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. Author manuscript; available in PMC: 2014 Aug 1.
Published in final edited form as: J Marriage Fam. 2013 Jul 1;75(4):981–994. doi: 10.1111/jomf.12048

Still the Favorite? Parents’ Differential Treatment of Siblings Entering Young Adulthood

Sonja E Siennick 1
PMCID: PMC3826983  NIHMSID: NIHMS476577  PMID: 24244050

Abstract

This study examined within-family stability in parents’ differential treatment of siblings from adolescence to young adulthood and the effect of differential treatment in young adulthood on grown siblings’ relationship quality. The author used longitudinal data on parent – child and sibling relations from the sibling sample of the National Longitudinal Study of Adolescent Health (N = 1,470 sibling dyads). Within-dyad fixed effects regression models revealed that the adolescent sibling who was closer to parents went on to be the young adult sibling who was closer to and received more material support from parents. Results from an actor – partner interdependence model revealed that differential parental financial assistance of young adult siblings predicted worse sibling relationship quality. These findings demonstrate the lasting importance of affect between parents and offspring earlier in the family life course and the relevance of within-family inequalities for understanding family relations.

Keywords: family relations, family support, intergenerational relationships, parent–child relationships, siblings, young adults

Bonds with parents and siblings are important resources for individuals across the life course. This is especially true at major life transitions, such as the transition to adulthood, when emotional and material support from parents can have important effects on young adults’ adjustment and attainment (Fingerman, Cheng, Tighe, Birditt, & Zarit, 2012; Johnson & Benson, 2012). Yet in many families parents give different amounts of affection and support to different siblings (Fingerman, Miller, Birditt, & Zarit, 2009; Suitor, Pillemer, & Sechrist, 2006). This differential treatment is important both because it could create within-family inequalities in offspring outcomes and because it could undermine the bond between siblings (Conger & Little, 2010). It thus is important to understand the roots of differences in young adult siblings’ relations with their parents and the implications of those differences for the sibling relationship itself.

Theoretical and empirical work on parent – offspring relations suggests that previous intergenerational relationship characteristics influence current relationship quality and support decisions (Aquilino, 1997; Parrott & Bengtson, 1999). A separate body of work on parents’ differential treatment of siblings shows that such disparities are common and can affect sibling dynamics (Whiteman, McHale, & Soli, 2011). This study bridges the gap between these foundations by examining whether parents give more affection and material support to the grown sibling with whom they historically were closer and shared more time and whether disparities in parental affection and material support predict worse young adult sibling relationship quality. I tested these hypotheses using prospective longitudinal data from a large national sample of siblings. The findings contribute new information about the amount of continuity in parental differential treatment across an important developmental transition and about the effect of developmentally relevant domains of such treatment on the sibling bond.

A Within-Family Approach to Intergenerational Solidarity

This study drew on intergenerational solidarity theory (Bengtson & Roberts, 1991; Silverstein, Bengtson, & Lawton, 1997) to conceptualize affection, association, and support as self- and mutually reinforcing elements of parent – offspring cohesion. The theory characterizes parent – offspring relations as multidimensional, with the specific dimensions being affection, association (contact), function (support exchange), consensus (value agreement), norms of familial obligation, and structure (opportunity for association). Although there is mixed empirical support for various proposed models of the causal paths among the dimensions, affection, association, and function do appear to be interdependent (Hogerbrugge & Komter, 2012). Specifically, parents and offspring who are emotionally closer and spend more time together tend to exchange more emotional and material support (Bengtson & Roberts, 1991; Rossi & Rossi, 1990; Silverstein et al., 1997).

Although most tests of solidarity theory have used cross-sectional data, the theory potentially can shed light on the longitudinal pathways from early family relations to support between adult relatives (Silverstein, Parrott, & Bengtson, 1995). Solidarity theory distinguishes the relationship features that create the potential for later kin support from the support itself. According to this perspective, affection, association, and function are interrelated because high levels of affinity and contact predispose parents and offspring to help each other in the future (Hogerbrugge & Komter, 2012; Silverstein, Conroy, Wang, Giarrusso, & Bengtson, 2002; Silverstein, Gans, & Yang, 2006). Consistent with this, in between-family studies, relationship quality prospectively predicts both parent – offspring closeness and parent – offspring support (Aquilino, 1997; Parrott & Bengtson, 1999; Swartz, Kim, Uno, Mortimer, & O’Brien, 2011). This is consistent with theorists’ description of current parent – offspring affection and support as reflecting accumulations of family solidarity over time (Silverstein et al., 2002).

Research on parental differential treatment does not often draw on solidarity theory, but this research does show that adult siblings often differ in key elements of intergenerational solidarity, including how close they are with their parents and how much material and other support they exchange with their parents (Fingerman et al., 2009; Suitor, Pillemer, & Sechrist, 2006). If these disparities reflect within-family differences in intergenerational solidarity, and if current solidarity is shaped by earlier levels of cohesion, then the direction of parental differential treatment should show stability as offspring age. Indeed, differential treatment is common in childhood and adolescence (Whiteman et al., 2011), and retrospective studies suggest that parental favoritism may have momentum over time (Bedford, 1992). Prospective studies of parent – offspring relations across offspring’s transitions to adulthood would shed light on the amount of stability in parental favoritism (Suitor, Sechrist, Plikuhn, Pardo, & Pillemer, 2008), the beginnings of processes observed in later-life families (e.g., Boll, Ferring, & Filipp, 2003; Fingerman et al., 2009), and the cognitive – emotional roots of siblings’ relative access to parental resources that can aid in their transitions.

On the basis of this past work, I expected that sibling differences in parent – adolescent affection and association would predict later sibling differences in parent – young adult affection and material support (function). Although function potentially can encompass several types of tangible and intangible support, during young adulthood material support comes to the forefront as a key means by which parents can shape offspring life chances (Swartz, 2009). The major forms of regularly occurring material support are financial assistance (including cash transfers and help paying bills or purchasing things) and housing assistance (coresidence; Swartz et al., 2011). Interestingly, coresidence could be an indicator not only of function but also of the structural dimension of solidarity (e.g., if it increases opportunities for parents to give money). The longitudinal links between early affection and association and later affection and material support could be stronger when parents and favored offspring continue to live together. It thus also is important to examine whether stability in siblings’ relative intergenerational solidarity depends on whether siblings continue to coreside with parents as young adults.

Differential Solidarity and Young Adult Siblings’ Relationships

This study also drew on social comparison theory to conceptualize sibling inequalities in relations with parents as a link between the characteristics of inter- and intragenerational relationships. Specifically, intergenerational solidarity may actually undermine sibling cohesion if siblings experience unequal levels of solidarity with parents. Social comparison theory posits that individuals evaluate themselves by comparing themselves with others, and particularly with similar others (Festinger, 1954). Unfavorable evaluations harm emotional well-being and interpersonal relationships (Festinger, 1954). Siblings are an especially relevant point of reference, and indeed the only direct comparison, for evaluations of parental treatment (Feinberg, Neiderhiser, Simmens, Reiss, & Hetherington, 2000). Parental differential treatment thus may create feelings of hostility, competitiveness, and inequity between siblings (Whiteman et al., 2011). This should be especially true for the sibling who is less favored, because low relative status causes the most emotional harm (Festinger, 1954). Past research has shown that differential treatment is associated with lower quality sibling relationships during adolescence (McHale, Crouter, McGuire, & Updegraff, 1995; Shanahan, McHale, Crouter, & Osgood, 2008) and at midlife (Boll et al., 2003; Suitor et al., 2009).

Although parents’ unequal treatment could undermine sibling relationship quality during young adulthood, scholars have not yet systematically examined this possibility (Conger & Little, 2010). Because siblings remain each other’s best point of comparison for parental treatment across the transition, and because parental support remains important during this age range, it is likely that sibling comparison processes persist as well. It is important to determine whether they do because, once established, the quality of relationships between adult siblings appears to be fairly stable across the shared life course (White, 2001).

Past studies have predicted midlife siblings’ relationship quality from broad measures of perceived parental favoritism and supportiveness (Boll et al., 2003; Suitor et al., 2009) yet, as described above, intergenerational solidarity theory posits that different dimensions of solidarity may have unique causes and consequences and distinct roles in pathways of family relations. It thus is possible that certain types of parental differential treatment have especially harmful effects on sibling relations. With respect to the transition to adulthood, a new material domain of sibling rivalry could emerge as the variance in siblings’ material well-being increases and as parental provision of material resources becomes more voluntary (Conger & Little, 2010). In addition, parent – offspring functional solidarity, especially material support, could be more readily observable by siblings than are other dimensions of solidarity. It thus is possible that young adult siblings are especially sensitive to inequalities in material support from parents.

Finally, scholars have distinguished between parents’ actual differential treatment of siblings and siblings’ perceptions of that treatment (e.g., Boll et al., 2003). Because similar others are the key reference points for social comparison processes (Festinger, 1954), siblings may not be negatively affected by unequal treatment if they view it as justified by differences between them (Kowal & Kramer, 1997; McHale & Pawletko, 1992). This implies that the degree of similarity between siblings, perhaps especially on key predictors of parental support such as age and gender, may moderate the effects of differential treatment (Shanahan et al., 2008). This study thus also examined whether the effects on young adult sibling relations of parental differential treatment depend on sibling age and gender differences.

The Current Study

In this study, I tested the following hypotheses. Hypothesis 1 posited that sibling differences in affective and associational solidarity with parents during adolescence will predict sibling differences in affective and functional solidarity with parents during young adulthood. Specifically, within sibling pairs, the adolescent sibling who is closer to and spends more time with parents will go on to be the young adult sibling who is closer to and receives more material support from parents. Because intergenerational relationships may shift as offspring age and leave the parental home (Aquilino, 1997), I used supplementary analyses to examine whether these associations hold among siblings of the same age and whether they depend on siblings’ continued coresidence with parents. Hypothesis 2 predicted that disparities in young adult siblings’ affective and functional relationships with parents, and especially in parents’ differential provision of material support, will be associated with lower concurrent sibling relationship quality. This should be especially true from the perspective of the disfavored sibling. Because differential treatment could have the strongest harmful effects on relations between similar siblings (Kowal & Kramer, 1997), I used supplementary analyses to examine whether the effects of such treatment on young adult siblings’ relationship quality depend on sibling age and gender differences. The analyses account for several known correlates of parent – offspring relationship characteristics and sibling relationship quality, including age and the age gap between siblings, gender and whether the sibling dyad was mixed gender, race and ethnicity, family size (including number of children and number of parents), and family economic circumstances (Conger & Little, 2010; Suitor et al., 2009; Swartz, 2009).

Method

Data

The data are from the sibling sample of the National Longitudinal Study of Adolescent Health (Add Health; http://www.cpc.unc.edu/projects/addhealth). Add Health is an ideal source of data for this project because it features a large national sample of siblings and comprehensive longitudinal data on these siblings’ family relationships during adolescence and young adulthood. Add Health drew on a nationally representative sample of adolescents who were in Grades 7 through 12 during the 1994 – 1995 school year. Participants were selected via a two-stage stratified sampling design. First, 132 schools were randomly selected from a national sampling frame stratified by region, urbanicity, school size, school type, and racial composition. Then, students in each school were stratified by grade and gender, and a nationally representative probability sample of nearly 19,000 adolescents was selected for the longitudinal in-home component of the study. Many of these respondents had siblings who incidentally also were selected for inclusion in the study. In addition, the Add Health investigators purposefully oversampled twins, half-siblings, and unrelated siblings. This resulted in a sibling sample (N = 5,398) that provided the data used in the present study.

To date, in-home respondents have completed four in-person survey interviews. The key measures for this study come from the Wave 2 adolescent interviews (conducted in 1996), when the Add Health investigators first asked questions about relationships between study siblings, and from the Wave 3 young adult interviews (2001 – 2002). I also include some background information from Wave 1 (1994 – 1995), because that wave featured parent interviews that collected information about household socioeconomic status. Wave 4 did not collect information on sibling relationships and its data were not used in this research. Because parents experiencing partnership transitions could change the way they allocate family resources, I focused on full siblings who did not acquire or lose a parent figure between Waves 2 and 3. To create the analytical sample, I selected the sibling pairs in which both members participated at Wave 3 (N = 3,848 unique respondents within 2,151 unique sibling pairs; some respondents had multiple participating siblings). I then removed pairs of cousins, adoptive siblings, and other unrelated pairs (leaving 3,515 respondents in 1,914 pairs). To ensure that I was studying respondents’ relations with the same parents over time, I selected pairs in which each sibling was still in touch at Wave 3 with the parents about whom they reported at Wave 2 and in which neither had acquired a new residential parent (e.g., a stepparent) between Waves 2 and 3 (3,414 respondents in 1,856 pairs). Finally, I limited the sample to full siblings (2,940 cases representing 2,741 unique respondents within 1,470 pairs). Some analyses used data only on same-age siblings (twins and one set of triplets; 1,146 cases representing 1,138 unique respondents within 573 pairs).

I use multiple imputation to reduce potential bias from item-missing data. I used the ice (Royston, 2005) and mim (Carlin, Galati, & Royston, 2008) procedures for Stata to create five complete data sets featuring imputed values for missing cases and to combine estimates across the five and account for variance across them. To improve imputation quality, all study variables as well as auxiliary variables (e.g., family warmth during adolescence, adolescent delinquency) were included in the imputation procedure.

Adolescent (Wave 2) Measures

Parent – adolescent affection (α = .87) was an item response theory (IRT) scale of 10 items assessing respondents’ emotional relationships with their residential parents, including how close they were to their mothers and to their fathers (1 = not close at all, 5 = extremely close), how much each parent cared about them (1 = not at all, 5 = very much), whether each parent was warm and loving toward them, whether they were satisfied with the way they and each parent communicated, and whether they were satisfied with their relationship with each parent (1 = strongly agree, 5 = strongly disagree for the last three item types). The last three item types were reverse coded before scaling, so higher scores indicate higher relationship quality. I created this scale, and other IRT and Rasch scales as noted below, using Thissen, Chen, and Bock’s (2003) MULTILOG 7.0 program. IRT and Rasch scaling techniques use measurement models to estimate respondents’ latent “true” scores on the construct of interest, based on the observed indicators (Raudenbush, Johnson, & Sampson, 2003). The resulting scores have desirable statistical properties: They are approximately normally distributed and, unlike summative scales, they are not dominated by the most commonly endorsed items and are not dependent on the number of items included. Scores for respondents in single-parent households were based on the IRT parameters from the entire sample and their available items.

The scale of parent – adolescent association (α = .71) includes items assessing whether in the past 4 weeks respondents had gone shopping, played a sport, participated in a religious event, talked about dating or parties, attended a cultural or sports event, talked about a personal problem, talked about school work or grades, worked on a school project, or talked about other school-related things with their residential mothers and fathers (0 = no, 1 = yes for each item). Scores were created via a Rasch model. Although ordinal indicators of association might have permitted finer distinctions, the Rasch model makes optimal use of the dichotomous indictors by taking into account differences in their rarity and using them to create an unbounded, continuous scale with the desirable properties described above. Scores for respondents in single-parent households were based on the Rasch parameters from the entire sample and their available items.

Finally, adolescent sibling relationship quality (α = .69) is based on the scale used by McHale and colleagues (McHale, Bissell, & Kim, 2009) and is an IRT scale of how often respondents felt love for the surveyed sibling (1 = very often, 5 = never), how much time the siblings spent together (1 = a lot, 4 = none), and how much time they spent with the same friends (1 = a lot, 4 = none). Items were reverse coded so higher scores indicate higher relationship quality. For each sibling pair, the two siblings’ scores on this scale were averaged to create a dyadic measure.

Young Adult (Wave 3) Measures

Parent – offspring affection (α = .83) was an IRT scale of six items assessing whether grown respondents enjoyed doing things with their mothers and with their fathers (1 = strongly agree, 5 = strongly disagree), whether each parent was warm and loving toward them (1 = strongly agree, 5 = strongly disagree), and how close they felt to each parent (1 = extremely close, 5 = not close at all). Items were reverse coded so higher scores indicate higher relationship quality.

Two measures of parent – offspring material support were used. Parent – offspring coresidence indicated whether respondents lived with a parent at the time of the Wave 3 interview (0 = no, 1 = yes). Respondents also reported whether in the past year each parent had given them money or paid for anything significant for them (excluding birthday and holiday gifts). Recipients indicated the total value of assistance from each parent by choosing from a list of ranges, from under $200 to over $1,000. Together, these items provided the lower and upper bounds of the total value of parental financial assistance to each respondent. Financial support from parents was measured as the logged midpoint of the respondent’s personal range of dollar values. The average amount received across the entire sample was $161; the average among the subset of respondents who received any financial support was $902. To check for robustness, in a supplemental version of the model predicting financial support, I used interval regression to predict the logged upper and lower bounds of the value of support from signed within-dyad difference scores on the predictors. This type of model is useful when the dependent variable is interval censored (i.e., when respondents’ scores on the outcome are known to fall within a specific range but their exact scores are unknown). The substantive findings were unchanged (results are available on request). When respondents answered the affection and support questions about multiple mothers or fathers (e.g., biological and stepparents), I used information pertaining to the parents about whom they reported at Wave 2.

Finally, young adult sibling relationship quality (α = .80) was an IRT scale of three items assessing how close respondents felt to the surveyed sibling (0 = not at all, 4 = very), how often they turned to that sibling when they had problems (0 = never, 4 = very often), and how many interests and goals they had in common with that sibling (0 = none, 4 = all).

Control Variables

I included measures of respondents’ age in years at Wave 3 and of whether their gender was male (0 = no, 1 = yes), as well as measures of each sibling pair’s age difference in years and of whether or not the pair was a mixed-gender dyad. Race and ethnicity were a set of dummy variables indicating Hispanic (0 = no, 1 = yes), Black (0 = no, 1 = yes), or other non-White race (0 = no, 1 = yes); White was the omitted reference category. Sibship was measured as the number of other siblings of any age in the household at Wave 2 (0 = none, 1 = one, 2 = two or more). A measure of household socioeconomic status was the mean of the z scores of the residential parents’ occupational prestige and educational level as reported by the responding parent at Wave 1; higher values indicate higher socioeconomic status. For respondents in single-parent households this measure represents the mean of the z scores of the relevant parent’s occupational prestige and educational level. Parental economic hardship indicated whether at Wave 1 the responding parent reported not having enough money to pay bills (0 = no, 1 = yes). Finally, I included a measure of whether the siblings lived in a two-parent household at Wave 2 (0 = no, 1 = yes). Descriptive statistics for the study variables are shown in Table 1.

Table 1.

Descriptive Statistics for Study Variables (N = 2,940 Cases in 1,470 Sibling Dyads)

Variable M SD Range
Parent – adolescent affection 0.10 0.85 −3.20 – 1.47
Parent – adolescent association 0.02 0.78 −1.42 – 2.88
Adolescent sibling relationship quality 0.002 0.77 −2.09 – 1.04
Parent – adult offspring affection 0.01 0.78 −3.36 – 0.93
Parent – adult offspring coresidence (1 = yes) 0.41 0.49 0 – 1
Parental financial support of adult offspring (logged dollars) 5.08 3.11 0 – 8.16
Adult sibling relationship quality 0.10 0.85 −2.27 – 1.80
Sibling difference in parent – adolescent affection 0.80 0.67 0 – 4.02
Sibling difference in parent – adolescent association 0.73 0.59 0 – 3.31
Sibling difference in parent – adult offspring affection 0.66 0.61 0 – 3.45
Only one adult offspring coresides with parents (1 = yes) 0.36 0.48 0 – 1
Sibling difference in parental financial support 2.61 2.86 0 – 8.16
Age in years at the adult interview 21.95 1.72 18 – 27
Male gender (1 = yes) 0.48 0.50 0 – 1
Sibling age difference 1.44 1.50 0 – 7
Mixed-gender sibling dyad (1 = yes) 0.35 0.48 0 – 1
Hispanic (1 = yes) 0.15 0.36 0 – 1
Black (1 = yes) 0.20 0.42 0 – 1
Other non-White race (1 = yes) 0.11 0.31 0 – 1
Sibship 0.52 0.70 0 – 2
Household socioeconomic status during adolescence 0.03 0.87 −2.19 – 1.53
Parental economic hardship during adolescence (1 = yes) 0.20 0.41 0 – 1
Two-parent household during adolescence (1 = yes) 0.67 0.48 0 – 1
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Analytic Strategy

The analytic strategy had two components. First, I examined whether within sibling pairs higher levels of parent – adolescent affection and association predicted higher levels of parent – adult affection, greater odds of parent – adult coresidence, and higher levels of parent – adult financial support. I did this via fixed-effects regression models. Conceptually and statistically, in designs where individuals are nested within groups, the variance in a given predictor or outcome can be separated into a group-level component and an individual-level component. For example, although my own level of intergenerational support partly reflects how generally supportive my parents are toward their offspring, it also is partly idiosyncratic to my personal intergenerational relationship. Examinations of sibling disparities require the isolation of the latter, individual-level variance. Fixed-effects models achieve this by distinguishing between a sibling pair’s mean score on a variable (e.g., the average amount of financial support that my sibling and I received) and an individual sibling’s deviation from the pair’s average (e.g., the difference between the amount of financial support that I received and the average amount received by my sibling and me), and by basing estimates only on the latter. The models are conceptually similar to analyses using signed difference scores as predictors and outcomes, and the substantive results from such analyses resemble those presented here (results are available on request).

A powerful feature of the fixed-effects approach is that the influence of all factors that do not differ between siblings, whether they are observed or unobserved, is excluded by design (Firebaugh, 2008). For example, although household socioeconomic status may affect parents’ overall provision of financial support, it cannot explain why different siblings in the same household receive different amounts of support. Variables that characterize sibling pairs or families, as opposed to individual siblings, thus can be (and in fact must be) excluded from the model. Coefficients in the models represent the associations between an individual sibling’s deviation from the pair’s mean score on the outcome and that sibling’s deviations from the pair’s mean scores on the predictors. For example, the coefficient for age in predicting financial support indicates whether the older sibling in a pair receives more or less financial support. Positive coefficients for parent – adolescent affection or association in predicting parent – adult affection or support thus would indicate that the sibling who is favored during adolescence continues to be favored in young adulthood. I used linear regression for the models predicting parent – adult affection and financial support and logistic regression for the model predicting coresidence. In supplementary models I examined whether the findings hold among same-age siblings. Additional models included interaction terms between parent – adolescent affection and association and parent – offspring coresidence to determine whether any longitudinal effects of these forms of solidarity depended on continued coresidence with parents.

Second, I examined whether parents’ differential treatment of young adult siblings negatively affected sibling relationship quality. First, for each sibling pair, I created three variables representing the absolute values of the differences between the two siblings’ scores for parent – offspring affection, coresidence, and financial support. I then predicted sibling relationship quality from these unsigned differences, and from controls for adolescent sibling relationship quality, demographic characteristics, and sibling age and gender differences, via an actor – partner interdependence model (APIM; Kenny, Kashy, & Cook, 2006). The APIM allows the modeling of dyadic interdependence by predicting outcomes as a function of qualities of both members of a dyad and of the dyad itself. In this study, as described in more detail below, the APIM was estimated via a multilevel model that allowed the simultaneous estimation of a within-dyad model and a between-dyad model. The APIM also addressed the statistical problem of dependence arising from the nesting of individual respondents within sibling dyads and, for the 9% of respondents with more than one participating sibling, the nesting of sibling dyads within families. If this nesting were not addressed, the significance tests would be too liberal, because sibling reports of relationship quality varied systematically across the nesting units.

In the multilevel model, Level 1 featured data for individuals (including a specific sibling’s scores on the individual-level predictors), Level 2 featured data for sibling dyads (including the unsigned difference scores on the intergenerational relations measures), and Level 3 featured data for families (including all variables that are constant across the siblings in a family). The ultimate dependent variable in the analysis was individual respondents’ reports of the quality of their relationship with a specific study sibling. The Level 1 model predicted these individual reports from individual-level information (i.e., measures of both siblings’ relations with parents, controlling for both siblings’ ages and genders). The main coefficients of interest came from Level 2. The multilevel framework treats both individual siblings’ reports of their relationship quality as indicators of the dyad’s underlying “true” level of relationship quality, represented by the Level 2 intercept (cf. Raudenbush et al., 2003). This intercept serves as the outcome for the Level 2 predictors, which are measures of disparities in the siblings’ relations with parents and sibling age and gender differences. The coefficients for the disparity measures thus indicate the effect of those disparities on a latent continuous measure of dyadic sibling relationship quality, adjusted for the control variables. Negative coefficients would indicate that more differential parental treatment predicts lower dyadic sibling relationship quality. Supplementary analyses included interactions between differential parental treatment and sibling age and gender differences to examine whether differential treatment has the greatest impact on relations between demographically similar siblings.

Results

Stability in Parental Differential Treatment from Adolescence to Young Adulthood

The fixed-effects analyses of whether sibling inequalities in parent – adolescent affection and association predicted later inequalities in parent – offspring affection and material support are presented in Table 2. The top half of the table shows the results for all full sibling pairs. Model 1 shows that, within sibling dyads, the sibling who experienced more parent – adolescent affection continued to experience more parent – offspring affection as a young adult. Multiplying the coefficient for parent – adolescent affection (0.20) by the average absolute sibling difference in parent – adolescent affection scores (0.80) revealed that adolescents who experienced a typical degree of favoritism on this measure went on to have affection scores approximately one-fifth of a standard deviation (0.16) above their grown siblings’ scores. For a dyad reporting extreme favoritism (an absolute adolescent difference score 2 SD above the mean [2.14]), the resulting sibling difference in later parental affection was half a standard deviation (0.43). Preferential treatment in terms of parent – adolescent association did not predict more parent – adult affection. Finally, the modest total R2 value (.13) was similar to those reported in past between-family studies (e.g., Aquilino, 1997). The proportion of within-family variance explained was even more modest (not shown in table; R2within = .06).

Table 2.

Fixed Effects Coefficients Predicting Between-Sibling Differences in Young Adults’ Relationships With and Support From Parents, Among All Full Siblings and Same-Age Full Siblings (Twins)

Dependent variables
Model 1 Model 2 Model 3
Parent – offspring relationship qualitya Parent – offspring coresidenceb Parental financial supporta
Predictor B SE β B SE OR B SE β
All full siblings (N = 2,940)
 Parent – adolescent affection 0.20*** 0.03 .22 0.14 0.09 1.15 0.33** 0.09 .09
 Parent – adolescent association 0.01 0.03 .01 −0.08 0.11 .92 −0.09 0.12 .02
 R2 (total) .13 .04
 χ2 58.43
 df 4
 Proportion coresiding with parents .41
Twins (n= 1,146)
 Parent – adolescent affection 0.13** 0.04 .15 0.46** 0.17 1.58 0.43** 0.12 .12
 Parent – adolescent association 0.08 0.04 .08 −0.38† 0.20 .69 −0.09 0.18 .02
 R2 (total) .04 .07
 χ2 69.02
 df 4
 Proportion coresiding with parents .40
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Note: Controls are offspring male gender and, for “All full siblings” models, age (omitted from the table). OR = odds ratio.

a

Linear coefficients shown.

b

Logistic coefficients shown.

†

p < .10.

**

p < .01.

***

p < .001.

Model 2 in the top half of Table 2 shows that the sibling with higher levels of parent – adolescent affection or association did not have significantly greater odds of later coresidence with parents. The positive coefficient for parent – adolescent affection suggested that if either of the two dimensions of solidarity foreshadowed later coresidence it was this one, but the coefficient was not statistically significant (b = 0.14, p > .05). Finally, Model 3 in the top half of Table 2 shows that the sibling with higher parent – adolescent affection went on to receive significantly more financial support from parents. Predicted values revealed that, all else equal, in dyads who reported an average disparity in parent – adolescent affection the favored sibling went on to receive 30% more money ($184 vs. $142). In dyads who reported an extreme disparity (an absolute difference score 2 SD above the mean), the favored sibling went on to receive twice as much money ($229 vs. $114). Still, the total R2 value was modest (.04). Also, sibling differences in parent – adolescent association did not predict later differences in the odds of receiving financial support.

Although these analyses controlled for age, intergenerational support is age linked, raising the concern that the above results reflect parents’ different treatment of offspring of different ages. As a check for robustness, the bottom half of Table 2 shows estimates from similar analyses of data only from same-age sibling dyads. Even with age held constant, the sibling who experienced more parent – adolescent affection went on to experience more parent – offspring affection and to receive more money from parents as a young adult. In addition, among same-age siblings, early differences in affection predicted later differences in coresidence with parents, such that in a twin pair reporting an average disparity in affection the favored adolescent went on to have 45% higher odds of coresiding with parents than did his or her sibling ([exp(0.46)]0.80 = 1.45). Again, greater parent – adolescent association failed to predict greater parent – offspring affection or material support. If anything, the adolescent who spent more time with parents had lower odds of coresiding with parents as a young adult (b = −0.38, p < .10).

Additional analyses revealed that in both the full sibling sample and the twin sample parent – adolescent affection and association failed to interact with later parent – offspring coresidence to predict parent – offspring affection or financial support (results are available on request). This indicates that longitudinal associations between these forms of inequality did not depend on siblings’ continued coresidence with parents. Together, these results suggest that the direction of sibling differences in intergenerational solidarity has stability across the transition to adulthood, such that parents are closer to and more materially supportive of the grown offspring with whom they previously had a closer affective relationship.

Effects of Disparities in Parent – Young Adult Relations on Sibling Relationship Quality

The APIM examining whether disparities in parent – offspring relationships affect young adult siblings’ dyadic relationship quality is presented in Table 3. The coefficients for the dyad-level predictors indicated that sibling differences in current parent – offspring affection and coresidence did not affect sibling relationship quality, but differences in the amount of received parental financial support did. Relative to dyads who received equal amounts of financial support, a $100 disparity in support reduced dyadic sibling relationship quality by approximately 0.11 SD (ln[$100] × −0.02 = −0.09). The difference was modest, but it was visible net of earlier sibling relationship quality (itself a strong predictor of grown siblings’ relationship quality) and the control variables. Predicted values based on the dyad-level and individual-level coefficients together indicated that the modest effect of unequal support may have been driven mainly by its effect on the disfavored sibling’s report of sibling relationship quality. For instance, in a dyad reporting a $100 disparity in support, the favored sibling’s report of sibling relationship quality was close to average (0.11), but the disfavored sibling’s report was slightly below average (0.03).

Table 3.

Actor – Partner Interdependence Model Coefficients Predicting Young Adult Sibling Relationship Quality From Parental Differential Treatment (N = 2,940 Cases in 1,470 Sibling Dyads)

Predictor B SE
Dyad level
 Sibling difference in parent – offspring affection −0.01 0.03
 Only one adult offspring coresides with parents −0.05 0.04
 Sibling difference in parental financial support −0.02* 0.01
 Adolescent sibling relationship quality 0.40*** 0.03
Individual level
 Parent – respondent affection 0.22*** 0.02
 Parent – respondent coresidence 0.06 0.03
 Parental financial support of respondent 0.01† 0.01
 Sibling’s parent – offspring affection 0.03 0.02
 Parent – sibling coresidence −0.05 0.03
 Parental financial support of sibling −0.01 0.01
Estimated parameters 27
Deviance 6,176.45
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Note: Family-level controls are race and ethnicity, sibship, household socioeconomic status, parental economic hardship, and two-parent household during adolescence (omitted from the table). Dyad-level controls are sibling age difference and sibling gender difference (omitted from the table). Individual-level controls are age and male gender (omitted from the table).

†

p < .10.

*

p < .05.

***

p < .001.

Additional analyses revealed that the effect of parental differential treatment on sibling relationship quality was not moderated by sibling age and gender differences. Terms for the interaction of age difference in years with disparities in parent – offspring affection (b = 0.02, p > .05), coresidence (b = 0.01, p > .05), and financial support (b = −0.0001, p > .05) in predicting sibling relationship quality were not statistically significant (full results are available on request); neither were terms for the interaction of the mixed-gender dyad indicator with disparities in parent – offspring affection (b = 0.06, p > .05), coresidence (b = 0.11, p > .05), and financial support (b = 0.01, p > .05). As a final check on whether same-age siblings might be most affected by unequal treatment, I estimated an APIM using data only from same-age siblings. The pattern of findings was similar to the pattern in Table 3, although a larger standard error meant that the coefficient for differences in financial support was only marginally significant (b = −0.02, p < .10).

In sum, the findings suggest that within-family inequalities in parent – adolescent relationship quality foreshadow later inequalities in parent – offspring relationship quality and parents’ provision of material support and, in turn, inequalities in parental financial support may undermine the quality of grown siblings’ relationships.

Discussion

Inequality exists as much within families as it does between them (Conley, 1999). This observation implies that if parents help shape young adult outcomes, they may not do so uniformly for all of their offspring (Fingerman et al., 2012). In this study I examined the relational precursors to sibling inequalities in affection and material support received from parents during the transition to adulthood. I also examined the implications of differential treatment by parents for young adult siblings’ relationship quality. I proposed that disparities in adolescent siblings’ affective and associational solidarity with parents would foreshadow disparities in young adult siblings’ affective and functional solidarity with parents and that these latter disparities in turn would reduce sibling closeness. These questions can be addressed only by research designs that account for the multiple interwoven dyads within families. This approach thus underscores the importance of the broader family context for studies of dyadic intergenerational relations (Spitze, Ward, Deane, & Zhuo, 2012; Ward, 2008).

I found partial support for Hypothesis 1: that the direction of sibling differences in parent – offspring solidarity would be stable across siblings’ transition to adulthood. Consistent with the predictions of solidarity theory (Silverstein et al., 2002, 2006), the adolescent sibling who was closer to parents tended to remain closer to parents across the transition and to receive more material support as a young adult. These effects were moderate in size, although most of the variance in parental affection and financial support remained unexplained. In addition, differences in affection did not predict later differences in parent – offspring coresidence among the complete sibling sample. Taken together, these findings suggest that parents do give more love and support to the grown child with whom they historically had a better relationship, but intergenerational relations and siblings’ relative statuses can undergo a considerable amount of change as offspring enter adulthood.

Contrary to expectations, sibling differences in parent – adolescent association were not a consistent predictor of later differences in parent – offspring affection or support. This finding appears to counter the prediction that contact is an important precondition to functional solidarity (Hogerbrugge & Komter, 2012). Although this null finding could mean that solidarity theory should be modified, there are other potential explanations. First, a better measure of association might predict later differential solidarity. The measure used here covered nine types of shared time, but it was based on dichotomous indicators; more nuanced measures may have yielded different results. Second, association could predict differential affection or support over shorter time lags; such a relationship would be missed in this study’s design. Third, at Wave 2 all respondents coresided with parents, so most siblings probably had some amount of contact with parents. Still, the primacy of differential affection in predicting later differential affection and support suggests that a history of general emotional goodwill, rather than past opportunities for interaction, may be the element of solidarity that most influences later parent – offspring relations.

The results also partially support Hypothesis 2: Consistent with social comparison theory (Festinger, 1954), differential intergenerational solidarity appeared to reduce young adult siblings’ relationship quality. Yet this effect was specific to differential financial support. Sibling relations did not appear to suffer when the siblings received unequal amounts of affection or housing support from parents. These differences in effects could stem in part from differences in the amount of variability in the financial support, affection, and housing support variables. Still, the importance of money in this young adult sample also could reflect developmental changes in the most salient domains of intergenerational relationships (Conger & Little, 2010). Specifically, money may be an especially valuable family commodity during the transition to adulthood. It is interesting that the sibling who received more financial support tended to perceive less impact of the disparity on the sibling relationship. This also is consistent with social comparison theory, and with scholars’ assertion that different relatives can have very different appraisals of the same family event (Aquilino, 1999; Suitor, Sechrist, Steinhour, & Pillemer, 2006).

Siblings’ differing views highlight the influence of perception on relationship outcomes. This study measured sibling inequalities via siblings’ independent reports of their intergenerational relationships. Although some aspects of those relationships, such as living with parents, might be readily observable, respondents may not have had complete knowledge of their parents’ treatment of siblings. Furthermore, even when respondents accurately perceived that their siblings were favored by some measure, they may have perceived that favoritism as fair (Boll, Ferring, & Filipp, 2005). Such scenarios might explain why inequalities in parental affection or coresidence failed to influence sibling relationship quality. Scholars should continue to examine whether real and perceived parental favoritism affect sibling relations, because siblings are an important latent source of support for adults (White & Riedman, 1992), and they eventually may need to coordinate the care of aging parents and the settling of parents’ estates.

Despite good reasons to expect that they would, I found little evidence that parent – offspring coresidence and sibling age and gender gaps explained or moderated the observed relationships. These results confirm the robustness of the findings and the generality of the processes examined, but they also contradict past findings that home-leaving produces discontinuity in family relations (Aquilino, 1997) and social comparison theory’s prediction that low status in relation to similar others matters most (Festinger, 1954). Perhaps dyadic intergenerational relations change when offspring move out of the parental home, even if siblings’ relative statuses within the family do not. Also, perhaps grown siblings judge their similarity to each other not on the basis of demographics but on the basis of other factors. For instance, for young adults, the relevant dimensions of similarity could involve college enrollment, family formation, or other major developmental tasks.

This study has broader implications for theories of family development and relationships. The findings confirm several predictions from solidarity theory’s model of intergenerational relations (Silverstein et al., 2006), under which affinity accumulates over time and lays the groundwork for later kin support. Yet they also indicate that these relational elements should be considered in the context of the wider family network. Adolescence could be a critical period not only for dyadic relationship development, but also for the establishment of within-family hierarchies (Aquilino, 1999; Rossi & Rossi, 1990). This study suggests that siblings’ relative within-family statuses show some stability once they are established early in the shared life course. The link between favoritism and rivalry also raises the possibility that family dynamics are self-reinforcing over time, such that less close children come to feel marginalized not only by parents, but also by other immediate kin. It thus appears important for scholars to account for the institutional memory of families when examining variation in family solidarity later in the shared life course (Bedford, 1992).

This study also has implications for theory and research on stratification. Between-family studies show that background socioeconomic status has powerful effects on young adults’ own socioeconomic attainment (Swartz, 2009). The present findings show that individuals stand to benefit not only from their membership in certain families, but also from their statuses within those families. It thus may be incorrect to think of siblings as sharing a unitary socioeconomic background (Conley, 1999). Rather, the internal social structures of families of origin also can shape young people’s material outcomes.

The results suggest several promising directions for future research. First, because family relations may vary by gender (Rossi & Rossi, 1990), researchers could usefully examine whether maternal and paternal differential treatment are equally stable and have comparable effects on sibling relations. In this study reports of relations with mothers and with fathers were moderately positively correlated (Pearson rs ranged from .44 to .74 depending on the dimension), which leaves room for differences in the causes and consequences of relations with each parent. Parent gender also could interact with offspring gender to shape the examined processes. Second, researchers could integrate work on the relational predictors of parents’ support of young adult offspring with work on the offspring life circumstances that appear to trigger this support. For example, parents’ affection toward children could enhance children’s chances of attending college, which in turn could give parents an opportunity to express their latent willingness to financially support those children. Finally, we need more research on the longer-term effects of parental support on adult offspring outcomes. Because parents do not uniformly support their grown children, a focus on sibling differences could provide a useful framework for examinations of how consequential this support is for offspring well-being and attainment and whether it has lasting effects on family relationships.

This study has some limitations. It relied on offspring reports of their relationships with parents. It did not examine negative aspects of intergenerational relationships or intergenerational ambivalence, which could affect various aspects of solidarity (Hogerbrugge & Komter, 2012). It did not examine some potentially important forms of material support, such as gifts and vehicle transfers. Unlike financial and housing assistance, these forms tend to be nonrecurring, but they are common and could be intertwined with family dynamics. Finally, actual parental support is not a perfect indicator of the latent availability of support (Silverstein et al., 1997), and I had no measure of parents’ willingness to support unsupported offspring. Still, this study’s longitudinal within-family design, developmentally relevant measures, and attention to both parent – offspring and sibling relations make important contributions to a growing literature on the lifelong importance of families of origin.

In sum, intergenerational affection and material support may be in part a reflection of the favorable predispositions established in specific dyads during earlier phases of the shared life course, and they may have ripple effects on other family bonds. Still, there clearly is much room for other sources of continuity and change in intergenerational relationships, and there is much to be learned about the connections between the multiple interwoven dyads within many families. This study thus provides only a partial answer to these overarching questions about resource distribution in families: Who gets what, why, and to what effect?

Acknowledgments

Funding for this research and the resulting publication was provided in part by the Florida State University Council on Research & Creativity through a First Year Assistant Professor award. I thank Wayne Osgood, Eric Stewart, and Patricia Warren for their helpful comments; Roshni Ladny and Melissa Nadel for research assistance; and Eric Baumer for feedback on an early version of the design. This research used data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from Grant P01-HD31921 for this analysis.

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