Gendered Emotional Support and Women’s Well-Being in a Low-Income Urban African Setting

Abstract

In most contexts, emotional support is crucial for the well-being of low-income single women and their children. Support from women may be especially important for single mothers because of precarious ties to their children’s fathers, the prevalence of extended matrifocal living arrangements, and gendered norms that place men as providers of financial rather than emotional support. However, in contexts marked by economic insecurity, spatial dispersion of families, and changing gender norms and kinship obligations, such an expectation may be problematic. Applying theories of emotional capital and family bargaining processes, we address three questions: What is the gender composition of emotional support that single mothers receive? How does gender composition change over time? Does the gender composition of emotional support affect the self-reported stress of single mothers? Drawing on data from a unique data set on 462 low-income single mothers and their kin from Nairobi, Kenya, we uncover three key findings. One, whereas the bulk of strong emotional support comes from female kin, about 20 percent of respondents report having male-dominant support networks. Two, nearly 30 percent of respondents report change favoring men in the composition of their emotional support over six months. Three, having a male-dominant emotional support network is associated with lower stress. These results challenge what is commonly taken for granted about gender norms and kinship obligations in non-Western contexts.

Keywords

emotional support emotional capital mothers poverty Kenya gender

Emotional support is critical for the well-being of low-income single mothers and their children. The extant scholarship—most of it from the United States and western contexts—emphasizes the role of women as the primary providers of such support driven both by circumstance, namely, the absence of stable relationships with romantic partners, and a gendered view of women as uniquely equipped to effectively perform emotional labor. Do women dominate the emotional support networks of single mothers in non-western contexts? Is the emotional support provided by women especially beneficial for single mothers’ well-being? We are aware of no research that has asked either question. In this analysis, we integrate theories of emotional capital (Nowotny 1981) and family bargaining processes (Agarwal 1997; Folbre 1986) to examine this relationship through the lens of poor single mothers in a slum community in Nairobi, Kenya. This context is important because it enables us to advance the scholarship on emotional capital to include non-western settings in the midst of profound social and economic transformation.

Emotional support for single mothers in sub-Saharan Africa may be expected to come primarily from women given the tenuous link between single mothers and their children’s fathers, the continuing importance of extended matrifocal living arrangements (Jackson 2015), strong consanguinal ties to sisters and mothers (Oyewumi 2002; Sudarska 1998), and the persistence of gendered expectations of men as financial rather than emotional providers (Smith 2017). At the same time, however, limited job prospects for both men and women (Hunter 2006; Tsikata and Razavi 2009) and rapidly changing gender norms and perceptions of kinship obligations may be altering expectations and the receipt of emotional support from both women and men. This dynamic tension, therefore, provides an ideal backdrop to address three questions: What is the gender composition of emotional support networks for single mothers? How does this gender composition change over time? Does the gender composition of emotional support affect self-reported stress of single mothers?

Korogocho, the site for this analysis, shares similar characteristics with other low-income communities in urban Africa, namely, inadequate access to basic services, poor housing, limited employment opportunities, and crime. The area also has elevated rates of infant and child mortality as well as HIV and domestic violence (Beguy et al. 2015; Madise et al. 2012). Despite the numerous child care facilities in the slum area, many of these services are unaffordable or of low quality (Clark, Kabiru, et al. 2017). These settlements have become the “public face” of social inequality in rapidly urbanizing contexts in Africa, serving as home to both recent and more established residents, all struggling to maintain livelihoods amidst economic and physical precarity. Women, in particular, are vulnerable given that they no longer live in proximity to trusted kin and are wary of forming nonkin relationships (Cotton and Beguy 2013; Madhavan and Landau 2011). Our earlier work has shown that women are less likely to receive emotional support from nonresident kin who live in nonslum (wealthier) urban settings, suggesting ideational shifts in kinship obligations favoring investment in immediate family rather than extended kin (Madhavan et al. 2018). However, Mudege and Ezeh (2009) have shown that in this context, older women are better at maintaining and activating social ties than older men. This “gender advantage,” the authors contend, is a result of working primarily in the domestic sphere, which strengthens close and reciprocal ties, in contrast to the male-dominant public sphere characterized by weak ties (Granovetter 1973).

In this analysis, we do not address the question of gender advantage directly (i.e., we are not comparing men and women) but rather focus on the gender composition of women’s emotional support networks to better understand the relative benefits and liabilities of having female- or male-dominant networks (i.e., gendered emotional support for women’s well-being). The importance of this study is underscored by one significant trend occurring in sub-Saharan Africa—men and women moving to urban areas in search of employment, education, anonymity, and liberation from kin responsibilities. Whereas urban spaces may offer economic opportunities and independence, women, in particular, often find themselves facing poor job prospects and potential male partners with limited employment options, leaving them to raise children with little involvement of fathers or their kin. Therefore, these circumstances may undermine any “gender advantage” they may hold in accessing support from kin and alter the gender composition of emotional support. Through this analysis, we contribute to a larger discussion about how social change in Africa, manifested in shifting gender norms and expectations of kin support, may be impacting women’s well-being in urbanizing contexts.

Understanding Gendered Emotional Capital

In this article, we interrogate the female-centric portrayal of emotional capital by integrating concepts from the family bargaining model, which recognizes economic exigencies and variation in family structure and changing gender norms in non-western contexts. In doing so, we also advance theory on the extent to which gender matters in explaining well-being outcomes by explicitly considering structural constraints (i.e., economic security) and agency (i.e., how women and men alter their identities as a response to rapid social transformation).

The Gender Composition of Emotional Support Networks

Inspired by Bourdieu’s (1986) work on forms of gendered capital, Nowotny (1981) defines emotional capital as “knowledge, contacts and relations as well as access to emotionally valued skills and assets, which hold within any social network characterized at least partly by affective ties” (148). Nowotny’s work emphasizes the gendered nature of emotional capital. She sees it as a resource that women have in far greater abundance than men because of their dominant position in the domestic sphere, which they actively use to maintain family connectivity. Bell (1990) takes this one step further by arguing that there is an economy of emotions within families in which mothers balance the family emotional budget. The concept of “gendered emotional capital” can be credited to Reay (2004) through her examination of class differences in mothers’ expenditures of time and emotions on their children’s education. However, the assumption that women are more likely to provide emotional support within the domestic sphere depends, in part, on the role of family structure and the extent to which women participate in the public sphere.

Much of the work on emotional capital relies on euro-centric models of family that center on nuclear arrangements in which women rely on their spouses for primary emotional support for themselves (Levitt, Weber, and Clark 1986; Rook, Dooley, and Catalano 1991) but take charge of managing the emotional needs of their partners and children. While they make emotional investments in extended (primarily female) kin in their roles as “kin keepers” (Salari and Zhang 2006) through various forms of communication (Di Leonardo 1987), such connections would be seen as secondary to the nuclear ties. These models rely on the distinction of nuclear from extended kin and prioritize women’s roles in the domestic sphere. Moreover, the primacy of women as emotional support providers is predicated on this division of space and roles.

When we change our gaze to contexts that explicitly challenge conceptions of family centered on the conjugal relationship, we find that the gendered emotional capital model falls short. Stack’s (1974) seminal ethnography on social support in a low-income African American context underscores the critical role of female emotional bonds that encompass a range of biological and “fictive kin” relationships, though more recent work has documented a decline in the use of “kin care” among African Americans (Brewster and Padavic 2002). Similarly, Landry (2000) argues that middle-class African American women have always held roles in private and public spheres through linkages—emotional and practical—to a wide range of kin and nonkin. A long line of anthropological scholarship in various contexts in Africa has emphasized the relative importance of consanguineous over conjugal ties (Fortes 1944; Riesman 1992; Sudarska 1980). Tanner (1974), in a comparative study of matrifocal arrangements, shows that women not only provide support to one another but also hold significant power in economic and ritual realms. These studies, therefore, suggest that in many parts of sub-Saharan Africa where matrifocial extended families predominate, women are likely to be the primary managers of emotional capital but do so for a range of kin and nonkin in both domestic and public spheres. However, this may be changing in line with sociocultural transformations and economic constraints.

Fluidity in the Gender Composition of Emotional Support Networks

Gendered emotional capital theory makes an implicit assumption that gender norms remain relatively stable. However, a recent study demonstrates variation in the way younger and older generations of women are renegotiating caregiving and support provision (Conlon et al. 2014). Social and cultural change underway in many African countries is particularly pronounced and has altered the meaning and stability of unions, kinship obligations, and gender against a backdrop of economic insecurity. In Kenya, a rich scholarship has documented the ways in which gender norms have been changing to empower women (Hakansson 1994; Mwangi 1996; Silberschmidt 2005) albeit with unexpected consequences, such as an increase in gender-based violence (Bradley 1995). Whereas young women and men are seeking more independence through spatial and social distancing (Adepoju 1995; Bocast 2017; James 2017) and exercising greater decision-making power in the marriage process (Clark, Kabiru, and Mathur 2010; Smith 2001), they face formidable challenges in establishing financial independence. Women migrants in urban spaces face difficulties in retaining connections to their kin in places of origin (Babou 2008) and, in some cases, experience social isolation (Dinat and Peberdy 2007; Erulkar and Ferede 2009). Rural women also have experienced social displacement, as shown in Cliggett’s (2005) study of the Gwembe Tonga of Zambia. Cliggett shows that older women no longer reap the benefits of the matrilineal system, in particular, social support from their women kin, as a result of shifts in the political economy that have increasingly favored men’s access to land and other resources.

Where do men fit in? Recent scholarship has criticized the earlier work on emotional capital for essentializing gender (Cottingham 2016; Zembylas 2007). Drawing on data from a study of male nurses that demonstrates their potential for providing emotional care, Cottingham (2016) argues that emotional capital is neither gender neutral nor exclusively feminine. Indeed, recent work on fathers has recognized their roles beyond that of breadwinners to include nurturing (Marsiglio and Roy 2012). Recent scholarship on men and masculinity in the African context points to a competing set of discourses that opens up opportunities for challenging hegemonic masculinity. On one hand, the provision of financial support continues to be a normative expectation for men given their advantages in the labor market and traditional gender norms that cast men as breadwinners (Madhavan, Townsend, and Garey 2008; Silberschmidt 2005). However, the difficulty of accessing employment for men across Africa (Overå 2007), and the relatively high level of female labor force participation (ILO 2016), has altered expectations of support from male and female kin. These factors also have led to increasing male disempowerment (Hunter 2006; Silberschmidt 2005; Walker 2005) which, in turn, may further entrench the emotional detachment visible in multipartner sexual practices (Stern and Buikema 2013). At the same time, however, men are challenging traditional ideas of masculine behavior by engaging in child care activities (Clark, Cotton, and Marteleto 2015; Swartz and Bhana 2009) and emotionally investing in more caring, equitable relationships with spouses and children (Enderstein and Boonzaier 2015; Sennott and Angotti 2016; Sideris 2005). Adding further nuance, Quayle et al. (2017) contend that the extent to which hegemonic masculinity can be challenged partly depends on women who actively play a role in either maintaining traditional norms or encouraging more “collective models.” These studies point to the potential for greater fluidity in gendered emotional capital, which may be reflected in shifts in the gender composition of emotional support networks.

Re-evaluating the Links between Emotional Capital and Women’s Well-being

Why should gendered emotional capital matter for women’s well-being? The buffering model posits that social support—emotional and practical—decreases stress by providing more robust coping mechanisms (Balaji et al. 2007; Brown and Gary 2007; Cohen and Wills 1985; Dietsch et al. 2011; Taylor and Roberts 1995). Emotional support, in particular, is critical to resilience in the face of chronic disadvantage (Henly, Danziger, and Offer 2005), stigmatized conditions such as HIV infection (Gielen et al. 2001), and acute illness (Berkman, Leo-Summers, and Horwitz 1992; Bloom and Spiegel 1984). However, kin relationships and female ties, in particular, can be both cooperative and conflictual (Madhavan 2001) and possibly lead to exploitation (Meillassoux 1981). A recent analysis of kinship solidarity among women in 13 countries identifies four types of solidarity ranging from “tight knit” to “detached,” recognizing the enormous variation in kin connectivity (Nauck and Becker 2013).

What is not clear is whether gender composition matters and why. Using the bargaining approach, we contend that gendered support offers both benefits and liabilities because of the transactional and dynamic nature of the process. Female-dominated networks could alleviate stress through shared experiences as women. This is less about gender essentialism and more about strategic solidarity based on sharing common circumstances. Burleson (2003) shows that women who experience many stressful situations may be more trusting of other women or generally more attuned to who can provide emotional support. Thus, in the wake of a particularly stressful event, women may be more likely to reach out to other women for emotional support. Alternatively, these same bonds among women could increase stress because of reciprocity obligations that are activated in response to chronic vulnerability. A key observation made by Stack (1974) was that, although women were often the primary source of emotional support, they also expected emotional care work by the recipient in return. Either explanation could lead to a positive association between the presence of women in one’s emotional support network and stress.

Male-dominant networks also could either minimize or decrease women’s overall stress. On the one hand, male-dominant emotional support may be reflective of isolation from women, which could increase stress. On the other hand, greater inclusion of men may buffer against stress because women may perceive more economic stability linked to traditional gender norms of men as breadwinners. In addition, women may actively pursue a more collective model in which male emotional investments may reap more stability for all. Although men’s roles as emotional support providers in this community may not yet be an accepted gender norm, it may be becoming an important component of how men and women bargain to maintain financial and emotional stability in the family economy. In other words, women who can depend on men—partners, brothers, and fathers—for emotional support may also enjoy financial stability given the continuing male advantage, albeit marginal, in the labor market. In exchange, women’s own financial contributions, which are essential for maintaining livelihoods, combined with their “gender advantage” in activating kin support, may be increasingly valued by men. Additionally, because livelihoods are so precarious, stress may be sensitive to change in gender composition of emotional support even over short periods of time.

Against this complex background, we contend that Reay’s (2004) original formulation of gendered emotional capital has limited value in understanding what emotional support networks look like and whether gender composition matters for the well-being of women. We offer an alternative that integrates Nowotny’s (1981) framework of emotional capital with models of family bargaining processes developed by feminist economists (Agarwal 1997; Folbre 1986; McElroy and Horney 1981) and economic anthropologists working in Africa (Berry 1993; Guyer and Peters 1987). This scholarship situates women within a web of relationships with close and extended kin and identifies both cooperative and conflictual dimensions. Importantly, it recognizes women’s agency in leveraging available capital—social, economic, and emotional—to promote their self-interest even if sociocultural norms explicitly seek to limit their roles. We adapt this approach to better understand the “emotional economy” of these arrangements. In doing so, we offer three key insights for advancing theory on gendered emotional capital. First, it recognizes that women draw on emotional capital from female and male kin as a form of cooperation but also that competing demands and multiple pressures (e.g., from new partners or other women) may limit the amount of emotional capital that can be received from any one kin and/or create tension. Second, this approach explicitly allows space for men through transactions in which their emotional investments are part of a collective effort to meet the various needs of kin groups. Third, it enables a more dynamic approach to emotional economies by incorporating temporal shifts in the gender composition of emotional capital over time as a response to contextual volatility. Our analysis will, therefore, address the following questions: What is the gender composition of low-income single mothers’ emotional support networks? Does the gender composition change over time or remain relatively static? If it changes, does it become increasingly female or male dominant? Are female-dominant or male-dominant networks associated with lower stress? Are changes in the gender composition associated with changes in stress over time?

Methods

Quantitative data on kin support that extends beyond the coresidential household are not typically available. It is for this reason that we undertook a project to collect data on kinship structure and support for low-income single mothers in a slum community in Nairobi, Kenya. This community is one of two that comprise the Nairobi Urban Health and Demographic Surveillance System (NUHDSS), which has been collecting demographic data on approximately 60,000 individuals three times a year since 2002 (APHRC 2014). Access to a sampling frame and a highly developed research infrastructure make the site an ideal location for our study, which was conducted in 2015–2016. We developed and administered a new survey instrument, called the Kinship Support Tree (KST), to 462 single mothers defined as not married or cohabiting at the time of interview and with at least one child under the age of seven, whom we refer to as the focal child. We conducted a second wave of data collection six months later in which we successfully retained 412 (89 percent) of the original sample. The survey was developed in close collaboration with our Kenyan colleagues to ensure cultural competence, and the survey was administered in Swahili, the main spoken language in the community.

We asked the women to enumerate close kin from the perspective of the focal child and provide demographic data on all kin. Close kin included the biological father, maternal and paternal grandparents, aunts and uncles of the child. From these kin, we further identified “potential kin” as those who were reported alive and over the age of seven and, therefore, in a position to provide support (children can provide child care support in this context). For each of these kin, we asked about the type, quantity and frequency of support provided to the mother and the focal child. We also asked questions on the role of nonkin, but it yielded only a small number of reports. We collected data on three types of support: financial, child care and emotional. This analysis is limited to emotional support, though our previous work has examined the other types of support (Clark et al. 2017). Table 1 describes the sample of single mothers at both waves.

Table 1:

Selected Sample Descriptives

	Wave 1, % (n)	Wave 2, % (n)
Stress level
Very low/low	9 (43)	14 (56)
Normal amount	62 (288)	56 (229)
Very high/high	28 (131)	31 (127)
Change in stress level
Increase		24 (99)
Same		52 (216)
Decrease		24 (97)
Physical health status
Very poor/poor	14 (64)	20 (81)
Fair	17 (79)	16 (67)
Very good/good	69 (319)	64 (264)
Age of respondents
15-24	37 (172)	34 (141)
25-29	25 (117)	26 (107)
30-34	18 (83)	18 (76)
35+	19 (90)	21 (88)
Ethnicity
Kikuyu	41 (190)	43 (179)
Luo	25 (114)	24 (97)
Kamba	8 (39)	9 (35)
Luhya	16 (72)	15 (60)
Other	10 (47)	10 (41)
Employment status
Working	85 (393)	67 (275)
Not working	15 (69)	33 (137)
Relationship to biological father of focal child
Ever married cohabitation	29 (132)	50 (204)
Ever been in informal union	42 (192)	40 (164)
Never in relationship	29 (135)	10 (43)
Missing	0.7 (3)	0 (1)
Number of children
One or two	71 (329)	66 (270)
Three or more	29 (133)	34 (142)
Potential kin (mean)	7.5	8.4
Proportion female	0.52	0.50
Proportion male	0.48	0.50
Food insecurity
Yes	81 (376)	75 (309)
No	19 (86)	25 (103)
N	462	412

Most women reported average levels of stress (62 percent and 56 percent at the two waves, respectively) but about a third reported very high levels at both waves. On change measures, just over half of all women reported no change in stress (52 percent), while the remaining 48 percent is divided evenly across increase and decrease in stress. On self-reported health, about 60 percent of respondents at both waves reported being in very good health.

Our sample is skewed toward younger ages, which would explain why most women have one or two biological children. Most of the respondents were working either part- or full-time, but in this context, work is usually limited to low-paying, highly insecure jobs in the informal economy. While there is ethnic diversity in the sample, the largest group is Kikuyu (41 percent), partly a function of their spatial proximity to Nairobi. The relationship with the child’s biological father is important for the analysis because women who have had a formal relationship with the fathers of their children may be more likely to receive emotional support from them compared to those who were in informal relationships. In Wave 1, 29 percent of respondents reported that they had been married or in a formal union with the biological father, 42 percent reported that they had been in some type of informal union, and another 29 percent reported having had no relationship. In Wave 2, the percentage of women reporting ever having been married or in a formal union with the biological father increased to 50 percent, the percentage reporting never in a union decreased to 10 percent, and the percentage in informal union remained fairly stable at around 40 percent. These changes may reflect the sample eligibility criteria in both waves—in Wave 1, women had to be single to be in the study, a condition not imposed in Wave 2. Therefore, women’s partnerships with their children’s biological fathers could have evolved into cohabiting unions or marriages over the intervening six months. There is a fairly even gender distribution within potential kin networks suggesting that it is not differences in the availability of men or women that is driving the results. Lastly, the vast majority of women in both waves (81 percent and 75 percent) reported having experienced food insecurity.

Emotional support was ascertained through responses to three statements: “You can talk to [person] about a personal issue that is bothering you”; “[Person] shares an affectionate, warm relationship with you”; and “If there is a crisis for yourself, I can count on [person] to help me.” The respondent could give one of four responses to each statement: agree, somewhat agree, do not agree, and do not know. Because very few respondents chose “do not agree” as a response to any of the statements, we developed an indicator of “strong emotional support” to define relationships for which the respondent “agreed” to all three statements. Combining these responses with the sex of the kin member, we created counts for the number of females and number of males who provide strong emotional support. These, in turn, were used to construct our main explanatory variable: gender composition of emotional support network. This is a three-category variable: female dominant (reference), male dominant, and gender parity. A female-dominant network has more women than men; a male-dominant has more men than women; and gender parity has equal numbers of women and men. While we fully recognize the difficulties of quantifying something as complex as emotional support, our approach utilized a validated measure of emotional closeness between parents and children (Driscoll and Pianta 2011) for single mothers and their kin. Furthermore, the questions were pilot tested and discussed extensively with our Kenyan counterparts to ensure internal validity, particularly after translating into Swahili.

Our analysis followed two approaches. First, we used pooled data from both waves of the study to maximize sample size (N=874) and employed logistic regression models to examine the association between gender composition of emotional support network and women’s self-reported stress level. Stress was measured using one of five responses to the question, “How would you rate your stress level?” very low, low, normal, high, and very high. To facilitate analysis, we dichotomized the outcome as high/very high stress (1) and very low/low/normal stress (0) to predict the deleterious outcome. Control variables include mother’s age, mother’s ethnicity, mother’s employment status, number of biological children, household wealth quintile, food security, mother’s relationship with the biological father of the focal child, size of the potential kin group, and survey wave. In addition, recognizing the link between stress and physical health, we included an indicator of women’s self-reported health as a continuous variable ranging from 1 (very poor health) to 5 (very good health). We used the cluster command in Stata to address the correlated standard errors of having repeated observations for the same woman.

Second, we used a multinomial logistic approach to examine the relationship between change in the gender composition of emotional support networks and change in stress for the 412 women who were in both waves of the study. The gender composition change variable includes three categories—became female dominant (referent), became male dominant, and no change. The stress change variable also includes three categories: no change (referent), decrease in stress, and increase in stress. We used the same control variables as for the first set of models but all measured at Wave 1 and also include the gender composition of emotional support network at Wave 1.

Who Provides Emotional Support and Does It Matter?

We begin this section with a picture of emotional support providers, the extent of variation in gendered support and change over time.

On average, 51 and 44 percent of potential kin in Wave 1 and Wave 2, respectively, reported providing strong emotional support to the single mothers in our sample (Table 2). When we limit the denominator to only female potential kin, these figures rise to 58.5 and 55.2 percent in the two waves, respectively. If we constrain it to male potential kin, the figures decrease to 39.8 and 32 percent. These figures provide evidence that female kin are more likely than male kin to provide strong emotional support. Not surprisingly, we also found that, on average, women tend to be overrepresented among kin who provide strong emotional support to women, though the more interesting story is in the relative weight of women’s and men’s emotional support provision. The figures for gender composition of emotional support network tell us that, in aggregate, 55 and 61 percent of women reported female dominant support groups in the two waves, respectively. At the same time, however, nearly 20 percent of women reported male dominant groups at both waves. Additionally, 15 percent of women in Wave 1 and 13 percent in Wave 2 reported gender parity in their emotional support groups. These aggregate numbers, however, mask change at the individual level over time. We found that about 20 percent of women’s emotional support networks became more female dominant and 30 percent became more male dominant. We now turn to an analysis that allows us to see whether such variation matters for stress.

Table 2:

Descriptives of Emotional Support Providers

	Wave 1	Wave 2
	Mean	Mean
Potential kin who provide strong emotional support, %	51.3	44.3
Potential female kin who provide strong emotional support, %	58.5	55.2
Potential male kin who provide strong emotional support, %	39.8	32.0
Gender composition of emotional support network	% (n)	% (n)
Female dominant	55.2 (255)	60.7 (250)
Male dominant	19.7 (91)	19.2 (79)
Equal	15.6 (72)	13.1 (54)
Missing	9.4 (44)	7 (29)

Change over waves in gender composition of emotional support network		% (n)
Became more female dominant		20.2 (83)
Became more male dominant		30 (124)
No change		26 (107)
Missing (where ratio is 0 in either wave)		23.8 (98)
N	462	412

Table 3 shows results from logistic regression models examining the relationship between gender composition of emotional support network (in three categories) and high stress. Model 2 includes a control for health to account for the correlation of health and stress.

Table 3:

Pooled Logistic Regression Results Examining the Relationship between Gender Composition of Emotional Support Network and Self-Reported Stress

	High Stress
	Model 1	Model 2
	OR (SE)	OR (SE)
Gender composition of emotional support network
Female dominant	Ref	Ref
Male dominant	0.65 (0.14)*	0.60 (0.13)*
Equal	0.57 (0.15)*	0.54 (0.14)*
Number of potential kin	1.07 (0.03)**	1.08 (0.03)**
Health status		0.70 (0.07)***
N	797	797

p < 0.05; **p < 0.01; ***p < 0.001(two tailed test).

Controls: mother’s age, mother’s ethnicity, mother’s employment status, household wealth quintile, total number of children, past relationship with biological father of focal child, food insecurity, survey wave, and number of potential kin.

The results show that, compared to having a female-dominant network, having a male-dominant emotional support network decreases the odds of reporting high stress by 35 percent. In other words, having more men relative to women appears to mitigate stress even after controlling for health (Model 2), which has the expected negative effect. Moreover, having a gender parity network is also beneficial, with a 43 percent decrease in the odds of reporting high stress compared to having a female-dominant group. There is no difference between the male-dominant and gender-parity categories (results not shown). Also, it is notable that the greater the number of potential kin to draw on for emotional support, the higher the stress.

Taken together, these results underscore the need to consider gendered emotional capital as a function of financial exigencies and changing gender norms, both in domestic and public spheres. Moreover, given the precarity of economic and physical life in low-income urban communities, the relationships and effects we are attempting to measure are likely to vary significantly over even short periods of time. It is to this that we now turn. Table 4 shows results of multinomial models relating change in the gender composition of emotional support networks with change in stress. The sample size of 346 reflects missing data from either wave for 66 women.

Table 4:

Multinomial Regression Results Examining the Relationship between Change in Gender Composition of Emotional Support Network and Change in Self-Reported Stress

	Change in Stress
	Increase vs. Same	Decrease vs. Same
Change in gender composition of emotional support network	RR (SE)	RR (SE)
Became female dominant	Ref	Ref
Became male dominant	0.47 (0.27)	0.29 (0.21)
No change	0.65 (0.30)	0.37 (0.22)
Gender composition of emotional support network (Wave 1)
Female dominant	Ref	Ref
Male dominant	0.50 (0.21)	0.21 (0.11)*
Equal	0.50 (0.24)	0.09 (0.07)**
N	346	346

p < 0.05; **p < 0.01; ***p < 0.001(two tailed test).

These results suggest that change in stress in either direction is not sensitive to change in gender composition of emotional support networks at least over a six-month period. The lack of any effects is likely attributable to the variable construction and the length of the interval. The compositional change variable collapsed different types of shifts into the same category to ensure adequate sample sizes for analysis. For example, moving from gender parity to female-dominant and from male-dominant to female-dominant are both subsumed under one category, which may be muting any effects across categories. Six months may be too short a period to detect change in stress. Therefore, it is likely premature to claim that shifts in gender composition of emotional support networks have no effect on change in stress level. In ancillary analysis (not shown), we found that a decrease in the proportion female of emotional support providers is associated with an increase in stress. This suggests that while maintaining a female-dominant emotional support group may exacerbate stress (Table 3), the loss of one of these women may be even more stressful. The significant effect of the gender composition in emotional support provision at Wave 1 is likely attributable to selection effects such that women who start off with low stress and male-dominant/gender parity groups are unlikely to report even further reduction in stress.

Conclusion

This article addresses an understudied topic in a non-western context: the gender composition of emotional support and its impact on women’s well-being in urban Kenya. Given the profound social transformation underway in contexts such as Kenya and the tenuous link to stable employment that characterize the lives of the urban poor, there is likely to be a complex process of adjustment to new expectations for both women and men with implications for women’s well-being. On a descriptive level, we found that while women still dominate emotional support provision, there is notable variation in what gendered emotional capital looks like. About one-third of respondents report having male-dominant or gender-parity emotional support networks. We also found change in the gender composition of emotional support networks, with a trend toward higher levels of male involvement over a six-month period. Our regression results show that women who have male-dominant or gender-parity emotional support groups have lower stress than their counterparts with female-dominant groups. Put simply, men as emotional support providers benefit women, at least as measured by stress. However, the relationship does not hold for decreasing stress over time.

Conceptually, this analysis makes some key contributions. First, theories of emotional capital need to allow space for men driven by both necessity and changing norms about gender. In this sense, our work is an attempt to move away from essentializing gender, though it is likely that the Kenyan context entails less volition on the part of men than the male nurses in Cottingham’s (2016) study described earlier in the paper. Second, the roles of women and men as purveyors of emotional capital within the context of an extended family arrangement need to be approached differently from their roles in a nuclear family arrangement. The findings are suggestive of a dynamic marked by bargaining among women and men that entails costs and benefits to both, rather than a strict division of gendered labor contributions. On one hand, as evidenced by our results for stress, women may stand to gain from men’s increased visibility as emotional support providers in exchange for the benefits that men derive from women’s income generation and social connections. On the other hand, women who have recently experienced a stressful event may seek out more emotional support from other women. Because there are no dates or temporal ordering of events in this model. However, our finding that higher levels of stress are associated with large potential kin networks undermines this interpretation. Instead, it suggests that women’s reciprocal obligations with other female kin may induce additional stress. While we did not collect data on reciprocal support provision, it is likely that mutual expectations of support sustain anxiety, particularly when expectations are not met. For men, new demands placed on them may affect their well-being, something we did not examine in this analysis. Finally, the analysis has underscored the fluidity of gendered emotional capital and the need to incorporate a dynamic component to further theoretical development.

On a practical level, these findings suggest a more nuanced approach to understanding the benefits and liabilities of bringing women together in organizations such as “burial societies”—indigenous savings associations—that operate in a number of African countries to promote women’s empowerment and well-being. Whereas poor women likely welcome the access to a financial safety net through the pooling of resources and emotional support, they have to assume responsibility for comaintaining the emotional economy; in some cases, this may increase stress. Moreover, it is relevant to note that men’s visibility in the domestic sphere, and in particular, fathering, is being promoted by government legislation in Kenya (e.g., mandatory child support payments) but also by men themselves who want their paternal rights recognized when unions dissolve. It is far too soon to tell whether such efforts strengthen emotional linkages and whether such connections yield benefits for women, men, and children. Future research should incorporate qualitative approaches to uncover the complex interplay of gendered obligations, policy shifts, and macro-level change. Such work could also explore how women and men understand the value of emotional capital and their respective roles in providing and receiving it. In closing, we suggest that the focus on the gendered dimensions of emotional capital offers a unique opportunity to appreciate the challenges that low-income women face in maintaining reliable social support in contexts in which relationships between women and men are continuously tested in response to economic and social volatility.

Footnotes

Authors’ Note:

We are grateful to Laura Carpenter and Nicole Angotti for providing valuable feedback on earlier drafts. We are indebted to our interviewer team in Nairobi, Kenya, for data collection. This project was funded by a grant from the Eunice Shriver National Institute of Child Health and Human Development (1R21-HD078763-01A1).

Sangeetha Madhavan is an associate professor of African American studies and sociology and associate director of the Maryland Population Research Center at the University of Maryland, College Park. Her research interests include family structure and change, parenting and children’s well-being in Africa.

Shelley Clark is the James McGill Professor of Sociology and director of the Centre on Population Dynamics at McGill University. Her research focuses on gender, health, family dynamics, and life course transitions in sub-Saharan Africa.

Yuko Hara is a doctoral student in sociology at the University of Maryland, College Park. Her research focuses on gender and family issues, reproductive health, and well-being.

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