Abstract

Contextual characteristics influence infant mortality above and beyond family-level factors. The widespread practice of polygyny is one feature of many sub-Saharan African contexts that may be relevant to understanding patterns of infant mortality. Building on evidence that the prevalence of polygyny reflects broader economic, social, and cultural features and that it has implications for how families engage in the practice, we investigate whether and how the prevalence of polygyny (1) spills over to elevate infant mortality for all families, and (2) conditions the survival disadvantage for children living in polygynous families (i.e., compared with monogamous families). We use data from Demographic and Health Surveys to estimate multilevel hazard models that identify associations between infant mortality and region-level prevalence of polygyny for 236,336 children in 260 subnational regions across 29 sub-Saharan African countries. We find little evidence that the prevalence of polygyny influences mortality for infants in nonpolygynous households net of region-level socioeconomic factors and gender inequality. However, the prevalence of polygyny significantly amplifies the survival disadvantage for infants in polygynous families. Our findings demonstrate that considering the broader marital context reveals important insights into the relationship between family structure and child well-being.

Introduction

Polygyny—the practice of one man being married to multiple wives at the same time—is a common family structure in many parts of sub-Saharan Africa. A growing literature exploring the child health implications of living in polygynous families has linked polygyny to both positive (Amankwaa 1996; Amankwaa et al. 2001) and negative (Gage 1997; Gyimah 2003) determinants of child survival; however, generally speaking, children in polygynous families experience poor health and high mortality.1 Compared with children in monogamous families, they are more likely to be nutritionally deficient (Gibson and Mace 2007; Hadley 2005), and their risk of mortality before age 5 is elevated (Amey 2002; Gyimah 2009; Omariba and Boyle 2007; Strassman 1997).

The literature on polygyny and child health has treated the practice exclusively as a characteristic of families. However, polygyny is more than an individual family structure: it represents a specific cultural approach to marriage, family, and reproduction. Researchers often describe the entire region of sub-Saharan Africa as polygynous (e.g., Timæus and Reynar 1998), but in reality, the prevalence of the practice varies tremendously both within and between countries (Lesthaeghe 1989; Murdock 1967; Reniers and Watkins 2010). Settings in which polygyny is widespread tend to be economically, socially, and culturally distinct from those in which the practice is rare. For example, polygyny is most common in rural, agrarian contexts (Boserup 1985; Jacoby 1995). Beyond these socioeconomic differences, widespread polygyny also reflects a distinct set of cultural customs (Bradley 2004; Hayase and Liaw 1997; Tobias 2001), which are evident in the unique demographic patterns (Cahu et al. forthcoming; Ezeh 1997) and gender norms that characterize highly polygynous settings (Agadjanian and Ezeh 2000; Cahu et al. forthcoming).

The distinct economic, social, and cultural features of highly polygynous settings suggest that beyond its implications for the families that practice it, the contextual prevalence of polygyny may be relevant to understanding patterns of infant mortality in sub-Saharan Africa. The contextual prevalence of polygyny could be associated with infant mortality spuriously, through its relationship with socioeconomic disadvantage. Alternatively, the shared experience of living in a setting where polygyny is culturally normative, reflecting widespread gender inequality (Agadjanian and Ezeh 2000; Cahu et al. forthcoming), may lead to a more direct association between the contextual prevalence of polygyny and infant mortality. Furthermore, because polygyny in highly polygynous settings is socially and economically distinct from polygyny where the practice is uncommon (Gwako 1998; Kilbride and Kilbride 1990; Zeitzen 2008), the contextual prevalence of polygyny may condition the survival disadvantage associated with living in a polygynous family.

In this article, we investigate whether and how the prevalence of polygyny may (1) spill over to elevate infant mortality for all families or (2) condition the survival disadvantage for infants in polygynous families (i.e., compared with monogamous families). We use data from Demographic and Health Surveys (DHS) to estimate a series of multilevel discrete-time hazard models among 236,336 children in 260 subnational regions in 29 sub-Saharan African countries. Our findings suggest that known relationships between family structure and child well-being vary according to the broader marital and cultural context.

Background

Polygyny is practiced in contemporary societies on all continents (Zeitzen 2008). Although the practice is declining worldwide, it remains particularly resilient in parts of sub-Saharan Africa (Van de Walle 2006). Demographers have long recognized polygyny’s salience to multiple aspects of Africa’s demographic landscape (Dorjahn 1959; Muhsam 1956) and have studied its implications for the individuals in such unions and their children. Research on the implications of polygyny for children, in particular, demonstrates that children in polygynous families experience significant health and survival disadvantages (Amey 2002; Gage 1997; Gibson and Mace 2007; Gyimah 2009; Hadley 2005; Omariba and Boyle 2007; Strassman 1997).

Why do children in polygynous families experience health disadvantages compared with their peers in monogamous families? The principal hypothesis for the polygyny-child health disadvantage is resource dilution (Desai 1992). According to this perspective, even if polygynous men are wealthier than their monogamously married counterparts, the greater number of women and children in polygynous households dilutes the per capita resources and, in turn, increases children’s susceptibility to poor nutrition, illness, and ultimately, mortality. However, empirical support for the resource dilution hypothesis is mixed. Polygynous children in Ethiopia and Tanzania, for example, experience poorer nutritional outcomes (Hadley 2005; Sellen 1999); in other contexts, though, there is no meaningful difference in nutritional status by family structure (Desai 1992; Strassman 1997). A second explanation centers on the fact that use of maternal and child health care services tends to be lower among polygynous women (Stephenson et al. 2006), which, in turn, increases children’s risk of mortality. A third explanation argues that gender asymmetry is especially acute in polygynous families, reflecting gender inequalities and power differences within the household (Bove and Valeggia 2009; Zeitzen 2008) that have negative consequences for child health and survival (Kravdal 2004).

Polygynous Contexts and Infant Mortality

The demographic literature on polygyny and child health has focused exclusively on the consequences for those children who live in polygynous families; however, anthropological and sociological research on polygynous groups concurs that the practice is more than an individual family structure: widespread polygyny represents a unique cultural environment and a distinct approach to marriage, family, and reproduction (Bradley 2004; Hayase and Liaw 1997; Tobias 2001). We extend this insight, highlighting two distinct ways that the contextual prevalence of polygyny may be associated with infant mortality above and beyond children’s own family structure. First, the association may be spurious: the correlation between polygyny and infant mortality may be driven by the fact that polygyny is most common in the poorest, least-developed areas of sub-Saharan Africa (Boserup 1985; Jacoby 1995), where the disease burden is high and access to health care is limited. Second, if widespread polygyny reflects accentuated institutionalized gender inequalities (Agadjanian and Ezeh 2000; Goody 1973; White and Burton 1988), the broader cultural milieu may produce a direct association between the contextual prevalence of polygyny and infant mortality.

Polygyny is most widespread in rural, agrarian areas of sub-Saharan Africa (Boserup 1985; Jacoby 1995). In these settings, human labor (particularly female labor) yields high economic value, and men use polygyny as a strategy to increase their family’s productivity.2 Additionally, polygyny is most prevalent in settings where women’s education levels are low (Bove and Valeggia 2009; Lesthaeghe et al. 1986). Existing research shows that children in least-developed, rural settings experience severe health disadvantages (Fotso 2006; Van de Poel et al. 2007); thus, highly polygynous settings may feature high levels of infant mortality simply because of these other shared characteristics. From this perspective, the contextual prevalence of polygyny may indeed be correlated with infant mortality, but the association should be fully explained by the absence of socioeconomic development that characterizes these (primarily rural) areas.

A second line of reasoning posits that the contextual prevalence of polygyny could be related to infant mortality through the gender inequality widespread polygyny reflects. Highly polygynous settings are typically patrilineal and patrilocal (Goody 1973; Lesthaeghe 1989; White and Burton 1988), wherein the dominant marital, lineage, and residential customs reflect a broader system of social stratification that privileges men—particularly older men (Zeitzen 2008). These gender and age inequalities solidify men’s dominance in social, economic, educational, political, and reproductive domains (Agadjanian and Ezeh 2000; Cahu et al. forthcoming), extending beyond the families that practice polygyny themselves. In highly polygynous societies, for example, women’s access to land, inheritance, and formalized power tends to be constrained (Goody 1973; White and Burton 1988). Furthermore, qualitative research shows that both women and men in these settings tend to view wives as “property” of the husband and believe that men should have full control over reproductive decisions—views that are far less common in settings where polygyny is rare (Agadjanian and Ezeh 2000). Highly polygynous settings in sub-Saharan Africa feature greater acceptance of domestic violence and preference for sons across both monogamous and polygynous unions (Cahu et al. forthcoming), offering further evidence that polygyny is bound with gendered attitudes that are deeply embedded in the local culture and more widespread than the practice itself. Combined with evidence that children experience acute health disadvantages in communities where women lack social status and power (Bose 2011; Kravdal 2004), widespread polygyny may reflect gender inequalities that exacerbate the risk of infant mortality.

Related to gender inequality, the distinctive gender relations that characterize highly polygynous settings may further lead to an association with infant mortality by, for example, discouraging paternal involvement and investment in children. According to Caldwell and Caldwell (2002), polygyny is often associated with men maintaining financial and social distance from their wives and children. This creates separation between mothers and fathers, illustrated by the fact that women in highly polygynous settings—regardless of their own family structure—are less likely to discuss reproductive decisions with their husbands than are wives in settings where polygyny is rare (Agadjanian and Ezeh 2000). Distant gender relations and infrequent spousal communication are associated with low paternal engagement (McBride and Rane 1998), which poses known risks to children’s health and well-being (Lamb 2004). According to this line of thought, settings where polygyny has “cultural, normative, and numeric strength” (Zeitzen 2008:39) are those where women both lack social status and power and carry the overwhelming responsibility for childcare, making these especially risky environments for infant health and survival.

Polygynous Contexts and Elevated Infant Mortality for Polygynous Families

Beyond elevating infant mortality across all family structures, the contextual prevalence of polygyny may accentuate the known survival gap between infants in polygynous and those in monogamous families. There are at least two reasons to expect the risk associated with living in a polygynous family (compared with a monogamous family) to be exacerbated where the practice is widespread. The first relates to how the family structure differs as a function of the marital and gender context. In settings where polygyny is uncommon, families engaged in the practice tend to resemble their monogamous counterparts (Kilbride and Kilbride 1990). In other words, the negative beliefs about and taboos associated with the practice (Gwako 1998) could lead polygynous families to adapt (consciously or subconsciously) a cultural approach to marriage, family, and childrearing that mirrors the overwhelmingly monogamous local context. For instance, in contemporary sub-Saharan African societies where polygyny is rare, most polygynous men visibly conform to the monogamous culture by having one “public wife” and other “outside” wives (Bledsoe 1990, 1995). Furthermore, qualitative work has found that where the practice is rare, polygynously married women expect to be more involved in marital decisions than their polygynously married counterparts in contexts where the practice is widespread (Agadjanian and Ezeh 2000).

Just as the marital context influences how families practice polygyny, it may likewise influence the associated infant mortality disadvantage. In settings where polygynous culture is anomalous, greater levels of spousal communication and equality, each of which are known to benefit women’s and children’s health (Furuta and Salway 2006), may elevate the survival of children in polygynous unions to levels that resemble the experience of their peers in monogamous families. Conversely, although we expect the broad-based gender inequality reflected in polygynous culture to elevate infant mortality for all families, its customary and normative strength may be associated with intensified gendered hierarchies within polygynous families in particular (Nyblade and Menken 1993; Zeitzen 2008). Thus, the prevalence of polygyny and its accompanying characteristics may exacerbate the survival disadvantage of infants living in polygynous families where it is prevalent and dampen the survival disadvantage where the practice is rare.

A second perspective emphasizes the economic heterogeneity between polygynous families in settings where it is more versus less widespread. As previously discussed, the primary hypothesis for why children in polygynous families experience poorer health is that the practice increases the number of wives and siblings, thereby diluting the family’s per capita resources (Desai 1992). However, the extent of resource dilution in polygynous families may vary as a function of its concentration. Although polygyny is generally practiced among relatively wealthier men, in areas where it is widespread (typically rural, least-developed environments), the practice offers a unique set of economic benefits. The predominantly rural and agrarian economies of highly polygynous contexts incentivize men—perhaps even those who are unable to adequately provide for a larger family—to augment their family’s labor supply by marrying additional wives (Boserup 1985; Jacoby 1995). From this perspective, the general socioeconomic deprivation that characterizes highly polygynous settings, matched with polygyny’s normative nature and the economic benefits it offers, may be distinctive in featuring large numbers of economically disadvantaged men who practice polygyny. This combination of disadvantages could render children in polygynous unions in highly polygynous settings particularly susceptible to the deleterious health consequences of diluted resources.

Conversely, the economic systems of African settings where polygyny is rare tend to be distinct (e.g., urban, more monetized), providing men with little economic incentive to have multiple wives. The ever-increasing cost of living (e.g., housing shortages, unemployment, weak kinship support, and cost of childrearing) makes large, polygynous families an economic liability (Gwako 1998; Solway 1990). In these settings, the socioeconomic environment, combined with polygyny’s nonnormative nature, discourages the overwhelming majority of men from becoming polygynous. Because it may be relatively wealthy men who become polygynous in such settings, the families who do practice polygyny could be buffered from the deleterious effects of resource dilution. If this is indeed the case, differences in the risk of infant mortality between polygynous and monogamous families should be minimal in settings where polygyny is less common and more sizable in areas where polygyny is widespread.

Hypotheses

In light of (1) the economic, social, and cultural factors associated with the contextual prevalence of polygyny, and (2) evidence that the nature of polygyny varies in accordance with its concentration, we hypothesize the following:

Hypothesis 1a (H1a):

The contextual prevalence of polygyny will be positively associated with infant mortality, regardless of individual family structure.

Hypothesis 1b (H1b):

Contextual socioeconomic development (e.g., rurality, lack of infrastructure) and social and cultural norms (e.g., gender inequality) will explain this association.

Hypothesis 2 (H2):

The contextual prevalence of polygyny will condition the survival disadvantage between polygynous and monogamous families. The survival disadvantage will be smallest where polygyny is rare and largest where it is widespread.

Data

We use data from the Demographic and Health Surveys (DHS) to analyze associations between the contextual prevalence of polygyny, family structure, and infant mortality in sub-Saharan Africa. We use data from 29 sub-Saharan African countries in which the DHS fielded surveys between 2000 and 2010.3 In each survey, response rates are consistently above 90 %.4 Because the DHS collects nearly identical data on family structure, reproductive histories, and infant mortality across countries, we are able to harmonize and leverage them for multinational analyses.

In each country, the DHS uses a stratified random sampling approach, with clusters providing the primary sampling unit. Within each selected cluster, the DHS randomly samples families. Household heads complete a full roster of members, from which the DHS identifies eligible men and women. Women are asked whether they have children and, if so, to provide detailed information on each live birth (e.g., date of birth, whether the child is still alive, and the month and year of death for all deceased children), from which the DHS generates the birth-oriented data sets we use here.

Analytic Sample

We restrict our sample to births that occurred within the five years prior to the survey. This restriction minimizes recall error for birth and death reports and ensures that current family characteristics (discussed later in this article) correspond reasonably well with a child’s environment since birth. This restriction also ensures that infants of older mothers, relative to those of younger mothers, are not disproportionately represented in the sample. We exclude approximately 2 % of births with missing data on study variables. Our final analytic sample consists of 236,336 births in the five years preceding the survey. See Table 3 in the  Appendix for information on the surveys and countries included.

In response to the tremendous variation in the prevalence of polygyny within and between African countries (Lesthaeghe 1989; Murdock 1967; Reniers and Watkins 2010), our contextual unit of focus is the subnational region.5 In some countries, subnational regions represent political districts; in other countries, they represent administrative or geographical boundaries. To characterize the 260 regions in our sample, we use DHS data from the women’s, men’s, and household questionnaires. On average, 1,145 women, 488 men, and 964 households are sampled in each region. Given the large number of cases in each region, we include the index family when creating the region-level measures (described in the next section) and confirm (via sensitivity analyses, not shown) that this does not alter our estimates.6 Table 4 in the  Appendix contains a complete list of subnational regions, as well as information for each on the size of the household, female, and male samples.

Analytic Approach

Key Measures

Infant Mortality

In light of evidence that polygyny does not affect mortality uniformly throughout childhood (Gyimah 2009; Ukwuani et al. 2002), we focus on mortality during the first year of life. The outcome variable in our analyses is the hazard of mortality before age 1. More specifically, the outcome is the risk of death between birth and 1 year (0–11 months) or between birth and the survey date, in the case of children who were not yet 1 year old at the time of the survey.

Age of Child

To accommodate our discrete-time hazard modeling strategy (described in more detail in the following section), we restructure the data from an individual-based data set, in which every birth contributes a unique observation, to a time-based data set, in which observations refer to a unit of time (i.e., months) and each birth contributes multiple records.

Family Structure

We leverage three survey questions to create our four-category measure of family structure. First, all mothers reported their marital status: currently married, divorced, separated, widowed, or never married. Second, married mothers were asked whether co-wives are present in the marital union; third, all unmarried mothers were asked whether they are cohabiting with a male partner. With this information, we characterize children as having monogamously married (reference group), polygynous, cohabiting, or single mothers.7

Region-Level Prevalence of Polygyny

We use the DHS women’s data files for each country (i.e., nationally representative samples of women) to aggregate women’s reports of polygyny by region. More specifically, we create an indicator of the percentage of women (15–49 years old) in each region who reported being in a polygynous union. Because we operationalize polygyny using a female-centered approach, our estimates of region-level prevalence of polygyny are higher than a male-centered approach would yield. However, male- and female-centered approaches are highly correlated (Timæus and Reynar 1998), and because our argument rests not on absolute levels of polygyny but on the relative prevalence of the practice, we adopt the conventional approach of using women’s reports.

Region-Level Socioeconomic Development

To help explain a potential association between the contextual prevalence of polygyny and infant mortality (H1b), we control for socioeconomic development, which is known to be associated with infant health and survival (Sastry 1996). First, using the household data files, we calculate the percentage of households in each region that the DHS lists as “rural” (versus “urban”; see Kravdal and Kodzi 2011 for a similar approach). Second, to account for differential access to basic infrastructure, which is known to influence infant health and survival (Wang 2003), we aggregate the household data by region to estimate the percentage of households that report having electricity. (See Sastry (1996) and Kravdal (2002) for similar approaches.)

Region-Level Gender Inequality

To further explain a potential association between the contextual prevalence of polygyny and infant mortality (H1b), we construct a female-to-male ratio of the average educational attainment in each region to account for the extent of gender inequality. The female-to-male educational attainment ratio is commonly leveraged in the development literature as an indicator of gender inequality (e.g., United Nation’s Gender Inequality Index (http://hdr.undp.org/en/statistics/gii/)).8 We use the representative data sets to estimate average educational attainment in each region, separately for women and for men. We then convert these averages into a ratio that captures the average educational attainment of women relative to that of men in each region.

Cross-Level Interaction Between Contextual Prevalence of Polygyny and Family Structure

We interact the region-level prevalence of polygyny with family structure to create a continuous by categorical cross-level interaction. This allows us to assess whether the contextual prevalence of polygyny conditions the relationship between family structure and infant mortality (H2).

Controls

Country Level

Because a host of country-level factors may influence the associations among the contextual prevalence of polygyny, family structure, and infant mortality, our multilevel hazard models include a set of dummy variables representing each of the 29 countries in our sample. This country-level fixed-effects approach allows us to control for constant, unobserved factors that vary across sub-Saharan African countries and that may be associated with infant mortality.

Family-Level and Child-Level Controls

Based on the established literature on infant mortality in sub-Saharan Africa, we include a robust set of controls that are standard in infant mortality research. In terms of family characteristics, we control for the number of household members, whether the mother is Muslim (= 1), mother’s completed years of formal education, and total sibship size (number of siblings with the same mother). To account for socioeconomic inequality across families, we control for the DHS–constructed wealth index.

A set of child-specific controls focus on measuring the established correlates of infant mortality that could vary by family structure: maternal age at the time of the focal child’s birth (19 years or younger, 20–34 (reference group), or 35 and older), duration of the preceding birth interval (none: child is first birth (reference group), 24 months or less, and more than 25 months). Finally, we control for the child’s gender (female = 1), birth order, and whether the child is a multiple (= 1).

Methods

We estimate infant mortality using multilevel discrete-time hazard models, which are ideal for working with censored observations. Infants who are still alive at the end of the observation period or who have not yet reached their first birthday are right-censored. In addition to the issue of censoring, our data are structured hierarchically: some infants share the same family, and as a result of overlapping genetic, behavioral, and socioeconomic factors, they may share similar levels of mortality (Curtis et al. 1993; Omariba et al. 2007; Sastry 1997). Children are also nested within subnational regions (N = 260) and within countries (N = 29).

To address censoring and the hierarchical nature of our data, we estimate a series of random-effects discrete-time logit models:
formula
where htijkl is the hazard that infant i in family j in region k in country l dies at time t; Xijkl is a vector of child-level covariates; Yjkl is a vector of family-level covariates; Zkl is a vector of region-level covariates; Cl are country dummy variables that allow us to control for unobserved confounders at the country level9; uj is the family-level random effect; is the subnational region-level random effect; and the represent the corresponding coefficients. We account for the effect of age on mortality () by including a dummy variable for each month.
To test our hypotheses of whether (H1a) and how (H1b) the contextual prevalence of polygyny is associated with infant mortality, and whether the contextual prevalence of polygyny conditions the relationship between family structure and infant mortality (H2), we specify five multilevel hazard models:
formula
(1)
formula
(2)
formula
(3)
formula
(4)
formula
(5)

Model (1) estimates the association between the region-level prevalence of polygyny and infant mortality net of family structure for infant i in family j in subnational region k in country l; where Xijkl is a vector of child-level covariates; Yjkl is a vector of family-level covariates; Cl are country dummy variables; uj is the family-level random effect; is the subnational region-level random effect; and the represent the corresponding coefficients. Model (2) includes region-level indicators of socioeconomic development (i.e., rurality, access to infrastructure) to determine whether these factors explain the association between the prevalence of polygyny and infant mortality in Model 1. Model 3 includes a region-level gender inequality indicator (i.e., female-to-male education ratio) to determine whether, and to what extent, it helps explain the association observed in Model 1. Model 4 includes both the socioeconomic and gender inequality indicators to test whether the association between the contextual prevalence of polygyny and infant mortality is fully explained. To examine our second hypothesis, Model 5 extends Model 4 by including a cross-level interaction term between the region-level prevalence of polygyny and family structure to determine whether the infant survival disparity between polygynous and monogamous families is conditional on the broader marital context.

Results

Of the 236,336 births in our analytic sample, 16,323 infants died during their first year of life, representing 6.9 % of the analytic sample.

Figure 1 provides a visual representation of the distribution of polygyny across the 260 subnational regions within the 29 selected sub-Saharan African countries. Corroborating findings from previous research, Fig. 1 demonstrates considerable heterogeneity in the prevalence of polygyny (i.e., percentage of women in polygynous unions) both within and across sub-Saharan African countries (Lesthaeghe 1989; Reniers and Watkins 2010). For instance, in the West African country of Mali, the percentage of women in polygynous unions ranges from as low as 7.2 % in one region to 50.9 % in another. In general, countries with an overall lower prevalence of polygyny (e.g., Congo (Brazzaville), Namibia, and Rwanda) have less heterogeneity across regions.

Table 1 provides a descriptive overview of the characteristics of infants, families, and subnational regions in our sample. Among the full sample, the average region-level prevalence of polygyny is 27.8 %. The majority of families live in predominantly rural regions (71.2 %) where relatively few families (19.8 %) have electricity. Overall, the majority of infants live in monogamous families, but approximately one-fourth live in polygynous ones. On average, infants in our sample live with approximately seven people, have mothers who completed three years of formal education, and have four siblings. A sizable minority have mothers who identify as Muslim (37.5 %).

Table 1 further demonstrates the contextual and compositional differences between subnational regions with varying levels of polygyny. In these descriptive analyses, we categorize regions that are more than one standard deviation below the regional mean of polygyny as “low prevalence” (≤13 %), regions one standard deviation below/above the mean as “average prevalence” (14 % to 43 %), and regions more than one standard deviation above the mean as “high prevalence” (≥44 %). In terms of contextual differences, we find that, as hypothesized, socioeconomic disadvantage and gender inequality are concentrated in highly polygynous settings. In settings where polygyny is below average, 60.9 % of households are rural and 24.6 % are electrified, compared with over 84.3 % rural and only 9.9 % electrified in high polygyny settings. Furthermore, while women in low polygyny regions have completed more than three-fourths as much formal schooling as men, on average, women in highly polygynous regions have completed less than one-half as much formal schooling as their male counterparts. In addition to these contextual differences, the composition of families varies as a function of the prevalence of polygyny. As expected, sibship size is larger and household wealth is lower among infants in higher-prevalence settings. Furthermore, mothers in high-prevalence polygynous settings are more likely to self-identify as Muslim and have completed fewer years of formal education.

Table 2 shows estimates from hazard models of mortality during infancy (0–11 months). Results in Model 1 support H1a: net of individual family structure and a standard set of controls at the family and child levels, infants living in regions where polygyny is more prevalent experience higher mortality risk. In fact, each unit increase in the prevalence of polygyny is associated with an approximately 0.5 % higher risk of infant mortality (p < .001). Given that the prevalence of polygyny ranges from as low as 1.0 % to as high as 64.8 % across the 260 regions in our sample, the magnitude of this association is substantial—a 32 % difference across the marital context spectrum.

In addition to the contextual prevalence of polygyny, a number of family- and child-level characteristics are significantly associated with infant mortality. Each of these falls in line with previous research on infant mortality in developing contexts. Each year of mother’s formal schooling is associated with 2 % lower risk of infant mortality. Children born to very young or to older mothers experience particularly elevated mortality risk (8 % and 32 %, respectively) compared with children born to women between the ages of 20 and 34 years. Furthermore, female infants experience 16 % lower risk of infant mortality, and those of twin births experience 22 % higher risk of infant mortality. With regard to family structure, infants in polygynous families experience 42 % higher mortality than infants in monogamous families. Additionally, children in cohabiting unions have a 20 % higher risk of mortality than children in monogamous unions, and infants in single-mother families have the highest risk of mortality (59 %). The results further show that there is substantial between-family and between-region variation in the risk of infant mortality, as indicated by the variance estimates of 0.233 and 0.151, respectively.

Model 2 extends Model 1 to assess whether region-level socioeconomic characteristics help to explain the association between the contextual prevalence of polygyny and infant mortality (H1b). Controlling for a region’s rurality and access to infrastructure reduces the association between the contextual prevalence of polygyny and infant mortality by half (from .005 to .003) and lowers it to nonsignificance. In other words, the association between the contextual prevalence of polygyny and infant mortality is attributable to other regional characteristics: polygyny is widespread in sub-Saharan Africa’s most rural and socioeconomically disadvantaged settings in which infant mortality is highest. As shown by the reduction in the region-level variance component from Model 1 to Model 2 (0.151 to 0.149), accounting for region-level socioeconomic development explains a portion of the between-region differences in infant mortality risk.

Examining whether and to what extent differences in gender inequality explain the association between the prevalence of polygyny and infant mortality, Model 3 shows that infants in more gender-equal settings have a marginally significant survival advantage. That is, each unit increase in women’s completed education relative to men’s is associated with a 22 % lower risk of infant mortality. Furthermore, in comparison to Model 1, the association between the contextual prevalence of polygyny and infant mortality is attenuated (from .005 to .004), suggesting that a portion of the risk associated with living in a region where polygyny is more prevalent is attributable to corresponding levels of gender inequality.

Simultaneously controlling for regional differences in socioeconomic development and gender inequality (Model 4), we find that these (admittedly crude) contextual indicators explain the generalized elevated risk of infant mortality associated with living in a region where polygyny is more prevalent. Only residence in settings with greater socioeconomic development (i.e., electricity) remains independently associated with infant mortality (p < .10): each percentage increase in electrified households is associated with a 1 % lower risk of infant mortality.

In Model 5, we assess whether the risk associated with living in a polygynous family is conditional on the contextual prevalence of polygyny (H2) by adding cross-level interaction terms (i.e., between region-level prevalence of polygyny and family structure). The positive interaction between region-level prevalence of polygyny and family-level polygyny indicates that the survival disadvantage associated with polygyny (compared with monogamy) is exacerbated in settings where the practice is widespread (p < .001). For infants in polygynous families, their already elevated risk of mortality, compared with children in monogamous families, increases by approximately 1 % per percentage increase in region-level polygyny. Thus, children in polygynous families (versus monogamous ones) in regions where polygyny is seldom practiced (about 1 %), experience a 13 % higher risk of infant mortality; children in polygynous families in the most highly polygynous contexts (about 65 %) experience approximately 77 % higher risk of infant mortality than their peers in monogamous families.

To illustrate the disparities in infant mortality by family structure and region-level prevalence of polygyny, Fig. 2 depicts Kaplan-Meier hazard estimates of infant mortality risk that hold all other covariates (shown in Model 5) at their mean value. For ease of presentation, we categorize subnational regions as we did in the descriptive analyses: subnational regions more than one standard deviation below the regional mean of polygyny are classified as “low prevalence,” regions one standard deviation above/below the mean are “average prevalence,” and regions more than one standard deviation above the mean are “high prevalence.” The central finding from Fig. 2 is that the region-level prevalence of polygyny influences the size of the survival gap between family structures. In all contexts, infant mortality is higher in polygynous families than in monogamous families (log-rank test p < .05), but as shown, the size of this disparity increases with the region-level prevalence of polygyny. That is, in support of H2, the polygyny-infant survival disadvantage is amplified in high-polygyny settings and dampened in low-polygyny settings—that is, net of the household wealth index and a robust set of additional confounders. This provides suggestive, although not conclusive, evidence of a process of cultural convergence, whereby polygynous families in low-prevalence areas more closely mirror the overarching monogamous culture, as supported by their converging rates of infant mortality.

Discussion

Although declining worldwide, polygyny continues to thrive in many parts of sub-Saharan Africa (Bove and Valeggia 2009; Van de Walle 2006). Building on evidence that the prevalence of polygyny reflects a complex bundle of economic, social, and cultural features, and that its prevalence has implications for how polygynous families engage in the practice, we explore whether the prevalence of polygyny is associated with elevated infant mortality. We further examine the extent to which the marital context conditions the known survival disadvantage for children in polygynous families (i.e., compared with monogamous families) in particular.

Our multilevel fixed-effects approach controls for unobserved country-level influences on infant mortality and confirms that polygyny is associated with higher infant mortality at both the family level and the contextual level. Recent multinational research has documented a link between polygyny and mortality in early childhood (i.e., before age 5) in sub-Saharan Africa (Omariba and Boyle 2007), and our study, using a more rigorous methodological approach, further confirms the survival disadvantage during infancy. At the family level, we show that children in polygynous families have a 42 % higher likelihood of mortality than their counterparts in monogamous ones.

In addition to the sizable survival disadvantage for infants in families that practice polygyny, our results reveal that the contextual prevalence of polygyny is associated with infant mortality. The association is, however, largely spurious, and is explained by the concentrated socioeconomic disadvantage and, to some extent, the widespread gender inequality that characterizes highly polygynous settings.

Although the contextual prevalence of polygyny is not independently associated with infant mortality for all families, the contextual prevalence of polygyny has significant implications for the morality risk of infants in polygynous families. Net of the same regional confounders that explain the direct association between contextual polygyny and infant mortality, the infant mortality disparities between polygynous and monogamous families are significantly amplified where polygyny is widely practiced—the 13 % elevated risk of mortality in low-polygyny settings increases sixfold in settings with the highest prevalence of polygyny. Because of data limitations, we are unable to formally test hypotheses about why this is the case, but we offer a possible theoretical explanation. The differences in the mortality disadvantage associated with polygyny across marital contexts could be driven by variability in how families practice polygyny. That is, the smaller mortality gap between children in monogamous and polygynous families in low polygyny settings may be due to the fact that polygynously married men and women in these contexts adapt their interpersonal dynamics and relationships to fit the surrounding culture of monogamy. In other words, although there is little evidence that polygyny has a deleterious effect on infant mortality for children in monogamous families, monogamous culture appears to dampen the infant mortality disadvantage of children in polygynous families.

This explanation brings us squarely into the territory of analyzing cultural processes, which is distant from the terrain most demographers regularly explore (Bachrach forthcoming). Demographic data to test whether and how interpersonal dynamics vary within polygynous relationships across marital contexts—and, in turn, whether these processes explain differences in the size of the mortality gap between polygynous and monogamous families—simply do not exist. The absence of data on the family dynamics that may contribute to children’s health experiences reflect the tendency of demographic surveys to focus on tracking events and discrete statuses rather than on processes. Echoing Hobcraft’s (2006) call for more demographic research that accounts for dynamic processes within families, our findings underscore the need for population-based data sources that are suitable for exploring the interpersonal and relational aspects of family life. In sub-Saharan Africa, such data could facilitate a richer understanding of the regional variation in gender relations and cultural practices of polygynous families, and enable us to better understand whether and how these distinctions ultimately influence children’s health.

Although we suspect that cultural processes underlie the differential mortality risk associated with polygyny across marital contexts, we also acknowledge that our analyses do not fully capture the role of economic heterogeneity between polygynous families across contexts. Although the differential risk of mortality among polygynous families persists net of household wealth (Model 5, Table 2), the DHS’s wealth index reflects a family’s shared household assets and material resources but does not capture consumable resources (e.g., cash, crops). Because these are exactly the resources at greatest risk of dilution across multiple co-wives and sibling groups, the question of whether polygynous families’ access to such resources varies across marital contexts is both an important and an outstanding one. In supplementary descriptive analyses (not shown), we find that household wealth disparities between polygynous and monogamous families are consistent across marital contexts; additional multivariate models confirm that the inclusion of household wealth as a control does not attenuate the differential risk of infant mortality associated with polygyny. These analyses suggest that economic processes are not the primary drivers of the differential infant mortality risk associated with polygyny, but more detailed data on multiple dimensions of polygynous families’ resources would allow researchers to more rigorously explore the role of economic disparities across marital contexts.

Although we still do not know precisely why the polygyny–infant mortality association differs as a function of polygyny’s concentration, our study convincingly demonstrates that marriage and family have important implications for infant mortality in sub-Saharan Africa. On the one hand, our findings could be read optimistically as evidence that the infant mortality gap between polygynous and monogamous families may shrink over time. Social changes, such as rising female education, urbanization, and migration, are lowering the practice of polygyny across sub-Saharan Africa (Timæus and Teynar 1998). As these changes continue, polygyny will become increasingly rare in most of sub-Saharan Africa, thereby reducing the number of children exposed to this particular mortality risk. On the other hand, if socioeconomic development occurs unevenly across subnational regions, polygyny may become an even more spatially concentrated practice. The mortality disparities for children in polygynous families could persist, or even be magnified, in these settings of concentrated disadvantage. Therefore, even as polygyny continues to decline across sub-Saharan Africa as a whole, or within particular subnational regions, marriage patterns will remain critical for understanding infant health and survival in this part of the world.

Beyond polygyny and infant survival in sub-Saharan Africa, our study highlights, more generally, the relevance of the broader marital context for understanding how family characteristics influence children’s well-being. Our study advances the idea that marital practices are contextual and cultural phenomena and not merely characteristics of families themselves. That the polygyny disadvantage is largest in contexts where the practice is widespread parallels evidence from the West that the educational disadvantage associated with having a single parent (compared with a two-parent family) is amplified where single-parent families are most common (Pong et al. 2004). This evidence demonstrates that research linking family-level processes to their contextual conditions produces valuable insights into child well-being.

The field of demography has a rich history of linking family-level processes to structural conditions (e.g., poverty, urbanicity), and our focus on the marital context extends this tradition in new ways. Marital practices are closely related to structural conditions, as we show here; however, the marital context also taps into more nebulous cultural factors (e.g., gender relations) that are critically relevant to demographic outcomes. Our approach exemplifies how demographers can link families to their contexts in ways that extend beyond the measurement of material conditions, shifting the focus to factors that simultaneously encompass material and cultural phenomena that cannot be easily disentangled. Further expanding standard notions of the aspects of context that are demographically salient may be a fruitful avenue for generating further insights into demographic patterns and processes.

Acknowledgments

Emily Smith-Greenaway wishes to acknowledge the support of the Predoctoral Traineeship in Family Demography (No. T-32HD 007514) by the Eunice Kennedy Shriver National Institute of Child Health and Human Development to the Pennsylvania State University Population Research Institute. We acknowledge assistance provided by the Population Research Center at Penn State University, which is supported by an infrastructure grant by the National Institutes of Health (2R24HD041025-11). We also wish to thank three anonymous reviewers for their comments, and several colleagues for providing us feedback on earlier versions of the manuscript: Lauren Bachan, Michelle Frisco, Monica Grant, Adam Lippert, Wayne Osgood, Jenny Van Hook, and the participants of the International Perspectives on Family Structures and Child Well-being at McGill University (November 30–December 1, 2012).

Appendix

Notes

1

One study using the 1990 Nigerian Demographic and Health Survey shows that although polygyny is not associated with survival during the neonatal and childhood periods, it is positively associated with child survival during the postneonatal period (Ukwuani et al. 2002).

2

Some anthropologists (notably, Goody 1973) have refuted that economic factors motivate widespread polygyny and point to the importance of social and cultural features. Although we do not discuss this disagreement, we describe the social and cultural elements of polygyny.

3

Of the 48 countries in sub-Saharan Africa, we exclude 13 countries from our study because the DHS did not operate in these countries between 2000 and 2010 (Angola, Botswana, Central African Republic, Comoros, Côte D’Ivoire, Djibouti, Equatorial Guinea, Guinea-Bissau, Mauritius, Seychelles, Somalia, South Sudan, and Togo). Furthermore, we exclude five countries because the data are not publically available (Cape Verde, Eritrea, The Gambia, Mauritania, South Africa) and one country (Lesotho) because polygyny data were not collected, resulting in a final sample of 29 countries.

4

Response rates are published in the survey documentation reports for each country, which are available online (http://www.measuredhs.com/).

5

Although the DHS does include smaller aggregate units (i.e., “clusters”), they are not intended for contextually focused analyses but instead are enumeration areas that are drawn only for the purpose of sampling.

6

Samples for each region are large—on average, containing 964 households (ranging from 266 to 7,091), 1,145 women (ranging from 306 to 7,297), and 488 men (ranging from 80 to 3,358). As a result, the inclusion versus omission of the index household from the aggregate analyses makes no difference. For instance, in the Kigal region of Mali—the smallest sample of women (N = 306) for any of our regions—7.19 % of women are in polygynous unions. If we omitted the index family when creating this index, the value would vary across families by less than one-third of 1 %. Given that it makes little difference, we include the index family because (1) we prefer having a uniform value for each region, and (2) removing the index family alters but does not fully eliminate the correlation between the aggregate level and individual level (Raudenbush and Bryk 2002).

7

The cross-sectional nature of the data prohibits us from accounting for changes in family structure between a child’s birth and the time of the survey or, in the case of deceased children, the time of their death. Thus, it is possible that monogamous unions became polygynous after the child’s birth and/or death. In fact, entry into a polygynous family could be a direct response to the death of a child. We reduce the likelihood of misclassifying families’ structure by limiting the analyses to births that occurred in the five years prior to the survey; however, this bias is still possible and should be kept in mind when interpreting results.

8

A limitation of the female-to-male education ratio is that it reflects only one dimension of gender inequality (i.e., educational attainment). However, because education is a central determinant of individuals’ income, occupation, and health, it is an ideal measure for capturing inequalities between women’s and men’s life chances more broadly. The DHS also measures gender inequality through a series of questions about women’s involvement in household decision-making; however, these questions are asked in only two-thirds of the countries in our study, and are similarly limited by their focus on a single dimension of inequality.

9

A country-level fixed-effects approach allows us to control for constant, unobserved factors that vary across sub-Saharan African countries. Because a fixed-effects approach is less efficient, our analyses will yield more conservative estimates.

References

Agadjanian, V., & Ezeh, A. C. (
2000
).
Polygyny, gender relations, and reproduction in Ghana
.
Journal of Comparative Family Studies
,
31
,
427
442
.
Amankwaa, A. A. (
1996
).
Prior and proximate causes of infant survival in Ghana, with special attention to polygyny
.
Journal of Biosocial Science
,
28
,
281
295
. 10.1017/S0021932000022355
Amankwaa, A. A., Eberstein, I. W., & Schmertmann, C. P. (
2001
).
Polygyny and infant morality in western Africa: Evidence from Ghana
.
African Population Studies
,
16
,
1
13
.
Amey, F. K. (
2002
).
Polygyny and child survival in West Africa
.
Social Biology
,
49
,
74
89
.
Bachrach, C. (Forthcoming).
Culture and demography: From reluctant bedfellows to committed partners
.
Demography
.
Bledsoe, C. (
1990
).
Transformations in sub-Saharan African marriage and fertility
.
The Annals of the American Academy of Political and Social Science
,
510
,
115
125
. 10.1177/0002716290510001009
Bledsoe, C. (
1995
).
Marginal members: Children of previous unions in Mende households in Sierra Leone
.
Situating fertility, anthropology and demographic inquiry
(pp.
130
153
).
Cambridge, UK
:
Cambridge University Press
.
Bose, S. (
2011
).
The effect of women’s status and community on the gender differential in children’s nutrition in India
.
Journal of Biosocial Science
,
43
,
513
533
. 10.1017/S002193201100006X
Boserup, E. (
1985
).
Economic and demographic interrelationships in sub-Saharan Africa
.
Population and Development Review
,
11
,
383
397
. 10.2307/1973245
Bove, R., & Valeggia, C. (
2009
).
Polygyny and women’s health in sub-Saharan Africa
.
Social Science & Medicine
,
68
,
21
29
. 10.1016/j.socscimed.2008.09.045
Bradley, M. (
2004
).
Cultural configurations of Mormon fundamentalist polygamous communities
.
Nova Religio
,
8
,
5
19
. 10.1525/nr.2004.8.1.5
Cahu, P., Falilou, F., & Pongou, R. (Forthcoming).
Demographic transition in Africa: The polygamy and fertility nexus
. In Agyei-Mensah, S. & Mturi, A. J. (Eds.),
Fertility diversity and its future prospects in Africa
.
Caldwell, J. C., & Caldwell, P. (
2002
).
Africa: The new family planning frontier
.
Studies in Family Planning
,
33
,
76
86
. 10.1111/j.1728-4465.2002.00076.x
Curtis, S. L., Diamond, I., & McDonald, J. W. (
1993
).
Birth interval and family effects on postneonatal mortality in Brazil
.
Demography
,
30
,
33
43
. 10.2307/2061861
Desai, S. (
1992
).
Children at risk: The role of family structure in Latin America and West Africa
.
The Population and Development Review
,
689
717
.
Dorjahn, V. R. (
1959
).
The factor of polygyny in African demography
. In Bascom, W. R., & Herskovitz, M. J. (Eds.),
Continuity and change in African cultures
(pp.
87
112
).
Chicago, IL
:
Phoenix Books
.
Ezeh, A. C. (
1997
).
Polygyny and reproductive behavior in Sub-Saharan Africa: A contextual analysis
.
Demography
,
34
,
355
368
. 10.2307/3038289
Fotso, J. C. (
2006
).
Urban-rural differentials in child malnutrition: Trends and socioeconomic correlates in sub-Saharan Africa
.
International Journal for Equity in Health
,
5
,
9
19
. 10.1186/1475-9276-5-9
Furuta, M., & Salway, S. (
2006
).
Women’s position within the household as a determinant of maternal health care use in Nepal
.
International Family Planning Perspectives
,
32
,
17
27
. 10.1363/3201706
Gage, A. J. (
1997
).
Familial and socioeconomic influences on children’s well-being: An examination of preschool children in Kenya
.
Social Science & Medicine
,
45
,
1811
1828
. 10.1016/S0277-9536(97)00113-5
Gibson, M. A., & Mace, R. (
2007
).
Polygyny, reproductive success and child health in rural Ethiopia: Why marry a married man?
.
Journal of Biosocial Science
,
39
,
287
300
. 10.1017/S0021932006001441
Goody, J. (
1973
).
Polygyny, economy, and the role of women
. In
The character of kinship
(pp.
175
190
).
Cambridge, UK
:
Cambridge University Press
.
Gwako, E. L. M. (
1998
).
Polygyny among the Logoli of western Kenya
.
Anthropos
,
93
,
331
348
.
Gyimah, S. O. (
2003
).
Interaction effects of maternal education and household facilities on childhood diarrhea in sub-Saharan Africa: The case of Ghana
.
Journal of Health & Population in Developing Countries
,
5
,
1
17
.
Gyimah, S. O. (
2009
).
Polygynous marital structure and child survivorship in sub-Saharan Africa: Some empirical evidence from Ghana
.
Social Science & Medicine
,
68
,
334
342
. 10.1016/j.socscimed.2008.09.067
Hadley, C. (
2005
).
Is polygyny a risk factor for poor growth performance among Tanzanian agropastoralists?
.
American Journal of Physical Anthropology
,
126
,
471
480
. 10.1002/ajpa.20068
Hayase, Y., & Liaw, K. L. (
1997
).
Factors on polygamy in sub-Saharan Africa: Findings based on the Demographic and Health Surveys
.
The Developing Economies
,
35
,
293
327
. 10.1111/j.1746-1049.1997.tb00849.x
Hobcraft, J. (
2006
).
The ABC of demographic behaviour: How the interplays of alleles, brains, and contexts over the life course should shape research aimed at understanding population processes
.
Population studies
,
60
,
153
187
. 10.1080/00324720600646410
Jacoby, H. G. (
1995
).
The economics of polygyny in sub-Saharan Africa: Female productivity and the demand for wives in Côte d’Ivoire
.
Journal of Political Economy
,
103
,
938
971
. 10.1086/262009
Kilbride, P. L., & Kilbride, J. C. (
1990
).
Changing family life in East Africa: Women and children at risk
.
University Park
:
Pennsylvania State University Press
.
Kravdal, Ø (
2002
).
Education and fertility in sub-Saharan Africa: Individual and community effects
.
Demography
,
39
,
233
250
.
Kravdal, Ø (
2004
).
Child mortality in India: The community-level effect of education
.
Population Studies
,
58
,
177
192
. 10.1080/0032472042000213721
Kravdal, Ø, & Kodzi, I. (
2011
).
Children’s stunting in sub-Saharan Africa: Is there an externality effect of high fertility?
.
Demographic Research
,
25
(
article 18
),
565
594
. 10.4054/DemRes.2011.25.18
Lamb, M. E. (
2004
).
The role of the father in child development
.
Hoboken, NJ
:
John Wiley & Sons
.
Lesthaeghe, R. J. (
1989
).
Reproduction and social organization in sub-Saharan Africa
.
Berkeley
:
University of California Press
.
Lesthaeghe, R. J., Kaufmann, G., & Meekers, D. (
1986
).
The nuptiality regimes in sub-Saharan Africa
(IPD Working Paper No. 1986–3).
Brussels, Belgium
:
Interuniversity Programme in Demography, Vrije Universiteit Brussel
.
McBride, B. A., & Rane, T. R. (
1998
).
Parenting alliance as a predictor of father involvement: An exploratory study
.
Family Relations
,
47
,
229
236
. 10.2307/584971
Muhsam, H. V. (
1956
).
Fertility of polygamous marriages
.
Population Studies
,
10
,
3
16
.
Murdock, G. P. (
1967
).
Ethnographic atlas: A summary
.
Ethnology
,
6
,
109
236
. 10.2307/3772751
Nyblade, L., & Menken, J. (
1993
).
Husband-wife communication: Mediating the relationship of household structure and polygyny to contraceptive knowledge, attitudes and use
.
Proceedings of the IUSSP General Conference, Montreal, August 1993
(Vol.
1
, pp.
109
120
). Liege: IUSSP.
Liege, Belgium: IUSSP
.
Omariba, D. W. R., Beaujot, R., & Rajulton, F. (
2007
).
Determinants of infant and child mortality in Kenya: An analysis controlling for frailty effects
.
Population Research and Policy Review
,
26
,
299
321
. 10.1007/s11113-007-9031-z
Omariba, D. W. R., & Boyle, M. H. (
2007
).
Family structure and child mortality in sub-Saharan Africa: Cross-national effects of polygyny
.
Journal of Marriage and Family
,
69
,
528
543
. 10.1111/j.1741-3737.2007.00381.x
Pong, S., Dronkers, J., & Hampden-Thompson, G. (
2004
).
Family policies and children’s school achievement in single-versus two-parent families
.
Journal of Marriage and Family
,
65
,
681
699
. 10.1111/j.1741-3737.2003.00681.x
Raudenbush, S. W., & Bryk, A. S. (
2002
).
Hierarchical linear models: Applications and data analysis methods
.
Thousand Oaks, CA
:
Sage Publications, Inc.
.
Reniers, G., & Watkins, S. (
2010
).
Polygyny and the spread of HIV in sub-Saharan Africa: A case of benign concurrency
.
AIDS
,
24
,
299
307
. 10.1097/QAD.0b013e328333af03
Sastry, N. (
1996
).
Community characteristics, individual and household attributes, and child survival in Brazil
.
Demography
,
33
,
211
229
. 10.2307/2061873
Sastry, N. (
1997
).
Family-level clustering of childhood mortality risk in northeast Brazil
.
Population Studies
,
51
,
245
261
. 10.1080/0032472031000150036
Sellen, D. W. (
1999
).
Polygyny and child growth in a traditional pastoral society
.
Human Nature
,
10
,
329
371
. 10.1007/s12110-999-1007-8
Solway, J. S. (
1990
).
Affines and spouses, friends and lovers: The passing of polygny in Botswana
.
Journal of Anthropological Research
,
46
,
41
66
.
Stephenson, R., Baschieri, A., Clements, S., Hennink, M., & Madise, N. (
2006
).
Contextual influences on the use of health facilities for childbirth in Africa
.
American Journal of Public Health
,
96
,
84
93
. 10.2105/AJPH.2004.057422
Strassman, B. I. (
1997
).
Polygyny as a risk factor for child mortality among the Dogon
.
Current Anthropology
,
38
,
688
695
. 10.1086/204657
Timæus, I. M., & Reynar, A. (
1998
).
Polygynists and their wives in sub-Saharan Africa: An analysis of five Demographic and Health Surveys
.
Population Studies
,
52
,
145
162
. 10.1080/0032472031000150346
Tobias, B. Q. (
2001
).
A descriptive study of the cultural mores and beliefs toward HIV/AIDS in Swaziland, Southern Africa
.
International Journal for the Advancement of Counselling
,
23
,
99
113
. 10.1023/A:1010614313756
Ukwuani, F. A., Cornwell, G. T., & Suchindran, C. M. (
2002
).
Polygyny and child survival in Nigeria: Age-dependent effects
.
Journal of Population Research
,
19
,
155
171
. 10.1007/BF03031975
Van de Poel, E., O’Donnell, O., & Van Doorslaer, E. (
2007
).
Are urban children really healthier?
.
Social Science & Medicine
,
65
,
1986
2003
. 10.1016/j.socscimed.2007.06.032
Van de Walle, É (
2006
).
African households: Censuses and surveys
.
Armonk, NY
:
ME Sharpe
.
Wang, L. (
2003
).
Determinants of child mortality in LDCs: Empirical findings from Demographic and Health Surveys
.
Health Policy
,
65
,
277
299
. 10.1016/S0168-8510(03)00039-3
White, D. R., & Burton, M. L. (
1988
).
Causes of polygyny: Ecology, economy, kinship, and warfare
.
American Anthropologist
,
90
,
871
887
. 10.1525/aa.1988.90.4.02a00060
Zeitzen, M. K. (
2008
).
Polygamy: A cross-cultural analysis
.
Oxford, UK
:
Berg Publishers
.