Sharing the Burden of the Transition to Adulthood: African American Young Adults’ Transition Challenges and Their Mothers’ Health Risk

Ashley B Barr; Leslie Gordon Simons; Ronald L Simons; Steven R H Beach; Robert A Philibert

doi:10.1177/0003122417751442

. Author manuscript; available in PMC: 2021 Jul 21.

Published in final edited form as: Am Sociol Rev. 2018 Jan 10;83(1):143–172. doi: 10.1177/0003122417751442

Sharing the Burden of the Transition to Adulthood: African American Young Adults’ Transition Challenges and Their Mothers’ Health Risk

Ashley B Barr ^a, Leslie Gordon Simons ^b, Ronald L Simons ^b, Steven R H Beach ^b, Robert A Philibert ^c

PMCID: PMC8294643 NIHMSID: NIHMS1713572 PMID: 34294941

Abstract

For many African American youth, the joint influences of economic and racial marginalization render the transition to stable adult roles challenging. We have gained much insight into how these challenges affect future life chances, yet we lack an understanding of what these challenges mean in the context of linked lives. Drawing on a life course framework, this study examines how young African Americans’ experiences across a variety of salient domains during the transition to adulthood affect their mothers’ health. Results suggest that stressors experienced by African Americans during the transition to adulthood (e.g., unemployment, troubled romantic relationships, arrest) heighten their mothers’ cumulative biological risk for chronic diseases, or allostatic load, and reduce subjective health. These results suggest that the toll of an increasingly tenuous and uncertain transition to adulthood extends beyond young people to their parents. Hence, increased public investments during this transition may not only reduce inequality and improve life chances for young people themselves, but may also enhance healthy aging by relieving the heavy burden on parents to help their children navigate this transition.

Keywords: transition to adulthood, allostatic load, subjective health, African Americans, stress contagion, life course

A growing and increasingly rigorous literature documents the deleterious effect of psychosocial stress on health. To date, a variety of chronic stressors, including racial discrimination (Lewis et al. 2010), neighborhood disadvantage (Bellatorre et al. 2011; Do et al. 2007), economic hardship (Simons et al. 2016), incarceration (Massoglia and Pridemore 2015; Schnittker and John 2007), and relationship discord (Hostinar 2015; Miller et al. 2013; Robles and Kiecolt-Glaser 2003), have been shown to increase vulnerability to chronic diseases of aging (CDAs). Such vulnerability manifests in both prevalence and onset of CDAs and CDA precursors, like biomarkers of inflammatory and cardiovascular risk, and excess mortality (Beatty Moody et al. 2014; Brody et al. 2015; Kelly and Ismail 2015; Kiecolt-Glaser and Glaser 1999; Miller et al. 2009; Richardson et al. 2012).

Because many of the psychosocial stressors linked to impaired health are more common in the lives of African Americans than in those of their white counterparts (Broman 2005; Chou, Asnaani, and Hofmann 2012; Clark et al. 1999; Pettit and Western 2004; Pew Research Center 2016; Williams 2012), it is not surprising that African Americans suffer a health disadvantage. Relative to other racial/ethnic groups, African Americans experience earlier onset and higher prevalence of cardiovascular disease, type 2 diabetes, and dementia (see Williams 2012) and suffer from higher rates of morbidity and mortality related to these CDAs (Cherrington et al. 2012; Hartley 2004). As Geronimus and colleagues (2006:826) argue, these health disparities are “a consequence of the cumulative impact of repeated experience with social or economic adversity and political marginalization.” In other words, navigating the mundane environmental stress (Carroll 1998; Peters and Massey 1983) of being black in the United States is taking a toll on African American bodies, so much so that racism has been characterized as a fundamental cause of health disparities (Phelan and Link 2015).

We have made great strides in understanding the extent to which and the mechanisms whereby psychosocial stress gets under the skin, weathering physiological as well as psychological systems and ultimately manifesting in CDAs (see, e.g., Brody, Lei, Chae, et al. 2014; Brody, Lei, Chen, et al. 2014; Chen et al. 2013; Geronimus et al. 2006). Differences in the experience of psychosocial stress help explain inequalities in unhealthy aging between racial/ethnic groups (Phelan and Link 2015; Williams 2012) and heterogeneity in the aging process within racial/ethnic groups (Simons et al. 2016). Despite these developments, this research has been largely constrained by an individualistic understanding of stress and its health effects. Life course development, and therefore healthy aging, is not merely an intra-individual process, however. Rather, as suggested by life course theory and its foundational principle of linked lives (Elder 1985, 1998), we live our lives interdependently and therefore must study them as such (Settersten 2015). Hence, a life course approach implores us to broaden our understanding of the stress-health relationship to include stress contagion, or the transfer of stress across individuals (Pearlin et al. 2005; Thoits 2010; Waters, West, and Mendes 2014), and its implications for health.

Scholars have rarely considered contagion effects when explaining individual or group differences in healthy aging. For U.S. parents, however, a potentially important and overlooked source of stress contagion may be the challenges faced by their offspring during the transition to adulthood. This may be especially true for parents of African American children, for whom the transition to stable adult roles has become particularly tenuous. The increasingly extended and uncertain transition to adulthood in the United States (Furstenberg 2010; Settersten and Ray 2010a, 2010b), particularly for African American youth (Corcoran and Matsudaira 2008), implores us to open our line of inquiry beyond understanding the effects of this transition on young people themselves. We must begin to understand whether the challenges experienced by young adult children proliferate to the parents, who are so often held responsible for ensuring children’s successful transition to adult roles. This study takes up this task by drawing on a life course framework—embedding linked lives within the sociohistorical context of an extended and unequal transition to adulthood—to examine the extent to which the challenges experienced by African American young adult children serve as a source of stress contagion, affecting their mothers’ health. The failure to consider such contagion effects may underestimate the impact of growing inequality and limited public support across the transition to adulthood and restrict our conceptualization of salient stressors at midlife.

THE TRANSITION TO ADULTHOOD AMONG AFRICAN AMERICANS

The changing nature of the transition to adulthood in the United States has sparked much research. Young people today take longer than in the past to meet the traditional markers of adulthood, such as leaving home, getting married, and finding a stable job (Furstenberg 2010; Settersten and Ray 2010b). For many African American young people, the joint influences of economic and racial marginalization render the transition to stable adult roles particularly challenging. Across domains that are salient during the transition to adulthood (e.g., identity development, educational and vocational pursuits, and romantic relationships [Arnett 2014; Roisman et al. 2004; Schulenberg, Bryant, and O’Malley 2004; Settersten and Ray 2010a]), African Americans experience marked challenges.

For instance, young African Americans are more likely than any other racial/ethnic group to be disconnected from the social institutions of school, work, and military (DeLuca, Clampet-Lundquist, and Edin 2016; Settersten and Ray 2010a, 2010b), to experience inconsistent employment (Danziger and Ratner 2010), and to have been imprisoned or involved in the juvenile justice system (Osgood et al. 2005; Pettit and Western 2004; Raphael 2007). African Americans are the most likely group to undertake parenting outside of a marital relationship (Child Trends 2015), and some studies find they are more likely than their white counterparts to experience more hostile and less supportive romantic relationships (Halliday Hardie and Lucas 2010; Kurdek 2008; for an exception, see Halpern-Meekin et al. 2013). Finally, African Americans report higher levels of everyday discrimination than do other racial/ethnic groups (Chou et al. 2012; Clark et al. 1999; Doherty 2013), and the transition to adulthood presents opportunities for new and more intense exposure to racism and discrimination through interactions with adult institutions (Brody et al. 2006; Gee, Walsemann, and Brondolo 2012; Hardaway and McLoyd 2009; Hope, Hoggard, and Thomas 2015).

Not only do these challenges cut across salient domains during the transition to adulthood, but they also intersect with one another such that challenges in one domain may beget challenges in another. For example, racial discrimination presents challenges for establishing a positive self-concept (Kogan et al. 2015), educational pursuits (Cabrera et al. 1999; Johnson et al. 2014), labor market opportunities (Gaddis 2015), romantic relationships and parenthood (Doyle and Molix 2014), and steering clear of the criminal justice system (Burt, Simons, and Gibbons 2012; Hope et al. 2015; Unnever, Cullen, and Barnes 2016). Similar intersections during the transition to adulthood have been noted between romantic relationships and education (Schmidt and Lockwood 2015), educational pursuits and criminal justice involvement (Kirk and Sampson 2013), criminal justice involvement and labor market opportunities (Pager 2003), and so on.

A burgeoning literature documents the vast differences in resources and support among young people before and during the transition to adulthood and the impact of experiencing these intersecting challenges on future life chances (DeLuca et al. 2016; Furstenberg 2010; Osgood et al. 2005; Settersten and Ray 2010b; Silva 2012). This research clearly illustrates that, in many ways, disparate experiences during the transition to adulthood are an extension of inequalities found earlier in life (Alexander, Entwisle, and Olson 2014). Poor and working-class youth, for instance, often lack the social, cultural, and economic capital that their middle- and upper-class peers draw on to facilitate the expansion of human capital or to withstand setbacks during the transition to adulthood (Silva 2012). This literature also suggests, however, that the transition to adulthood has become an important fulcrum in the life course, directing some young people on trajectories of increasing advantage and others on trajectories of increasing disadvantage (DeLuca et al. 2016; Furstenberg 2008, 2010; Settersten and Ray 2010a). That is, the importance of the transition to adulthood for modifying (or solidifying) life course trajectories—for better or for worse—has seemingly grown.

STRESS PROLIFERATION, STRESS CONTAGION, AND LINKED LIVES DURING THE TRANSITION TO ADULTHOOD

Our attention to inequalities in the experience of the transition to adulthood, and our growing understanding of the ways these experiences are linked to earlier and later life stress, has been guided by a stress proliferation framework (Pearlin, Aneshensel, and Leblanc 1997; Pearlin et al. 2005), although not always explicitly. For instance, as indicated earlier, research has linked early experiences of stress exposure to intersecting inequalities during the transition to adulthood (e.g., Fomby and Bosick 2013; Gonzales 2011; Kirk and Sampson 2013; Osgood et al. 2005; Raphael 2007; Silva 2012) and has linked these inequalities to later life chances (Arditti and Parkman 2011; Armstrong and Hamilton 2015; Napolitano 2015; Pew Research Center 2014; Settersten and Ray 2010a). Such work exemplifies two processes central to a stress proliferation framework, that of stress during one period leading to the accumulation of stress across the life course (Umberson et al. 2014), and that of stress in one domain giving rise to stress in another, also known as stress spillover (Carr and Umberson 2013). Hence, the stress proliferation framework central to studies of health is also fundamental to the study of the transition to adulthood. This proliferation, however, has been conceptualized and evaluated largely as an intra-individual process, with stress proliferating either across the life course or across salient domains during this period.

Despite much research on stress proliferation, we lack an understanding of the implications of an extended, uncertain, and high-stakes transition to adulthood in the context of linked lives. This is because the stress proliferation literature has, until recently, largely ignored the notion that stress may also proliferate across individuals, a process known as stress contagion, stress transfer, or stress crossover (Carr and Umberson 2013; Wethington 2000). In reference to caregiver stress, for example, Pearlin and colleagues (2005:213) note that this stress “can also come to penetrate the lives of others.” Such a relational understanding of stress is consistent with the life course notion that lives are lived interdependently, and it compels the study of stress to expand beyond one of intra-individual effects. Scholars have found the inter-individual proliferation of stress—which we will call stress contagion to distinguish it from the intra-individual proliferation of stress—in a variety of relationships. For example, stress, and in some cases its health implications, has been shown to spread from mothers to infants (Waters et al. 2014), across romantic partners (Engert et al. 2014; Rook, Dooley, and Catalano 1991; Trail et al. 2012), from teachers to students (Oberle and Schonert-Reichl 2016), and from parents to adult offspring (Turney 2014). Given this evidence of stress contagion, particularly in family relationships, Thoits (2010:S45) definitively argues that “stress can proliferate across generations” and insists that “[o]ne of the most important relationships, of course, is that between parents and children.”

Mechanisms of Stress Contagion during the Transition to Adulthood

Consonant with the notion of stress contagion, the challenges encountered by young adult children may yield implications not only for their own lives but also for the health and well-being of their aging parents. How might this be the case? Although the mechanisms of stress contagion in general, and from young adult children to parents in particular, receive less attention than the presence of the effects, the literature thus far points to several possible and plausibly intertwined pathways whereby challenges faced by young adult children might impair their parents’ health. As Wethington (2000) frames them, these include shared fate, obligations, and commitments.

Shared fate refers to the parental stress that may arise via passive exposure to young adult children’s challenges. Because parents and young adult children may share networks, households, and responsibilities, young adult challenges may reverberate across families by requiring family members to adjust their roles or by affecting family functioning. For instance, young adult children’s challenges may impair the parent-child relationship (or that of other family members) and reduce parenting satisfaction. Relationship satisfaction with family members promotes health by reducing the impact of stress and offering meaning and purpose (Umberson and Montez 2010). Parental relationships with young adult children, particularly children perceived as not making progress on the road to adulthood, are marked by ambivalence (Fingerman et al. 2006; Fingerman, Cheng, Tighe, et al. 2012). This relationship strain may, in turn, tax parental health.

Another form of shared fate posits a more direct pathway linking young adult challenges to parental health. This pathway assumes that young adult challenges induce physiological or psychological distress in young people themselves, and that this distress is directly transferred to parents via affective or physiological coregulation, also known as synchrony. Research on romantic partners shows that “partners’ affective states fluctuate in synchrony or as a function of each other” (Schoebi 2008:596) as a result of conscious or unconscious processes. Other research shows a similar coregulation effect with physiological states across attachment relationships (Sbarra and Hazan 2008), including those between romantic partners (Ferrer and Helm 2013; Saxbe and Repetti 2010; Timmons, Margolin, and Saxbe 2015), mothers and infants (Waters et al. 2017), and parents and adolescent children (Saxbe, Del Piero, and Margolin 2015). As Fingerman, Cheng, Tighe, and colleagues (2012:59) note, today “parents and [young adult] offspring are highly involved in one another’s lives,” perhaps increasing the potential for both affective and physiological coregulation in response to young adult challenges.

The second pathway is that of obligation, or an increased burden of support. Parental support—both instrumental and emotional—for young adult children has increased over time as the transition to adulthood has extended further into the life course (Fingerman, Cheng, Tighe, et al. 2012; Fingerman, Cheng, Wesselmann, et al. 2012; Hartnett et al. 2013). This support includes housing, financial assistance, emotional support, and advice-giving. Importantly, parents offer more support to young adult children who are struggling on the road to adulthood and less support to children making greater headway (Swartz et al. 2011). Much like caregiver stress takes a toll on health (Bennett, Fagundes, and Kiecolt-Glaser 2013; Bennett and Leggett 2017; Son et al. 2007), giving support to struggling children may tax economic and socioemotional coping resources, thereby serving as its own health-deteriorating stressor for parents (Fingerman et al. 2015).

A third pathway—that of commitment or investment—posits that young adult children’s challenges may induce distress in parents by invoking additional worry and rumination about future life chances. The transition to adulthood is already a source of worry for parents, and African American parents report more worry for their young adult children than do their white counterparts (Hay, Fingerman, and Lefkowitz 2007, 2008). Having a child who is experiencing real or perceived difficulty on the path to adulthood would reasonably tap into parents’ emotional investment in their children and compound this worry. Importantly, worry enhances both physiological and psychological distress (Brosschot 2010; Brosschot, Gerin, and Thayer 2006; Brosschot, Verkuil, and Thayer 2010).

No matter the mechanism, the phenomenon of stress contagion during the transition to adulthood may be uniquely salient in the United States, due to an entrenched ideology of intensive mothering and limited public investments in young people’s transitions to adulthood. As Hays (1998:22) argues, “the history of ideas about child rearing in the United States is … a story of the increasing intensification of child rearing,” such that mothers are expected to make substantial time, money, energy, emotional, and identity investments in raising their children. Although there is variation in the extent to which mothers are able to enact intensive mothering practices, research suggests this intensive mothering ideology spans race and social class groups (Blair-Loy 2009; Elliott, Powell, and Brenton 2013; Hays 1998; Lareau 2011). Fathers, however, are relatively protected from this ideology (Shirani, Henwood, and Coltart 2012). A context of intensive mothering may exacerbate all of the noted mechanisms of stress contagion. For instance, with respect to commitment and investment, mothers may be invested in enhancing their children’s life chances and in sustaining their own identity as a good mother, thereby potentially compounding the worry and stress of transition challenges. Coupled with this ideology of intensive mothering, the United States relies on parents more heavily than do other developed countries to guide and assist children through the transition to adulthood (Furstenberg 2010; Schulenberg and Schoon 2012). This may be the case for African American families, in particular. Given historical and contemporary structures of racial inequality, young African Americans experience a fundamentally more challenging transition to adulthood than do other racial/ethnic groups. Moreover, African American mothers must help their children navigate through this “hostile environment” (Collins 1990) while being, on average, less equipped than their majority counterparts with the human, social, and economic capital (Richard 2014; Wang and Parker 2014) that enables some parents to serve as effective “safety nets and scaffolds” (Swartz et al. 2011).

Contextualizing Stress Contagion

Research examining the intra-individual effects of stressors on health shows that these effects are not uniform. Rather, individual and contextual characteristics may amplify or buffer individuals from the health consequences of stress (Birditt, Newton, and Hope 2014; Pauley, Floyd, and Hesse 2015; Thoits 2010). Hence, the effects of stress contagion on maternal health may vary systematically. In particular, with respect to the transition to adulthood, some work suggests that both the experience of transition challenges and their real or perceived stakes for the remainder of the life course may vary by child gender and the timing of such challenges (i.e., whether young people experience challenges earlier or later in the transition to adulthood). Stress contagion may vary along these dimensions, as well.

Given that the transition to adulthood has been extended more generally (Arnett 2014; Settersten and Ray 2010a), parents expect some degree of difficulty and uncertainty during this transition. In fact, parents are ready and willing to help as their children embark on the road to adulthood (Fingerman, Cheng, Tighe, et al. 2012; Fingerman, Cheng, Wesselmann, et al. 2012; Fingerman et al. 2015). As young people move through the transition to adulthood, however, parents may expect children’s difficulties and their need for assistance to diminish (Hartnett et al. 2013). If it does not, parents may perceive these difficulties as “off-time” and believe they have a dwindling opportunity to correct trajectories and avoid deleterious long-term outcomes. The importance of the timing of transitions and stressors is central to a life course perspective (Elder 1998; Pearlin et al. 2005; Wheaton and Clarke 2003). Research suggests that off-time stress is more disruptive than on-time or normative stress (Carr 2014; Carr and Umberson 2013; George 1993; Stroebe et al. 2007; Wheaton and Clarke 2003; Wickrama et al. 2003). To the extent that parents perceive challenges faced by young adult children later in the transition to adulthood as off-time, less normative, or more consequential for life chances, hardship experienced later in the transition to adulthood may have more pronounced consequences for maternal health than challenges experienced earlier.

Difficulty experienced by young men versus young women might also be perceived differently by their parents, resulting in different implications for parental health. For African American parents, helping or preparing to navigate a child’s transition to adulthood means not only navigating the hostile environment of racism but also that of gendered racism (Collins 1990, 2005; Crenshaw 1991; Crenshaw, Ocen, and Nanda 2015; Dow 2016). These intersecting inequalities manifest during the transition to adulthood in different experiences for African American young men and women. African American young men, for instance, are more likely than their female counterparts to be disconnected from school and work (Bureau of Labor Statistics 2016; Lopez and Gonzalez-Barrera 2014; Ryan and Bauman 2016; Settersten and Ray 2010b) and to experience discrimination and negative police encounters (Najdowski, Bottoms, and Goff 2015; Ryan and Bauman 2016). These inequalities also manifest, however, in how African American parents view the implications of racism for their sons’ and daughters’ life chances. Although African American mothers worry about their girls growing up amid endemic racism, African American girls often have an extended woman-centered network of “othermothers” and kin to offer support, guidance, and a “wider range of models of Black womanhood” (Collins 2015:321). Hence, mothers’ worries for their daughters tend not to be as dire as their worries for their sons. As one African American mother stated in interviews with Dow (2016:162), “I think it is hard to be a black girl and a black woman in America, but I think it is dangerous and sometimes deadly to be a black boy and a black man.”

This gendered lens through which African American mothers view the consequences of racism and their control over these consequences in their children’s lives stems from the need to contend with the controlling image of the “thug” (Collins 1990; Dow 2016). Elliott and Aseltine (2012) point out that African American mothers’ concern for their boys’ well-being centers on criminality, both their actual risk of engaging in criminal behavior and their risk of being criminalized by other people and important institutions. Challenges across salient domains during the transition to adulthood, including troubled romantic relationships, disengagement from school or work, and racial discrimination, do indeed place young men at risk of engaging in criminal behavior (Backman 2017; Barr and Simons 2015; Burt and Simons 2015; Thornberry and Christenson 1984). Transition challenges might also contribute to the “symbolic liability” (Dow 2016) of African American male bodies, no matter youths’ actual criminal behavior, thereby reifying stereotypes of black male criminality and placing young men at risk of facing the potentially deadly consequences of these stereotypes. As Crenshaw and colleagues (Crenshaw 1989; Crenshaw et al. 2015), Collins (1990, 2005), and other intersectional feminist scholars (Morris 2016; Wun 2014) have argued, this general sense of African American boys and men suffering more noxious consequences from racism than African American girls and women is misguided in many ways, and is itself a product of gendered racism. This view often leads to the exclusion of women’s and girl’s experiences and further reifies the perceived gender difference in the costs of racism. Nonetheless, to the extent that young men’s challenges across the transition to adulthood, even if of the same type or degree as young women’s, are perceived by parents as more dismal and more consequential for life chances, stress contagion in parent-son relationships may be greater than that in parent-daughter relationships.

THE CURRENT STUDY

In the current study, we consider what an extended, uncertain, and often tenuous transition to adulthood for African Americans means in the context of linked lives. More specifically, we use longitudinal data from a sample of several hundred mothers of African American, young adult children (hereafter referred to as YACs) to evaluate how challenges experienced by these YACs during the transition to adulthood are associated with their mothers’ health. We assess how this stress contagion varies as a function of YACs’ gender and age.

Over the past few decades, the flood of research on the changing nature of the transition to adulthood has drawn several relevant and important conclusions. First, young people today experience an extended and more complicated transition to adulthood than did previous generations (Settersten and Ray 2010a, 2010b). Second, in the United States, much of the responsibility for ensuring a successful transition to stable adult roles falls on parents, both culturally and with respect to public policy (Hays 1998; Schoeni and Ross 2005; Settersten 2008). Third, African American young people appear to be uniquely disadvantaged in the transition to adulthood, and their parents have fewer of the resources necessary to cast a wide safety net (Corcoran and Matsudaira 2008). Finally, the transition to adulthood appears to be increasingly important for future life chances; that is, its trajectory-modifying potential has grown (Pew Research Center 2014; Settersten and Ray 2010a). Taken together, these realities suggest that the transition to adulthood may have implications not only for the health and well-being of young adults themselves, but also for their aging parents. African American parents, who already suffer from higher prevalence and earlier onset of chronic diseases of aging than do their white counterparts, may be particularly susceptible (Geronimus et al. 2006; Williams 2012).

Consonant with this logic, we hypothesize that challenges facing African American young adults across a variety of salient domains during the transition to adulthood will predict worse health among mothers, independent of parent, youth, and family factors, that may make the transition to adulthood more difficult and impair mothers’ health (Hypothesis 1). Furthermore, consistent with research indicating that off-time stressors are more disruptive than on-time stressors (e.g., Carr 2014; George 1993; Stroebe, Schut, and Stroebe 2007), we expect transition challenges experienced by older YACs will be more detrimental for mothers’ health than will challenges experienced by younger YACs, as they may be deemed less normative and more harmful for future life chances (Hypothesis 2). Finally, we do not hypothesize a gender difference in the association between young adult transition challenges and mothers’ health, but we do test for potential gender differences given research suggesting that the consequences of racism for young men are often (mis)perceived (e.g., Collins 2005; Crenshaw et al. 2015) to be greater than those for young women (Dow 2016).

In testing these hypotheses, we expand existing research in several ways. First, we use multiple indicators of health that help balance each other’s limitations. One measure—allostatic load—is a biological composite indicative of cumulative biological risk for chronic diseases of aging (Brody, Lei, Chen, et al. 2014; Geronimus et al. 2006; McEwen 2000; McEwen and Seeman 2009; Seeman et al. 2001; Slopen et al. 2014). Allostatic load provides an index of multisystemic wear and tear on the body while avoiding the bias inherent in self-reported measures of health (Grol-Prokopczyk, Freese, and Hauser 2011; Zajacova and Dowd 2011). Unlike this biomarker measure, however, our self-reported measures of health—psychological distress and self-rated health—are measured at multiple time points and therefore allow more sophisticated analytic techniques to establish proper time ordering. Together, our biomarker and self-report measures offer a fuller understanding of health and health risk in response to YAC challenges during the transition to adulthood. Second, we capitalize on the longitudinal nature of the survey data to control for a wide range of family, mother, neighborhood, and YAC factors that may account for selection into a more difficult transition to adulthood or endogeneity between mothers’ health and YAC experiences. Third, we draw on multiple reporters—mothers, YACs, and objective biomarkers of health, thereby reducing the same-reporter bias that plagues survey research (Podsakoff et al. 2003). Along with the ability to assess selection factors across a variety of contexts, this enhances our confidence in stress contagion. Finally, our focus on African American families foregrounds individuals at greater risk for poor health outcomes and a difficult transition to adulthood, while simultaneously examining and acknowledging often overlooked within-group heterogeneity in these outcomes and experiences (Bryant et al. 2008).

DATA AND METHODS

Sample

Data for this study come from Waves 4 through 6 of the Family and Community Health Study (FACHS). FACHS began in 1997 as an investigation of neighborhood and family effects on the development of African Americans living in Iowa and Georgia. Upon recruitment, families had a 5th grader in the public school system and were drawn from a variety of communities within each state, differing on racial composition and economic level, so as to capture heterogeneity among African American families (for detailed sampling procedures, see Simons and Burt 2011; Simons et al. 2011). The first wave of FACHS contained 889 African American 5th graders, their primary caregivers (mostly mothers), and other family members (siblings and secondary caregivers) when present in the home. The fourth, fifth, and sixth waves of data, those utilized here, were collected from 2004 to 2005, 2007 to 2008, and 2010 to 2011, respectively, with the target children (here referred to as young adult children, or YACs) averaging about 19 years of age at Wave 4, 22 years at Wave 5, and 24 years at Wave 6. As indicated elsewhere (Barr, Culatta, and Simons 2013), these young African Americans are similar to a national sample of African Americans on educational and family measures (e.g., educational attainment and fertility). These youths’ maternal caregivers, the focus of the current study, averaged about 44 years of age at Wave 4, 46 years at Wave 5, and 49 years at Wave 6. Early waves of data collection emphasized youth deviant behavior and mental health, but Wave 5 of FACHS included biomarkers of health for caregivers to better understand how psychosocial and contextual stressors across the life course affect healthy aging and risk for chronic diseases of aging (Lei et al. 2015; Simons et al. 2016).

Wave 4 of FACHS, the start point for the current study, contains data from 720 primary caregivers.¹ Of these, 629 were biological or adoptive mothers, and hence the focus of the current study. Of these 629 mothers, 575 were reinterviewed at Wave 5 and were asked to complete a blood draw, height and weight assessments, and blood pressure assessments. In total, 414 mothers completed the nonintrusive assessments, and 393 completed the blood draw. In the analyses presented here, our final sample size varies by outcome. For analyses assessing subjective health (i.e., psychological distress and self-reported health), we use the full sample (N = 629). For those assessing biological risk (i.e., allostatic load), we use only the mothers for whom we had successful measurement of all biomarkers included in the allostatic load index (N = 382). Importantly, analyses indicated that the group of mothers who participated across waves did not differ significantly from those who did not participate across waves with regard to age, education, number of children in the household, or presence of a secondary caregiver. Furthermore, mothers who consented to blood draws did not differ in measurable ways from those who did not consent.

Dependent Variables

Allostatic load.

Health risk across multiple bodily systems (e.g., immune and cardiovascular) tends to co-occur in response to environmental stress (Danese and McEwen 2012; Hotamisligil 2006). Such multisystemic risk—or cumulative wear and tear on the body—is called “allostatic load” (Juster, McEwen, and Lupien 2010; McEwen 2003; Seeman et al. 1997; Szanton, Gill, and Allen 2005) and can be used to predict morbidity, acute subclinical conditions, and mortality (Danese and McEwen 2012; Duru et al. 2012; Karlamangla, Singer, and Seeman 2006; Seeman et al. 2001; Seeman et al. 1997). Consonant with past work on allostatic load, we constructed an allostatic load index using six biomarkers, all assessed at Wave 5, that span immune, cardiovascular, and endocrine systems and thus offer a snapshot of mothers’ overall biological risk. These biomarkers include body mass index (BMI) and resting systolic and diastolic blood pressure to assess cardiovascular risk, glycated hemoglobin (HbA1c), an indicator of diabetes risk and metabolic control, and two measures of inflammatory risk, C-reactive protein (CRP) and Soluble IL-6 receptor (sIL-6R). Because HbA1c, CRP, and sIL-6R displayed a skewed distribution (skewness > 1.5; kurtosis > 8), we used a log transformation to normalize the distribution (Cohen and Cohen 1983). We then combined each biomarker into an allostatic load index by summing the number of biomarkers for which the participant scored in the top quartile of risk for the sample, a process known as the elevated-risk zone method (Singer et al. 2004). The resulting index ranged from 0 to 5, as nobody was high risk on all six indicators. Roughly 70 percent of mothers in the analysis were high risk on at least one biomarker.

Self-reported poor health.

Unlike the biomarker assessments, we assessed self-reported health across multiples waves (Waves 4 through 6). At each wave, mothers rated their general health (“In general, would you say your health is…”) from 1 “excellent” to 5 “poor.” To be consistent with other measures of health risk, response options were left intact so that higher values indicated worse health, or increasing health risk. Mean scores on self-reported poor health ranged from 2.75 (SD = .953) at Wave 4 to 2.96 (SD = .933) at Wave 6. As we will describe in the plan of analysis, Wave 4 assessments of self-rated health, which occurred at the beginning of YACs’ transition to adulthood, served as control variables in all models, and Waves 5 and 6 assessments served as outcomes in longitudinal models.

Psychological distress.

We assessed psychological distress across Waves 4 through 6. At each wave, mothers answered five questions asking how much during the past week (1 “not at all” to 3 “extremely”) they felt depressed, discouraged, hopeless, like a failure, and worthless. Items were averaged to form an index of psychological distress (α = .82). Mean scores on psychological distress ranged from 1.276 (SD = .366) at Wave 4 to 1.262 (SD = .352) at Wave 6. As with measures of self-rated health, Wave 4 assessments of psychological distress served as control variables in all models, and Waves 5 and 6 assessments served as outcomes in longitudinal models.

Primary Independent Variable

Young adult children’s challenges.

We assessed challenges for YACs across six domains to allow for a general assessment of difficulty or stress experienced during the transition to adulthood. These challenges span salient domains of work, schooling, relationships, and identity development during the transition to adulthood (Arnett 2014; Roisman et al. 2004; Schulenberg, Bryant, and O’Malley 2004; Settersten and Ray 2010a), and they have proven consequential for young African Americans’ ability to transition to stable adult roles (Arditti and Parkman 2011; McClendon, Kuo, and Raley 2014; Wang 2015). These challenges include unemployment, high levels of racial discrimination, educational disengagement, troubled romantic relationships, unmarried parenthood, ² and arrest. All challenges were reported by YACs at Waves 5 and 6 when YACs averaged 22 and 24 years of age, respectively.

Unemployment was assessed with a question that asked YACs if they had been “unemployed at any time when you wanted a job” in the past 12 months. “Yes” responses were coded 1; “no” responses were coded 0. At Wave 5, 49 percent of YACs reported recent unemployment; 47 percent reported recent unemployment at Wave 6.

Racial discrimination was assessed with 13 items from the widely used and validated Schedule of Racist Events (Landrine and Klonoff 1996). These questions assessed the frequency (1 “never” to 4 “frequently”) with which YACs experienced various discriminatory events during the past year. These events included things like being insulted, being treated disrespectfully at a place of business, and being hassled by the police “just because of [respondents’] race or ethnic background” (for a full list of items, see Burt et al. 2012). Items were averaged at each wave to form an index of YAC racial discrimination (α = .90 at both waves). We then split this index into quartiles at each wave, with YACs in the fourth quartile coded 1 for having experienced high levels of racial discrimination and all others coded 0. At each wave, 24 percent of YACs experienced high levels of racial discrimination.

Given the centrality of a college degree to future capital (Hout 2012), and the overall importance of a college degree to FACHS youth (at age 18, 81 percent of FACHS youth aspired to a college degree or higher), we coded YACs as being educationally disengaged during the transition to adulthood if they were not enrolled in any form of higher education and did not yet have a college degree. At Wave 5, 45 percent of YACs fell into this category, and 40 percent did so at Wave 6.

For partnered YACs, we assessed romantic relationship trouble with two items tapping relationship satisfaction (e.g., “How satisfied are you with your relationship?”), five items tapping partner’s hostility (e.g., “During the past month, how often did your romantic partner insult or swear at you?”), and three items tapping partner’s warmth (e.g., “During the past month, how often did your romantic partner act loving and affectionate toward you?”). The satisfaction and warmth items were reverse-coded to indicate more troubled relationships. Each subscale was standardized and summed to form a measure of relationship trouble. Nunnally’s reliability for linear combination of measures was .90. We then split this relationship trouble index into quartiles, with YACs in the fourth quartile coded 1 for having experienced a troubled (i.e., generally hostile and unsatisfactory) romantic relationship, and everyone else, including single YACs, coded 0 for not experiencing a troubled relationship. At Wave 5, 14 percent of YACs were involved in a troubled romantic relationship; 10 percent of YACs were involved in such a relationship at Wave 6.

We coded YACs as unmarried parents (1 = yes, 0 = no) if they reported having at least one biological child but not being currently married. This described 26 percent of YACs at Wave 5 and 40 percent of YACs at Wave 6.

Finally, we coded YACs as having been arrested if they responded affirmatively to a question asking whether they were arrested in the past 12 months (1 = yes, 0 = no). At Wave 5 and at Wave 6, 14 percent of YACs reported being arrested in the past year.

We then summed these binary measures tapping stressors across multiple domains to create an index of the number of different YAC transition challenges recently experienced. Conceptually, this measure indicates the general difficulty YACs were experiencing transitioning to stable adult roles during the early years of the transition to adulthood. The average number of different transition challenges experienced was 1.72 at Wave 5 and 1.77 at Wave 6; about 85 percent of YACs experienced at least one of these challenges at each wave.

Covariates and Moderating Variables

Given that difficulties during the transition to adulthood are not random occurrences (Alexander et al. 2014; Osgood et al. 2005; Silva 2012), and that mothers may have been at risk for poor health prior to this transition, we control for a variety of factors that might select some YACs into more challenging transitions and mothers into poor health. These include a variety of potential maternal stressors outside of the YAC relationship.

YAC covariates include gender, age, delinquent behavior (a 15-item count index of antisocial activity from the conduct disorder section of the Diagnostic Interview Schedule for Children, Version 4 [Shaffer and Fisher 1996]), whether the YAC lived at home,³ and a measure of whether the YAC experienced a serious illness or injury in the past year. All YAC covariates were reported by YACs at Wave 4, the beginning of the transition to adulthood.

Mother and family covariates include mother’s age, presence of a cohabiting or marital romantic partner (1 = partner present, 0 = no coresidential partner), romantic relationship quality (measured via the same two relationship satisfaction items as YACs, α = .89),⁴ mother’s perceived social support outside of her romantic relationship and YAC relationship (six items tapping perceived support from closest friend and relative, α = .79), mother’s relationship quality with her YAC (measured via two items asking about satisfaction and happiness with YAC, α = .91), mother’s education (1 = college degree, 0 = no degree), family economic hardship (measured via four items concerning the family’s financial ability to meet its needs [Conger et al. 1992], α = .85), mother’s experience of recent unemployment (1 = unemployed in past year, 0 = not unemployed in past year), whether the family owns it home (1 = own home, 0 = does not own home), mother’s perceived community disorder in her neighborhood (Sampson, Raudenbush, and Earls 1997, α = .87), the total number of children in the family, mother’s experiences of racial discrimination (a reduced version of the index used for YACs, α = .93), mother’s self-described race (1 = non-African American, 0 = African American; 8 percent were non-African American), state of recruitment (1 = Georgia, 0 = Iowa), and three assessments of mother’s prior health—self-reported poor health and psychological distress, both described earlier, and the number of physician-diagnosed chronic health problems. The number of physician-diagnosed chronic health problems was measured by asking mothers if “a doctor ever told you that you were suffering from” eight chronic health conditions, including heart trouble, diabetes, and kidney disease. All mother and family controls were assessed via mothers’ reports at Wave 4. In addition to serving as covariates, YAC gender and age also served as potentially moderating factors. Table 1 reports descriptive statistics and bivariate correlations for all study variables.

Table 1.

Descriptive Statistics and Bivariate Correlations among Study Variables (N = 629)

		1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29
1.	Mother allostatic load (W5)	—
2.	Mother age (W4)	.17	—
3.	Mother diagnosed health problems (W4)	.17	.17	—
4.	Mother poor self-rated health (W4)	.23	.10	.34	—
5.	Mother poor self-rated health (W5)	.24	.00	.28	.58	—
6.	Mother poor self-rated health (W6)	.25	.04	.22	.51	.57	—
7.	Mother psychological distress (W4)	−.05	−.04	.18	.29	.21	.19	—
8.	Mother psychological distress (W5)	−.01	−.12	.10	.23	.25	.18	.49	—
9.	Mother psychological distress (W6)	.11	−.04	.11	.24	.19	.26	.49	.50	—
10.	Mother racial discrimination (W4)	.02	.14	.07	.04	.02	−.03	.14	.07	.07	—
11.	Mother relationship quality with YAC (W4)	.05	.00	−.05	−.04	−.04	−.07	−.20	−.07	−.06	−.08	—
12.	Mother non-African American	−.07	.12	.00	.02	−.07	−.05	.06	.02	−.01	−.04	−.14	—
13.	Mother romantic partner present (W4)	.02	−.02	−.10	−.06	−.09	−.05	−.06	−.10	.01	.03	−.02	.06	—
14.	Mother romantic relationship quality^a (W4)	.01	.00	−.10	−.21	−.27	−.28	−.18	−.21	−.21	−.07	.15	−.09	—	—
15.	Mother social support (W4)	.03	.04	−.07	−.13	−.08	−.11	−.16	−.14	−.22	.04	.02	.03	.01	.30	—
16.	Mother recent unemployment (W4)	.04	−.09	.00	.06	.10	.09	.04	.09	.05	−.03	.03	−.04	−.07	−.08	−.08	—
17.	Mother college degree (W4)	−.06	.26	−.02	−.15	−.19	−.18	−.05	−.09	−.09	.18	−.04	.11	.10	.11	.10	−.09	—
18.	Number of children in family (W4)	.08	.15	−.03	.04	−.02	.02	.01	−.04	.09	−.01	.04	.01	.02	−.05	−.01	.09	−.08	—
19.	State (1 = Georgia, 0 = Iowa)	−.08	−.06	.02	−.09	−.03	.05	−.02	−.03	.01	−.28	.06	−.25	−.05	.11	−.07	.01	−.03	−.06	—
20.	Neighborhood disorder (W4)	.03	−.08	.04	.09	.09	.04	.15	.18	.13	.08	.04	−.06	−.11	−.20	−.13	.04	−.11	.06	.03	—
21.	Family owns home (W4)	−.09	.18	−.04	−.16	−.16	−.20	−.11	−.15	−.09	.11	.00	.08	.24	.16	.16	−.16	.14	−.02	.06	−.12	—
22.	Family economic hardship (W4)	.08	.00	.15	.26	.26	.29	.24	.20	.23	.00	−.05	−.08	−.31	−.36	−.21	.20	−.15	.04	.06	.18	−.32	—
23.	YAC transition to adulthood challenges (W5)	.12	−.09	.02	.06	.00	.07	.08	.05	.14	.02	−.12	−.01	−.09	−.02	.00	.10	−.12	.10	−.05	.05	−.04	.11	—
24.	YAC transition to adulthood challenges (W6)	.09	−.02	.08	.13	.05	.10	.09	.08	.07	.07	−.14	.00	−.03	−.10	.14	.11	−.07	.08	−.04	.08	−.03	.00	.50	—
25.	YAC living at home (W4)	−.03	−.10	−.05	−.01	.05	.03	−.08	.03	−.03	−.14	−.02	.00	−.04	.08	.00	−.03	−.12	−.12	.27	−.05	−.03	.04	.03	.01	—
26.	YAC illness or injury (W4)	−.01	.02	.03	.00	.02	.05	.06	−.01	.04	.01	−.01	.10	.01	.11	−.02	.07	.01	−.03	−.06	−.03	−.02	−.01	.05	.01	−.10	—
27.	YAC deviant behavior (W4)	−.04	−.04	−.02	−.05	−.02	.01	.03	.03	.06	−.01	−.07	.10	.02	−.02	−.06	.06	.02	−.03	−.04	.02	−.02	.00	.13	.11	−.04	.15	—
28.	YAC age	.06	.11	.04	.04	.01	−.02	.03	.00	−.01	.12	.00	.02	.02	−.01	.04	.06	.02	.11	−.40	.01	−.15	.01	.17	.13	−.26	−.02	.04	—
29.	YAC female	.03	.06	.08	.03	.09	.02	.08	.08	.01	.05	−.07	.01	−.01	−.08	−.09	.00	−.03	.02	−.02	.08	−.08	.00	−.15	−.13	−.04	.04	−.01	−.01	—
	Full Sample
	Mean^b	1.46	44.11	.55	2.75	2.90	2.96	1.28	1.27	1.26	1.86	3.64	.08	.41	.02	2.71	.20	.13	3.23	.52	1.28	.55	2.19	1.72	1.77	.59	.14	.15	18.79	.56
	SD	1.33	6.26	.93	.95	.98	.93	.37	.37	.35	.69	.60	.27	.49	.75	.32	.40	.34	1.52	.50	.43	.50	.70	1.24	1.23	.49	.34	.49	.89	.50
	Min.	.00	32.00	.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	.00	.00	3.24	2.00	.00	.00	.00	.00	1.00	.00	1.00	.00	.00	.00	.00	.00	16.00	.00
	Max.	5.00	79.00	8.00	5.00	5.00	5.00	3.00	3.00	3.00	3.91	4.00	1.00	1.00	.88	3.00	1.00	1.00	11.00	1.00	3.00	1.00	4.00	5.00	5.00	1.00	1.00	3.00	21.00	1.00
	Female YACs
	Mean^b	1.48	44.40	.62	2.77	2.96	2.97	1.30	1.29	1.26	1.90	3.60	.08	.41	−.03	2.68	.19	.13	3.25	.51	1.32	.52	2.19	1.56	1.64	.57	.15	.14	18.78	—
	SD	1.39	6.62	1.02	.95	.95	.96	.38	.41	.35	.68	.64	.28	.49	.77	.33	.39	.34	1.54	.50	.45	.50	.69	1.14	1.18	.50	.36	.45	.91	—
	Male YACs
	Mean^b	1.41	43.70	.46	2.71	2.79	2.93	1.24	1.23	1.25	1.83	3.68	.08	.42	.09	2.74	.19	.15	3.19	.54	1.25	.59	2.20	1.93	1.96	.61	.12	.15	18.79	—
	SD	1.26	5.64	.82	.91	.98	.91	.32	.30	.35	.71	.56	.27	.49	.73	.31	.39	.36	1.48	.50	.38	.49	.70	1.36	1.29	.49	.33	.54	.86	—

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Note: Shaded cells indicate a significant bivariate relationship at p < .05. YAC = young adult child.

Measured here only for partnered mothers.

Mean = proportion for binary variables.

Analytic Strategy

Because our subjective assessments of mothers’ health (psychological distress and self-reported poor health) were measured across multiple waves, but our biological measure of mothers’ health (allostatic load) was measured only at Wave 5, we used two types of analyses to assess the association between YAC transition challenges and mothers’ health risk. These analyses offer different strengths and weaknesses for understanding this relationship.

We predicted allostatic load, a count variable with non-negative integer values and over-dispersion, using negative binomial regression. Because allostatic load was measured only at Wave 5 and only for a subsample of respondents, we restricted the analytic sample to the biomarker subsample (N = 382), and the analysis includes data only from Waves 4 and 5. YAC challenges were measured contemporaneously with the dependent variable at Wave 5, and control variables were drawn from Wave 4. The model proceeded in several steps. First, we ran a path model in which all control variables predicted YAC transition challenges (also specified as a count outcome), which predicted mothers’ allostatic load. This model was doubly robust, in that it assessed the role of controls in predicting both transition challenges and allostatic load, as well as the relationship between allostatic load and transition challenges. We then added interaction terms to assess potential variation in the stress contagion effect of YAC challenges on mothers’ allostatic load by YAC gender and age. For these analyses, the log-odds coefficients were transformed (exponentiated) into their respective incident rate ratios (IRRs), which indicate the change in the expected count of high-risk biomarkers given a one-unit change in the respective independent variable. Values above one indicate a positive association; values between zero and one indicate a negative association. Because of known issues with interpreting interaction terms in nonlinear models, we used predicted values to aid in interpretation. That is, we plotted the predicted value of allostatic load at each level of transition challenges by gender and age while holding all other variables constant at their mean (binary variables held at zero).

Although the allostatic load models allow for an understanding of biological risk, one major limitation is the assessment of this risk at only one point in time and contemporaneously with YAC transition challenges. Although we controlled for various prior measures of health in assessing the association between YAC transition challenges and mothers’ allostatic load, we could not rule out with certainty the possibility that mothers’ elevated health risk took root before the transition to adulthood or even enhanced the difficulty of this transition. Preliminary models in which mothers’ self-reported health, psychological distress, and diagnoses failed to predict YAC challenges during the transition to adulthood offer a reason for confidence in the presumed causal order. However, we further examined the issue of possible reverse causality or bidirectionality via cross-lagged models of subjective health. These models enable a better understanding of time ordering by examining the relationships between Wave 5 and Wave 6 measures of mothers’ psychological distress, self-reported poor health, and YAC challenges, independent of control variables at Wave 4.⁵

The cross-lagged models linking YAC challenges to mothers’ subjective health proceeded in the same manner as those predicting allostatic load. We first implemented a path model in which Wave 5 measures of mothers’ health and YAC challenges predicted one another at Wave 6, independent of all Wave 4 controls. Then, we examined potential differences in these cross-lagged effects by YAC gender and age. Both measures of mothers’ subjective health approximated normality in their distributions, so we treated them as continuous variables in the cross-lagged models. YAC challenges were treated as an overdispersed count variable via negative binomial regression. Because this analysis did not rely on valid biomarker assessments, we used the full available sample of mothers (N = 629).

For all models, we mean-centered all continuous independent variables for a more useful interpretation of the intercept. Furthermore, we relied on full information maximum likelihood (i.e., maximum likelihood for missing values) to handle missing data. Approximately 16 percent of respondents were missing data on one or more of the independent variables of interest. This approach, implemented in MPlus Version 7.4, is more efficient and relies on fewer assumptions than does multiple imputation, and it produces less biased estimates than listwise deletion (Acock 2013; Allison 2012; Young and Johnson 2013).

RESULTS

Allostatic Load Models

Prior to testing study hypotheses, it is important to note that there appears to be some selection into YACs experiencing a greater number of challenges during the transition to adulthood. This is consistent with prior work and with our understanding of stressors proliferating across the life course (Alexander et al. 2014; Osgood et al. 2005; Silva 2012). As bivariate associations presented in Table 1 indicate, female YACs; YACs with older, more educated, and partnered mothers; and YACs with higher-quality relationships with their mothers experienced fewer transition challenges. Furthermore, older YACs; YACs engaged in more delinquent behavior during late adolescence; YACs with more siblings; and YACs whose mothers reported unemployment or greater economic hardship experienced a greater number of transition challenges. In preliminary regression models predicting transition challenges at Wave 5, however, these factors explained only about 13 percent of the variance in transition challenges. When coupled with the significant but relatively weak bivariate associations in Table 1, selection processes appear to be present but not strong among this sample of African Americans. This, of course, is consistent with existing literature suggesting that the transition to adulthood is generally difficult for African Americans, given historical and contemporary structures of inequality.

Nonetheless, it is important to account for these factors in predicting transition challenges and mothers’ allostatic load, and in assessing the relationship between the two. Table 2 shows results for the negative binomial path models doing just that.⁶ In these models, both transition challenges and allostatic load at Wave 5 were regressed on all Wave 4 controls. Table 2, however, shows only the coefficients predicting allostatic load, the dependent variable of interest. As reported in Model 1 of this table, each additional challenge experienced by YACs was associated with a 10 percent increase in mothers’ expected count of high-risk biomarkers independent of all covariates, including mothers’ prior subjective health, YAC characteristics, and several indicators of socioeconomic status and other potential stressors not related directly to the YAC. In fact, challenges faced by young adult children held more predictive power than did mothers’ own relationship quality, education, economic hardship, and racial discrimination, none of which retained conventional levels of statistical significance in the full models. In perhaps what is the bluntest comparison, each additional transition challenge was comparable in its effect on mothers’ health risk to an additional 2.4 years of maternal age. This finding offers support for Hypothesis 1.

Table 2.

Negative Binomial Path Model Predicting Mothers’ Allostatic Load (Exponentiated Coefficients Presented)

	1	2
	e^{^b}	e^{^b}
YAC Transition to Adulthood Challenges (W5)	1.101^*	1.189^***
x Female	—	.829^*
x YAC age	—	1.104^**
Mother age (W4)	1.022^**	1.024^***
Mother diagnosed health problems (W4)	1.089	1.097^*
Mother poor self-rated health (W4)	1.219^***	1.213^***
Mother psychological distress (W4)	.765	.780
Mother racial discrimination (W4)	.943	.932
Mother relationship quality with YAC (W4)	1.090	1.075
Mother non-African American	.728	.754
Mother romantic partner present (W4)	1.192	1.155
Mother romantic relationship qualitya (W4)	1.067	1.046
Mother social support (W4)	1.225	1.284
Mother recent unemployment (W4)	1.041	1.004
Mother college degree (W4)	.891	.822
Number of children in family (W4)	1.005	1.009
State (1 = Georgia, 0 = Iowa)	.812	.815
Neighborhood disorder (W4)	1.033	1.075
Family owns home (W4)	.851	.839
Family economic hardship (W4)	1.063	1.074
YAC living at home (W4)	.966	.947
YAC illness or injury (W4)	.960	.945
YAC deviant behavior (W4)	.947	.974
YAC age (W4)	.969	.818^*
YAC female	1.076	1.520^*
Intercept	1.369^*	1.168

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Note: N = 382. YAC = young adult child. Path model includes regression of young adult transition challenges on all covariates.

Coded as an internal moderator; continuous variables mean-centered.

p < .05;

^**

p < .01;

^***

p < .001 (two-tailed tests).

Model 2 of Table 2 indicates that this contagion effect was not uniform: YAC gender and age conditioned this effect.⁷ More specifically, stress contagion from YACs to mothers was stronger for male YACs than for female YACs and for YACs experiencing challenges at older ages versus younger ages. These significant interaction effects are graphed in Figures 1 and 2, respectively. As shown in Figure 1, mothers’ allostatic load was not associated with daughters’ transition challenges, but it was positively associated with sons’ challenges. For each additional challenge experienced by young men, mothers’ predicted allostatic load count increased by about 19 percent. The overlapping confidence intervals suggest that the difference between males and females is not statistically significant in the probability metric. Thus, the significant interaction term is either detecting a larger ratio of change for males compared to females or potentially differences in residual variance between the two groups.

Figure 1. — Mothers’ Predicted Allostatic Load by YAC Transition Challenges and YAC Gender

*Note:* 95% confidence intervals shown.

Because young men scored higher than young women on the transition challenges index (W5 mean_women = 1.56, W5 mean_men = 1.93) and were significantly more likely to experience arrest (18 versus 10 percent), high levels of racial discrimination (28 versus 19 percent), and school detachment (57 versus 40 percent), it was important to assess if these gender differences in the frequency of given stressors drove the gender effects noted earlier. To do so, we conducted two supplemental analyses. First, we used two alternative specifications of transition challenges, each coded into a binary variable indicating (1) any challenge versus no challenge and (2) two or more challenges versus one or no challenge. No matter the operationalization, the moderation effect by gender remained statistically significant, such that stress contagion from YACs to mothers was higher for young men than for young women. The second set of supplemental analyses eliminated each stressor from the transition challenges index one by one to examine whether one particular stressor might be driving the main effects and any gender differences in effects. The main effects of transition challenges and the gender × challenges interaction effects mirrored those found in the models presented. Hence, it does not appear that the gender difference in stress contagion was attributable to the slightly different distribution of these stressors by gender or to the influence of any one specific (gendered) stressor.

As Figure 2 shows, mothers’ allostatic load was also more strongly associated with the challenges of older YACs than those of younger YACs. For older YACs (one standard deviation above the mean), each additional challenge was associated with a 30 percent increase in the expected count of mothers’ health-risk biomarkers. For younger YACs (one standard deviation below the mean), each additional challenge was associated with only a 9 percent increase in the expected count of mothers’ health-risk biomarkers. Based on the overlapping confidence intervals, the difference is only statistically significant at the highest number of YAC challenges. Again, the difference in results between the interaction term, which is assessing change on a multiplicative scale, and the probabilities, which are assessing change on an additive scale, suggests either that there is an age effect when looking at the ratio of change or that the interaction term is detecting differences in residual variance between younger and older YACs. It is important to note that the age range for YACs is quite restricted in FACHS (16 to 21 years of age at Wave 4 and 19 to 25 years of age at Wave 5, when transition challenges were measured), so differences in the timing of these transition challenges is only a few years and is restricted to a relatively early stage of the transition to adulthood.

Cross-Lagged Model of Subjective Health

Figure 3 shows results from the cross-lagged model of the associations between YAC transition challenges and mothers’ subjective health—psychological distress and self-reported poor health. This model regresses Wave 6 assessments of YAC transition challenges and the two measures of mothers’ subjective health on these same measures at Wave 5. It includes all controls present in the allostatic load models. Hence, this model allows for a longitudinal and bidirectional assessment of these associations and models them slightly further into the transition to adulthood.

As expected, Figure 3 indicates there was general continuity across all measures from Wave 5 to Wave 6. That is, all Wave 5 measures positively predicted their respective Wave 6 measures. Results also indicate that YAC challenges significantly elevated the risk for poor self-rated health and psychological distress among mothers, whereas mothers’ health indicators did not significantly predict YAC transition challenges. These results, although based on subjective health assessments, offer additional support for the directionality of stress contagion flowing from YACs to their mothers during the transition to adulthood and support Hypothesis 1. Unlike the models predicting allostatic load, however, contagion effects for mothers’ subjective health were not dependent on YAC gender or age (p > .10 for all interactions; results not shown). The results from the cross-lagged models predicting subjective health thus fail to support Hypothesis 2 or a gender effect.

DISCUSSION

The past decade has produced a flurry of research on the role of psychosocial stress in healthy aging, but one context of stress that has yet to be fully considered is that of ensuring a successful transition to adulthood for one’s children. For parents of African American children, this task is particularly great, as young African Americans tend to experience greater difficulty than their majority counterparts completing education, attaining stable work, avoiding police contact, and building stable and rewarding relationships. These transition challenges yield substantial implications for young people’s future life chances. In the present study, we suggested that these intra-individual effects may actually underestimate the impact of a difficult transition to adulthood, because they fail to consider the implications of this transition in the context of linked lives (Elder 1998). We proposed that the difficulties experienced by African Americans making the transition to adulthood not only yield implications for their own life chances but may also be a source of stress contagion for their parents.

Our findings suggest this is indeed the case. African American young adults’ challenges across a variety of salient life domains during the transition to adulthood were associated with elevated allostatic load, a composite measure of biological risk, as well as greater psychological distress and worse self-rated health among their mothers. These effects across varied health outcomes held even after accounting for earlier assessments of maternal health, other contexts of maternal stress (e.g., relationship, neighborhood, and socioeconomic), and factors that forecast higher degrees of uncertainty and instability during the transition to adulthood.

We also found evidence that stress contagion from young adult children to their mothers may vary by young adult characteristics, at least in predicting biological health risk (i.e., allostatic load). There was some indication that challenges experienced by young men were more detrimental to their mothers’ biological health than were challenges experienced by young women. This gender difference was not attributable to the gendered distribution of any specific stressor or to young men’s slightly higher frequency of challenges more generally. Consistent with research suggesting that mothers may view the toll of enduring racism as more costly for their sons than for their daughters (Dow 2016), these gendered effects may have been due to mothers’ heightened worry for the safety, welfare, and life chances of their African American sons. Future research must investigate this gender effect to understand the degree to which this is indeed the case, especially given two alternative explanations. First, it may be that the relatively crude measures of transition challenges used here missed important gendered gradations in the severity of these challenges (e.g., perhaps young men’s experiences of discrimination are more distressing or violent, or their experiences of arrest carry the potential of harsher sentences if convicted). Second, given that we did not find gender differences when comparing the predicted values of allostatic load (as indicated by overlapping confidence intervals at each level of transition challenges), the significant interaction term might simply indicate differences in the residuals. Understanding these distinctions is especially important in light of scholarly and popular discussions of young women’s relative exclusion from conversations and research on police brutality and other costs of endemic racism (Collins 2005; Crenshaw et al. 2015; Morris 2016) and the lack of support for such a gendered effect in models examining subjective health.

The second factor that conditioned the stress contagion effect on mothers’ physiological risk was the age at which young adult children experienced transition challenges. The same precautions are in order with these age effects as with the gender effects, however. In addition, all of the young people in this study were in the early stages of the transition to adulthood. Hence, older offspring were no more than a few years ahead of their younger counterparts. Nonetheless, stress contagion effects were more pronounced among mothers whose young adult children encountered transition challenges at older ages (e.g., age 22 versus age 19). As the transition to adulthood has been extended across the past several decades, it has become normative for young people to experience some degree of difficulty, uncertainty, and hardship (Settersten and Ray 2010b). When this hardship extends later and later into the transition, however, mothers may begin to sense that something is astray and to worry more about getting their children back on track. Importantly, however, we do not know if the difficulties experienced by older offspring are new or are simply a continuation of earlier challenges. In other words, the age effect found here may be an effect of cumulative stress contagion rather than young adult age. The cross-lagged models of subjective health give weight to this possibility by showing continuity in young adult transition challenges across time. Future research extending this line of inquiry further into the transition to adulthood and utilizing within-individual change models can and should parse this out.

The fact that we did not find gender- and age-based stress contagion in the cross-lagged models predicting subjective measures of health may be attributable to several factors. These subjective assessments of health may be less sensitive measures than the allostatic load. Or, there may be real differential effects by health outcome. Although subjective and objective assessments of health status are positively correlated (Christian et al. 2011; Jylha, Volpato, and Guralnik 2006; Kuhn, Rahman, and Menken 2006), they are also distinct and hence may have different risk factors and mechanisms of effects. Alternatively, as indicated earlier, the significant interaction terms in the biological risk models could be picking up differences in residual variation between groups. Potential gender and age differences in contagion effects is an important avenue of inquiry, and various indicators of health should be examined.

Our findings are best considered in light of several limitations. First, our measure of allostatic load was limited to one point in time. Despite the theoretical foundations supporting a causal relationship of stress contagion from young adult challenges to parental health, a note of caution is in order. As others have indicated (e.g., Wethington 2000), it is difficult to identify and measure contagion effects. With respect to contagion from young adult children to mothers, this is so for two main reasons. First, parents and children often share environments and environmental stressors. Second, much like any claim to causality, selection processes present complications. For instance, some of the same things thought to harm parental health (e.g., racial discrimination [Beatty Moody et al. 2014] and economic hardship [Simons et al. 2016]) are also expected to increase young peoples’ difficulty during the transition to adulthood (Alexander et al. 2014; Hope et al. 2015). Such complications mean the appropriate time ordering and accuracy of stressor and outcome measurements is vital, as well as the theoretically-informed and appropriately-broad selection of control variables. The current study drew on the breadth of data available from the FACHS mothers and their young adult children and utilized multiple analytic techniques and sensitivity analyses in an effort to minimize these complications. Nonetheless, further refinement of measures and statistical techniques, particularly those that are able to use more than two waves of data to capture within- and between-individual effects, would be a worthy pursuit for future research.

Second, the period of time under investigation included only the beginning years of the transition to adulthood. Recent research suggests that young people might not assume stable adult roles and an adult identity until their late-20s or early-to-mid-30s (Panagakis 2015; Settersten and Ray 2010a). Hence, we need additional research that follows young people for longer periods of time, assesses how the challenges they face across the transition to adulthood change by degree and perhaps by type, and links these changes to changes in parental health.

Third, although there is reason to believe that the responsibility facing African American parents as their children transition to adulthood is greater than that facing their majority counterparts, this study measured heterogeneity among African Americans themselves, both in the experience of the transition to adulthood and in stress contagion effects, and therefore could not explore differences in stress contagion by race or ethnicity. Work examining between-group differences is certainly warranted, as it is unclear whether the challenges experienced by young adult offspring would be equally salient stressors for mothers from other racial/ethnic groups. Motherhood and mothering assume a unique prominence for African American women and in African American communities (Collins 2015; Edwards 2000; Gilkes 1994). Although this motherwork often brings status, an affirmative identity, and power in African American communities (Collins 2015), the centrality of this role might make African American mothers more susceptible to stress contagion from offspring (or from other vulnerable members in the community). Alternatively, the more communal act of mothering in African American communities might make these mothers less susceptible than non-African American mothers to stress contagion from offspring. Although these potential group differences should be investigated, they should not obscure the heterogeneity in the experiences of African American young people and their influence on maternal health highlighted here.

Fourth, the current study could not examine stress contagion from young adult children to their fathers or paternal caregivers. Research shows that despite fathers’ increased involvement in recent decades, they are generally “insulated against the demands of intensive parenting” (Shirani et al. 2012:25). This suggests stress contagion from offspring may be less salient for fathers than it is for mothers. Other work, however, suggests that fathers are heavily invested in their identity as fathers and that African American fathers, in particular, are less bound up in notions of the package deal (Townsend 2002), more involved with their children’s care, and more easily assume the role of social parent compared to their majority peers (Edin and Nelson 2013; Edin, Tach, and Mincy 2009; Jones and Mosher 2013). Hence, it is vital that future work examine the presence and processes of stress contagion among fathers.

Fifth, FACHS is a heterogeneous sample of African American young people, their families, and the communities in which they live. Accordingly, FACHS respondents prove similar to national samples of African Americans on many measures. Still, FACHS is not a national probability sample of African American young people or their caregivers. Although we expect the sample is not unique in any way that would make FACHS mothers differentially susceptible to stress contagion compared to other African Americans, FACHS young people experienced the transition to adulthood during the Great Recession. The national economic crisis could have exacerbated young adult stressors and their impact on mothers’ health. It is equally plausible, however, that given generalized uncertainty and difficulty for young people across the nation during this time, stress and stress contagion were muted in the current sample. Such potential cohort effects should be explored using repeated cross-section data.

Finally, additional research should better examine the mechanisms of stress contagion. For instance, to what extent is stress contagion from offspring to mothers during the transition to adulthood largely due to shared fate (e.g., family disruption, coregulation), obligations (e.g., increased caregiver burden), commitments (e.g., rumination or worry), or some combination of these and other mechanisms (e.g., negative affect, social disaffiliation, or disintegration)? Supplemental analyses (not shown) revealed that accounting for changes in mothers’ economic hardship and the quality of the relationship between mothers and their young adult children (rather than simply controlling for earlier assessments) did not mitigate the stress contagion found here. Other mechanisms, which rely less on functional, conscious adaptations as a response to young adult challenges and more on emotional, unconscious adaptations, like coregulation or worry, might better explain stress contagion between young adult children and mothers. Research indicates that worry or rumination (i.e., perseverative cognition) does not need to be conscious to take a toll on health and is disadvantageous whether it occurs in anticipation of or following stressors (Brosschot 2010; Brosschot et al. 2006; Brosschot et al. 2010). Another important avenue for future research is the extent to which stress contagion varies across cultural contexts related to intensive mothering and the degree to which mothers’ own identities serve as a mechanism (i.e., a unique form of investment) whereby young adult challenges manifest in mothers’ health outcomes. Additional measures that would enable a test of this and other mechanisms are necessary.

Despite these limitations, this study suggests a need to examine the stress-health relationship in the context of linked lives. It also encourages a broader life course approach that considers the meaning and importance of these linked lives in a sociohistorical context of increasing uncertainty, deeply rooted structures of inequality, intensive mothering, and limited public assistance for families struggling to launch their children into adulthood. Our results show that challenges experienced by African American young adult children were significant impediments to their mothers’ health, a population already at disproportionately high risk of unhealthy aging and premature death (Williams 2012).

The total toll that the transition to adulthood takes on the health of aging parents has yet to be seen, but this work suggests it might be substantial. On its surface, this is bad news: the transition to adulthood may be exacerbating inequality not only among young people but also among their parents. These findings, however, also suggest that interventions aimed at increasing healthy aging may be more fruitful if they target both individual and relational health risks. Parents are already taking on the heavy burden of helping their children navigate a tenuous and uncertain transition to adulthood (Fingerman, Cheng, Tighe, et al. 2012; Fingerman, Cheng, Wesselmann, et al. 2012). Parents with few resources are no less willing to help than are those with ample resources, despite their greater challenge (Fingerman et al. 2015). Hence, efforts to encourage more intensive parenting to offset or prevent transition challenges would likely be fruitless at best and, as this study suggests, detrimental at worst. Perhaps most encouraging is that the current findings suggest that investing more public resources in assisting young people across the transition to adulthood might be doubly beneficial, elevating the life chances of young adults and, in so doing, enhancing parental health.

Recent work by DeLuca and colleagues (2016:66) suggests that efforts to enhance economic opportunity for young people via investments in education, job training, and affordable housing are vital. They also note, however, that public efforts to provide youth with opportunities to form “identity projects,” or a source of meaning outside their challenging circumstances that “provides a strong sense of self and is linked to concrete activities” may be helpful. As their work shows, these identity projects were the most beneficial factor in keeping young people “on track,” and they were most protective for youth when they formed within or around existing institutions, like school, work, or community. Unfortunately, the current study cannot measure or test the protective influence of identity projects on young people or their parents. If future research supports their positive impact, however, reversing policies implemented over the past decade to limit public financing of institutional programs that might foster youth identity projects (e.g., arts education, including extracurriculars and school-community partnerships [Parsad and Spiegelman 2012]) may promote better health for both young people and their aging parents.

Acknowledgments

The authors wish to thank Robert Adelman, Mary Nell Trautner, Kristen Schultz Lee, and Jessica Houston Su for their helpful comments on previous drafts.

Funding

This work was supported by the National Heart, Lung, Blood Institute (R01 HL118045), the National Institute on Child Health and Human Development (R01 HD080749), the National Institute on Aging (R01 AG055393), the National Institute on Drug Abuse (R21 DA034457), and the National Institute of Mental Health (R01 MH62699, R01 MH62666). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Biographies

Ashley B. Barr is an Assistant Professor in the Department of Sociology at the University at Buffalo, SUNY. Her research focuses on the development of romantic and family relationships and their influence on health and well-being across the life course.

Leslie Gordon Simons is a Professor of Sociology at the University of Georgia. Her current research focuses on the socio-contextual predictors and consequences of various family processes, chief among them being parent-child relationships.

Ronald L. Simons is a Distinguished Research Professor in the Department of Sociology at the University of Georgia, Co-Director of the Center for Gene-Social Environment Transactions, and Senior Fellow in the Owens Institute for Behavior Research. His current research investigates the manner in which social factors become biologically embedded and influence development and health across the life course.

Steven R. H. Beach is a Distinguished Research Professor in the Department of Psychology at the University of Georgia and the Co-Director of the Center for Family Research. His current research focuses on understanding links between family processes, epigenetics, and healthy aging.

Robert A. Philibert is a Professor of Psychiatry at the University of Iowa and the Director of the Psychiatric Genetics Laboratory. His current research aims to understand the molecular biology of behavioral health in order to generate clinically useful biomarkers and to devise more effective clinical interventions.

Notes

^1.

These caregivers were not necessarily the primary caregiver at the start of recruitment. Because respondents’ primary caregiver sometimes changed, FACHS continued to follow caregivers from Wave 1 and entered into the study any individual who took over these responsibilities across waves. The current sample is composed of all current primary caregivers, independent of whether they acted in this role at Wave 1.

^2.

Nonmarital childbearing is more common and occurs earlier among African Americans than among other racial/ethnic groups; in 2014, however, the average age of first birth among African Americans was 24.2 (Mathews and Hamilton 2016). Hence, births occurring prior to the study period are still earlier than average among this group of young people. Furthermore, despite the relative normativity of early and nonmarital childbearing among African Americans, research by Barber, Yarger, and Gatny (2015) indicates that, when compared to their white peers, African American women generally hold more negative attitudes about early and nonmarital childbearing and have a similar desire to avoid pregnancy. Nonetheless, given that marriage is uncommon among young adults, and especially among African American young adults, we also examined models using an indicator of single parenthood where respondents were neither married to nor cohabiting with a partner. Results were similar across operationalizations of this particular transition challenge.

^3.

Evidence is mixed with respect to whether living at home during the transition to adulthood indicates difficulty transitioning to adult roles. For some young people, living at home is a temporary choice that allows them to accumulate capital. For others, living at home represents a necessary and more permanent situation indicative of economic or other distress (Sandberg-Thoma, Snyder, and Jang 2015; Settersten and Ray 2010a). Rather than assume that living at home is an inherent challenge during the transition to adulthood, we exclude it from our index of YAC challenges and simply control for it in all models.

^4.

We coded mother’s relationship satisfaction as an internal moderator (Frech and Williams 2007; Mirowsky 1999) so that single mothers could be retained in all models.

^5.

Although mothers’ self-rated health and psychological distress measures are also available at Wave 4, not all the YAC challenges are available at that wave, ruling out the possibility of within-individual change models over three waves.

^6.

In addition to the models presented, we also conducted propensity models to examine the sensitivity of our results to different modeling strategies. To do so, we recoded transition challenges into a dummy variable indicating having experienced two or more transition challenges (85 percent experienced one or more, so a distinction between none and any was relatively meaningless and offered too small of cell sizes for propensity modeling). We specified multiple transition challenges as the treatment and used an inverse probability weighting regression adjustment (IPWRA) approach to assess treatment effects. Unlike conventional propensity matching approaches, IPWRA is doubly robust, such that selection into treatment (2+ transition challenges) is modeled via a logistic regression, and a formal model of the outcome (maternal health risk) is still used. All control variables were entered in both the treatment and outcome models. As others have shown (Funk et al. 2011), this doubly robust feature offers more protection against model misspecification. Results from the IPWRA models indicate that respondents who experienced two or more transition challenges had mothers who scored .37 units higher on the allostatic load index relative to those who experienced one or no transition challenges (p < .05). When propensity models were separated by gender, young men who experienced two or more transition challenges had mothers who scored nearly a full point (.95 units) higher on the allostatic load index relative to those who experienced one or no transition challenges (p < .001). Treatment effects in the IPWRA models for women were not statistically significant. This pattern of results was consistent with those presented in the negative binomial models, yet the negative binomial models allowed us to retain the count measure of transition challenges.

^7.

Interaction significance and patterns of effects are similar when we examine each interaction independent of the other interaction.

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PERMALINK

Sharing the Burden of the Transition to Adulthood: African American Young Adults’ Transition Challenges and Their Mothers’ Health Risk

Ashley B Barr

Leslie Gordon Simons

Ronald L Simons

Steven R H Beach

Robert A Philibert

Abstract

THE TRANSITION TO ADULTHOOD AMONG AFRICAN AMERICANS

STRESS PROLIFERATION, STRESS CONTAGION, AND LINKED LIVES DURING THE TRANSITION TO ADULTHOOD

Mechanisms of Stress Contagion during the Transition to Adulthood

Contextualizing Stress Contagion

THE CURRENT STUDY

DATA AND METHODS

Sample

Dependent Variables

Allostatic load.

Self-reported poor health.

Psychological distress.

Primary Independent Variable

Young adult children’s challenges.

Covariates and Moderating Variables

Table 1.

Analytic Strategy

RESULTS

Allostatic Load Models

Table 2.

Figure 1.

Figure 2.

Cross-Lagged Model of Subjective Health

Figure 3.

DISCUSSION

Acknowledgments

Funding

Biographies

Notes

References

ACTIONS

PERMALINK

RESOURCES

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