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In the debate on the dynamics of demographic change in sub-Saharan Africa, fertility decline and marriage postponement are interpreted in two opposing ways. While these trends are classically associated with socioeconomic progress, some argue that worsening living conditions are obliging individuals to limit their fertility and modify their marriage behaviour. Starting from the latter hypothesis, this article explores changes in marriage and union formation in Kinshasa (DR Congo), a city prey to severe and long-term economic difficulties. Via an individual-level analysis based on event history data from the MAFE survey, the authors examine whether growing economic hardship is a factor in declining marriage intensity and marriage postponement.

1Early union formation was long considered one of the main characteristics of marriage in sub-Saharan Africa (Tabutin and Schoumaker, 2004). Without radically challenging this affirmation, research over the last 20 years has revealed the complexity and heterogeneity of marriage regimes across different cultural environments, along with an increase in age at entry into union (Antoine, 2002; Tabutin and Schoumaker, 2004; Calvès, 2007; Hertrich, 2007). Union postponement has been especially pronounced in African cities, for both women and men (Locoh and Mouvagha-Sow, 2005; Calvès, 2007; Shapiro and Gebreselassie, 2013). It is accompanied by the emergence of new forms of union and the decline of traditional models (Locoh and Mouvagha-Sow, 2005). In particular, the generally close link between union and formal marriage is becoming weaker. [1] As couples marry later—or forego marriage altogether— non-marital cohabitation is becoming more frequent and prolonged (Calvès, 2007; Bocquier and Khasakhala, 2009). [2]

2While the expansion of female education is often seen as a driver of these changes, research over the last 20 years has also revealed the impact of economic hardship among young people in African cities (Antoine et al., 1995; Calvès, 2007; Gurmu and Mace, 2008; Bocquier and Khasakhala, 2009; Antoine and Béguy, 2014; Shapiro, 2015). In a comparative analysis of four African cities (Dakar, Lomé, Antananarivo, and Yaoundé), Antoine (2006) showed that entry into union is delayed by young men’s housing and employment difficulties. Likewise, Calvès (2007) showed that in the early 2000s in Ouagadougou (Burkina Faso), unemployment had become a greater barrier to union formation for men than in the past. While the relationship between the economic situation and male entry into union is well established in a wide range of contexts (for example, in Ouagadougou, Dakar, Yaoundé, and Antananarivo), the link is more variable and more complex for women. In Dakar and Lomé, for example, women employed in the public sector are more likely to marry than inactive women, while the reverse is observed in Antananarivo (Antoine, 2006). The general trend is nonetheless towards ever-later female entry into union, accompanied by marriage postponement and a decline in the proportion of couples who marry. In Ouagadougou, Calvès (2007) observed a lengthening of the union formation process and a postponement of religious, traditional, or civil marriage ceremonies. Given that these ceremonies and the associated dowry payments can be expensive, economic hardship is also a factor behind the lengthening interval between union and marriage.

3In this article, we focus on trends in unions and marriages in Kinshasa, the capital of the Democratic Republic of Congo (DR Congo), and the effects of economic hardship on conjugal behaviours and union formation. Marriage in Kinshasa has rarely been studied, despite being the second most populous city in sub-Saharan Africa, with experience of severe economic disruption over the last three decades largely unparalleled elsewhere in the region. Since the 1990s in particular, its history, like that of the country as a whole, has been marked by an acute economic crisis and a drastic deterioration in living conditions (Shapiro, 2015). Given the severity of the crisis, marriage practices may have been affected more severely than in other African cities.

4Several studies of union formation in Kinshasa reveal an increase in age at entry into union for both men and women (Shapiro and Tambashe, 2003; Kalambayi, 2007; Shapiro, 2015). Recent research by Shapiro (2015) based on the 2007 Demographic and Health Survey (DHS) also shows that union postponement in Kinshasa is associated with a sharp decline in marriages in favour of consensual unions and suggests that the poor economic climate has contributed to this trend. The extent of these changes, however, is not well documented. Likewise, the influence of living conditions on entry into union and marriage in Kinshasa has not been clearly established. While the economic crisis in Kinshasa coincides with union and marriage postponement, the DHS surveys used in Shapiro’s study do not provide the retrospective data needed to measure the effect on individuals. To our knowledge, no studies of Kinshasa have identified a link at the individual level between economic hardship and union formation and/or marriage.

5Our analyses are based on rich event history data—unique in the context of Kinshasa—that can be used to track changes in union formation and marriage for both men and women, and to assess the influence of individual-level living and employment conditions on these behaviours.

6This article seeks to verify and document union postponement and marriage decline in Kinshasa through descriptive analysis. It also aims to assess the role of individual-level economic factors on marriage practices and their evolution across cohorts. As has been shown in other urban African contexts (Antoine, 2006; Calvès, 2007; Bocquier and Khasakhala, 2009), we posit, first, that the joblessness and low living standards of individuals and their households are contributing to marriage postponement by lowering the likelihood of both union formation and subsequent marriage. Some of these postponements may be due to deteriorating labour market and living conditions, the young generations being more adversely affected by the crisis and by economic hardship at the time of entry into union. Second, we posit that the effect of economic conditions on marriage is stronger for men than for women, men being responsible for a large share of the marriage expenses (including the dowry) and male employment being perceived by women and their families as a major asset for union and marriage. Third, given the rising cost of marriage and of young adult emancipation more generally (including access to housing), economic variables (employment, living standard) should carry more weight for the younger generations than the older ones. In other words, even if employment and living conditions influenced marriage in the past, economic hardship is a stronger limiting factor today (Antoine, 2006; Calvès, 2007). Fourth, we posit that the birth of a child enables young people to delay or avoid marriage. This ‘shortcut marriage’ strategy (known as Nzela ya mukusé in Kinshasa) should be reflected in a much lower share of marriages among young people with a child, and the effect should also be more marked for the young generations if the practice is driven by worsening economic conditions.

I – Background

1 – Kinshasa: a city in crisis and in transition

7A city of more than 10 million people (United Nations, 2015), Kinshasa is still marked by the political and socioeconomic crises of past decades. DR Congo’s real per capita GDP—around USD 300 in 2009 (date of the survey used here)—has been divided by 3 since the 1970s (World Bank, 2017). The fall in per capita GDP accelerated in the 1990s, a decade marked by severe political and economic disruption (Shapiro, 2015). The looting episodes in Kinshasa in 1991 and 1993, [3] the political regime change marked by the downfall of President Mobutu in 1997, and the country’s successive wars have all played a part in its economic decline and have left profound scars on the population of Kinshasa. Urban youth unemployment has spiralled upward since the early 1990s. According to the 1-2-3 Survey [4] of 2012, more than 50% of the labour force aged 15–24 are unemployed in Kinshasa, as are 20%–30% of the 25–34 age group (DRC Government and UNDP, 2010; Institut national de statistique, 2014). [5] Young people who do find work are often employed in the informal sector, in a survival economy (Trefon, 2004; DRC Government and UNDP, 2010; Ayimpam, 2014; Institut national de statistique, 2014). In a context where housing costs have also increased, it is difficult for these young unemployed or precariously employed people to leave the parental home (Meyitondelua, 2016). [6]

8The economic decline in Kinshasa has also prompted a surge in international migration, mainly towards neighbouring countries (Angola and Congo-Brazzaville) and South Africa (Flahaux and Schoumaker, 2016; Schoumaker et al., 2018). The effects of this crisis on education are more heterogeneous, however. Men’s educational levels fell in Kinshasa in the wake of the 1990s crisis, but women’s levels continued to progress until recently, and while women have still not caught up with men, the gender education gap has narrowed. [7] In a context where hypergamy is the norm for women, this change may also be driving a postponement of entry into union.

2 – Changing marriage practices

9In traditional Congolese society, marriage is above all a collective, social, and clan affair (Erny, 1987). The family exercises control over the union throughout its duration, starting with the choice of spouse. At the start of a union, the man is presented to his partner’s family. This opening of dialogue is accompanied by a ‘gesture’ (known as a predowry), such as a case of drinks or a small sum of money. The union is officialized by a traditional marriage only after the husband has paid the dowry to his wife’s family. A civil and/or religious wedding may also—but not necessarily—take place after the dowry payment. Traditionally, women married early and entry into union was practically universal. [8] Entry into first union and marriage generally took place within several days or weeks of each other because tradition demanded that men fulfil the conditions of marriage (dowry payment and ceremony) at the very start of the union. Unions without subsequent marriage were rare (Kalambayi, 2007).

10Several studies have highlighted the changes in family life in Kinshasa (Ngondo and Pitshandenge, 1996; Shapiro and Tambashe, 2003; De Boeck et al., 2005; Shapiro, 2015). As in other African cities, tradition is giving way to new union formation practices, notably in the wake of educational expansion (Shapiro, 2015) and the ethnic mixing that is typical of urban life (Thiriat, 1999; Ngondo a Pitshandenge and Kalambayi, 2003; Antoine, 2006). In addition, despite (or perhaps because of) the decline in living standards, the cost of marriage has increased considerably in the last 30 years (Shomba Kinyamba, 2004; Meyitondelua, 2016). While it was customary to consider the dowry as symbolic, this no longer seems to be the case in the city, and the amounts involved today can sometimes be very high. We have no precise data on this question, but qualitative studies show that sums of several thousand US dollars are not rare, [9] often accompanied by goods such as jewellery, cases of drinks, loincloths, televisions, and even power generators (Meyitondelua, 2016). The dowry also tends to increase in size with the woman’s educational level, notably to compensate for the lost future earnings corresponding to her qualifications (Shomba Kinyamba, 2004; Meyitondelua, 2016).

11The cost of marriage includes not only the dowry (to be paid by the groom) but also the cost of the various wedding ceremonies: presentation of the groom to the bride’s family, customary marriage and, in some cases, civil and/or religious marriage. These expenses (room rental, music, food, drinks, etc.) can amount to several thousand dollars, with a large share being paid by the groom and/or his family. In a context of economic crisis and pauperization in Kinshasa, this high cost is a considerable obstacle to marriage (De Boeck et al., 2005), and the number of ‘everlasting engagements’ appears to be increasing (Meyitondelua, 2016). Even young people with jobs in the formal sector may need to save for several years, sometimes taking up several jobs, before they have enough money to get married (Meyitondelua, 2016). Participation in tontine systems and requests for financial support from Church members are other strategies used by young people to pay for their wedding (Meyitondelua, 2016).

12Under these difficult conditions, young people in Kinshasa are also finding alternative solutions. They may obtain permission from the families to enter a consensual union after paying a predowry and making a promise—not always kept—to pay a dowry in the future (Meyitondelua, 2016). They may also ‘oblige’ the families to accept a consensual union. This ‘shortcut marriage’ strategy involves having a child outside marriage and informing the parents once the deed is done (De Boeck et al., 2005). As a result, the young woman is generally turned out of the parental home and goes to live with her partner, either independently or with his parents. Couples can thus cement their union without going through the traditional stages, and notably without paying a dowry. The man will sometimes pay a symbolic fine (Meyitondelua, 2016), and the union may be formalized later through a dowry payment. The ‘shortcut’ is contributing to the dissociation between unions and marriage and to the increase in consensual unions.

II – Data and methods

1 – Data

13The data are drawn from the MAFE (Migration between Africa and Europe)-Congo survey conducted in Kinshasa in 2009 on a representative sample of 1,638 adult s (684 men and 954 women aged 25 and over) (Schoumaker et al., 2013). [10] While focusing mainly on international migration, the MAFE survey recorded details of the respondents’ residential, conjugal, reproductive, and occupational life histories (Beauchemin, 2015). [11] Data of this kind have rarely been collected in Africa, and never before in DR Congo. The variables used are presented below, and the sample is described in Table 1.

14In the unions module, the history of all unions lasting more than 1 year (with or without marriage) is recorded. The start date and, if applicable, end date are noted for each union. Apart from the criterion of at least 1 year’s duration, respondents are left free to judge what type of relationship constitutes a union. In Kinshasa, a union habitually corresponds to a lasting relationship generally—but not necessarily—characterized by the presentation of the man to his partner’s family and the payment of a predowry. Note that a union is not necessarily cohabiting. The couple may start living together some time after the union has started or even move apart while remaining in the union (Nappa Usatu et al., 2015). Two additional questions indicate whether the union included a marriage and, if so, in which year the marriage took place. [12] The most important marker of traditional marriage being the dowry payment, its date corresponds to the date on which the dowry was paid. While the marriage may take place in the same year as entry into union, the two events may also be spaced further apart. Moreover, some unions do not lead to marriage either because the couple separated before it took place or because the marriage plans were postponed or abandoned. Information on dates of entry into union and marriage is used to construct the dependent variables of the descriptive and multivariate analyses.

15Data on educational trajectories and economic activities lasting at least 1 year are also analysed. Three time-varying variables are constructed. The first concerns labour market status and distinguishes between the non-employed (including the unemployed and other inactive people), students, and people in employment, who are divided into three categories (elementary, intermediate, or higher-level occupations). [13] The second gives the number of years spent in education: 0–6 years, 7–12 years, and 13+ years. [14] The third measures living standard by combining two variables: one indicating, for each period of economic activity, whether respondents were sure of having enough to live on from day to day, rather unsure, or very unsure; [15] and another indicating the household’s financial capacity to pay for basic goods (more than sufficient, sufficient, just sufficient, insufficient) for each period of residence in a dwelling. These two time-varying variables are combined to construct a subjective living standard indicator. [16] People with a low living standard are those who report not being able to afford basic goods and being very unsure of having enough to live on from day to day. People with a high living standard are those who report being easily able to afford basic goods and being very sure of having enough to live on from day to day. The intermediate category groups the other situations. The evolution of this variable (results not presented) reveals a deterioration of living standards in Kinshasa, in line with the macroeconomic data and the city’s worsening employment situation as indicated in the 1-2-3 surveys.

Table 1

Characteristics of the sample of respondents at age 15 and at the time of the survey

Table 1
Variables At time of survey (2009) At age 15 Weighted percentage Unweighted numbers Weighted percentage Unweighted numbers Union (t) Never in a union 34.0 483 90.9 1,515 Ever in a union 66.0 1,143 9.1 111 Marriage (t) Never-married 50.0 788 92.9 1,538 Ever-married 50.0 838 7.1 88 Sex Male 43.1 677 43.1 677 Female 56.9 949 56.9 949 Cohort Age 25–29 (born in 1980–1984) 21.4 325 21.4 325 Age 30–39 (born in 1970–1979) 30.3 536 30.3 536 Age 40–49 (born in 1960–1969) 24.4 395 24.4 395 Age 50+ (born before 1960) 23.9 370 23.9 370 Labour market status (t) Non-employed (inactive and unemployed) 26.8 397 12.7 208 Student 6.6 85 81.5 1,312 Elementary occupation 49.7 848 5.7 102 Intermediate occupation 7.8 137 0.1 3 Higher-level occupation 9.1 159 0.0 1 Living standard (t) Low 17.4 270 4.0 60 Intermediate 78.4 1,265 67.9 1,102 High 4.2 91 28.1 464
Table 1
Years in education (t) 0–6 11.2 173 13.6 200 7–12 34.7 601 86.4 1,426 13+ 54.1 852 0.0 0 Presence of a child (t) No children 23.0 318 98.2 1,597 At least one child 77.0 1,308 1.8 29 Place of socialization Born in Kinshasa 55.5 951 55.5 951 Arrived in Kinshasa before age 12 11.8 186 11.8 186 Arrived in Kinshasa at age 12 or older 32.7 489 32.7 489 Parents’ vital status (t) Both living 41.4 646 83.4 1,369 One deceased 31.9 540 15.1 231 Both deceased 26.7 440 1.5 26 Age group (t) < 30 21.4 325 100.0 1,626 30–34 15.0 267 - - 35–39 15.3 269 - - 40+ 48.3 765 - - Overall 100.0 1,626 100.0 1,626

Characteristics of the sample of respondents at age 15 and at the time of the survey

Notes: t signifies a time-varying variable. In the event history analyses, the age group varies over time while the cohort remains constant. Twelve of the 1,638 respondents were excluded due to missing values, leaving a total of 1,626.
Source: MAFE-Congo survey (2009).

16The birth histories tell us whether the respondents had a child in any given year. In the models of union formation, this variable indicates whether the respondent already has a child born outside a union. In the models of transition from union to marriage, only births within a union are considered in order to test whether the presence of a child is an obstacle to marriage, as suggested by the ‘shortcut’ strategy. [17] Two control variables are also considered. The first informs on the place of socialization to take account of the fact that people born in Kinshasa are less likely than others to attach importance to traditional marriage. It distinguishes between people born in Kinshasa, those who arrived before age 12, and the others. The second measures the survival of parents—a time-varying factor—via a question on the biological parents’ years of death (if no longer living). We posit that women with no surviving parents will enter a union more quickly than other women because early marriage provides a means to gain independence from their guardian (most often an uncle). For men with no parents, on the other hand, marriage will be delayed because they need more time to acquire money for the dowry.

17Like all information collected retrospectively, these data have some limitations. By definition, they only concern people who are alive and living in Kinshasa. We must assume that the people in the sample are similar to those who have died or emigrated and that the respondents correctly recall the reported events. Regarding unions and marriages, events may be omitted and the wrong dates may be reported, but given that only unions lasting at least 1 year are considered, these risks are limited.

2 – Method

18The analyses are divided into two parts. The first describes the changes across cohorts in age at entry into union, age at first marriage, and transition from union to marriage. The analysis of changes in the timing and intensity of first union, of marriage, and the transition from union to marriage is based on a comparison of four cohorts of respondents (aged 25–29, 30–39, 40–49, and 50+ in 2009). The Kaplan–Meier estimator is used to construct transition curves by cohort and by sex, making it possible to describe changes in both the timing and intensity of unions and marriages.

19The second part analyses the effects of respondents’ economic status on entry into union, transition from union to marriage, and age at marriage using discrete-time event history models (Allison, 1995). Separate models are estimated for men and women to determine whether trends and factors vary by sex. Age at marriage is also analysed for two groups of cohorts to test whether the role of economic hardship increases over time, as observed in other African cities (Antoine et al., 1995; Calvès, 2007). For the discrete-time models, the data are organized into person-years. The observations are repeated for each year in which the individual is liable to experience the event. This period begins at age 10 for union formation and marriage [18] and at time of entry into union for transition from union to marriage. [19] The dependent variable has a value of 1 for the year in which the individual experienced the event and 0 for the years in which the event did not occur. For individuals who did not experience the event before the survey, the dependent variable has a value of 0 for all years up to the survey date (censoring). [20] The discrete-time event history models are estimated with logistic regressions (Allison, 1995).

III – Results

1 – Postponement of unions and fewer marriages

20Figure 1 shows a large increase in age at entry into first union across the cohorts among both men and women living in Kinshasa and a substantial gender difference in timing. In the MAFE survey, the male median age at first union rose from 24.3 years for the cohort aged 50 and older (born before 1960) to 29.5 years for the cohort aged 30–39 (born in 1970–1979), and to above 30 years in the most recent cohort (1980–1984). For women, it rose from 17.3 years to 23.1 years for these same cohorts. Without being rigorously identical, these changes are consistent with those measured in the DHS surveys of 2007 and 2013 (Table 2), which show a delay in entry into first union for both men and women. [21] Union postponement in Kinshasa is similar to that observed in other African cities (Antoine, 2006), but union remains practically universal nonetheless. In the older cohorts, almost all men and women have experience of at least one union in their lifetime. However, among men, more than 20% of the 1970–1979 cohort had still not entered a union by the end of their 30s, and this trend appears to be confirmed in the most recent cohort.

Figure 1

Percentage of individuals not yet in a union by age, sex, and cohort (Kaplan–Meier estimators)

Figure 1

Percentage of individuals not yet in a union by age, sex, and cohort (Kaplan–Meier estimators)

Source: MAFE-Congo survey (2009).
Table 2

Median age (years) at first union in Kinshasa by cohort and by sex, according to three data sources

Table 2
Cohort Men Women DHS 2007 DHS 2013–2014 MAFE 2009 DHS 2007 DHS 2013–2014 MAFE 2009 1980–1984 (age 25–29) > 28.0 31.4 > 30.0 23.5 22.2 23.1 1970–1979 (age 30–39) 28.3 27.6 29.5 20.9 21.5 21.2 1960–1969 (age 40–49) 25.7 27.7 25.2 18.7 17.9 18.5 1950–1959 (age 50+) 26.3 26.0 24.3 - - 17.3

Median age (years) at first union in Kinshasa by cohort and by sex, according to three data sources

Note: The median ages shown as older than (>) an age signify that the proportion of people already in a union at the time of the survey among the oldest in the cohort has not yet reached 50%.
Source: Demographic and Health Surveys in DR Congo, 2007 and 2013–2014 (authors’ calculations, among individuals living in Kinshasa at the time of the surveys), and MAFE-Kinshasa survey.

21The changes are even more pronounced for marriage (Figure 2). While marriage was very common (though not universal) in the oldest cohort, it has declined steadily since then, notably in the cohort aged 40–49 who were in their early 20s in the early 1990s. This postponement of first marriage and its progressive decline have continued in the more recent cohorts. At age 39, less than half the men and around 70% of women in the 1970–1979 cohort (aged 30–39 at the time of survey) were ever-married. In the youngest cohort (1980–1984, aged 25–29 at the time of the survey), barely 15% of men (35% of women) were married at age 29, versus 65% (more than 90% of women) in the oldest cohort (born before 1960, aged 50+ at the time of the survey). The curves show clearly that marriage in Kinshasa is not only being postponed, as is the case for unions, but also that its frequency is declining sharply among both men and women.

Figure 2

Percentage of not yet married individuals by age, sex, and cohort (Kaplan–Meier estimators)

Figure 2

Percentage of not yet married individuals by age, sex, and cohort (Kaplan–Meier estimators)

Note: First marriages also include marriages following a second or third union. Out of 1,017 first marriages, 977 followed a first union, 31 a second union, and 9 a third.
Source: MAFE-Congo survey (2009).

22The changes in the timing and frequency of first unions are due partly to new patterns of union formation, but also to a large decrease in the share of unions that lead to marriage, especially unions followed by marriage in the same year (Figure 3). The trend is progressive across cohorts for men and women alike. While he majority of men and women in the oldest cohort (around 80%) married in the year of their union, the percentage falls to 60% in the 1960–1969 cohort and to between 40% (men) and 50% (women) in the 1970–1979 cohort. In the youngest cohort, only a quarter of women marry in the year of entry into union. [22] After his first year, the timing of marriage becomes similar across the cohorts.

23We are indeed witnessing a postponement of union formation and a clear trend towards later and less frequent marriage. Marriage, which was widely practised and the accepted norm, is losing ground to consensual unions, known in Kinshasa as ‘Yaka tofanda’ (‘Let’s sit down together’).

Figure 3

Percentage of people in a union but not yet married by time (in years) since entry into union (all union orders), sex, and cohort (Kaplan–Meier estimators)

Figure 3

Percentage of people in a union but not yet married by time (in years) since entry into union (all union orders), sex, and cohort (Kaplan–Meier estimators)

Notes: The results are not shown for men in the youngest cohort as the number who have entered a union is too small (n = 13). All unions liable to lead to a first marriage are considered. Some individuals are therefore represented several times (1,520 unions for 1,355 individuals with experience of at least one union). Similar results are obtained when only first unions are considered. Separations are treated as censored cases, so individuals leave the population at risk of transition from union to marriage when the union is dissolved. They may return to this population if they enter a new union. In this case, union duration starts again at 0. The analyses are weighted.
Source: MAFE-Congo survey (2009).

2 – Limited effect of economic hardship on union formation

24How is economic hardship, that of young men especially, linked to later entry into union? Does union postponement reflect growing financial difficulties? The event history analyses presented in Table 3 aim to answer these two questions. Models 1b and 2b, which include all the variables described above, reveal the importance of male employment in union formation. For men, having a job (a higher-level occupation in particular) favours entry into union, but this is not the case for women, for whom a highly qualified job delays union formation. This difference has also been observed in other African cities (Antoine, 2006; Bocquier and Khasakhala, 2009). For men, this positive effect of employment is consistent with our hypothesis that male employment is seen as an asset for union formation. For women, greater financial independence— via a highly qualified job—is associated with more freedom to choose a partner and with later entry into union. Conversely, non-employed women may see a union as a way to improve their economic and social status, and this would explain the stronger propensity to enter a union among women who are jobless or in an elementary occupation.

Table 3

Event history models of entry into first union in Kinshasa (odds ratios)

Table 3
Independent variables Men Women Gross effects 1a Net effects 1b Gross effects 1a Net effects 1b Cohort Born before 1960 (Ref.) 1 1 1 1 1960–1969 0.73*** 0.85 0.60** 0.60*** 1970–1979 0.41*** 0.54*** 0.45*** 0.46*** 1980–1984 0.18*** 0.27*** 0.29*** 0.31*** Labour market status (t) Non-employed (Ref.) 1 1 1 1 Student 0.73 0.70 0.57*** 0.60*** Elementary occupation 1.81** 1.45 0.99 0.95 Intermediate occupation 2.77*** 1.73 1.46 1.33 Higher-level occupation 2.37*** 1.61* 1.01 0.63* Living standard (t) Low (Ref.) 1 1 1 1 Intermediate 2.00* 1.63 0.86 0.80 High 2.74** 1.93 1.11 0.91 Years in education (t) 0–6 years (Ref.) 1 1 1 1 7–12 years 0.65 1.06 0.80 1.26 13+ years 0.50** 0.94 0.49*** 0.92 Presence of a child (t) No children (Ref.) 1 1 1 1 At least one child 1.49* 1.15 0.63 0.55* Place of socialization Born in Kinshasa (Ref.) 1 1 1 1 Arrived in Kinshasa before age 12 1.21 0.92 1.24 1.14 Arrived in Kinshasa at age 12 or older 2.09*** 1.52*** 1.38* 1.06 Parents’ vital status (t) Both living (Ref.) 1 1 1 1 One deceased 1.28 1.24 1.12 1.00 Both deceased 2.33*** 1.69** 1.61 1.37 Sample sizes N (individuals) 677 677 949 949 N (person-years) 12,229 12,229 11,761 11,761

Event history models of entry into first union in Kinshasa (odds ratios)

Statistical significance: * p < 0.10, ** p < 0.05, *** p < 0.01.
Notes: t signifies a time-varying variable. Duration is controlled for in all models by an age function and its natural log. This function adequately summarizes the relationship between the probabilities of first union and age and provides a better fit with the data than age and age squared. The gross effects of the independent variables are estimated controlling for age.
Source: MAFE-Congo survey (2009).

25The effect of living standard on union formation, while positive for men, is not significant in the multivariate models. This suggests that standard of living is not a discriminating factor. However, as we will see below, its influence is much greater for formalization of the union through marriage. We also note that male migrants who arrived in Kinshasa before age 12 enter a union earlier, as do men whose parents are both deceased. The most highly educated women also delay their entry into union (this is a classic observation), but the effect is not significant in the multivariate models after controlling for labour market status. It is pursuing one’s education that reduces the likelihood of entering a union (odds ratio 0.60) rather than the number of years of education as such.

26Another important finding is that the differences across cohorts remain strongly significant for both sexes after controlling for socioeconomic variables (comparisons of Models 1a and 1b for men, 2a and 2b for women). In other words, only part of the increasing delay in union formation across cohorts is due to changes in the socioeconomic characteristics of the individuals in these cohorts. For men, comparison of the gross (1a) and net effects (1b) of the cohort coefficients shows that these differences are smaller after controlling for the socioeconomic variables. Compositional changes in the cohorts of men, and notably the increased unemployment and worsening living conditions of the youngest cohorts, [23] are contributing to male union postponement, but many other factors are also at play. For women, the differences across cohorts are practically unaffected by controls for socioeconomic variables, a finding which suggests that union postponement is not influenced by changes in the characteristics of the women in the different cohorts. Our results indicate that it may rather be the consequence of male postponement and other unobserved factors.

3 – From union to marriage: a strong effect of male employment and standard of living

27Table 4 gives the results of the event history models of transition from first union to marriage. As shown by the descriptive analyses (Figure 3), this transition is becoming less frequent. The event history models reveal the strong effects of male employment and standard of living on this transition. They are more pronounced than for union formation. These findings clearly show that financial difficulties are an obstacle to union formalization; men with a job (of whatever kind) and an intermediate or high standard of living are much more likely to formalize their union through marriage (Table 4, Model 3b). This result is consistent with qualitative studies that highlight the importance of male employment and, more generally, of their capacity to pay for the dowry and the wedding ceremonies (Meyitondelua, 2016). For women, employment has no effect on this transition, but the poorest women are also the least likely to marry (Table 4, Model 4b). Women may also contribute to the wedding expenses (Meyitondelua, 2016), as reflected by the effect of women’s living standards on marriage. As is the case for entry into union, women in education are less likely to marry. However, a high educational level increases the likelihood of formalizing a union through marriage, probably because the most educated women come from more advantaged social categories with sufficient resources to pay for a wedding. The analyses of transition from union to marriage also illustrate the ‘shortcut marriage’ strategy whereby young couples replace marriage with a birth as a means to set up home together. When the couple already has a child, the likelihood of marriage is almost halved, for men and women alike. [24]

Table 4

Event history models of transition from first union to first marriage in Kinshasa (odds ratios)

Table 4
Independent variables Men Women Gross effects 3a Net effects 3b Gross effects 4a Net effects 4b Cohort Born before 1960 (Ref.) 1 1 1 1 1960–1969 0.67* 0.83 0.51*** 0.46*** 1970–1979 0.37*** 0.48** 0.22*** 0.17*** 1980–1984 0.29** 0.24** 0.12*** 0.14*** Labour market status (t) Unemployed (Ref.) 1 1 1 1 Student 2.44** 1.33 0.37*** 0.30*** Elementary occupation 2.01** 1.70* 0.71 0.79 Intermediate occupation 3.82*** 2.87** 2.80*** 1.55 Higher-level occupation 4.14*** 2.73*** 3.44*** 1.41 Living standard (t) Low (Ref.) 1 1 1 1 Intermediate 2.78** 4.08*** 2.56** 2.73** High 3.00** 3.35*** 3.04*** 2.10 Years in education (t) 0–6 (Ref.) 1 1 1 1 7–12 0.83 0.67 0.79 1.48** 13+ 1.74 1.46 1.03 2.33*** Presence of a child born in the union (t) No children (Ref.) 1 1 1 1 At least one child 0.62** 0.58** 0.56*** 0.50*** Place of socialization Born in Kinshasa (Ref.) 1 1 1 1 Arrived in Kinshasa before age 12 1.99* 3.28*** 1.47 1.03 Arrived in Kinshasa at age 12 or older 2.61*** 2.46*** 1.99** 1.07 Parents’ vital status (t) Both living (Ref.) 1 1 1 1 One deceased 1.05 0.76 0.97 1.01 Both deceased 0.76 0.57 0.59** 0.56** Sample sizes N (individuals) 529 529 826 826 N (person-years) 2,544 2,544 3,956 3,956

Event history models of transition from first union to first marriage in Kinshasa (odds ratios)

Statistical significance: * p < 0.10, ** p < 0.05, *** p < 0.01.
Notes: t signifies a time-varying variable. Duration is controlled for in all models by a union duration function and its natural log. This function adequately summarizes the relationship between the probabilities of marriage and duration and provides a better fit with the data than duration and duration squared. All unions liable to lead to a first marriage are considered. Some individuals are therefore represented several times (1,520 unions for 1,355 individuals with experience of at least one union). The results calculated for first unions only are very similar.
Source: MAFE-Congo survey (2009).

4 – Influence of economic hardship on marriage and development of the ‘shortcut marriage’

28The above analyses identified the effects of economic variables on the two major transitions (union formation and transition from union to marriage). Table 5 presents the explanatory factors of age at first marriage. This last analysis provides a more synthetic vision of the determinants of marriage in Kinshasa.

29It confirms that a better financial situation—measured by a good job and a high standard of living—has a clearly positive effect on the likelihood of marriage for men and, to a certain extent, for women. The results also confirm that the most recent cohorts marry less, even after controlling for socioeconomic variables. This shows that the changes are not due simply to young people’s financial difficulties but also to more profound changes in social practices. The ‘shortcut marriage’ is also evidenced by our models. Having a child substantially reduces the likelihood of marriage, thus confirming that young Kinshasans with limited resources officialize their union not through marriage but through a birth.

30Comparisons across cohorts also suggest that economic variables are having an increasing effect on male marriage (Table 5, Models 5c and 5d). As in Ouagadougou (Calvès, 2007) and Dakar (Antoine et al., 1995), the gap between young men ‘with resources’ and those without appears to be widening over time. Having an elementary job is more favourable for marriage than in the past (significant difference, p < 0.10). Having a high standard of living also has a slightly stronger effect on marriage postponement among people born after 1970 than among those born before, but the difference in coefficients between cohorts is not significant at the 10% level. For women, on the other hand, the effect of standard of living is smaller (and non-significant) in the youngest cohorts but very pronounced and positive in the pre-1970 cohorts. In other words, while the difference by standard of living is widening for men, it is tending to narrow for women. These diverging trends need to be further investigated, but again illustrate the weaker relationship for women, compared to men, between standard of living and marriage. The effect of the presence of children, on the other hand, is significantly stronger for women in the young cohorts, reflecting the development of ‘shortcut marriage’ to circumvent formal marriage. Today, more so than in the past, having a child appears to be a strategy for avoiding marriage. The effect of having a child also appears to be increasing for men, but the change is not statistically significant.

Table 5

Event history models of age at first marriage in Kinshasa (odds ratios)

Table 5
Independent variables All cohorts Born before 1970 Born in 1970 or after Gross effects Net effects Net effects Net effects 5a 5b 5c 5d Cohort Born before 1960 (Ref.) 1 1 1 - 1960–1969 0.63*** 0.80* 0.77* - 1970–1979 0.28*** 0.40*** - 1 1980–1984 0.11*** 0.16*** - 0.53 Labour market status (t) Unemployed (Ref.) 1 1 1 1 Student 0.76 0.52* 1.00 0.31 Elementary occupation 1.44 1.23 0.55 3.19* Intermediate occupation 2.55*** 1.55 0.79 1.84 Higher-level occupation 2.63*** 1.60* 1.42 2.15 Living standard (t) Low (Ref.) 1 1 1 1 Intermediate 2.18* 1.87 1.94 1.82 High 3.47*** 2.37** 2.22** 4.11** Years in education (t) 0–6 (Ref.) 1 1 1 1 7–12 0.72 1.20 0.98 1.80 13+ 0.84 1.39 0.98 2.99 Presence of a child within the union (t) No (Ref.) 1 1 1 1 Yes 0.31*** 0.22*** 0.26*** 0.16*** Place of socialization Born in Kinshasa (Ref.) 1 1 1 1 Arrived in Kinshasa before age 12 1.68 1.41 1.00 1.89 Socialized outside Kinshasa 2.82*** 2.20*** 1.69** 2.55** Parents’ vital status (t) Both living (Ref.) 1 1 1 1 One deceased 1.13 1.04 1.24 1.10 Both deceased 1.55** 1.45** 1.90*** 1.62 Sample sizes N (individuals) 677 677 355 322 N (person-years) 14,332 14,332 7,888 6,444
Table 5
Independent variables All cohorts Born before 1970 Born in 1970 or after Gross effects Net effects Net effects Net effects 6a 6b 6c 6d Cohort Born before 1960 (Ref.) 1 1 1 - 1960–1969 0.48*** 0.49*** 0.50*** - 1970–1979 0.24*** 0.24*** - 1.00 1980–1984 0.11*** 0.13*** - 0.53** Labour market status (t) Unemployed (Ref.) 1 1 1 1 Student 0.58*** 0.50*** 0.40*** 0.76 Elementary occupation 0.91 0.89 0.75 1.20 Intermediate occupation 3.50*** 2.20*** 2.81** 1.49 Higher-level occupation 1.80** 0.68 0.52* 1.27 Living standard (t) Low (Ref.) 1 1 1 1 Intermediate 1.97** 1.52 1.73** 1.15 High 2.69*** 1.65** 2.02** 1.27 Years in education (t) 0–6 (Ref.) 1 1 1 1 7–12 0.83 1.55*** 1.81*** 1.67 13+ 0.74* 1.64* 2.00** 1.72 Presence of a child within the union (t) No (Ref.) 1 1 1 1 Yes 0.49** 0.54** 0.70 0.35** Place of socialization Born in Kinshasa (Ref.) 1 1 1 1 Arrived in Kinshasa before age 12 1.49** 1.29 1.79** 0.80 Socialized outside Kinshasa 1.84*** 1.15 1.26 0.98 Parents’ vital status (t) Both living (Ref.) 1 1 1 1 One deceased 1.08 1.03 1.09 0.93 Both deceased 1.44* 1.55** 2.23** 1.14 Sample sizes N (individuals) 949 949 410 539 N (person-years) 14,838 14,838 3,424 9,233

Event history models of age at first marriage in Kinshasa (odds ratios)

Statistical significance: * p < 0.10, ** p < 0.05, *** p < 0.01.
Notes: t signifies a time-varying variable. Duration is controlled for in all models by an age function and its natural log. This function adequately summarizes the relationship between the probabilities of marriage and age. The gross effects of the independent variables are estimated controlling for age. The coefficients in bold in columns 5d and 6d indicate that they differ significantly (p < 0.10) between the pre-1970 and post-1970 cohorts. The tests are performed by introducing interactions between a dichotomous variable (distinguishing the pre-1970 and post-1970 cohorts) and each of the independent variables into a single model. The significant interactions indicate changes in the regression coefficients.
Source: MAFE-Congo survey (2009).


31Following on from other studies in different African contexts, our results bring to light major changes in marriage practices in Kinshasa. Age at union formation is increasing, and marriage is taking place later and less frequently. The decline in marriage reflects a weakening of the institution in a context of economic crisis, spiralling marriage costs, and a rising cost of living more generally. While marriage was practically universal and coincided with entry into union among the older generations, it has now become optional. Other practices, such as ‘shortcut marriages’, are developing; while still not fully accepted by society, they are the only way for many young Kinshasans to start a family without the financial burden of a costly marriage.

32Our results show that financial hardship lowers the likelihood of marriage, and that these effects are more pronounced for men than for women. They are consistent with the situations observed in other African cities (Antoine, 2006). Financial hardship also has a stronger effect on marriage than on union formation, [25] confirming the hypothesis that the cost of marriage is a major obstacle to the formalization of unions. The deterioration of living conditions, as reflected by growing unemployment and a low standard of living, is associated with a decline in marriage from one cohort to the next and a general increase in the impact of financial factors on marriage among the young male cohorts. The gap is widening between young people who can easily afford to marry and those who cannot, doubtless due in part to the increasing costs of marriage and housing. Last, the inhibiting effect of a birth on the likelihood of marriage is linked to the ‘shortcut marriage’ strategy whereby unions are cemented by a birth rather than a marriage. A growing share of couples appear to be adopting this strategy, probably in partial response to financial hardship.

33Financial hardship influences marriage practices and is contributing to changes in these practices across cohorts, but it is not the only factor at play. While it is true that young men with few resources are finding it increasingly difficult to marry, the changes under way appear to be much broader and deep-rooted than a simple reaction to the economic crisis. Social norms are also changing, and young people appear to be gaining greater independence from their families (Hertrich, 2013). The economic crisis may have accelerated these changes and fostered greater tolerance of consensual unions, but these changes also reflect much broader transformations under way in Kinshasa, such as the expansion of women’s education.

34There are still many unanswered questions on marriage trends in this context. One concerns the cohabitation, or non-cohabitation, of couples in the city of Kinshasa. Financial hardship influences not only union formation and the decision to marry but also couples’ capacity to pay for their own home.

35The phenomenon of ‘living apart together’ seems to be developing among the young generations in Kinshasa, including among newlyweds who cannot afford to live under the same roof (Nappa Usatu et al., 2015). Union instability and its link to poverty in Kinshasa is another avenue to be explored. Union formation and marriage are just two components of the broader transformations under way in Kinshasa, whose dynamics and determinants deserve to be explored in greater depth.


  • [1]
    In this article, the term ‘marriage’ refers to formalized marriage (traditional, civil, or religious).
  • [2]
    Of course, causality is difficult to establish given that it is also the fact of being able to cohabit that enables young people to delay marriage or even avoid it altogether.
  • [3]
    The pillaging episode of September 1991 was sparked off at Kinshasa airport by soldiers protesting against their low pay at a time of hyperinflation and slow democratic transition. It then spread to other sections of the population, and the city of Kinshasa was ransacked in the space of a few days. A further episode in January 1993, again initiated by the army, led to several hundred deaths (Kalulambi Pongo, 2001; Shapiro and Tambashe, 2003; Ayimpam, 2014).
  • [4]
    The 1-2-3 survey concerns employment, the informal sector, and household consumption. The 2012 survey in DR Congo covered a national sample of 21,454 households, of which around 2,000 were in Kinshasa (Institut national de statistique, 2014).
  • [5]
    For all ages (10 years and above), the unemployment rate (ILO definition) in Kinshasa rose from 14.9% in 2005 to 18.8% in 2012 (Institut national de statistique, 2014).
  • [6]
    Several indicators calculated retrospectively using MAFE survey data confirm this deterioration in living conditions and employment. According to the survey, 23% of 25- to 34-year-olds reported that their household could barely afford or could not afford to buy basic goods in the 1980s; in the 2000s, the proportion rose to 34%. The MAFE survey also identified a large rise in the unemployment rate in the 25–34 age group, with an increase from 11% in the 1980s to 20% in the 2000s.
  • [7]
    In the most recent DHS conducted in 2013, 23% of women aged 25–29 in Kinshasa had attended higher education, versus 8% of those aged 45–49. Conversely, the share of men with higher education has fallen, primarily among the cohorts born from the late 1960s onwards, who reached the age of entry into higher education in the late 1980s. In 2013, 33% of men aged 25–29 in Kinshasa had attended higher education, versus 45% of those aged 45–49 (calculations based on the 2013 Demographic and Health Survey in DR Congo).
  • [8]
    According to the 1955–1957 demographic survey in Congo, women’s mean age at first marriage was 18.3 years (Lopez-Escartin, 1992).
  • [9]
    These data are drawn from semi-structured interviews conducted by Rose Meyitondelua in 2016 with 17 residents of Kinshasa (10 women and 7 men) aged 25–75 (Meyitondelua, 2016).
  • [10]
    The sample is a three-stage stratified sample with sampling fractions that vary across the strata. Weighting is used in all analyses to take account of these variable sampling fractions (Schoumaker et al., 2013). The standard deviations of the regression coefficients are also adjusted to take account of the complex sampling plan.
  • [11]
    The full questionnaire is available at
  • [12]
    Marriage may be traditional, civil, or religious. No distinction is made in the questionnaire. In practice, traditional marriage precedes any civil and/or religious marriage. The date recorded thus corresponds to the first marriage, i.e. the traditional marriage.
  • [13]
    Elementary occupations do not require any training, while higher-level occupations require higher education.
  • [14]
    This variable measures the number of years spent as a student but does not necessarily correspond to the level of qualification achieved.
  • [15]
    It is based on the following question item: ‘All in all, would you say that during this period you had enough to live on from day to day? (1) Yes, absolutely; (2) No, not at all; (3) It depended.’
  • [16]
    The variations in these variables over time are not captured perfectly because they are only measured when respondents change jobs or move to a new dwelling. However, as job and address changes are quite frequent, they can be measured with relative accuracy.
  • [17]
    Births before formalized marriage are far from rare: 29% of survey respondents who were unmarried (at the time of the survey) already had at least one child, around two-thirds of children being born during the current union.
  • [18]
    Age 10 corresponds to the age at which the first events are observed in the database. For reasons of comparability, the same age is chosen for both men and women even though entry into union is later for men. The absence of events at young ages for men does not influence the results of the discrete-time models.
  • [19]
    To avoid the problem of simultaneity between unions and marriages reported in the same year, a period of 6 months was added between entry into union and marriage. Different durations were compared, and they produced comparable results.
  • [20]
    For analysis of transitions between union and marriage, union dissolutions are treated as censored cases. In these cases, the dependent variable is 0 for all durations between entry into union and union dissolution.
  • [21]
    This postponement contrasts with the situation in DR Congo as a whole. DHS survey data show that median age at entry into union is stable at around 23 years for men and 17–18 years for women.
  • [22]
    The numbers of men are too small because very few men in the youngest cohort have entered a union. The low proportion of women in the youngest cohort who marry in the year of entry into union may be linked to a selection effect: people who entered a union at a young age are over-represented, and these unions may less often lead to marriage. This finding is nonetheless consistent with the general trend, which appears to be robust.
  • [23]
    The proportion of young people with a favourable economic position (higher-level occupation, high standard of living) decreases across the cohorts (results not presented). Because these categories are associated with a greater likelihood of entry into union, their declining weight in the population accounts for part of the decrease in this likelihood, i.e. the delay in union formation.
  • [24]
    Models distinguishing births in the union and outside the union were also tested (results not shown). An out-of-union birth has no effect on the likelihood of marriage for women and a slight positive effect on the transition from union to marriage for men.
  • [25]
    Standard of living has no significant effect on union formation, and only higher-level occupations have an effect.

Kinshasa, a metropolis with a population of 10 million, has undergone major economic, social, and demographic transformations over recent decades. This article analyses changes in marriage practices in Kinshasa against a backdrop of worsening economic conditions and high unemployment. Data from the MAFE survey (Migration between Africa and Europe) conducted in Kinshasa in 2009 reveal the decline in first unions and in marriages, for men and women alike. Event history analyses show that economic hardship reduces the likelihood of marriage. The effects of economic factors are stronger for men than for women, and the difference in marriage likelihood between rich and poor men has widened over time. These findings can be explained in part by the rising cost of marriage, shouldered mainly by the groom and his family, and the growing difficulty of acquiring the necessary sums of money. In this context, consensual unions and non-marital births are becoming more frequent and are tending to replace formal marriage.

  • marriage
  • union
  • employment
  • DR Congo
  • Kinshasa
  • event history
  • economic crisis

Difficultés économiques et transformation des unions à Kinshasa

Kinshasa, mégapole de près de 10 millions d’habitants, a connu d’importantes transformations économiques, sociales et démographiques au cours de ces dernières décennies. Cet article analyse les transformations des pratiques matrimoniales dans un contexte de détérioration des conditions économiques et de pénurie d’emplois. Les données de l’enquête du projet Mafe (Migration entre l’Afrique et l’Europe), réalisée en 2009 à Kinshasa, mettent en évidence le recul des premières unions et des mariages, pour les hommes comme pour les femmes. Des analyses biographiques montrent que les difficultés économiques diminuent les chances de se marier. Les effets des facteurs économiques sont plus prononcés pour les hommes que pour les femmes, et l’écart dans les chances de mariage entre les hommes qui disposent de ressources et ceux qui en ont moins s’est lui aussi accentué au fil du temps. Le coût croissant du mariage, qui repose en grande partie sur le futur marié et sa famille, ainsi que les difficultés croissantes pour répondre à ces exigences financières, expliquent en partie ces résultats. Dans ce contexte, les unions libres et les naissances hors mariage se développent et tendent à se substituer aux mariages.


Dificultades económicas y transformación de las uniones en Kinshasa

Kinshasa, megapol de casi 10 millones de habitantes, ha conocido importantes transformaciones económicas, sociales y demográficas durante las últimas décadas. Este artículo analiza las transformaciones de las prácticas matrimoniales en un contexto de deterioración de las condiciones económicas y de escasez de empleos. Los datos de la encuesta Mafe (Migración entre Africa y Europa) realizada en Kinshasa en 2009, muestran el retroceso de las primeras uniones y de los matrimonios, tanto en los hombres como en las mujeres. Un análisis biográfico muestra que las dificultades económicas reducen la probabilidad de casarse. El efecto de los factores económicos es más pronunciado en los hombres que en las mujeres, y la diferencia en la probabilidad de contraer matrimonio entre los hombres con recursos y los que tienen menos se ha acentuado con el tiempo. El coste creciente del matrimonio, que pesa en gran parte sobre el futuro marido y su familia, así como las dificultades crecientes para responder a las exigencias financieras, explican en gran parte estos resultados. En este contexto, las uniones libres y los nacimientos fuera del matrimonio son cada vez más frecuentes y tienden a reemplazar el matrimonio.


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Jocelyn Nappa
University of Kinshasa, DR Congo.
Bruno Schoumaker
Université catholique de Louvain, Belgium.
Correspondence: Bruno Schoumaker, IACS, Place Montesquieu 1/L2.08.03, 1348 Louvain-la-Neuve, Belgium.
Albert Phongi
Université pédagogique nationale, Kinshasa, DR Congo.
Marie-Laurence Flahaux
Institut de recherche pour le développement, LPED, Aix-Marseille Université, France and University of Oxford, United Kingdom.
Translated by
Catriona Dutreuilh
This is the latest publication of the author on cairn.
This is the latest publication of the author on cairn.
This is the latest publication of the author on cairn.
Uploaded on on 31/10/2019
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