Journal of Adolescence 36 (2013) 1039–1051

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Journal of Adolescence

journal homepage: www.elsevier .com/locate/ jado

Mothers’ marital history and the physical and mental healthof young adults: An investigation over the early life course

Kandauda (K.A.S.) Wickrama a,1, Tae Kyoung Lee a,1, Catherine Walker O’Neal b

aHuman Development and Family Science, University of Georgia, 103 Family Science Center I, Athens, GA 30602, USAbHuman Development and Family Science, University of Georgia, 107 Family Science Center II, Athens, GA 30602, USA

Keywords:Mothers’ marital historyEconomic pressureParentingYoung adults’ health

E-mail addresses: wickrama@uga.edu (K.(K.A.S.)1 Tel.: þ1 706 542 4926.

0140-1971/$ – see front matter Published by Elsevihttp://dx.doi.org/10.1016/j.adolescence.2013.08.012

a b s t r a c t

Using survey data from 12,424 adolescents and their mothers over 13 years in the na-tionally representative National Longitudinal Study of Adolescent Health, the purpose ofthis study was to examine a life course model exploring the pathways linking mothers’marital history (identified as latent classes) and young adult health outcomes. Duringyoung adulthood (Wave 4), respondents ranged in age from 19 to 32. The resultsdemonstrated unique long-term influences of stressful marital history typologies ofmothers (prior to 1995) on the physical and mental health of young adults (2008) withreference to consistently married mothers after controlling for health status in 2001. Theseinfluences operated through family processes (economic pressure and parental rejection)and adolescent psychosocial adjustment (self-esteem, academic performance, and delin-quent behavior). Our findings show that vulnerable groups of youth, in terms of mothers’marital history, can be identified early for appropriate intervention efforts.

Published by Elsevier Ltd on behalf of The Foundation for Professionals in Services forAdolescents.

Although previous research has documented the general healthiness of adolescents and young adults compared to olderindividuals, an increasing number of studies indicate rising numbers of health problems in young adulthood (Roux, Jacobs, &Kiefe, 2002; Shay et al., 2013). It is important to understand increasing health problems and emerging health inequalitiesduring the earlier years in order to obtain information that might help to prevent the long-term impact of health problemsover the life course (Avison, Aneshensel, Schieman, & Wheaton, 2009; Bauldry, Shanahan, Boardman, Miech, & Macmillan,2012).

Previous research suggests that parents’ marital status has a persistent influence on adolescents’ and young adults’physical and mental health outcomes (Bramlett & Blumberg, 2007; Wickrama, Conger, Lorenz, & Jung, 2008). Particularly,previous studies have shown that the instability, duration, and dissolution timing of parents’ marriage (or marriage-likerelationships) shape children’s family context at key developmental phases and may, consequentially, have a persistent in-fluence on youth’s psychosocial adjustment as well as mental and physical health outcomes (Cavanagh, 2008; Elder, 1998).Thus, we expect that typologies of parents’ marital, or marriage-like relationship, history (particularly, those of mothers –

hereafter referred to as mothers’ marital history), based on these temporal relationship properties, may have unique long-term influences on young adults’ health outcomes. Consistent with the life course perspective, we utilize the life coursepath-dependent mechanism to illustrate these long-term health influences (DiPrete & Eirich, 2006; Elder, 1998; O’Rand &Hamil-Luker, 2005; Willson, Shuey, & Elder, 2007). The path-dependent mechanism denotes that early life circumstancesinfluence the later health outcomes of an individual through the individual’s experiences over the life course.

Wickrama), ltk501@uga.edu (T.K. Lee), cwalker1@uga.edu (C.W. O’Neal).

er Ltd on behalf of The Foundation for Professionals in Services for Adolescents.

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In the present investigation, the path-dependent mechanism explains how mothers’ marital history influences youngadults’ health through family processes and adolescent developmental processes. That is, mothers’ stressful marital historiesare expected to influence adverse family processes, including family economic problems and ineffective parental practices(Gershoff, Aber, Raver, & Lennon, 2007; McConley et al., 2012). In turn, economic problems and ineffective parental practices,particularly parental rejection, are expected to influence adolescent psychosocial adjustment (Conger, Conger, &Martin, 2010;Wickrama et al., 2008), which have consequences for young adults’ mental and physical health outcomes (e.g., Vujeva &Furman, 2011).

Previous research focusing on the associations between parents’ marital history and the health outcomes of youth hasbeen fragmental and has not adequately investigated these associations in a comprehensive manner over the early life course.Moreover, most existing literature on parents’ marital history and the developmental outcomes of youth has mainly focusedon youth’s romantic relationship outcomes (e.g., Amato, 2004). To our knowledge, no study has investigated the influence ofmothers’ marital history on young adults’ physical health outcomes.

Using data from 12,424 adolescents and their mothers over 13 years in the nationally representative National LongitudinalStudy of Adolescent Health (Add Health), the present study investigates these associations in a comprehensive manner. Asshown in the theoretical model illustrated in Fig. 1, the present study specifically examines (a) the path-dependent mech-anisms involving family processes and adolescent adjustment problems through which mothers’ marital history influencesthe health outcomes of young adults (paths B1, B2, and B3) and (b) other unspecified paths linking both mothers’ maritalhistory (path A1) and family processes (path A2) to the health outcomes of young adults. As Fig. 1 indicates, all of thesepathways may additively influence young adults’ health over the life course.

Whereas cross-sectional measures of family structure provide a static view of the family context in which children areraised (Hagestad, 2003), our life course investigation of young adults’ health emphasizes the need to consider the maritalhistory trajectories of mothers over time (i.e., patterns of change and stability) for several reasons. First, inter-individualvariation (heterogeneity) in trajectories of mothers’ marital history is greater than the variation in cross-sectional measureof family structure because cross-sectional family structure does not reveal the intricacies in mothers’ timing, transitions, anddurations of marriage (Avison, Davies, Willson, & Shuey, 2008). Second, our investigation of change and stability of mothers’marital history provides information about chronic and cumulative stress exposure of mothers over a significant number ofyears (Davies, Avison, & McAlpine, 1997). Third, our investigation of mothers’ marital history may capture the longitudinalfamily context in which children grow up over their childhood and early adolescence. Thus, we argue that marital historytypologies of mothers may better explain health outcomes of young adults than cross-sectional measures of family structure.We will use latent class analysis (LCA) to empirically identify typologies of marital history trajectories of mothers based onavailable information over 19 years, as we will discuss in the analysis section.

The persistent influence of mothers’ marital history on health outcomes of young adults

Life course research has increasingly focused on the long-term persistent influence of early disadvantages that regulatehealth inequalities over the life course. As previously indicated these long-term influences may operate through path-dependent mechanisms over the life course.

Path-dependent mechanisms: family processes

As shown in Fig. 1, paths B1 to B3 illustrate the persistent effect of early adversities on young adults’ health through path-dependent mechanisms involving family processes (O’Rand & Hamil-Luker, 2005), which suggests that early adverse expe-riences are linked to later failures in a successively contingent manner, creating a chain of insults from childhood/earlyadolescence to adulthood, resulting in health problems during young adulthood (Wickrama et al., 2008). That is, the asso-ciation between mothers’ stressful marital history, captured by timing, duration, and instability, and young adults’ health ismediated by adverse family processes and adjustment problems (cognitive, behavioral, and psychological vulnerabilities [orcompetencies]) in youth. These mechanisms are discussed in the paragraphs that follow.

Fig. 1. The theoretical framework.

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Mothers’ marital history and family processesAs depicted by path B1 in Fig. 1, we expect that mothers’marital history influences family economic problems and parental

practices (Sun & Li, 2001; Wu, Hou, & Schimmele, 2008). Carlson, McLanahan, and England (2004) showed that women oftentransition in and out of marriages and marriage-like relationships due to low supportiveness, low relationship commitment,partners with substance use problems, high levels of conflict, and physical violence. Thus, children of parents with frequentmarital transitions may have experienced more stressful family circumstances. Furthermore, multiple sources of stress maystem frommothers’ frequent relationship transitions including loss of social relations/resources, residential moves, change inemployment, and economic problems (Amato, 2004; Cavanagh & Huston, 2006). Also, these changing family circumstancescreate ineffective parent–child relationships, a chaotic family context, and sense of insecurity. These stressors may haveserious developmental consequences for children and adolescents. Yet, the influence of these stressful family experiencesmay vary based on the child’s age. Thus, we expect that each marital history typology may lead to different stressful familyexperiences that may proliferate in distinct ways over the child’s early life course (different etiological processes) with uniquedevelopmental and health consequences. But less is known about these developmental-health processes stemming fromparents’ marital history.

Family economic pressure. Economic hardship is often a product of single parent households with only one source of income.However, in terms of experiencing family economic hardship, recently single mothers and mothers who have experiencedmultiple disruptions may differ frommothers who were single parents for a long duration. These consistently single mothersmay have overcome economic problems over time or made successful adjustments to minimize economic hardship. Stressfulfamily economic conditions associated with disrupted marital relations and adverse family economic conditions have psy-chological consequences for parents. Distressed parents are more likely to be irritable, authoritarian, and rejecting, oftenresulting in ineffective parenting practices (Burke, 2003; Conger et al., 2002; Wong, 2006).

Ineffective parental practices. Previous literature has shown that children of consistently single mothers may experience earlysocialization deficiencies, a lack of parental monitoring, and chronically low family income that can set the stage for lateradjustment and health problems (Hao & Xie, 2002; Wu & Martinson, 1993). Similarly, children of mothers with early maritaldisruption (during early childhood) may also experience poor quality parent–child relationships, which may lay a foundationfor later adjustment problems (McLanahan, 1985; Yabiku, Axinn, & Thornton, 1999). In contrast, other research suggests thatthe stability of any given family structure (i.e., longer duration of relationships or single status) may be more beneficial forchildren’s adjustment than changes in family structure (Cavanagh, Crissey, & Raley, 2008). This may be due to the fact thatconsistency in family type allows the family members to negotiate and set family expectations, practices, and rules (Wu &Martinson, 1993).

Recent research has shown that single mothers and those who experience relationship disruptions may engage in moreineffective parental practices than married mothers (McConley et al., 2012). Changes in parents’ marital status, includingremarriage or divorce, may shift parents’ focus from parenting to their romantic relationship (Carlson et al., 2004). This mayalso result in ineffective parenting, such as parental rejection (Wood, Repetti, & Roesch, 2004). Similarly, the timing andduration of mothers’ marital transitions may also shift their focus and influence their parental practices. This information isnot captured by cross-sectional measures of marital status.

Furthermore, instability in a parent’s relationship is associated with lower levels of parental control and supervision ofchildren. Particularly, ‘short-term’ step-parents may not have the interest and authority to monitor their step-children(Cavanagh, 2008; Teachman, 2003). These circumstances are most salient during the critical period of adolescencebecause family expectations and rules are less well defined and enforced (Cavanagh, 2008). In the present investigation, wefocus particularly on parental rejection because research suggests that parental rejection is one of the most consequentialineffective parental practices (Wickrama et al., 2008).

Family processes and adolescent psychosocial adjustmentAs shown in path B2 in Fig. 1, family economic problems and ineffective parenting influence a broad variety of adolescent

adjustment problems including psychological, cognitive, and behavioral vulnerabilities (Conger & Conger, 2004; Wickramaet al., 2008). Children raised by divorced or single mothers are more likely to experience persistent economic hardship thanchildren of consistentlymarried parents (Sun& Li, 2001). Particularly, children of frequently divorced or remarriedmothers aremore likely to experience severe economic problems aswell as economic uncertainty and insecurity. Also, research has shownthat those experiencing family economic problems in early childhood, on average, have negative feelings of self (Prawitz,Kalkowski, & Cohart, 2013; Spence, Najman, Bor, O’Callaghan, & Williams, 2002). That is, experiencing family economicproblems may erode children’s psychological resources, such as self-esteem, which are linked to psychological vulnerabilitiesincluding depressive symptoms. In addition, family poverty limits parents’ ability to invest in their children, which may bedetrimental for their cognitive development (reflected in impaired educational performance) (Bradley & Corwyn, 2002).

Some research suggests that youth from economically disadvantaged families have limited opportunities thereby reducingthe “opportunity costs” of delinquent behaviors (Upchurch, Levy-Storms, Sucoff, & Aneshensel, 1998). Other research alsosuggests that family economic problems lead to adolescent delinquency because of their association with hostile and violentfamily contexts (Jarjoura, Triplett, & Brinker, 2002). In turn, adolescents exposed to violent and hostile contexts are morelikely to engage in delinquent or oppositional behavior (Fagan & Wright, 2012).

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Furthermore, numerous empirical studies provide evidence for the association between ineffective parenting practicesand adolescents’ delinquent behavior, impaired self-esteem, and remedial educational performance (Branje, Hale, Frijns, &Meeus, 2010; Rohner & Britner, 2002).

Adolescent adjustment and health outcomes

Although we will not test the mechanisms that link adolescent adjustment problems to adverse health outcomes, webriefly indicate numerous psychosocial mechanisms documented by previous research that may explain this influence.Impaired psychological (e.g., self-esteem) and cognitive (e.g., academic competency) resources increase the propensity toengage in risky lifestyle behaviors. The behavioral choices of youth (e.g., smoking and drinking) with impaired cognitiveabilities (e.g., academic performance) may be based on the easy gratification of desires as well as their inability to appreciatelong-term consequences and lack of perseverance in achieving goals (Hirschi & Gottfredson, 1993; Simons, Simons, Conger, &Brody, 2004). Furthermore, youth with impaired self-esteem often drift toward risky lifestyles because their lack of self-worth may undermine positive lifestyle behaviors (Macht & Simons, 2000; Umberson, Liu, & Reczek, 2008). In addition,delinquent youth’s lack of social connectedness and lack of attachment to conventional institutions may weaken socialcontrol, which acts as a deterrent to risky health behaviors. It has been well-documented that individuals who frequentlyengage in health-damaging behaviors experience higher rates of disease and illness (House, Strecher, Metzner, & Robbins,1986; Wickrama, Lorenz, Conger, & Elder, 1997) as well as poor mental health (Pisinger, Toft, Aadahl, Glümer, &Jørgensen, 2009; Regier et al., 1990).

Furthermore, through similar psychosocial mechanisms, vulnerable youth may experience stressful life transitionsincluding early school dropout, early cohabitation, and an early transition out of their parents’ home. Research has shown thatsuch stressful precocious, or off-time, life transitions have adverse physical and mental health consequences (Wickrama &Baltimore, 2010; Wickrama et al., 2008). Adolescent adjustment problems may also hinder youth’s socioeconomic attain-ment, which has been shown to have adverse health consequences (Wickrama, Conger, Lorenz, & Martin, 2012).

Unspecified pathways leading to poor health in young adulthood

Even after accounting for the previously discussed adolescent psychosocial and behavioral adjustment problems, asshown in paths A1 and A2, mothers’ marital history and family processes may exert long-term negative consequences onchildren’s physical and mental health. These influences may operate through other life experiences not specified in thecurrent model. For example, the stressful family circumstances stemming frommothers’marital history and family processes,such as family residential instability and parental absence, may have long-term mental and physical health consequences(Pearlin, Schieman, Fazio, & Meersman, 2005). In addition, we expect that mothers’ marital history influences their adultchildren’s health through extra-familial characteristics associatedwith thesemarital histories. For example, research suggeststhat single parents and mothers with unstable marriages live in socioeconomically adverse communities in relatively highpercentages (Sampson, Raudenbush, & Earls, 1997) due to both social selection and social causation (social selection makescommunity adversity a mediator between mothers’ marital history and young adults’ health). The threatening, noxious, andhazardous (‘community stress’) environment, and related social disorganization, in these communities negatively influencesyouth’s health over and above the influence of family circumstances (Leventhal & Brooks-Gunn, 2000) by initiating andmaintaining adverse biological processes (Singh-Manoux, Ferrie, Chandola, & Marmot, 2004).

Biological research has shown that chronic stressful experiences contribute to poor physical health through a number ofphysiological mechanisms including the activation of the hypothalamic–pituitary–adrenocortical (HPA) axis andsympathetic-adrenal-medullary (SAM) system. These biological systems are implicated in one’s ‘allostatic load’ as reflected bypoor glucose control, higher glycosylated values, psychomotor retardation, dysfunction in adrenergic and cholinergic activity,high levels of cortisol, and airway constriction (Dowd, Simanek, & Aiello, 2009; Singh-Manoux et al., 2004). Chronic stress alsocontributes to changes in the immune system, increasing susceptibility to infectious disease and even cancer (Ader, Felten, &Cohen,1991; Herbert et al., 1994; Lovallo, 2005). Furthermore, youth’s sensitivity to these risks increases with age, resulting ina cumulative process (Bauldry et al., 2012).

Also, previous research suggests that those with unsuccessful marriages often engage in health-risk behaviors, such assmoking and alcohol use (Fleming, White, Oesterle, Haggerty, & Catalano, 2010), which may influence their children’s healthdirectly and increase the likelihood that they will also engage in risky health behaviors (Wickrama, Conger, Wallace, & Elder,1999). In addition, mothers with frequently changing relationships are more vulnerable to infectious diseases and experiencerelatively poor health (Lorenz, Melby, Conger, & Xu, 2007), which may influence the health of their offspring.

Specific study hypotheses

a. Mothers’ marital history (W1, 1995) will influence family processes including family economic hardship and ineffectiveparenting practices (parental rejection) (W1, 1995).

b. Family processes (economic hardship and parental rejection) will influence adolescent psychosocial adjustment (self-esteem, delinquent behavior, academic performance) (W3, 2001).

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c. Adolescent adjustment (self-esteem, delinquent behavior, academic performance) at W3 (2001) will influence thephysical and mental health of young adults (W4, 2008) after controlling for physical and mental health during adoles-cence (W3, 2001).

d. Family processes (economic hardship and parental rejection) (W1, 1995) will influence young adults’ physical and mentalhealth (W4, 2008) after accounting for the mediating role of adolescent adjustment (W3, 2001).

e. Mothers’ marital history (W1, 1995) will influence young adults’ physical and mental health (W4, 2008) after accountingfor the mediating roles of family processes (W1, 1995) and adolescent adjustment (W3, 2001).

Method

Sample

Data for this study came from a nationally representative sample of adolescents participating in the National LongitudinalStudy of Adolescent Health (Add Health). In 1995, baseline (Wave 1) data were derived from a complex stratified cluster-sampling of middle and high school students, yielding 20,745 respondents of 12–19 years of age (average age was 15.5years), from 134 middle and high schools. To ensure diversity, the sample was stratified by region, urbanicity, school type(public vs. private), racial composition, and size. Second and third wave data were collected in 1996 and 2001 (N2 ¼ 14,738and N3 ¼ 15,100). We used in-home interview data from parents who responded to marital history questions in Wave 1 andadolescents who participated in Waves 1, 3, and 4 (young adulthood). Thus, the study sample included 12,424 adolescents.We usedWave 1 sample weights in the analyses. More information about Add Health is available at http://www.cpc.unc.edu/projects/Add Health. The final sample consisted of approximately 53% women, and 39% of respondents reported a minorityracial/ethnic status with the largest percentages reported for African American, Hispanic, Asian, and Native American,respectively.

We used Mplus software (version 7) to impute data for all missing data in Waves 1 (except for marital history data) andWave 3. Thus, the analytical sample included only non-imputed health outcome data in Wave 4 and marital history data inWave 1. A total of 19.97% of the data were imputed. Attrition and missing data analysis showed that adolescents whoparticipated in all four waves were slightly younger but otherwise confirmed that there was little difference between ado-lescents with missing data in our study sample and those with complete data.

Measures

Physical illnessA count of eight physician-diagnosed diseases and health problems and 11 sexually transmitted infections (STIs) assessed

young adult respondents’ physician-diagnosed physical illness at Wave 4 (2008). Examples of the diseases and STIs assessedinclude diabetes, heart disease, asthma, high blood pressure, genital warts, gonorrhea, and HIV/AIDS. A count of the eightphysician-diagnosed diseases and health problems at Wave 3 (2001) was also included in the model as a control variable.

Depressive symptomsAtWave 3 (2001) andWave 4 (2008), eight parallel items from the Center for Epidemiological Studies of Depression Scale

(CES-D; Radloff, 1977) were used to assess adolescent respondents’ distress feelings (e.g., “felt depressed and sad”) in the pastweek. Scale responses ranged from 0 ¼ never or rarely to 3 ¼ most of the time or all of the time. Positive affect items werereverse coded before summing all items. This resulted in an index of depressive symptoms ranging from 0 to 24. The scale hadadequate internal reliability (a ¼ .80 for both waves).

Mothers’ marital instability, duration, and timing (Wave 1, 1995)Latent class analysis (LCA) was used to develop five typologies of mothers’ marital history from variables indicating

mothers’ marital instability, duration, and timing (see the Analysis section for more detail). Marital instability assessed thenumber ofmarriages ormarriage-like relationships from1977 to 1995. The total number of partnered years from1977 to 1995(ranging from 0 to 19 years) captured relationship duration. Four variables representing the number of years partneredwithinfour time periods captured relationship timing (the latest period D1 [1990–1995], the late period D2 [1985–1990)], the earlyperiod D3 [1980–1985], and the earliest period D4 [1977–1980].

Family economic pressureParents responded to five dichotomously scored hardship items (0 ¼ no, 1 ¼ yes) assessing whether any member of the

household received social service benefits, including social security, supplemental security income, aid to families withdependent children, food stamps, or housing subsidies. The sum of these five items assessing family poverty yielded aninternally consistent index (a ¼ .85).

Parental rejectionFive items rated on a scale ranging from 1 ¼ strongly agree to 5 ¼ strongly disagree were summed. The items asked the

reporting parent whether they “got along well with the adolescent,” “made decisions about life together with this child,” “did

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not understand this child,” “felt this child cannot be trusted,” and “felt this child interferes with his/her activities.” The ratingsfor three items were reverse scored so that higher scores indicate greater parental rejection for all items. This scale hadadequate internal consistency (a ¼ .96).

Delinquent behaviorTwelve items from Wave 3 (2001) were used to assess adolescent delinquent behavior. This composite scale included

items such as whether and how often the adolescent engaged in a serious physical fight and deliberately damaged propertythat did not belong to them. Responses for each item ranged from 0 ¼ never to 3 ¼ five times or more. Sum scores werecomputed (possible range of 0–36) with higher scores indicatingmore delinquent behavior during adolescence. The scale hadgood internal consistency (a ¼ .78).

Academic competenciesAt Wave 1 (1995), adolescent respondents reported their recent letter grade point average (GPA) in school mathematics,

social studies, and science classes. These letter grades were transformed into a 4-point numerical scale (4 ¼ A, 3 ¼ B, 2 ¼ C,1 ¼ D). Sum scores were computed, ranging from 3 to 12 with higher scores indicating greater academic competencies.

Self-esteemAt Wave 2 (1996), respondents’ rated their agreement with 7 items assessing their feelings of self-worth. Sample items

include: “You have a lot of good qualities” and “You have a lot to be proud of.” Responses were given on a five-point scaleranging from 1¼ strongly agree to 5¼ strongly disagree. Items were reverse scored so that higher scores indicate the presenceof more self-esteem. Cronbach’s alpha indicated high internal consistency (a ¼ 86).

Race/ethnicityAdolescents reported their race/ethnicity at Wave 1. Dichotomous variables were used to assess race/ethnicity enabling us

to compare each minority race/ethnicity category to White adolescents (e.g., Black ¼ 1, otherwise ¼ 0). When the variablesrepresenting African American, Hispanic, and Asian races/ethnicities are included in the model (without the White category)the regression coefficients for each race/ethnicity category can be interpreted with reference to Whites.

Mothers’ educationWe controlled for mothers’ formal education at Wave 1 using 9 categories ranging from 1 ¼ 8th grade or less to

9 ¼ professional training beyond a 4-year college or university.

AgeWe controlled for adolescent age in years as reported in Wave 1.

GenderWe controlled for the gender of adolescent respondents (0 ¼ male; 1 ¼ female).

Analysis

Identification of typologies of mothers’ marital historyAvison et al. (2008) successfully used latent class analysis (LCA) to identify marital history typologies of mothers based on

available information aboutmarital status at three time points and information about partnered duration over 14 years. Theselatent classes of mothers’marital history predicted maternal mental health. We apply a similar approach, latent class analysis(LCA), to empirically identify typologies of mothers’marital history (hereafter referred to as classes), but we usemore detailedinformation about relationship change and stability (duration). These data reflect three important temporal characteristics ofrelationships that have been shown to influence the developmental outcomes of children: instability, timing, and duration.Accordingly, as indicated in the measurement section, we use six measures (indicators) to capture these temporal charac-teristics and identify latent classes in LCA.

Using these six indicators, we identified five classes of mothers’ marital history. According to the profiles of these latentclasses, these five classes largely represent: (1) mothers who experienced few disruptions (average number of disruptionsclose to one, m ¼ 1.27; hereafter referred to a single disruption) following a shorter-duration marriage, (2) mothers whoexperienced few disruptions (m ¼ 1.37; hereafter referred to as a single disruption) following a longer-duration relationship,(3) mothers who experiencedmultiple relationship disruptions early, (4) mothers who experiencedmultiple disruptions overan extended period of time, and (5) consistently married mothers.

Nested modelingNext, we examined two incrementally nested models to elucidate mediating processes. The first model examined the

effect of mothers’ marital history and family processes on young adult health outcomes. In the second model we addedadolescent adjustment variables as mediating processes. Young adult health outcomes in 2008 were predicted after con-trolling for health status in 2001 in order to examine change in health from 2001 to 2008. The Mplus (version 7) COMPLEX

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command was used to account for the nested structure of the school-based design used within the Add Health study. Modelfit was evaluated using the chi-square/degrees of freedom, comparative fit index (CFI), and the root mean square error ofapproximation (RMSEA). The Mplus software uses Sobel’s test to evaluate indirect effects.

Results

Table 1 presents descriptive statistics of the study variables. The mean scores of physical illness in W3 and W4 were .58and .69, respectively. Also, the mean scores of depressive symptoms in W3 and W4 were 4.02 and 4.71, respectively.

First, we identified consistently married mothers who reported one relationship and a total duration of 19 years. Then, weperformed LCAwith the remaining sample to identify latent classes of mothers’marital history (see Table 2). The results of theLCA showed that the AIC statistic decreasedwith the increasing number of classes from one to five indicating an improvementin the model fit. However, the solution with five classes contained three classes with relatively small class sizes (approxi-mately 100 respondents). Consequently, the 4-class solutionwas chosen because it provided substantively meaningful classesand the next best fitting model. Thus, there were a total of five classes after including the consistently married class. Table 3provides temporal characteristics of each class.

Fig. 2 illustrates the persistent influence ofmothers’marital history and family processes on physical illness and depressivesymptoms in young adulthood before considering the impact of adolescent adjustment. Fig. 3 illustrates the full model afterincluding indicators of adolescents’ psychosocial adjustment. As shown in Fig. 3, following the path-dependent mechanism,we found evidence that mothers’ marital history at Wave 1 (1995) may create a ‘chain of insults’ leading to young adults’health problems (Wave 4, 2008). More specifically, compared to consistently married parents, mothers belonging to othermarital history classes (i.e., single disruption following a shorter-duration relationship, single disruption following a longer-duration relationship, multiple early disruptions, and multiple disruptions occurring over an extended period of time) re-ported greater economic pressure (b ¼ .10, .10, .07, and .07, respectively). Mothers in the single disruption or a shorter-duration relationship class often reported more rejecting parenting (b ¼ .04). In turn, economic pressure served as aninfluential family process for academic competencies (i.e., GPA, b ¼ �.07) and adolescent depressive symptoms (b ¼ .05).Adolescents experiencing parental rejection had less psychological resources (i.e., self-esteem, b ¼ �.16), more behavioralvulnerabilities (i.e., delinquency, b ¼ .03), fewer academic competencies (b ¼ �.17), and poorer adolescent health outcomes(depressive symptoms and physical illness; b ¼ .10 and .05, respectively) than those with more positive experiences withparents.

Moreover, adolescents with fewer psychological resources and academic competencies and more behavioral vulnerabil-ities experienced more depressive symptoms (b ¼ �.05, �.08, and .05) as young adults. Their psychological resources andbehavioral vulnerabilities were also associated with their physical health in young adulthood (assessed by physical illness;b ¼ �.04 and .04). Most notably, this influence existed after controlling for physical illness and mental health in adolescence,indicating that adolescent psychological resources, academic competencies, and behavioral vulnerabilities influenced thechange in physical and mental health outcomes from adolescence (W3) to young adulthood (W4).

In addition, there was also support for unspecified mechanisms linking mothers’ marital history to the health of youngadults. For instance, mothers’ marital history classes directly influenced indicators of adolescent adjustment. Adolescentswhose mothers experienced a single relationship disruption (for both shorter and longer-duration relationships) and thoseexperiencing their mothers’multiple disruptions over an extended period of time, compared to consistentlymarriedmothers,reported more physical illness as adolescents (Wave 3) (b ¼ .06, .03, and .04, respectively). More importantly, independent ofthe effect on adolescent physical health, two of the marital history classes (i.e., single relationship disruption following a

Table 1Descriptive Statistics of Study variables (N ¼ 12,424).

Variables (wave) Mean/proportion SD Range

Economic pressure (W1) 1.37 .87 1.00–6.00Parental rejection (W1) 9.45 2.75 2.00–22.00Self-esteem (W3) 19.70 1.89 6.00–31.00Delinquency (W3) 2.71 3.35 .00–30.00GPA (W1) 8.65 2.81 1.00–13.00Depressive symptoms (CES-D, W3) 4.02 3.62 .00–24.00Depressive symptoms (CES-D, W4) 4.71 3.69 .00–22.00Physical illness (W3) .58 1.18 .00–26.00Physical illness (W4) .69 .83 .00–5.00White 54% .50 0–1Black 22% .41 0–1Hispanic 18% .34 0–1Asian 6% .24 0–1Mothers’ education (W1) 5.49 2.37 1.00–10.00Age (W1) 16.10 1.73 12.00–21.00Gender (female) 53% .50 0–1

Table 2Criteria used to decide on optimal solution for number of latent classes and mean score.

Number of classes BIC LMR

1 96,044.892 85,526.06 548.57***3 81,560.04 150.37***4 78,174.26 861.79**5 76,367.97 1351.24

Notes. BIC ¼ Bayesian Information Criteria, LMR ¼ Lo–Mendell–Rubin Likelihood Ratio Test,**p < .01, ***p < .001. Based on LMR test, the 4-class solution is the best model. Thus, including theconsistently married class, we can identify 5 classes.

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longer-duration relationship and multiple early disruptions) directly influenced young adults’ physical illness at Wave 4(b ¼ .03 and .04, respectively).

Some demographic differences were found within the model. For instance, although mothers’ education did not varysignificantly acrossmost of themarital history classes, therewas one statistically significant difference. Mothers’ experiencingmultiple early disruptions reported less education than consistently married mothers (r ¼ �.03, not shown in Fig. 3).

Racial and gender differences were also found. More specifically, compared to Whites, Blacks generally reported moreeconomic pressure (b ¼ .12) and fewer academic competencies (b ¼ �.06), whereas Asians reported more academic com-petencies (b ¼ .03). Hispanics also reported less parental rejection, lower psychological resources, and fewer academiccompetencies (b ¼ �.04, �.05, and �.04, respectively) thanWhites. Regarding health outcomes, Blacks generally fared worsethan Whites during adolescence and young adulthood in their reports of physical illness (b ¼ .09 and .04, respectively) anddepressive symptoms (b ¼ .04 and .03, respectively), whereas Asians reported better physical health than Whites in youngadulthood (b ¼ �.04). Compared to Whites, both Hispanics and Asians experienced more depressive symptoms in adoles-cence (b ¼ .06 and .03) (Table 4).

We also examined the mediating effect of mothers’ stressful marriage history on young adults’ physical health anddepressive symptoms. According to Sobel’s tests several significant indirect effects were evident. For all four stressful maritalhistory classes, there were statistically significant indirect effects on young adults’ reports of their physician-diagnosedphysical illnesses through economic pressure, parental rejection, and self-esteem. In addition, the associations between allof the mothers’ stressful marriage history classes and depressive symptoms were significantly mediated by economicpressure, parental rejection, self-esteem, delinquency, and academic performance.

Discussion

The primary goal of this studywas to examine the long-term health effects of mothers’marital history across young adults’early life course. Existing literature is fragmented with respect to theoretical and analytic models. To our knowledge, noprevious studies have incorporated a breadth of constructs including mothers’ marital history, family processes, adolescentpsychosocial adjustment, as well as young adult mental and physical health outcomes in the same analytical framework.Thus, the present study responded to this paucity of research by examining a theoretical model that explored severalpathways linking mothers’ marital history to young adults’ physical and mental health outcomes. We used life course path-dependent mechanisms to illustrate long-term pathways linking mothers’ marital history to the health of young adults.

We empirically identified five typologies of mothers’ marital history using latent class analysis (Muthén, 2004) based onthe frequency of marital disruption, timing of marital disruption (early/late), and duration of relationships. These empiricallyidentifiedmarital history typologies provided an acceptable fit to the data and were substantively meaningful. In doing so, weassessed the stability and change in family structure over the 19 years prior to the first wave of data collection. This periodoverlaps with the childhood and early/mid adolescence of most respondents in the sample. We expected that each maritalhistory typology may have unique developmental and health consequences due to different temporal characteristics of thetypologies. The results showed that all of the stressful marital history trajectories have unique long-term health effects

Table 3Mean score of indicators as a function of latent class membership.

Indicator (s) Single marital disruption/short duration (n ¼ 2013,16.9%)

Single marital disruption/long duration (n ¼ 4692,37.8%)

Multiple earlymarital disruptions(n ¼ 173, 1.4%)

Multiple recentmarital disruptions(n ¼ 142, 1.1%)

Consistent married(n ¼ 5314, 42.8%)

Marital frequency 1.27 1.37 3.75 3.41 1.00Marital duration (yrs.) 3.40 14.79 9.86 12.26 19.001991–1995 (D1) 3.73 4.95 3.75 3.35 5.001986–1990 (D2) 1.06 4.98 4.19 2.03 5.001981–1985 (D3) 1.01 4.97 1.45 4.14 5.001977–1980 (D4) 3.22 3.81 1.48 2.76 4.00

Multiple Recent Disruptions

Physical Illness

Single Disruption / Short Duration

Multiple Early Disruptions

Single Disruption / Long Duration

Parental Rejection

Economic Pressure

Depressive Symptoms

.10***

.07***

.08***

.10***

.06**

Mothers’ Marital History

Wave1 (1977-1995)

Young Adults’ Health

Wave 4 (2008)

Family Processes Wave 1 (1995)

.04**

.16***

.04*

.05**

.07***

.04**

.03*

.04**

Model fit(df) =.00 (0)

RMSEA= .00 CFI /TLI=1.00 / 1.00

.04**

.04**

x2

Fig. 2. Mediation of family process between parent’s marital history and depressive symptoms/physical illness of young adults. Note. Mother’s education iscontrolled; standardized coefficients are shown; non-significant pathways are not shown; consistent marriage is the reference group for the marital history;*p < .05, **p < .01, ***p < .001.

K.(K.A.S.) Wickrama et al. / Journal of Adolescence 36 (2013) 1039–1051 1047

compared to the consistently married typology. These unique influences of mothers’ marital history typologies on healthoutcomes of young adults would have not been revealed, if a cross-sectional measures of marital status or family structurewas used.

In general, results show that relationship timing, frequency, and duration are important temporal characteristics ofmothers’ marital history associated with the pathways to young adult health. As shown in Fig. 3, inconsistent with ourexpectation, all stressful mothers’marital history classes were associated with increased family economic pressure relative tothe consistentlymarried group. This suggests that any pattern of mothers’ stressful marital history has negative consequencesfor family economic conditions. Only one class of mothers’ marital history (single disruption with short marital duration)influenced parental rejection. Thus, when considering only the two single-transition groups (i.e., differing by short and longduration relationships), this suggest that marital duration, or marital stability, is important for single parents’ effectiveparenting. Both multiple transition groups did not directly influence parental rejection. It seems that these influences operateprimarily through family economic pressure.

As we previously argued, unspecified pathways can also capture the long-term health effects of mothers’ marital history(path A1) and family processes (path A2) on health outcomes of young adults. The results also showed the direct associationof mothers’marital history on the physical health of young adults. Thus, it seems that part of the long-term effect of mothers’marital history on young adults’ health outcomes operates through unspecified life course experiences (i.e., mediators).Particularly, the results presented in Fig. 3 and Table 3 show that the marital history classes indicating mothers’ early maritaldisruptions (i.e., both the early multiple transition group and the single-transition group with longer duration (in this groupsingle transition appeared to be occurred prior to 1977)) influenced the health of young adults directly, regardless of familyprocesses and adolescent health status. These influences seem to operate through unspecified pathways, such as earlydamages, which may manifest in later years.

None of mothers’marital history classes directly influenced depressive symptoms of young adults in Wave 4, rather theseinfluences operated through family processes and adolescent adjustment. Consistent with the hypothesized path-dependentmechanisms, early adverse experiences are linked to later failures in a successively contingent manner, creating a life courseprocess from childhood/early adolescence to adulthood. The results summarized in Fig. 3 show that the influence of mothers’

Fig. 3. The result of hypothesized model for health problems of young adults. Note. Mother’s education is controlled; standardized coefficients; non-significantpathways are not shown; consistent marriage is a reference group of marital history; correlation coefficient between depressive symptoms and academicperformance and between physical illness and depressive symptoms in W3 are �.07*** and .13***, respectively; *p < .05, **p < .01, ***p < .001.

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stressful marital history on young adult health outcomes (residual changes from 2001 to 2008) operated through adversefamily processes and adolescent adjustment problems including impaired self-esteem, poor academic performance, anddelinquent behavior. The results show that numerous indicators of poor adolescent adjustment are influenced by familyprocesses and, in turn, contribute to the impaired mental and physical health of young adults.

Furthermore, these observed direct associations may be a result of exposure to extra-familial stressful circumstancesstemming frommothers’marital history including adverse community conditions. Chronic stressmay link directly to physicalhealth problems through the disruption of physiological functions because it involves an allostatic load, the cumulative wearand tear on the body’s systems owing to repeated adaptations to stressors (Dowd et al., 2009). This involves a number ofphysiological mechanisms including the HPA and SAM systems (Ader et al., 1991; Herbert et al., 1994).

It is interesting that the results show only one association between a family process variable (economic pressure) andyoung adults’ health (bypassing adolescent adjustment) (Path A2). It seems that stressful family circumstances primarilyoperated through adolescent adjustment problems. In sum, the results of our theoretical model provides support for thenotion of a ‘chain of insults’ that sequentially linksmothers’marital history to adverse family processes (particularly economic

Table 4The effects of race, gender, and the level of mother education on endogenous variables in the hypothesized model (i.e., full model).

Predictors Economicpressure

Parentalrejection

Self-esteem Delinquency Academicperformance

Physicalillness (W3)

Depressivesymptoms(W3)

Physicalillness (W4)

Depressivesymptoms(W4)

b SE b SE b SE b SE b SE b SE b SE b SE b SE

Black .12*** .02 .01 .01 .02 .01 �.01 .01 L.06*** .01 .09*** .02 .04** .01 .04* .01 .03* .01Hispanic .03 .02 L.04** .02 L.05*** .01 .01 .01 L.04** .02 .02 .01 .06*** .02 �.01 .01 .00 .01Asian .01 .01 .01 .01 .00 .01 �.01 .01 .03* .01 �.01 .01 .03** .01 L.04*** .01 �.01 .01Sex �.01 .02 �.02 .02 .15*** .01 .22*** .01 L.09*** .01 L.12*** .01 L.09*** .01 L.16*** .01 L.07*** .01Mother

educationL.22*** .02 �.02 .01 .02 .01 .06 .02 .17*** .01 �.01 .01 L.05** .02 �.01 .01 L.03* .01

Notes. Standardized coefficients. The reference for minority races/ethnicities is White. Statistically significant differences are indicated in bold.SE ¼ standardized error, *p < .05, **p < .01, ***p < .001.

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processes), adverse family processes to adolescent adjustment problems, and adolescent adjustment problems to youngadults’ health problems.

Although, not tested in the present study, we also argue that the influence of mothers’ marital history may accumulateover time in several ways. First, the health effects of exposure (or the vulnerability) to stressful circumstances may increaseover time largely due to the decrease in ‘biological robustness’ of youth (age-by-exposure interaction). This cumulativeprocess is supported by the fact that adverse circumstances predicted young adults’ residual change in health from 2001 to2008. Second, the total influence of mothers’ marital history on young adults’ health may increase over time through theproliferation of new pathways over the life course.

Overall, findings from the present study are consistent with the hypothesized model, but several factors potentially limitthe scope and generalizability of the results. First, the present study used mostly self-report measures. Replication usingclinical health measures would alleviate concerns regarding potential self-report biases related to the measures used in thisstudy. Second, the six-year measurement interval between adolescence and young adulthood used in the present study maynot reveal the intricacies of changes in health outcomes. Third, potential confounding variables may exist, such as a disruptedadolescent transition (e.g., dropping out of school), which may influence both adolescent self-esteem and young adult healthoutcomes causing a spurious association. Fourth, we have not tested the potential moderating role of youth’s individualcharacteristics (e.g., self-esteem), characteristics of the transition from adolescence to young adulthood (e.g., precocioustransition events), and young adults’ socioeconomic context on observed associations between predictors and young adulthealth outcomes. Future research should extend this investigation by incorporating these missing mediators andmoderators.Fifth, we have only focused on mothers’ marital history during childhood and early adolescence from 1977 to 1995 and notduring later years from 1995 to 2008. Mothers’ marital changes and stability during this period may have also influencedhealth outcomes of young adults. Finally, genetic research has shown that variants of certain genes implicated in neuro-transmission (e.g., variants of DRD2 and AVPR1A) are associated with marital disruptions, as well as with mental health andphysical health problems (e.g., Elovainio et al., 2007; Walum et al., 2008). Thus, the association between mothers’ maritalhistory and the health of their offspring may be partially due to heredity (common genetic factors).

Despite these limitations, the present study makes a unique contribution to our knowledge about the influence ofmothers’marital history on the health outcomes of young adults and the influences through family processes and adolescentadjustment. Thus, the findings from this study have several theoretical and practical implications. This study emphasizes theneed for research investigating theoretical and analytical models, which examine longitudinal developmental processes andhealth outcomes over the early life course. That is, research locating micro-level developmental models within life coursecontexts utilizing a long view is needed. Failure to do so may result in incomplete and/or spurious findings. Also, the findingssuggest that socioeconomic adversity in the family of origin is transmitted intergenerationally through the impaired health ofyouth. Consequently, there is a need to integrate social attainment/developmental models and social epidemiological modelsto investigate the intergenerational transmission of socioeconomic adversity. Of particular interest, our finding regarding theunique persistent influence of mothers’ marital history on the health of young adults has critical policy and programimplications.

Authors’ contributions

KASW conceived of the study, participated in its design and drafted the manuscript; TKL performed the statistical ana-lyses; CWO helped to draft the manuscript. All authors read and approved the final manuscript.

Acknowledgments

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. RichardUdry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grantP01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperativefunding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and BarbaraEntwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the AddHealth website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for thisanalysis.

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