A Genetically Informed Study of the Intergenerational
\nTransmission of Marital Instability
\nBrian M. D\u2019Onofrio,
\nDepartment of Psychological and Brain Sciences, Indiana University, 1101 E, 10th Street,
\nBloomington, IN 47405
\nEric Turkheimer,
\nThe Department of Psychology, University of Virginia, 102 Gilmer Hall, P.O. Box 400400,
\nCharlottesville, VA 22904
\nRobert E. Emery,
\nThe Department of Psychology, University of Virginia, 102 Gilmer Hall, P.O. Box 400400,
\nCharlottesville, VA 22904
\nK. Paige Harden,
\nThe Department of Psychology, University of Virginia, 102 Gilmer Hall, P.O. Box 400400,
\nCharlottesville, VA 22904
\nWendy S. Slutske,
\nDepartment of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO
\n65211
\nAndrew C. Heath,
\nDepartment of Psychiatry, Washington University School of Medicine, Campus Box 8134, St.
\nLouis, MO 63110
\nPamela A. F. Madden, and
\nDepartment of Psychiatry, Washington University School of Medicine, Campus Box 8134, St.
\nLouis, MO 63110
\nNicholas G. Martin
\nRoyal Brisbane Hospital Post Office, Queensland Institute of Medical Research, 300 Herston
\nRoad, Q 4029, Brisbane, Australia
\nBrian M. D\u2019Onofrio: bmdonofr@indiana.edu
\nAbstract
\nEnvironmental or genetic influences, or both could account for the increased risk of divorce
\namong the offspring of separated parents. Previous studies have used covariates to statistically
\ncontrol for confounds, but the present research is the first genetically informed study of the topic (sample nursing essay examples by the best nursing assignment writing service).
\nThe investigation used the Children of Twins Design with twins, their spouses, and their young
\nadult offspring (n = 2,310) from the Australian Twin Registry to test whether selection on the
\nbasis of genetic or shared environment factors accounted for part of the inter-generational
\nassociation. The analyses also controlled for measured characteristics of both parents. The results
\nsuggest that both environmentally mediated and genetic risk account for the intergenerational
\ntransmission, supporting the roles of both selection and causation.
\nKeywords
\ndivorce; intergenerational transmission; multilevel models; selection effects
\nNIH Public Access
\nAuthor Manuscript
\nJ Marriage Fam. Author manuscript; available in PMC 2010 July 16.
\nPublished in final edited form as:
\nJ Marriage Fam. 2007 August 1; 69(3): 793\u2013809. doi:10.1111\/j.1741-3737.2007.00406.x.
\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nThe intergenerational transmission of divorce has been found in large samples throughout
\nthe world (see Pryor & Rogers, 2001), including the United States (Greenstein, 1995) and
\nAustralia (Rodgers, 1996). In fact, research has consistently shown that parental divorce is
\none of the strongest predictors of marital instability (Amato, 1999). Researchers have sought
\nto identify possible mediators of the association between parental and offspring marital
\ninstability. Various studies have examined factors such as age at first marriage and
\ncohabitation, differences in perspectives on the costs and benefits associated with marriage,
\nmodeling of unsuccessful relationship and interpersonal skills, mate selection, and lower
\ncommitment to marriage in the offspring of divorced parents (review in Fine & Harvey,
\n2006). Despite their unique foci, all these efforts share one general assumption: Parental
\ndivorce increases the risk for offspring marital instability through some causal mechanisms
\n(e.g., Amato, 2000). We refer to this view as the causal assumption.
\nIt is possible, however, that the statistical relation between parental and offspring marital
\ninstability is not causal. Selection factors that lead to marital instability in both generations
\nmay be responsible for the association (Amato, 2000; Emery, 1999). Figure 1 presents a
\ngraphical representation of two of the main classes of confounds when studying
\nintergenerational associations. First, common environmental factors may account for a
\nstatistical relation between a parental and an offspring characteristic. For example, couples
\nliving in poverty are more likely to separate, and socioeconomic status could be a third
\nvariable that explains the intergenerational association. Statistical procedures can control for
\npossible environmental selection factors, such as socioeconomic status (reviews in Amato,
\n2000; Emery), but such analyses cannot control for environmental factors that have not been
\nmeasured or have been measured inaccurately. Further, no study has included in-depth
\nassessments of characteristics and psychopathology in both parents. This is a major
\nlimitation, given that parental psychopathology is associated with changes in family
\nfunctioning, and the transmission of psychopathology could account for some of the
\nintergenerational transmission of divorce. Studies of the consequences of divorce that have
\nincluded measures of maternal psychopathology have underscored the important role of
\nselection factors (Capaldi & Patterson, 1991; Emery, Waldron, Kitzmann, & Aaron, 1999).
\nTherefore, exploring the risks for offspring relationship instability associated with the
\npsychopathology and demographic characteristics of both parents will provide a more
\ncomplete understanding of the processes responsible for the transmission of relationship
\ninstability.
\nSecond, genetic risks might also account for the association between parent and offspring
\nmarital instability, an example of passive gene-environment correlation (Scarr &
\nMcCartney, 1983). Passive gene-environment correlation occurs when genetic factors that
\ninfluence parental characteristics are passed down to the offspring and confer risk to the
\nchildren. In the most extreme case of genetic confounds, the association between the familial
\nrisk factor and offspring adjustment is fully accounted for by shared genetic liability in both
\ngenerations, rendering the parental variable a marker for genetic selection rather than
\nenvironmental causation. Because twin studies have shown that genetic factors influence
\ndivorce (D\u2019Onofrio et al., 2005, in press; McGue & Lykken, 1992), there is a possibility that
\ngenetic factors may confound the inter-generational transmission of divorce. Therefore,
\nexploring the possible role of genetic confounds is a critical research endeavor in exploring
\nfamily risk factors, such as parental divorce.
\nAlthough genes do not code for divorce, genetic factors may influence intermediate
\ncharacteristics, referred to as endophenotypes (Gottesman & Gould, 2003), that increase the
\nprobability of divorce. For example, personality characteristics, such as neuroticism (Karney
\n& Bradbury, 1995) or antisocial behavior (Emery, 1999), are associated with increased risk
\nfor divorce. Behavior genetic studies have consistently demonstrated that genetic factors
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\naccount for variation in such traits (reviews in Bouchard & Loehlin, 2001; Rhee &
\nWaldman, 2002), and a twin study illustrated that personality characteristics account for a
\nportion of the genetic variation in divorce (Jockin, McGue, & Lykken, 1996). In light of the
\ngenetic influences on divorce, Judith Harris has claimed, \u201cHeredity \u2026 makes the children of
\ndivorce more likely to fail in their own marriages. Parental divorce has no lasting effects on
\nthe way children behave when they are not at home\u201d (Begley, 1998).
\nWe are considerably more cautious, however, in drawing conclusions about the role of
\ngenetic factors explaining offspring adjustment problems associated with parental divorce.
\nRecent behavior genetic studies have found that genetic factors play a smaller role in
\ndivorce than originally estimated (review in D\u2019Onofrio et al., 2005). Furthermore, the source
\nof a risk factor can be separate from the mechanisms through which a risk factor influences
\nan offspring\u2019s adjustment (Rutter, Silberg, & Simonoff, 1993). A risk factor, such as
\ndivorce, could have an environmental effect (the risk mechanism) on children regardless of
\nwhether genetic or environmental factors account for variation in divorce (the source of the
\nrisk). Behavior genetic studies showing that genetic factors account for variability in divorce
\nraise the possibility that genetic factors account for the relations between parental divorce
\nand offspring adjustment, but this evidence does not substantiate the role. To our
\nknowledge, no investigation has yet explored the possibility that genetic factors confound
\nthe intergenerational transmission of marital instability.
\nBecause studies of the intergenerational transmission of divorce obviously cannot use
\nexperimental designs, research must use methodologies that disentangle risk factors that
\ntypically go together, especially genetic and environmental processes (Rutter, Pickles,
\nMurray, & Eaves, 2001). The need to incorporate behavior genetic designs in studies of risk
\nfactors and intergenerational transmission has been echoed by family researchers (Booth,
\nCarver, & Granger, 2000) and developmental psychologists (Collins, Maccoby, Steinberg,
\nHetherington, & Bornstein, 2000). Many genetically informative designs can be used to
\nexplore environmental risk processes (review in Rutter et al., 2001). The current analyses
\nused the Children of Twins Design, an approach that utilizes comparison groups that differ
\nin their genetic and environmental risks associated with parental characteristics, such as
\ndivorce (D\u2019Onofrio et al., 2003, 2005; Gottesman & Bertelsen, 1989; Heath, Kendler, Eaves,
\n& Markell, 1985).
\nThe Children of Twins Design
\nMost studies of the intergenerational transmission of marital instability have calculated the
\ndifference between offspring from intact and divorced homes, referred to as the divorce
\neffect, by comparing offspring whose parents are divorced to unrelated offspring from intact
\nfamilies. Statistical controls often are used to help account for the differences between the
\nunrelated families, but it is impossible to measure all potential selection factors. In the
\nChildren of Twins Design, offspring of adult twins who are discordant for divorce (one
\ncotwin has divorced and the other has not) are compared. That is, offspring from divorced
\nfamilies are compared to their cousins who did not experience the separation of their
\nparents, a within \u2013 twin family comparison (see Rodgers, Cleveland, van den Oord, &
\nRowe, 2000, for an explanation of the advantages of making comparisons at multiple levels
\nof analysis). The comparison of cousins differentially exposed to parental divorce controls
\nfor measured and unmeasured risk factors that all offspring in an extended family share.
\nOffspring of identical twins represent a unique comparison group. Because identical
\n(monozygotic) twins share 100% of their genetic makeup, the children of each twin are
\ngenetically related to their twin parent and their aunt\/uncle similarly (i.e., the offspring share
\n50% of their genetic makeup with their twin parent and their parent\u2019s cotwin). The
\ncomparison of offspring of discordant identical twins, therefore, contrasts cousins who share
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\nthe same degree of genetic risk associated with divorce from their twin parents. As a result,
\nthe divorce effect using children from identical twin pairs discordant for divorce is free from
\ngenetic confounds associated with divorce in the twin parents. Another important and often
\nunrecognized advantage of the Children of Twins Design is that it controls for
\nenvironmental (measured and unmeasured) factors in the twin family that make the twins
\nsimilar because twins share their family environment as well as their genes. If the divorce
\neffect in discordant identical families is lower than the divorce effect using unrelated
\ncomparisons, this suggests that selection factors, either genetic or shared environmental
\nconfounds, account for part of the intergenerational transmission. See D\u2019Onofrio et al.
\n(2005) for a graphical representation of the logic underlying the approach.
\nThe Children of Twins Design can also help to separate common environmental and genetic
\nprocesses by comparing the offspring of identical and fraternal (dizygotic) twins discordant
\nfor divorce. Offspring of identical twins are genetically related to each other as half siblings
\n(they share approximately 25% of their genes), whereas offspring of fraternal twins are
\ngenetically related as cousins (sharing roughly 12.5% of their genes). Because genetic
\ninfluences are controlled more fully in the offspring of identical twins, a larger within \u2013 twin
\nfamily divorce effect (the comparison of offspring in intact and divorced households) in
\nfraternal twin families than identical twin families suggests that genetic factors are partly
\nresponsible for the association. A lower divorce effect in offspring of identical twins than
\nfraternal twins would suggest that the selection factor would be correlated with genetic risk.
\nIf there is no difference in the within \u2013 twin family divorce effects between identical and
\nfraternal families, shared environmental factors would be most salient because the salient
\nconfounds would not correlate with genetic risk associated with divorce.
\nIn summary, the Children of Twins Design is able to partition an intergenerational
\nassociation into three processes. First, the difference among offspring of discordant identical
\ntwins provides an estimate of the processes specifically related to divorce within a nuclear
\nfamily (consistent with a causal connection). Second, small divorce effects in identical and
\nfraternal twin families imply that environmental factors that influence both generations
\naccount for the intergenerational transmission (supporting selection effects). Third, a small
\ndivorce effect in offspring of identical twins discordant for divorce but a larger divorce
\nestimate in fraternal twin families suggests a shared genetic pathway is responsible for the
\nincreased divorce risk in the offspring (also supporting selection effects).
\nA qualification is in order. The design offers many advantages over solely relying on
\nstatistical controls to account for possible confounds, but it does not control for every
\npossible environmental and genetic factor. The approach does not control for environmental
\nfactors that only influence one twin and their offspring (D\u2019Onofrio et al., 2003). The
\ninfluence of the spouse of the twins also is not accounted for in the design (Eaves, Silberg,
\n& Maes, 2005). The Children of Twins Design further assumes that there is no assortative
\nmating (Heath et al., 1985), the tendency for individuals to marry individuals who are
\nsimilar to them. The assumption can limit the ability of the design to differentiate between
\nenvironmental and genetic risk processes (see Discussion). Given these limitations,
\nincluding measures of nonshared environments and characteristics of the nontwin parents in
\nan attempt to account for these potential confounds and assumptions can provide a more
\nstringent test of the causal processes that account for the intergenerational transmission
\n(D\u2019Onofrio et al., 2005; Rutter et al., 2001).
\nThe current article sought to test whether the intergenerational transmission of divorce is
\nrobust to the use of a quasiexperimental approach of controlling for possible confounds, as
\nwell as the use of measured covariates. The present analyses, using a sample of adult twins,
\ntheir spouses, and their offspring from Australia, included detailed measures of possible
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\nselection factors in both parents to provide a more precise examination of selection effects.
\nThe inclusion of the measured characteristics, particularly assessments of psychopathology
\nin both parents, represents a major advance over many of the existent studies of the
\nintergenerational transmission of divorce that have only included measures of mothers as
\npossible selection factors. The analyses would support an environmentally mediated causal
\ninfluence of parental marital instability on offspring instability if the statistical relation
\nbetween parents on offspring remained when comparing offspring of identical twins
\ndiscordant for divorce (a within \u2013 twin family comparison that accounts for unmeasured
\nenvironmental and genetic factors) and the use of statistical covariates from both parents to
\naccount for possible confounds. If the relation between parents and offspring was reduced
\nby the use of the genetically informed design or the covariates, characteristics of parents or
\ntheir families correlated with parental divorce would partially or fully explain the
\nintergenerational transmission. Previous analyses of the Australia data set have found that
\nmost measures of offspring adjustment related to parental divorce, such as drug, alcohol,
\nbehavior, internalizing, and adjustment problems (D\u2019Onofrio et al., 2005), are not the
\nconsequences of genetic or environmental confounds, in as much as the design can control
\nfor these selection factors. In contrast, the association between parental divorce and
\ncohabitation, a well-known risk factor for later relationship instability, was completely
\naccounted for by selection factors (D\u2019Onofrio et al., 2006). A large Children of Twins study
\nin the United States also suggests that parental divorce may not cause increased depressive
\nsymptoms; rather, shared genetic liability in the parents and offspring may account for the
\nassociation (D\u2019Onofrio et al., in press). These findings underscore the importance of
\nstudying the intergenerational transmission of marital instability in a quasiexperimental
\ndesign.
\nMethod
\nSamples
\nAdult twins for the current analyses were drawn from the Australian National Twin
\nRegister. The twins in the current cohort were first assessed in 1980 with a self-report
\nsurvey (n = 8,183 individual twins, 69% response rate; Jardine & Martin, 1984). In 1988, the
\ntwins were assessed again with a mailed questionnaire (n = 6,327 individuals, 83% response
\nrate; Heath & Martin, 1994). Relatives of the twins (n = 14,421), including 3,318 spouses,
\nwere also assessed with a similar questionnaire (Lake, Eaves, Maes, Heath, & Martin, 2000).
\nFinally, the twins and their spouses (86% response rate) were assessed via telephone
\nbeginning in 1992 with a semistructured diagnostic interview (Heath et al., 1997). The study
\nincluded 5,889 individuals from the twin pairs and 3,844 of their spouses. The sample is
\nprimarily White, consistent with the demographics of Australia. Tests for self-selection
\nbiases in the longitudinal sample have found few detectable differences in terms of risk for
\nabnormal behavior (Heath et al., 1997).
\nThe Children of Twins study was designed to examine the intergenerational transmission of
\npsychopathology and risk associated with divorce. Offspring of adult twins were selected
\nfrom a control group and three at-risk subgroups: (a) twins with a history of alcohol
\ndependence or conduct disorder, or both, (b) twins with a history of depression, and (c)
\ntwins with a history of divorce. The adult twins were required to consent for the researchers
\nto contact their children, and the offspring also had to agree to participate. Approximately
\n85% (n = 1,409) of the targeted adult twins completed the screening, and 82% (n = 2,554) of
\nthe possible offspring completed the telephone interview. The offspring ranged from 14 to
\n39 years old (M = 25.1 years), and 51% were female. Offspring over the age of 18 years old
\n(n = 2,334) were included in the current analyses. More details about the adult and offspring
\nsamples are found elsewhere (D\u2019Onofrio et al., 2005).
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\nMeasures
\nCharacteristics of twins and their spouses\u2014A lifetime history of the adult twins\u2019
\nliving arrangements was included in 1988 questionnaire, and all assessments included items
\non current marital status and duration of the current status. On the basis of these items, a
\nlifetime history of divorce and marital separation (including separation from a cohabiting
\nrelationship longer than 6 months) was calculated for each twin. Living together as though
\nmarried for 6 months or more is considered common law marriage in Australia; thus, we
\nrefer to the relationships as marriages. Twin analyses indicated that additive genetic factors
\naccounted for 15% (95% CI = 5% \u2013 19%) of the variation in marital instability (D\u2019Onofrio
\net al., 2005). Nonshared environmental factors, environmental influences that make siblings
\nand twins different, accounted for most of the variance (85%, 81% \u2013 90%), with a minimal
\nrole of environmental factors that equally influenced both twins (0%, 0% \u2013 7%).
\nThe twins and their spouses each completed the Semi-Structured Assessment for the
\nGenetics of Alcoholism (Bucholz et al., 1994) as part of the 1992 study. The semistructured
\ninterview, developed on the basis of previously validated psychiatric research interviews,
\nhas demonstrated moderate to high reliability (Bucholz et al., 1994), especially in Australia
\n(Slutske et al., 1998). The interview assessed various characteristics of the adult twins and
\ntheir spouses that have been shown to increase the risk of relationship instability (e.g., Fine
\n& Harvey, 2006). These parental characteristics were included in analyses as measured
\ncovariates. Each parent\u2019s age at the birth of their first child was calculated using the twins\u2019
\nand their spouses\u2019 reports of all their children\u2019s dates of birth. Church attendance was
\nmeasured on a five-point Likert scale ranging from never to more than once a week. Highest
\nlevel of education was measured on a seven-point Likert scale ranging from less than 7
\nyears\u2019 schooling to university postgraduate training. Parental psychopathology was
\nmeasured with the number of lifetime symptoms of DSM-III-R diagnoses for conduct
\ndisorder, alcohol abuse, and major depression; lifetime history of ever using an illegal drug;
\nand lifetime history of suicidality as measured on a five-point Likert scale ranging from no
\nthoughts or plans of suicide to a previous serious suicide attempt (Statham et al., 1998).
\nSpousal information was only included in the analyses if the spouse was the biological
\nparent of all the offspring in the current study. The twin and spousal information was
\nconverted to maternal and paternal variables.
\nOffspring Relational Instability
\nThe offspring also completed the Semi-Structured Assessment for the Genetics of
\nAlcoholism, which included a number of items assessing current marital status and history
\nof cohabitation. On the basis of these variables, a lifetime history of relationship instability
\nwas calculated. Similar to the adult twins, relationship instability included individuals who
\nhad divorced, separated, had more than one marriage (excluding widowers), or had ended a
\ncohabiting relationship (defined as living with someone for over 6 months).
\nSample Propensity Weights
\nAs described above, the sample of twins for whom offspring data are available (the Children
\nof Twins sample) was selected from a larger, volunteer twin sample (the 1992 study). To
\navoid bias in parameter estimates and standard errors introduced by sample selection, we
\nconstructed a set of sample propensity weights for the twin data using the procedure outlined
\nin Heath, Madden, and Martin (1998). First, we identified predictors of whether one or both
\ntwins from a pair from the larger sample participated in the Children of Twins sample.
\nPredictors of pairwise participation in the subsample were examined because selection
\noccurred at the twin-pair level. Propensity weights were then constructed using the inverse
\nprobability of a pair participating in the Children of Twins sample. The ability of these
\npropensity weights to remove bias introduced by sample selection and nonrandom attrition
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\nwas tested by comparing the weighted and unweighted distributions for demographic and
\npsychiatric traits in the subsample and the 1992 sample of the adult twins (results available
\nupon request; Harden et al., 2007). The lifetime risk of separation and multilevel linear
\nmodels described below were estimated using the sample propensity weights to approximate
\npopulation-based parameters and to avoid bias in standard errors.
\nResults
\nThe Children of Twins Design is a three-level design (Nance & Corey, 1976). The 2,334
\noffspring were nested into 1,224 nuclear families, which were nested in 836 twin families.
\nDivorce status was missing for one twin in 14 of the families, influencing 24 offspring in the
\nstudy. These incomplete data, however, were not associated with offspring relationship
\ninstability (odds ratios [OR] = 0.89, p = .90) or parental divorce status (OR = 0.81, p = .66).
\nAs a result, the data were considered missing at random, and these twin families and
\noffspring were removed from the analyses, leaving 2,310 offspring in the analyses.
\nOur approach to analyzing the adult twin and Children of Twins data involved several steps.
\nFirst, survival analyses were conducted, ignoring the clustered nature of the data, to estimate
\nthe risk of marital separation for offspring in intact and divorced families. Second, the risk
\nof relationship instability was calculated separately for offspring from twin families who
\nwere discordant for divorce, which provides a comparison of cousins differentially exposed
\nto parental divorce. Third, the offspring of discordant twins were compared separately by
\nzygosity status. The comparison of offspring of identical twins controls for genetic risk
\nassociated with parental divorce from the twin parents. Thus, the comparison of cousins
\nfrom identical twin families provides a more stringent test of causality, although it does not
\naccount for every possible confound. No significance testing was done at this stage because
\nthe estimates of risk are purely descriptive. Formal significance testing was completed using
\nmodels that could both address the nonindependence of the observations and include the
\nsample weights. Fourth, associations between measured parental characteristics and
\noffspring relational instability were estimated to identify covariates that would be included
\nin subsequent genetically informed models. Finally, multilevel models were used to
\nincorporate the measured characteristics of the parents and the quasiexperimental approach
\navailable in the Children of Twins Design, as outlined in the introduction. The multilevel
\nmodels used in the current project ( help with nursing paper writing from experts with MSN & DNP degrees) are regression-based analyses that could account for the
\nnonindependence of the observations in the sample (e.g., multiple offspring per nuclear
\nfamily were included, which were nested under twin families). The multilevel models
\nestimated the magnitude of the intergenerational transmission comparing unrelated
\nindividuals, offspring of all twins who were discordant for divorce, and offspring of
\nidentical twin families who were discordant for divorce. The multilevel models also allowed
\nmeasured covariates to be included and weighted the analyses accordingly. Each model is
\nexplained in detail below.
\nAssociation Between Parental and Offspring Relationship Instability Using Different
\nComparisons
\nSurvival analyses were used to explore the inter-generational association of marital
\ninstability because of the right-censored nature of the offspring data (all the offspring have
\nnot lived through the risk period for the outcome). These analyses, ignoring the nested
\nnature of the data, were conducted to provide initial estimates of the intergenerational
\nassociation. The offspring who experienced a divorce and separation were initially
\ncompared to individuals in the entire sample, regardless of whether they had ever entered
\ninto a cohabiting or married relationship. The analyses were also conducted on a restricted
\nsubset of the data that only included offspring who had ever been in a relationship to
\ndetermine whether earlier initiation of intimate relationships accounted for the higher rate of
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\nseparation in the offspring from divorced families, but the results did not change (results
\navailable upon request).
\nFor the entire sample, 10.3% (237\/2,310) of the offspring had ever separated or divorced.
\nThe weighted percentage, which was based on the propensity sampling weights, was 10.1%.
\nThe risk for marital instability, controlling for the gender of offspring, was estimated using
\nCox Regression Models (Allison, 1995) at the age of 32, the last age at which comparisons
\ncould be made across all subgroups. The weighted estimated risk of separating, a KaplanMeier nonparametric estimate, was 18.1%. Table 1 presents the risk for relationship
\ninstability, including the raw percentages, the weighted percentages, and the Kaplan-Meier
\nestimates, using multiple comparisons. Using the entire sample, offspring from intact
\nfamilies had a lower risk of separating (16.0%) than offspring from divorced homes
\n(25.2%). The results replicate the established finding that offspring from divorced families
\nhave higher rates of marital instability.
\nInstead of comparing offspring from unrelated families, the comparison of twins discordant
\nfor divorce contrasted cousins (one set of cousins experienced the separation of their parents
\nbut the other cousins did not), which provides a stronger test of causality because cousins
\nshare traits that could confound the intergenerational transmission. If parental divorce
\ncaused offspring marital instability, the relation would be present at all levels of analysis
\n(e.g., Rodgers et al., 2000). Offspring from the intact twin families had less risk of
\nseparating (15.5%) than their cousins from divorced households (22.9%), a difference that is
\nsimilar in magnitude to the comparison of unrelated individuals, although perhaps a bit
\nsmaller.
\nThe prevalence and risk for offspring relationship instability were calculated separately for
\noffspring of identical and fraternal twins discordant for divorce. Comparison of the risks
\namong the groups provides an initial assessment of the processes responsible for the
\nintergenerational association between parental and offspring marital instability (for an
\nexplanation of the rationale see D\u2019Onofrio et al., 2003; Gottesman & Bertelsen, 1989). A
\ncomparison of the offspring of identical twins discordant for divorce provides the strongest
\nevidence of whether selection factors are responsible for the intergenerational relation.
\nOffspring of identical twins who are discordant for divorce receive the same genetic risk
\nassociated with divorce from the twins and shared environmental experiences that make the
\nadult twins similar. Therefore, differences between these two groups suggest that factors
\nwithin twin families associated with divorce account for the association, consistent with the
\ntheory that divorce causes the difference between offspring in intact and divorced homes. In
\ncontrast, if the magnitude of the difference in the offspring of the discordant identical twins
\nis less than the comparison of unrelated offspring, the pattern suggests that selection factors
\nare responsible for part of the intergenerational association. A comparison of offspring of
\nfraternal twins discordant for divorce provides a similar test, except these offspring differ
\nfrom the children of identical twins with respect to genetic risk associated with divorce from
\nthe twin parents. Therefore, genetic factors are implicated if the divorce effect in the
\noffspring of fraternal twin families is larger than in the offspring of identical twins
\ndiscordant for divorce. If the magnitude of the divorce effect is equivalent in each type of
\ntwin family and lower than the divorce effect estimated using unrelated offspring, common
\nenvironmental factors are implicated as selection factors.
\nChildren of identical cotwins whose parents remained married had a 17.1% risk for divorce,
\nwhereas children of identical cotwins whose parents divorced had a 22.0% risk for divorce.
\nThe offspring of discordant identical twin pairs differed in their risk for divorce, consistent
\nwith the hypothesis that the intergenerational association is causal, although the difference is
\nagain somewhat smaller than was found in the comparison of unrelated individuals. The
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\ndifference in risk in the offspring of fraternal twins discordant for divorce (16.9% vs. 24.1%)
\nappears to be larger than the difference in the offspring of identical twins discordant for
\ndivorce. The pattern of results suggests that risk factors specifically associated with parental
\ndivorce influence offspring risk for marital instability (the difference in marital stability
\nwhen comparing offspring of identical twins discordant for divorce). Genetic factors may
\npartially contribute to the risk of relationship instability in the offspring, however, because
\n(a) the divorce effect is smaller in identical twin families than the comparison of unrelated
\nindividuals and (b) the divorce effect is larger in offspring of fraternal twins discordant for
\ndivorce compared to offspring of discordant identical twins.
\nAssociations Between Parental Characteristics and Offspring Relationship Instability
\nThe Children of Twins Design cannot control for confounds that vary within twin families
\n(i.e., environmental influences that influence one twin and their offspring and the effects of
\nthe spouses of the twins) and the approach assumes no assortative mating. Therefore,
\nassociation between characteristics of both parents and offspring relationship instability was
\nestimated in order to include measurements of potential confounds in subsequent genetically
\ninformed analyses. Cox regression analyses with each individual parental characteristic were
\nconducted initially to identify characteristics of the parents associated with offspring
\nrelationship instability and to reduce the number of variables included in the genetically
\ninformative analyses. Because of the incomplete data on the mothers and fathers, the Cox
\nregression analyses were based on data sets in which the missing scores were estimated
\nthrough multiple imputation (MI) (Little & Rubin, 1987). As a result, the estimates of the
\nstandard errors using MI reflect the uncertainty of the data resulting from the missing values.
\nMore information was available for maternal versus paternal characteristics. The percentage
\nof missing values for mothers ranged from 4.2% to 8.5%, and the percentage of missing
\nvalues for fathers ranged from 11.0% to 24.5%. Because the nested nature of the data was
\nignored in the analyses, the significance levels are biased downward. Therefore, the analyses
\nrepresent a liberal approach to identifying salient variables. Variables that were marginally
\nrelated to offspring relationship instability were used in the subsequent multilevel models.
\nThe regression coefficients and OR associated with offspring relationship instability are
\npresented in Table 2. The results suggest that parental church attendance, age at first child,
\nhistory of conduct disorder, depression, and illegal drug use were associated with offspring
\nseparation. These variables from both parents were included in the subsequent genetically
\ninformed analyses.
\nMultilevel Models Utilizing Methodological and Statistical Controls
\nMultilevel models were conducted to quantify the magnitude of the association between
\nparental and offspring relationship instability using the different comparison groups within
\nthe Children of Twins Design, as well as to control for measured characteristics of both
\nparents. The multilevel models accounted for the nested nature of the data and estimated risk
\nfor offspring separation contingent on the offspring\u2019s age to take into account the rightcensored data. The nonlinear multilevel models were fit with the HLM 6.0 software
\n(Raudenbush, Byrk, Cheong, Congdon, & du Toit, 2004). Extensive details and algebraic
\nmodels of the approach are explained elsewhere (D\u2019Onofrio et al., 2005). We initially fit
\nthree-level multilevel models (Raudenbush & Bryk, 2002) because the sample included
\nmultiple offspring nested in nuclear families and two nuclear families nested in each twin
\nfamily. The multilevel model decomposed the residual variance in offspring relational
\ninstability into random effects at each level. The limited variance common to all offspring in
\na twin family (the highest level of analysis) caused estimation problems, however, and
\nsubsequent analyses only included two levels. For simplicity, the variance component that
\naccounted for the nested nature of the data was the only random effect estimated in each
\nmultilevel model. The fixed effect of offspring gender was included in each model. All
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\nmodels that incorporated statistical controls were conducted on five multiply imputed data
\nsets. Because of the estimation procedures used to fit nonlinear multilevel models in the
\nsoftware program HLM, nested models cannot be compared using the standard model fitting
\nindices, such as changes in deviance (M. Du Toit, personal communication, September 6,
\n2006; Raudenbush et al., 2004). Therefore, our interpretations of the models are based on
\nthe magnitude of the fixed effects associated with parental divorce, made with the
\nunstandardized coefficients (logits). Standardized estimates do not describe invariant causal
\nprocesses because they are influenced by factors unrelated to the specific relationship being
\nexplored (Kim & Ferree, 1981). Standardized estimates (OR), however, were also reported
\nfor descriptive purposes. We interpret the divorce effects cautiously on the basis of their
\nmagnitude, rather than relying solely on statistical significance, because some comparisons,
\nsuch as the offspring of identical twins discordant for divorce, rely on relatively small
\nsample sizes (see Discussion).
\nSix multilevel models were fit; results are shown in Table 3. Model 1 included only the
\nphenotypic effect of experiencing parental divorce, the comparison of offspring from
\ndivorced families to unrelated offspring in intact households. We refer to the estimate as
\nphenotypic because it represents the unadjusted association between two measured
\ncharacteristics and did not control for any genetic confounds. Parental divorce was
\nsignificantly associated with offspring relationship instability (b = .65 logits, SE = 0.19, OR
\n= 1.91, p < .001) in the first model, a finding that is consistent with previous research
\nshowing that offspring from divorced families are more likely to divorce than offspring from
\nintact families. Model 2 included parental divorce (phenotypic) and measures of maternal
\nand paternal church attendance, age at the birth of their first child, conduct disorder,
\ndepression, and use of illegal substances. The inclusion of the statistical controls for parental
\ncharacteristics slightly reduced the divorce effect, which remained significant (b = .52, SE =
\n0.22, OR = 1.68, p < .05). The parameters associated with the parental variables are difficult
\nto interpret because they estimate the unique contribution controlling for the presence of
\nevery covariate in the model. The estimates of the influence of divorce, the divorce effect, in
\neach model are presented in Figure 2. The figure illustrates how using statistical controls of
\ncharacteristics of both parents in the second model, the standard approach for controlling for
\npossible confounds, slightly reduced the risk of offspring relationship instability related to
\nparental separation. The results suggest that psychiatric and demographic characteristics of
\nboth parents account for only a minimal proportion of the intergenerational transmission of
\ndivorce.
\nModel 3 separated the association between parental divorce and offspring relational
\ninstability into between \u2013 and within \u2013 twin family effects. The effect of the average number
\nof divorces in a twin family (0, .5 [one twin divorced], or 1 [both twins divorced])
\napproximates the between-family effect of divorce (Jinks & Fulker, 1970). All cousins in a
\ntwin family share this variable regardless of whether their parents divorced. The parameter
\nassociated with variable (between), therefore, reflects whether individuals with more divorce
\nin their extended family have more marital instability than unrelated individuals who have
\nless parental divorce in their extended family. In contrast, the within \u2013twin family effect
\n(within) compares cousins who were differentially exposed to parental divorce. The contrast
\ncode to compare cousins of discordant twins was based on the difference between each
\ncotwin\u2019s divorce status and the twin-family average. Offspring from twin families who were
\neither concordant for marital stability (both twins had not experienced divorce) or marital
\ninstability (both twins had been divorced) received a value of 0 for the within \u2013 twin family
\neffect because there was no variation within twin pairs. The within \u2013 twin family variable
\neffectively compared offspring from the nondivorced cotwin (\u2212.5) to their cousins, the
\noffspring of the cotwin who was divorced (.5). If parental divorce had a direct,
\nenvironmentally mediated effect of their offspring\u2019s marital status, the association would be
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\nfound within twin families, which measures the divorce effect using cousins instead of using
\nunrelated individuals as the comparison group. The within-family effect of divorce (within)
\n(b = .62, SE = 0.33, OR = 1.87, p = .06) in Model 3 was commensurate with the phenotypic
\nassociation reported in the first model and the between \u2013 twin family effect (between) (b = .
\n67, SE = 0.25, OR = 1.95, p < .05). Model 4 included the between- and within-family
\nestimates as well as the statistical controls for the parental characteristics, and the statistical
\ncontrols again reduced the association between parental and offspring relationship instability
\n(b = .54, SE = 0.34, OR = 1.71, p = .11). Figure 2 illustrates how the intergenerational risk
\nwas slightly reduced when offspring whose parents were divorced were compared to their
\ncousins from intact families. The models still suggest, however, that parental divorce was
\nassociated with offspring relationship instability when comparing cousins differentially
\nexposed to parental divorce and including measured characteristics of both parents in the
\nmodel.
\nModel 5 included the between-family estimate of divorce (the average of the number of
\ndivorces of the two twins), but the within-family estimate of divorce was calculated
\nseparately for the identical and fraternal twins. The strongest test of causality in the Children
\nof Twins Design is the comparison of offspring of identical twins. Plus, the difference in the
\ndivorce effects measured in offspring of fraternal twins discordant for divorce compared to
\ndiscordant identical twins provides information on the nature of possible confounds (a larger
\ndivorce effect in offspring of fraternal twins discordant for divorce suggests that genetic
\nfactors account for part of the intergenerational association). Therefore, Model 5 included
\nthe interaction between the within-family divorce variable and zygosity type, which was
\ncoded identical = 0 and fraternal = 1. The multilevel models thus estimated two within \u2013
\ntwin family parameters: (a) the within \u2013 twin family effect in identical families and (b) the
\ndifference in magnitude between the within \u2013 fraternal and the within \u2013identical twin family
\neffects (bfraternal \u2212 bidentical). The comparison of cousins in identical twin families discordant
\nfor divorce (within identical) was sizeable (b = .52, SE = 0.41, OR = 1.68, p = .21),
\nconsistent with a causal relation between parent and offspring relationship instability. The
\ndifference between the fraternal and the identical within estimate (within [fraternal \u2212
\nidentical]) (b = .22, SE = 0.64, p = .73) suggests that genetic factors may slightly confound
\nthe inter-generational transmission of divorce, although the precision is limited by the
\nstatistical power to estimate the parameter. Model 6 estimated the divorce parameters
\nincluded Model 5 and added the measures of parental characteristics. The identical withinfamily estimate (b = .43, SE = 0.40, OR = 1.55, p = .27) was slightly reduced, but the
\ndifference in the two within-family estimates (b = .22, SE = 0.69, p = .75) remained the
\nsame. Figure 2 shows how the within \u2013 twin family effects in fraternal twin families are
\nslightly larger than the estimates of the within \u2013 twin family effects in identical twin
\nfamilies, again suggesting that genetic factors partially account for the inter-generational
\ntransmission of divorce. Yet, the comparison of offspring of identical twins discordant for
\ndivorce also revealed a sizeable divorce effect.
\nIn summary, the multilevel models illustrate how the Children of Twins Design and the use
\nof statistical controls help account for selection factors. The magnitude of the association
\nbetween parental and offspring marital instability, however, remained generally robust
\nthroughout, which is consistent with a causal relation. The initial multilevel model, which
\nestimated the unadjusted intergenerational relation, found that offspring from divorced
\nfamilies had a higher likelihood of marital instability than offspring from intact homes (b = .
\n65 logits, OR = 1.91). The use of statistical controls for characteristics of both parents
\nslightly reduced the effect in Model 2. Models 3 and 4 compared cousins who were
\ndifferentially exposed to parental to account for unmeasured confounds. Models 5 and 6
\nestimated the effect of parental divorce in offspring of identical twins discordant for divorce
\nand whether the divorce effect was larger in fraternal twin than identical twin families. The
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\ndivorce effect was slightly larger in fraternal families, suggesting that genetic factors shared
\nby parents and offspring partially account for the intergenerational transmission, but the
\ncomparison of identical twins in the final model (b = .43 logits, OR = 1.55) is also consistent
\nwith a causal association. To state it in a different way, 66% (.43 logits\/.65 logits) of the
\noriginal, unadjusted estimate of the intergenerational transmission was not accounted for by
\ngenetic confounds associated with divorce from the twin parents, nonmeasured
\nenvironmental confounds that make adult twins similar, and measured demographic and
\npsychological traits of both parents. Additional multilevel models that also controlled for
\nmeasures of parental personality factors, such as neuroticism, extra-version, and impulsivity,
\nin addition to those presented here, resulted in similar findings (results available by request).
\nDiscussion
\nConsistent with extensive research on Western families (Pryor & Rogers, 2001), the current
\nanalyses found a higher rate of relationship instability among the offspring of divorced
\nparents in a large sample of children of Australian twins, weighted to approximate
\npopulation-based parameters. The unique sample allowed us to conduct the first genetically
\ninformed analysis of the intergenerational association. The current study also provides a
\nmore rigorous test of causality than most previous studies because it included measured
\ncovariates of both parents to control for selection factors, including lifetime history of
\npsychiatric disorders assessed by semistructured psychiatric interviews.
\nThe results support both causal and selection processes (Hetherington, 1999). The use of the
\nChildren of Twins Design revealed that parental divorce (or risk factors specifically
\nassociated with parental marital instability within twin families) accounted for
\napproximately 66% of the initial, unadjusted estimate of the intergenerational transmission.
\nBecause our design allowed us to control for genetic and unmeasured environmental
\nselection effects (for the twin parents) as well as measured characteristics of both parents,
\nthis is perhaps the strongest evidence to date that parental divorce directly causes an increase
\nin offspring divorce.
\nOur results also suggest, however, that part of the intergenerational association
\n(approximately 34%) results from selection effects. Does the current study shed light on the
\nsources of the selection factors? Statistically controlling for characteristics of both parents
\n(Model 2) slightly reduced the overall magnitude of the association. Thus, families in which
\nboth parents have higher levels of psychopathology are more likely to get divorced and have
\nchildren with higher levels of marital instability. Yet, only by comparing offspring of
\nidentical twins discordant for divorce did the analyses more fully account for shared genetic
\nrisk passed from parents to their children. The selection factors that were controlled by (a)
\nthe use of the statistical covariates in Model 2 and (b) the comparison of offspring of
\nidentical twins discordant for divorce in Model 5 appear to be largely independent because
\nthe divorce effect in the model utilizing both approaches (Model 6) provided a smaller
\nestimate than when using either approach alone. Therefore, the measured covariates that
\nwere included in the model\u2014parental church attendance, age at first child, conduct disorder,
\ndepression, and illegal drug use\u2014do not mediate or explain the mechanisms through which
\ngenetic selection factors account for some of the intergenerational transmission of divorce.
\nAs such, the present analyses reveal only the broad, not the specific, genetic contributions to
\nthe increased risk of marital instability among offspring of divorced parents. Unspecified
\ngenetic factors partially account for an increased risk of divorce both in parents and in their
\nchildren. These results are consistent with concerns raised earlier about refining theories of
\nthe consequences of divorce for children (Emery, 1999; Hetherington, 2003). We suspect
\nthat one reason for this is that the results are attributable to multiple genetically mediated
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\nmechanisms. These likely include personality traits, broadly construed (Emery et al., 1999;
\nJockin, McGue, & Lykken, 1986), and also physical characteristics such as early menarche,
\na highly heritable developmental landmark (Mustanski, Viken, Kaprio, Pulkkinen, & Rose,
\n2004). Genetic selection effects also may be partially mediated through the environmental
\nexperiences. For example, adolescent girls whose early menarche is attributable to genetics
\nmay develop secondary sexual characteristics that attract the attention of older, perhaps
\nmanipulative men who are less stable or reliable romantic partners, and this experience, in
\nturn, leads to more divorce. Future research will need to explore the precise environmental
\nand genetic processes that mediate the intergenerational association by examining the traits
\nand personality characteristics of the offspring.
\nConcerns about genetic selection are not merely academic. Whether parental divorce is
\ncausal or merely correlated with offspring marital stability is tremendously important not
\njust conceptually but also practically, especially given the increase in divorce rates in the
\nUnited States and in other Western countries in the past 50 years (Pryor & Rogers, 2001)
\nand the current debate over government involvement to promote marriages and reduce
\ndivorces (McLanahan, Donahue, & Haskins, 2005). The present results imply that reducing
\nthe incidence of parental divorce or ameliorating the risk factors that frequently accompany
\nthe separation of parents (e.g., increased financial difficulties, parenting problems, lower
\ncommitment to marriage) may reduce the risk of marital instability in offspring. A number
\nof intervention studies with residential mothers and children from divorced families have
\nreduced the risk of mental health problems in offspring (e.g., Wolchik et al., 2002), but no
\nstudy has explored whether interventions can reduce the increased risk of relationship
\ninstability in the offspring of divorced parents.
\nA number of limitations must be considered when interpreting the results. Genetic and
\nenvironmental effects may well differ across cultures, cohorts, and time. Historical and
\ncross-cultural evidence clearly indicates broad environmental influences on divorce
\nthresholds. Like others, our research shows that genetic factors influence divorce risk within,
\nnot between, culture and cohort. The proportions of the variance attributable to genetic
\nselection and environmental causation are not fixed, especially in accounting for complex
\nsocial behaviors such as divorce. Thus, the present results may, or may not, apply to intergenerational linkages found in the United States or other Western countries.
\nThe study utilized sampling weights and statistical techniques to handle missing data (MI)
\nso that the results would generalize to the larger population of Australia, but the present
\nresults apply only to the Australia and are limited to offspring\u2019s experience of divorce (and
\nthe break up of long-term cohabiting relationships) early in adult life. Previous research,
\nhowever, suggests that the divorce rate in Australia is consistent with other non-U.S.
\ncountries (Pryor & Rogers, 2001), and results of divorce studies in Australia are generally
\ncommensurate with international studies (Rodgers, 1996). Nevertheless, the relative
\nimportance of genetic and environmental processes responsible for the intergenerational
\ntransmission of divorce may change when considering risk of marital instability throughout
\nthe entire life span. Our analytical approach of handling the right censoring may not
\naccurately account for the intergenerational association if different factors contribute to
\nrelationship instability in early versus later adult life.
\nAlthough the study is the first to examine genetic selection and also included many other
\npotential selection factors, the study is still based on correlational data. Therefore, the results
\nare limited by the constraints inherent in using any nonexperimental design and cannot
\nprove that parental divorce causes offspring relationship instability (D\u2019Onofrio et al., 2003;
\nRutter et al., 2001). Parental divorce could be a proxy for other environmental risk factors
\nthat actually cause the offspring to get divorced. As discussed above, the Children of Twins
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\nDesign does not control for genetic risk from the spouse of twins (Eaves et al., 2005). The
\nanalyses controlled for characteristics of both parents to address this limitation, but it is
\nimpossible to determine whether the measured covariates account for all the relevant
\ncharacteristics. Furthermore, characteristics of the offspring that increase the likelihood of
\ndivorce in both generations could also explain the relation (reciprocal influences).
\nThere are also methodological limitations to note. Some caution is warranted because the
\nstandard errors around many estimates were large. The Children of Twins Design also
\nassumes the absence of assortative mating (Heath et al., 1985). Assortative mating, the
\ntendency for individuals to marry similar people, may place some children at greater risk for
\nmarital separations because the offspring are exposed to two parents with increased levels of
\npsychopathology and other characteristics that are deleterious for offspring. Understanding
\nthe exact mechanisms underlying assortative mating, whether driven by genetic or
\nenvironmental processes, is therefore required to specify the risk mechanisms responsible
\nfor the association between parental and offspring characteristics (Heath et al., 1985). If
\nassortative mating is driven by genetic factors (e.g., Eaves, 1979), some offspring would
\ninherit greater genetic marital stability. Assortative mating, however, may also have
\nenvironmentally mediated effects on offspring, through processes such as modeling
\n(D\u2019Onofrio et al., 2003). A thorough analysis of the processes responsible for assortative
\nmating in the current sample of twins and their spouses is beyond the scope of the current
\nmanuscript, but other articles using the same sample are beginning to address the question
\n(e.g., Agrawal et al., 2006). We are currently working with other researchers on models that
\ncan incorporate the influence of spouses and the mechanisms responsible for mate selection.
\nA number of recommendations can be made for future studies exploring the
\nintergenerational transmission of divorce. Large-scale genetically informed studies need to
\nbe conducted with sizable, nationally representative samples to study divorce and other
\ntopic (sample nursing essay examples by the best nursing assignment writing service)s in marriage and families. Larger samples sizes would provide greater statistical
\nprecision around the estimates, allow comparisons among different ethnic and
\nsocioeconomic groups, enable further exploration of moderators of the intergenerational
\nassociation, and include measures of relationship instability across the life span. Additional
\ngenetically informative designs, such as adoption studies, must also be used because
\nidentifying causal environmental processes will require corroborating evidence from
\nmultiple research approaches, each with its own strengths and weaknesses.
\nMore generally, the present analyses together with additional, genetically informed studies
\nof the consequences of divorce (D\u2019Onofrio et al., 2005, 2006, in press), stepfather presence
\n(Mendle et al., 2006), parental abuse (Jaffee, Caspi, Moffitt, & Taylor, 2004), parental
\nconflict (Harden et al., 2007), parenting characteristics (Caspi et al., 2004; Neiderhiser et al.,
\n2004), and severe parental psychopathology (Gottesman & Bertelsen, 1989), indicate that
\ndemographers, sociologists, economists, and others studying population groups need to
\nrecognize the importance of genetic selection and control for genetic effects using twin and
\nsimilar family research designs (Rutter et al., 2001).
\nIn summary, the first genetically informed study of the intergenerational transmission of
\ndivorce suggests that genetic factors, a risk factor that has not been explored in many family
\nstudies, partially account for the association between parental and offspring relationship
\ninstability. At the same time, the findings are consistent with the importance of
\nenvironmentally mediated risk for offspring divorce. The findings contrast with theories that
\npostulate that family environmental experiences in general (Harris, 1998; Rowe, 1994), and
\nparental divorce in particular (Begley, 1998), do not influence offspring adjustment after the
\nchildren leave home. Ultimately, exploring the influence of parents and family risk factors
\nwill require research that integrates the underlying genetic and environmental processes.
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\nAcknowledgments
\nThe analyses were supported by a grant to the first author from the National Institute of Mental Health (MH67300).
\nData collection was funded by grants from the W. T. Grant Foundation, NIAAA (National Institute on Alcohol
\nAbuse and Alcoholism) (AA07535 and AA000264) and the National Alliance for Research on Schizophrenia and
\nDepression. The authors thank the staff of the Genetic Epidemiology Unit at QIMR (Queensland Institute of
\nMedical Research) for the data collection, in particular Alison Mackenzie for coordination, and the twins and their
\nchildren for cooperation in this research. Special thanks also to Mathilda du Toit for help with the analyses.
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\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nFigure 1.
\nEnvironmental and Genetic Confounds to Intergenerational Relations.
\nNote: Reciprocal effects are not considered in the current model. The direct path between
\nthe parental and the child trait is referred to as the quasicausal effect because it is consistent
\nwith a causal association but does not prove causality.
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\nJ Marriage Fam. Author manuscript; available in PMC 2010 July 16.
\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nFigure 2.
\nAssociation Between Parental and Offspring Relationship Instability Using Methodological
\nand Statistical Controls.
\nNote: Cousins = offspring of twins, regardless of zygosity. DZ = dizygotic or fraternal twin
\nfamilies. MZ = monozygotic or identical twin families.
\n1Statistical covariates (maternal and paternal church attendance, age at first child, conduct
\ndisorder, depression, and illegal drug use) were included in the models.
\nD\u2019Onofrio et al. Page 19
\nJ Marriage Fam. Author manuscript; available in PMC 2010 July 16.
\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nD\u2019Onofrio et al. Page 20
\nTable 1
\nRisk for Relationship Instability in Offspring Using Multiple Comparison Groups
\nFamily Structure Raw % Weighted % Weighted Estimated Risk n
\nEntire sample
\n Parents married 9.2 8.8 16.0 1,749
\n Parents divorced 13.6 14.5 25.2 561
\nDiscordant twin families
\n Parents married 10.3 8.7 15.5 464
\n Parents divorced 12.3 12.6 22.9 382
\nDiscordant fraternal twin families
\n Parents married 10.8 9.1 16.9 240
\n Parents divorced 9.1 12.2 24.1 176
\nDiscordant identical twin families
\n Parents married 9.8 8.3 17.1 224
\n Parents divorced 15.1 12.1 22.0 206
\nNote: Weighted estimates were based on analyses using the propensity sampling weights. Estimated risks are based on Kaplan-Meier
\nnonparametric survival analyses at the age of 32, controlling for the gender of the offspring.
\nJ Marriage Fam. Author manuscript; available in PMC 2010 July 16.
\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nD\u2019Onofrio et al. Page 21
\nTable 2
\nParental Characteristics Associated With Offspring Divorce\/Separation Status
\nMother Father
\nVariables b OR p b OR p
\nEducation \u2212.08 0.92 .26 \u2212.06 0.94 .45
\nChurch attendance
\na \u2212.10 0.90 .15 \u2212.12 0.89 .12
\nAge at first child
\na \u2212.08 0.92 <.01 \u2212.07 0.93 <.01
\nCigarette smoking .07 1.07 .70 .14 1.15 .59
\nConduct disorder
\na .14 1.15 .09 .11 1.12 .16
\nAlcohol abuse .06 1.06 .81 .17 1.19 .18
\nDepression
\na .06 1.06 .04 .03 1.03 .47
\nDrug use
\na .72 2.05 .05 .54 1.71 .10
\nSuicidality .08 1.08 .26 .17 1.19 .17
\nNote: All analyses are based on five multiply imputed data sets.
\nN = 1,210. The coefficients are based on Cox Proportional Hazard Models using multiple imputation, ignoring the nested nature of the data,
\nand are distributed as logits. OR = odds ratios. See text for units of measurement for each variable.
\naIncluded in subsequent multilevel models predicting offspring divorce\/separation status.
\nJ Marriage Fam. Author manuscript; available in PMC 2010 July 16.
\nNIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
\nD\u2019Onofrio et al. Page 22
\nTable 3
\nParameter Estimates From the Multilevel Models
\nModels
\n1 2 3 4 5 6
\nParameter b SE b SE b SE b SE b SE b SE
\nDivorce
\n Phenotypic .65
\n* 0.19 .52
\n* 0.22
\n Between .67
\n* 0.25
\n* .50 0.27 .68
\n* 0.25 .50 0.27
\n Within .62 0.33 .54 0.34
\n Within identical .52 0.42 .43 0.40
\n Within (fraternal-identical) .22 0.65 .22 0.69
\nOffspring gender \u2212.30 0.20 \u2212.26 0.20 \u2212.29 0.19 \u2212.26 0.20 \u2212.29 0.19 \u2212.26 0.20
\nMaternal variables
\n Church attendance .05 0.07 .05 0.07 .05 0.07
\n Age at first child \u2212.07 0.05 \u2212.07 0.05 \u2212.07 0.05
\n Conduct disorder .03 0.15 .04 0.15 .03 0.15
\n Depression .02 0.03 .02 0.03 .02 0.03
\n Illegal drug use \u2212.34 0.33 \u2212.34 0.33 \u2212.34 0.33
\nPaternal variables
\n Church attendance \u2212.07 0.09 \u2212.07 0.09 \u2212.07 0.09
\n Age at first child .01 0.04 .01 0.04 .02 0.04
\n Conduct disorder \u2212.24 0.14 \u2212.24 0.14 \u2212.24 0.15
\n Depression .09
\n* 0.04 .09
\n* 0.04 .09
\n* 0.04
\n Illegal drug use \u2212.35 0.22 \u2212.35 0.23 \u2212.35 0.23
\nNote: All parameters are unstandardized.
\nN = 2,310. Data are weighted. Models including the measured covariates are based on five multiply imputed data sets. Model 1 compares unrelated offspring. Model
\n2 includes statistical covariates to the model. Model 3 separates the influence of parental divorce into between \u2013 twin families and within \u2013 twin family (offspring of discordant twins) effects. Model 4
\nincludes statistical covariates to the model. Model 5 calculates the within \u2013 twin family effect for identical twin families and the difference between the fraternal and the identical within \u2013 twin family effects.
\nModel 6 includes statistical covariates to the model.
\n*
\np < .05.
\nJ Marriage Fam. Author manuscript; available in PMC 2010 July 16.<\/p>\n","protected":false},"excerpt":{"rendered":"
A Genetically Informed Study of the Intergenerational Transmission of Marital Instability Brian M. D\u2019Onofrio, Department of Psychological and Brain Sciences, Indiana University, 1101 E, 10th\u2026<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7724,7548,8080,8079,8077,8078,8081],"tags":[187,22,181,175,186,177,180,97,179,91,73,9,7,178,182,77,184,183,185],"class_list":["post-98423","post","type-post","status-publish","format-standard","hentry","category-best-dissertation-writing-services","category-dissertation-writing-services-cost","category-master-thesis-writing-service","category-online-thesis-writing-services","category-phd-dissertation-help-and-editing-helper-in-usa","category-professional-dissertation-writing-service","category-write-my-dissertation","tag-best-assignment-help-websites-in-canada","tag-best-nursing-paper-writing-service","tag-buy-psychology-essay","tag-cheap-psychology-essay-writing-service","tag-dissertation-assignment-help","tag-history-dissertation-writing-services-by-uk-writers","tag-nursing-assignment-acers","tag-nursing-assignment-help","tag-nursing-assignment-help-canada","tag-nursing-assignment-writers","tag-nursing-dissertation-writing-help-online","tag-nursing-paper-writing-service","tag-online-nursing-essay-writing-service","tag-online-nursing-papers","tag-online-psychology-assignment-help-writing-services","tag-pay-for-nursing-essay","tag-psychology-assignment-topics","tag-psychology-homework-market","tag-write-my-history-essay-for-me"],"_links":{"self":[{"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/posts\/98423","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/comments?post=98423"}],"version-history":[{"count":0,"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/posts\/98423\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/media?parent=98423"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/categories?post=98423"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.studyproessays.com\/help\/wp-json\/wp\/v2\/tags?post=98423"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}