showing that the rising cost of lobola has become a barrier to marriage. (34,44,45)


Our analysis of union patterns in rural South Africa demonstrates important differences between the experiences of women who had premarital births and those of women who did not. Almost half of women aged 10-35 who had never been in a union and lived in the Agincourt HDSS between 1992 and 2012 had had a premarital first birth, and these women were less likely to have entered a union than were women who had not had a premarital first birth. When we considered the amount of time elapsed since a premarital birth, however, we found that women were more likely to have entered a first union if they had had a birth in the same year than if they had not had a premarital birth. These findings echo results from two other African regions, Cameroon (22) and Moshi district, Tanzania, (23) which is notable given that at the time the studies were conducted these areas had lower rates of single motherhood and substantially lower ages at marriage than the Agincourt site does. Why, then, do we find similar results in South Africa? One answer may lie in our findings regarding union type. Although single mothers may have a union formation advantage shortly after giving birth, these unions are more likely to be nonmarital partnerships--and hence marked by social and economic disadvantage (27,45)--than are the unions of women who have not had a premarital birth. This suggests that the union formation advantage these mothers experience may be overcome by the type of union they enter. Thus, even in a context in which premarital first births are a common life course experience, (18,50) never-in-union single mothers continue to face disadvantages in forming unions.

Our findings suggest several areas for future research. First, our data do not allow us to assess the mechanisms that may underlie single mothers' reduced odds of entering a union. One explanation may be that having a premarital birth and getting married are competing risks for young women in rural South Africa. That is, having a premarital birth might preclude marriage and instead, as our results suggest, put women on the pathway to a nonmarital partnership. However, another explanation might be that single mothers in rural South Africa prefer to forgo committed relationships and instead support their children on their own or with the aid of their natal kin. Future studies examining the mechanisms driving single mothers' lower likelihood of entering a union would help clarify how women and men respond to premarital births and whether single mothers are able to access other sources of economic support for children, such as their own mothers' pensions. (36) In addition, research examining whether premarital births have become more common over time could provide nuance to our understanding of the strategies women and their families have developed for coping with unintended first births. (18)

Second, our results show a union formation advantage among single mothers soon after giving birth. The timing of these unions suggests that these mothers are partnering with the child's father, which may enhance men's social and economic support for their children. (25) However, these relationships may be short-lived, and research from South Africa has shown that family instability during childhood is associated with detrimental consequences for young adults. (50) Future research examining the quality of women's relationships and the trajectories of those relationships would be useful for assessing the extent to which unions formed soon after birth are likely to provide long-term benefits to women and children.

Finally, consistent with research from other areas of South Africa, (24) our results indicate that nonmarital partnerships have become more common in the Agincourt HDSS area. This suggests that such relationships may serve as a precursor or alternative to marriage when partners are committed to one another but the male partner cannot afford to pay lobola up front. (34,44,45) However, these results should be interpreted with caution, because we used retrospective data for unions that began prior to 2005, and the reporting of nonmarital partnerships that occurred in the past may be increasingly biased as time passes. For example, nonmarital partnerships that occurred in the past and dissolved prior to 2005 may have been excluded entirely from union histories. In addition, unions that began before 2005 as nonmarital partnerships and made the transition to marriages after the payment of lobola (a common sequence of events in the Agincourt HDSS) may have been misclassified as marriages. Moreover, as mentioned above, the Agincourt HDSS data do not allow us to determine whether a union that began as a nonmarital partnership later made the transition to a marriage. Studies are needed to examine the role of lobola in couples' decisions about living together, whether and when partners pay lobola and nonmarital relationships make the transition to marriages, and how these types of decisions affect relationship stability and the well-being of women, men and children.

One limitation of the Agincourt HDSS data is the lack of complete information about the factors that might be associated with both single motherhood and union formation (such as sexual behavior) and of comprehensive measures of socioeconomic status, such as women's income and access to other economic resources. (*) An advantage of the Agincourt HDSS data, however, is that they allow us to analyze union patterns among a relatively homogeneous sample (non-migrant women) facing similar structural conditions that are likely to affect both premarital childbearing and relationship dynamics. These conditions include high levels of unemployment, inadequate schools and health care facilities overburdened by the high incidence of both infectious and noncommunicable disease. (18,29,47,51,52) Our findings illustrate the challenges that single mothers face in establishing unions during early adulthood in a setting where premarital births are strikingly common. For those interested in the health and well-being of women and children, our results serve as an impetus to focus on premarital childbearing as an important determinant.


(1.) Garenne M, Tollman S and Kahn K, Premarital fertility in rural South Africa: a challenge to existing population policy, Studies in Family Planning, 2000, 31(1):47-54.

(2.) Garenne M et al., Understanding marital and premarital fertility in rural South Africa, Journal of Southern African Studies, 2001, 27(2): 277-290.

(3.) Kaufman CE, de Wet T and Stadler J, Adolescent pregnancy and parenthood in South Africa, Studies in Family Planning, 2001, 32(2): 147-160.

(4.) Manzini N, Sexual initiation and childbearing among adolescent girls in KwaZulu Natal, South Africa, Reproductive Health Matters, 2001, 9(17):44-52.

(5.) Statistics South Africa, Census 2001: Stages in the Life Cycle of South Africans, Pretoria, South Africa: Statistics South Africa, 2005.

(6.) Mchunu G et al., Adolescent pregnancy and associated factors in South African youth, African Health Sciences, 2012, 12(4):426-434.

(7.) Statistics South Africa, Marriages and Divorces, 2011, Pretoria, South Africa: Statistics South Africa, 2012.

(8.) Wood K and Jewkes R, Blood blockages and scolding nurses: barriers to adolescent contraceptive use in South Africa, Reproductive Health Matters, 2006, 14(27): 109-118.

(9.) Makiwane M, The Child Support Grant and teenage childbearing in South Africa, Development Southern Africa, 2010, 27(2): 193-204.

(10.) Makiwane M et al., Is the Child Support Grant Associated with an Increase in Teenage Fertility in South Africa? Evidence from National Surveys and Administrative Data, Pretoria, South Africa: Human Sciences Research Council, 2006.

(11.) Madhavan S and Thomas KJA, Childbearing and schooling: new evidence from South Africa, Comparative Education Review, 2005, 49(4):452-467

(12.) Marteleto L, Lam D and Ranchhod V, Sexual behavior, pregnancy, and schooling among young people in urban South Africa, Studies in Family Planning, 2008, 39(4):351-368.

(13.) Grant MJ and Hallman KK, Pregnancy-related school dropout and prior school performance in KwaZulu-Natal, South Africa, Studies in Family Planning, 2008, 39(4):369-382.

(14.) Lloyd CB, ed., Growing Up Global: The Changing Transitions to Adulthood in Developing Countries, Washington, DC: National Academies Press, 2005.

(15.) Gage AJ, Familial and socioeconomic influences on children's well-being: an examination of preschool children in Kenya, Social Science & Medicine, 1997, 45(12): 1811-1828.

(16.) Clark & and Hamplova D, Single motherhood and child mortality in Sub-Saharan Africa: a life course perspective, Demography, 2013, 50(5):1521-1549.

(17.) Harrison A and O'Sullivan LF, In the absence of marriage: long-term concurrent partnerships, pregnancy, and HIV risk dynamics among South African young adults, AIDS and Behavior, 2010, 14(5):991-1000.

(18.) Madhavan S, Harrison A and Sennott C, Management of non-marital fertility in two South African communities, Culture, Health & Sexuality, 2013, 15(5):614-628.

(19.) Zwang J and Garenne M, Social context of premarital fertility in rural South-Africa, African Journal of Reproductive Health, 2008, 12(2):98-110.

(20.) Johnson-Hanks J, Uncertain Honor: Modern Motherhood in an African Crisis, Chicago, IL, USA: University of Chicago Press, 2006.

(21.) Johnson-Hanks J, On the limits of life stages in ethnography: toward a theory of vital conjunctures, American Anthropologist, 2002, 104(3):865-880.

(22.) Calves A-E, Marginalization of African single mothers in the marriage market: evidence from Cameroon, Population Studies, 1999, 53(3):291-301.

(23.) Hattori MK and Larsen U, Motherhood status and union formation in Moshi, Tanzania 2002-2003, Population Studies, 2007, 61(2): 185-199.

(24.) Hosegood V, McGrath N and Moultrie T, Dispensing with marriage: marital and partnership trends in rural KwaZulu-Natal, South Africa 2000-2006, Demographic Research, 2009, 20(13):279-312.

(25.) Richter L, Chikovore J and Makusha T, The status of fatherhood and fathering in South Africa, Childhood Education, 2010, 86(6):360-365.

(26.) Collinson MA, Striving against adversity: the dynamics of migration, health and poverty in rural South Africa, Global Health Action, 2010, 3:5080, doi: 10.3402/gha.v3i0.5080.

(27.) Posel D and Rudwick S, Attitudes to marriage, cohabitation and non-marital childbirth in South Africa, paper presented at MASA 2012: The Micro-Econometric Analysis of South African Data conference, KwaZulu-Natal, South Africa, Nov. 12-13, 2012.

(28.) Blalock CL, Labor migration and employment in post-apartheid rural South Africa, doctoral thesis, Boulder, CO, USA: University of Colorado, 2014, doi:

(29.) Klasen S and Woolard I, Surviving unemployment without state support: unemployment and household formation in South Africa, Journal of African Economies, 2008, 18(1): 1-51.

(30.) Garenne M, A century of nuptiality decline in South Africa: a longitudinal analysis of census data, African Population Studies, 2016, 30(2 Suppl.):2403-2414.

(31.) Garenne M, Age at marriage and modernization in sub-Saharan Africa, Southern African Journal of Demography, 2004, 9(2):59-79.

(32.) Harrison A, Hidden love: sexual ideologies and relationship ideals among rural South African adolescents in the context of HIV/AIDS, Culture, Health & Sexuality, 2008, 10(2): 175-189.

(33.) Collinson MA, Tollman SM and Kahn K, Migration, settlement change and health in post-apartheid South Africa: triangulating health and demographic surveillance with national census data, Scandinavian Journal of Public Health, 2007, 35(Suppl. 69):77-84.

(34.) Posel D and Casale D, The relationship between sex ratios and marriage rates in South Africa, Applied Economics, 2013, 45(5):663-676.

(35.) Zwang J et al., Trends in mortality from pulmonary tuberculosis and HIV/AIDS co-infection in rural South Africa (Agincourt), Transactions of the Royal Society of Tropical Medicine and Hygiene, 2007, 101(9):893-898.

(36.) Schatz EJ, "Taking care of my own blood": older women's relationships to their households in rural South Africa, Scandinavian Journal of Public Health, 2007, 35(Suppl. 69): 147-154.

(37.) Goody J and Tambiah SJ, Bridewealth and Dowry, London: Cambridge University Press, 1973.

(38.) Steyn AF and Rip CM, The changing urban Bantu family, Journal of Marriage and the Family, 1968, 30(3):499-517

(39.) Home C, Dodoo FN-A and Dodoo ND, The shadow of indebtedness: bridewealth and norms constraining female reproductive autonomy, American Sociological Review, 2013, 78(3):503-520.

(40.) Dodoo FN-A, Marriage type and reproductive decisions: a comparative study in Sub-Saharan Africa, Journal of Marriage and the Family, 1998, 60(1):232-242.

(41.) ShopeJH, "Tobola is here to stay": rural black women and the contradictory meanings of lobolo in post-apartheid South Africa, Agenda, 2006, 20(68):64-72.

(42.) Hunter M, Tove in the Time of AIDS: Inequality, Gender, and Rights in South Africa, Bloomington, IN, USA: Indiana University Press, 2010.

(43.) De Haas M, Is there anything more to say about Lobolo? African Studies, 1987, 46(1):33-55.

(44.) Posel D, Rudwick S and Casale D, Is marriage a dying institution in South Africa? Exploring changes in marriage in the context of ilobolo payments, Agenda, 2011, 25(1): 102-111.

(45.) Casale D and Posel D, The male marital earnings premium in the context of bride wealth payments: evidence from South Africa, Economic Development and Cultural Change, 2010, 58(2):211-230.

(46.) MRC/Wits Rural Public Health and Health Transitions Research Unit, Agincourt, no date,

(47.) Kahn K et al., Profile: Agincourt Health and Socio-Demographic Surveillance System, International Journal of Epidemiology, 2012 41(4):988-1001.

(48.) Kahn K et al., Research into health, population and social transitions in rural South Africa: data and methods of the Agincourt Health and Demographic Surveillance System, Scandinavian Journal of Public Health, 2007, 35(Suppl. 69):8-20.

(49.) Gomez-Olive FX et al., Prevalence of HIV among those 15 and older in rural South Africa, AIDS Care, 2013, 25(9): 1122-1128.

(50.) Goldberg RE, Family instability and pathways to adulthood in urban South Africa, Population and Development Review, 2013, 39(2):231-256.

(51.) Worden N, The Making of Modern South Africa: Conquest, Apartheid, Democracy, fourth ed., Oxford, UK: Wiley-Blackwell, 2007

(52.) Tollman SM et al., Implications of mortality transition for primary health care in rural South Africa: a population-based surveillance study, Tancet, 2008, 372(9462):893-901.


Contexto: En las zonas rurales de Sudafrica, las mujeres a menudo retrasan la formacion de uniones conyugales hasta las edades de 25 a 29 anos, aunque los primeros nacimientos premaritales son comunes.

Metodos: Se usaron datos longitudinales provenientes del Sistema de Vigilancia Sanitaria y Sociodemografica (SVSS) de Agincourt relativos al medio rural de Sudafrica para examinar la relacion entre los nacimientos premaritales y la entrada a una union conyugal en 55,158 mujeres no migrantes en edades de 10-35 anos que participaron en al menos un censo anual entre 1993 y 2012. Se usaron modelos de historia de eventos discretos para determinar si las probabilidades de formacion de uniones diferlan entre mujeres que habian tenido un primer nacimiento premarital y quienes no lo habian tenido. Se identificaron asociaciones entre la maternidad en solterla y el tipo de union (matrimonios y uniones no maritales) usando regresion logistica.

Resultados: Cuarenta y cinco por ciento de las mujeres habian tenido un primer nacimiento premarital y 25% habian entrado a una primera union. Las mujeres que habian tenido un primer nacimiento premarital tuvieron menos probabilidades que otras mujeres de haber entrado a una primera union (razon de probabilidades, 0.6). Las mujeres quehablan tenido un nacimiento en el pasado ano tuvieron mayores probabilidades que aquellas sin un nacimiento premarital de haber entrado a una union (1.5), pero las mujeres tenlan probabilidades reducidas de formar una union si habian tenido un nacimiento 1-2 anos antes (0.9), o al menos cinco anos antes (0.8). Las uniones formadas dentro de los dos anos a partir de un nacimiento premarital tuvieron altos probabilidades de ser uniones no maritales (1.2-1.4).

Conclusiones: La maternidad en solterla es comun en el SVSS de Agincourt y las mujeres con un primer nacimiento premarital enfrentan desafios a la hora de establecer uniones comprometidas con sus parejas.


Contexte: En Afrique du Sud rurale, les femmes different souvent la formation d'une union jusqu'a la vingtaine avancee, bien que les premieres maternites prenuptiales soient courantes.

Methodes: Les donnees longitudinales du systeme de surveillance sociodemographique et sanitaire (HDSS) d'Agincourt en Afrique du Sud rurale ont servi a l'examen du rapport entre la maternite prenuptiale et la formation d'une union parmi 55 158 femmes non migrantes agees de 10 a 35 ans qui avaient participe a au moins un recensement annuel entre 1993 et 2012. Des modeles d'historique d'evenement en temps discret ont ete utilises pour determiner si la probabilite de formation d'une union differait entre les femmes devenues meres avant le mariage ou non. Les associations entre la maternite monoparentale et le type d'union (mariages ou partenariats non matrimoniaux) ont ete identifiees par regression logistique

Resultats: Quarante-cinq pour cent des femmes etaient devenues meres avant le mariage et 25% avaient forme une premiere union. Les femmes qui avaient eu un premier enfant avant le mariage etaient moins susceptibles que les autres d'avoir forme une premiere union (RC, 0,6). Celles qui avaient eu un enfant au cours de l'annee precedente etaient plus susceptibles que celles sans naissance prenuptiale d'avoir forme une union (1,5), mais la probabilite de formation d'union etait moindre si la naissance avait eu lieu un a deux ans plus tot (0,9) ou au moins cinq ans plus tot (0,8). Les unions formees au cours des deux annees suivant une naissance prenuptiale presentaient une probabilite elevee d'etre des partenariats non matrimoniaux (1,2-1,4).

Conclusions: La maternite monoparentale est courante dans le systeme Agincourt HDSS et les femmes caracterisees par une premiere maternite prenuptiale n'etablissent pas facilement d'unions engagees avec leurs partenaires.


This project was supported by a William and Flora Hewlett Foundation/Institute of International Education Dissertation Fellowship (Hewlett grant 2007-1542; HE Program F480000), and by grants to the University of Colorado from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24HD066613), the National Institute on Aging (R24AG032112) and The William and Flora Hewlett Foundation (2009-4069). The Agincourt Health and Socio-Demographic Surveillance System site is supported by the University of the Witwatersrand and Medical Research Council, South Africa, and by the Wellcome Trust, UK (grants 058893/Z/99/A, 069683/Z/02/Z, 085477/Z/08/Z and 085477/B/08/Z). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the funders. The authors thank Chodziwadziwa Kabudula, Sulaimon K. Afolabi and Casey Blalock for their assistance with data preparation.

Author contact:

By Christie Sennott, Georges Reniers, F. Xavier Gomez-Olive and Jane Menken

Christie Sennott is assistant professor, Department of Sociology, Purdue University, West Lafayette, IN, USA; and visiting researcher, MRC/Wits Rural Public Health and Health Transitions Research Unit, University of the Witwatersrand, Johannesburg, South Africa. Georges Reniers is associate professor, Department of Demography, London School of Hygiene and Tropical Medicine, UK; and honorary senior researcher, School of Public Health, University of the Witwatersrand. F. Xavier Gomez-Olive is research manager, MRC/Wits Rural Public Health and Health Transitions Research Unit, University of the Witwatersrand. Jane Menken is research professor, Institute of Behavioral Sciences, and distinguished professor, Department of Sociology, University of Colorado, Boulder, USA.

(*) Much of the literature reviewed here concerning unions focuses solely on marriages, because reliable data on nonmarital partnerships in South Africa are limited (source: Budlender D, Chobokoane N and Simelane S, Marriage patterns in South Africa: methodological and substantive issues, Southern African Journal of Demography, 2004, 9(1):1-25).

(*) The Child Support Grant is a needs-based government benefit provided to a child's primary caregiver. It was equal to R330 (around US$30) per child per month as of August 2015, and is available to support all children younger than 18 living in South Africa as long as the caregiver is a South African citizen or permanent resident and earns less than R3,300 per month (if single) or R6,600 per month (if married) (source: Government of South Africa, Child support grant, 2014,

(*) We conducted a sensitivity analysis in which we coded these women as single mothers. The results were largely consistent with what is reported below.

([dagger]) This category included the 1,199 women who reported having given birth and having entered a first union in the same year.

[double dagger] To account for left-censoring, only person-years in which the outcome event could have been observed are included. For example, a woman who had a child in 1998 but entered the site in 2000 did not contribute person-years to models for the years 1998 and 1999.

(*) This number does not include the 1,199 women who reported that they gave birth and entered a first union in the same year. If those women had been counted as single mothers, as they were in the duration of single motherhood variable (Table 1), women with premarital births would have accounted for 47% of the sample.

([dagger]) Using life tables, we also calculated the cumulative probability of union formation by age 36 among all women in the sample (59%), among women who had a premarital first birth (51%) and among women who did not have a premarital birth (70%).

([double dagger]) The association between premarital births and any union formation was attenuated but remained negative and statistically significant in the sensitivity analysis in which we coded women as single mothers if they had had a first birth in the same year that they entered a union (odds ratio, 0.94, p<0.01).

([section]) The difference between the third and fourth time periods was significant at p<.05, and the difference between the second and fourth periods was significant at p<.001. The increases over time in the odds of union formation shown in Tables 2 and 3 were driven by increases in the proportion of unions that were nonmarital partnerships. Whereas 68% of the unions among women in the sample in 1993-1997 were marriages and 32% were nonmarital partnerships, by 2008-2012 this pattern had reversed: Thirty-one percent of unions were marriages and 69% were nonmarital partnerships (p<.001).

(*) Information about household assets is available in the Agincourt HDSS; however, these data are of limited utility for our analysis because they were not collected until 2001. Nonetheless, we conducted a sensitivity analysis using a subsample of 32,748 never-married women (providing 168,528 person-years of data) who provided complete information on household assets in at least one year. Results showed that the negative association between having a premarital birth and any union formation was robust to the inclusion of a measure of household assets in the model.
TABLE 1. Selected characteristics of women aged 10-35, by women's
premarital birth history, Agincourt Health and Socio-Demographic
Surveillance System, 1993-2012

Characteristic                                      All
                                                    (N=55, 158)

In union by age 36 (***)                                 25.1
In nonmarital                                            63.6
partnership ([dagger]) (***)
Time since premarital
birth ([double dagger])
No premarital birth                                      53.0
<1 yr.                                                    4.6
1-2 yrs.                                                 12.6
3-4 yrs.                                                  9.6
[greater than or equal to]5 yrs.                         20.2
Mean age ([section]) (***)                               19.7
Mean age at first                                        19.7
birth (***)
Nationality (***)
South African                                            68.1
Mozambican                                               31.9
Education ([double dagger])([double dagger]) (***)
None                                                      9.2
Primary                                                  25.6
Some secondary                                           28.0
Completed secondary                                      25.1
Missing                                                  12.1
No. of person-years
contributed                                         323,274
Time period ([section]) (***)
1993-1997                                                27.3
1998-2002                                                24.1
2003-2007                                                26.2
2008-2012                                                22.4

Characteristic                                      Premarital
                                                    (N=24, 746)

In union by age 36 (***)                                 23.6
In nonmarital                                            60.1
partnership ([dagger]) (***)
Time since premarital
birth ([double dagger])
No premarital birth                                      na
<1 yr.                                                   na
1-2 yrs.                                                 na
3-4 yrs.                                                 na
[greater than or equal to]5 yrs.                         na
Mean age ([section]) (***)                               22.3
Mean age at first                                        19.6
birth (***)
Nationality (***)
South African                                            70.0
Mozambican                                               30.0
Education ([double dagger])([double dagger]) (***)
None                                                     10.0
Primary                                                  27.1
Some secondary                                           28.1
Completed secondary                                      24.0
Missing                                                  10.8
No. of person-years
contributed                                         169,653
Time period ([section]) (***)
1993-1997                                                30.5
1998-2002                                                26.0
2003-2007                                                24.4
2008-2012                                                19.1

Characteristic                                      No premarital
                                                    (N=30, 412)

In union by age 36 (***)                                 26.3
In nonmarital                                            65.8
partnership ([dagger]) (***)
Time since premarital
birth ([double dagger])
No premarital birth                                      na
<1 yr.                                                   na
1-2 yrs.                                                 na
3-4 yrs.                                                 na
[greater than or equal to]5 yrs.                         na
Mean age ([section]) (***)                               16.7
Mean age at first                                        21.9
birth (***)                                         ([dagger][dagger])
Nationality (***)
South African                                            66.5
Mozambican                                               33.5
Education ([double dagger])([double dagger]) (***)
None                                                      7.5
Primary                                                  23.0
Some secondary                                           27.9
Completed secondary                                      27.0
Missing                                                  14.6
No. of person-years
contributed                                         153,621
Time period ([section]) (***)
1993-1997                                                23.8
1998-2002                                                22.1
2003-2007                                                28.2
2008-2012                                                25.9

(***) p<.001 for difference between women who had a premarital birth
and those who did not. ([dagger]) Among women in union who provided
information about union type (N=5,864). ([double dagger]) As reported
in the year of union formation or censoring. ([section]) Values
calculated using person-years of data. ([dagger][dagger]) Among women
who had a child after entering a union (N=2,871).
([double dagger][double dagger]) Among women aged 20 or older
(N=34,674). Notes: All values are percentages unless otherwise applicable.

TABLE 2. Odds ratios (and 95% confidence intervals) from discrete-time
logistic regression model examining association between selected
characteristics of women aged 10-35 and union formation

Measure                Odds ratio

Premarital birth
No (ref)               1.00
Yes                    0.61 (0.58-0.64) (***)
10-14                  0.02 (0.02-0.03) (***)
15-19                  0.50 (0.48-0.53) (***)
20-24 (ref)            1.00
25-29                  1.01 (0.97-1.06)
30-35                  0.62 (0.58-0.66) (***)
South African (ref)    1.00
Mozambican             1.34(1.29-1.40) (***)
None (ref)             1.00
Primary                1.82(1.67-1.99) (***)
Some secondary         2.16(1.97-2.36) (***)
Completed secondary    2.41 (2.19-2.65) (***)
Missing                6.62 (6.00-7.30) (***)
Time period
1993-1997 (ref)        1.00
1998-2002              1.31 (1.23-1.39) (***)
2003-2007              1.81 (1.71-1.92) (***)
2008-2012              1.72(1.62-1.82) (***)
Pseudo-[R.sup.2]       0.107

(***) p<.001. Notes: Age and education are time-varying
characteristics. ref=reference category.

TABLE 3. Odds ratios (and 95% confidence intervals) from discrete-time
logistic regression model examining associations between selected
characteristics of women aged 10-35 and union formation

Characteristic               Odds ratio

Time since premarital birth
No premarital birth (ref)    1.00
<1 yr.                       1.51(1.41-1.60) (***)
1-2 yrs.                     0.91 (0.86-0.97) (**)
3-4 yrs.                     0.96 (0.90-1.03)
>5 yrs.                      0.76(0.72-0.80) (***)
10-14                        0.03 (0.02-0.03) (***)
15-19                        0.57(0.54-0.60) (***)
20-24 (ref)                  1.00
25-29                        0.97(0.92-1.01)
30-35                        0.59(0.55-0.63) (***)
South African (ref)          1.00
Mozambican                   1.33(1.27-1.38) (***)
None (ref)                   1.00
Primary                      1.79(1.64-1.95) (***)
Some secondary               2.11(1.93-2.31) (***)
Completed secondary          2.44(2.21-2.68) (***)
Missing education            6.46(5.86-7.13) (***)
Time period
1993-1997 (ref)              1.00
1998-2002                    1.30(1.23-1.39) (***)
2003-2007                    1.83(1.73-1.94) (***)
2008-2012                    1.71(1.61-1.81) (***)
Pseudo-[R.sup.2]             0.105

(**) p<.01. (***) p<.001. Notes: Age and education are time-varying
variables. ref=reference category.

TABLE 4. Odds ratios (and 95% confidence intervals) from logistic
regression model examining the association of selected characteristics
of women aged 10-35 and entrance into a nonmarital partnership versus a

Characteristic               Odds ratio

Time since premarital birth
No premarital birth (ref)     1.00
<1 yr.                        1.20(1.03-1.41) (*)
1-2 yrs.                      1.35(1.07-1.71) (*)
3-4 yrs.                      1.08(0.82-1.44)
>5 yrs.                       1.04(0.89-1.22)
10-14                         3.34(1.25-8.96) (*)
15-19                         1.83(1.55-2.16) (***)
20-24 (ref)                   1.00
25-29                         0.56(0.43-0.65) (***)
30-35                         0.53 (0.43-0.64) (***)
South African (ref)           1.00
Mozambican                    1.33(1.14-1.54) (***)
None (ref)                    1.00
Primary                       1.21 (0.87-1.69)
Some secondary                0.80(0.58-1.12)
Completed secondary           0.26(0.19-0.37) (***)
Missing                       0.79(0.56-1.12)
Time period
1993-1997 (ref)               1.00
1998-2002                     2.67(1.98-3.60) (***)
2003-2007                     8.14(6.08-10.91) (***)
2008-2012                    10.74(7.98-14.44) (***)
Pseudo-[R.sup.2]              0.143

(*) p<.05. (***) p<.001. Notes: Age and education are time-varying
variables. ref=reference category.
COPYRIGHT 2016 Guttmacher Institute
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Sennott, Christie; Reniers, Georges; Gomez-Olive, F. Xavier; Menken, Jane
Publication:International Perspectives on Sexual and Reproductive Health
Article Type:Report
Geographic Code:6SOUT
Date:Dec 1, 2016
Previous Article:HIV care providers' communication with patients about safer conception for people living with HIV in Tanzania.
Next Article:Abortion incidence and unintended pregnancy in Nepal.

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |