Parental emotional support during emerging adulthood and Baby Boomers’ well-being in midlife

Abstract

This study examined whether parental emotional support around emerging adulthood influenced well-being in midlife. We applied latent growth curve (LGC) models on 337 Baby Boomers who were in their late teens to early 20s when they entered the Longitudinal Study of Generations (LSOG) in 1971. There was a small but significant decline in self-rated health and positive emotions through 2005, but not depressive symptoms. Greater support from fathers in 1971 was associated with better self-rated health, less depression, and a slower decline in self-rated health across midlife. Greater support from mothers was associated with more positive emotions. These associations did not significantly differ among sons and daughters. Findings are discussed in the context of cumulative advantage/disadvantage and life-stage specific challenges to highlight the importance of parental emotional support during life transitions.

Keywords

emerging adulthood emotional support midlife

There has been growing attention paid to the lasting influence of early parent-child relationships on well-being in midlife and beyond (Mallers, Charles, Neupert, & Almeida, 2010). According to the life-course approach, past experiences may have profound impact on future life trajectories (Crosnoe & Elder, 2004). Social and economic changes since the late 20th century have provided ample opportunities to explore increasingly diverse patterns of life-course trajectories. As a result of a prolonged transition from adolescence to adulthood, and longer life-expectancy that delays retirement, emerging adulthood and the now middle-aged to older Baby Boom generation (Fingerman, Pillemer, Silverstein, & Suitor, 2012) have become important topics in human development. Contiguous generations do not age in a vacuum. Intergenerational family relationships serve as an important context for development. Guided by the cumulative advantage/disadvantage perspective (Dannefer, 2003), we explored whether parents’ emotional support during emerging adulthood was associated with increasingly divergent trajectories of well-being in a Baby Boom cohort. Building on research that illustrated the unique contribution of mothers and fathers in development (Mallers et al., 2010; Poon & Knight, 2012), we looked for potential differences between the effects of mothers’ and fathers’ emotional support on their daughters and sons.

Maternal and paternal emotional support during life transitions

Attachment theory suggests that supportive parent-child relationships in infancy and early childhood promote comfort with closeness and foster a willingness to explore the social world (Bowlby, 1982). Parents’ support remains influential in adulthood (Fingerman, Miller, Birditt, & Zarit, 2009). In one study, middle-aged and older adults who recalled poor childhood emotional support reported more depressive symptoms and health problems (Shaw, Krause, Chatters, Connell, & Ingersoll-Dayton, 2004). Prospective studies revealed that individuals who reported emotional closeness to their parents in young adulthood were more likely to be well-adjusted and physically fit several decades later (Andersson & Stevens, 1993; Crosnoe & Elder, 2004).

Derived from observed changes in human development during the late 20th century, emerging adulthood refers to a transitional period from adolescence to adulthood (Arnett, 2000) that is characterized by identity explorations. In studies that link early parent–child relationships to well-being in late life (e.g., Shaw et al., 2004), parents’ emotional support often tap at elements of unconditional positive regard (e.g., love) and autonomy support (e.g., trust). Less conditional positive regard and more autonomy support are associated with better emotional well-being and academic performance in late adolescence (Roth, Assor, Niemiec, Ryan, & Deci, 2009). During emerging adulthood, stronger parental emotional support may continue to prepare individuals to accomplish identity development.

Mothers and fathers interact with their children in different manners (Grossmann et al., 2002). While mothers are more involved as primary caregivers that provide physical comfort, fathers play with their child in a mature manner and try to understand the child’s perspective when giving suggestions and explanations (Grossman et al., 2002). By engaging the child this way, fathers may promote greater independence and better self-image. Research shows that supportive father–child relationship is associated with better self-control, more prosocial behaviors, and better peer relationships in early adolescence (Williams & Kelly, 2005). Identity explorations during emerging adulthood can result in rejections and disappointments (Arnett, 2000). Based on different parenting expectations in early childhood, mothers and fathers may contribute different degrees of nurturance and autonomy support to help their children through future life transitions in emerging adulthood and midlife.

Few studies have examined the longitudinal effects of maternal and paternal emotional support on well-being beyond midlife. In addition, cross-sectional and prospective studies suggest that the influence of mothers’ and fathers’ support may vary depending on the child’s gender (Mallers et al., 2010; Poon & Knight, 2012), rendering it important to include both female and male participants in this type of research. Of the two long-term longitudinal studies that measured maternal and paternal emotional support early in life, one only included adult sons (Harvard Study of Adult Development; Vaillant & Mukamal, 2001). In the other study that included both daughters and sons, emotional closeness to parents was retrospectively reported when participants were already in their 30s to mid-40s (Terman Study of the Life Cycle; Martin, Friedman, Clark, & Tucker, 2005).

Cumulative advantage/disadvantage in the life course

One mechanism through which parental support in emerging adulthood may affect well-being across midlife is cumulative advantage/disadvantage (Dannefer, 2003). Successes early in life may lead to additional advantages, whereas early risks may lead to further disadvantages. This results in increasingly divergent trajectories of inter-individual inequality. Researchers have identified psychosocial factors as possible catalysts of this phenomenon. For example, parental support at baseline was associated with a more positive self-reported health trajectory in a longitudinal study on adolescents aged 12–17 years, perhaps because supportive parents were more likely to encourage a healthy lifestyle in their children at a young age (Wickrama, Lorenz, & Conger, 1997).

Attempts to apply the cumulative advantage/disadvantage perspective to parental support have been complicated by the paucity of comprehensive longitudinal studies across an extended period of time beyond adolescence (Martin et al., 2005). To assess for cumulative advantage/disadvantage, some studies have relied on cross-sectional or prospective analysis of retrospective measures of early parent–child experiences and adulthood health outcomes (Mallers et al., 2010; Pitzer & Fingerman, 2010; Poon & Knight, 2012). Others have operationalized cumulative disadvantage as the sum of adverse childhood experiences (Felitti et al., 1998). Departing from these studies, a more advanced approach to assess for cumulative advantage/disadvantage involves conditional latent growth curve (LGC) models of health trajectories on longitudinal data (Wickrama et al., 1997).

The current study

This study expanded research into the role of mothers’ and fathers’ emotional support in emerging adulthood in affecting well-being in midlife among a Baby Boom sample, and examined if there was empirical support to the cumulative advantage/disadvantage phenomenon. We were not aware of other existing long-term longitudinal studies that have investigated the influence of mothers’ and fathers’ emotional support during emerging adulthood on both daughters and sons across more than three decades. We used LGC models to examine health trajectories as a continuous process across adulthood, making possible the investigation of individual and group variations in health trajectories as a function of mothers’ and fathers’ emotional support. Analysis of a dataset that included various measures of physical health, positive emotions, and depressive symptoms allowed us to look at both positive and negative outcomes longitudinally. We hypothesized that greater maternal and paternal emotional support in emerging adulthood would be associated with better self-rated health, more positive emotions, and less depression in midlife (Hypothesis 1). Informed by the cumulative advantage/disadvantage perspective, we predicted more positive trajectories of well-being across midlife when individuals endorsed more parental emotional support during emerging adulthood (Hypothesis 2). Although no specific hypothesis regarding the difference between father– and mother–child dyads was made, we explored these potential differences in post-hoc analysis.

Method

Sample

Nearly 400 three-generation families were randomly drawn from members of a Southern Californian health maintenance organization (HMO) in 1971 (Bengtson, Biblarz, & Roberts, 2002). Self-report questionnaires were administered in 1971, 1985, 1988, 1991, 1994, 1997, 2000, and 2005. To reduce the extraneous influence of early parental loss due to death or divorce (Poon & Knight, 2012), we limited our sample to 337 unmarried Baby Boomers whose parents were alive, married to each other, and living with the participant in 1971. Half of the participants were female. Their average age was 17.78 years (SD = 1.34; Range = 15–25). Of the 292 participants who reported their racial background, 79% identified themselves as non-Hispanic white. The next major group was “Other hyphenated identity” possibly from European immigrant communities (12%). Of the 266 participants who reported their household income, the median income fell within $17,000 to $18,999. This was more than twice as much as the median income of $7,913 in 1971 (U.S. Census Bureau, 2012). One-hundred and seventy three participants (51%) remained in the study in 2005. The percentage of female participants increased to 60%. Their average age was 51.80 years (SD = 1.70; Range = 50–59), again with 79% being non-Hispanic white.

Measures

Parental emotional support

Emotional support from mothers and fathers were measured separately in 1971, each with five items on the level of understanding, trust, fairness, respect, and affection (e.g., “How much affection do you feel your father/mother have for you?”). Each item was rated on a six-point scale from 1 (Not at all) to 6 (Extremely). Internal consistencies of paternal and maternal support were good (Cronbach’s α = .86 and .87, respectively). The five items were averaged, with a higher score indicating more support from a specific parent.

Self-rated health

Empirical evidence strongly supported self-rated health as a powerful predictor of morbidity and mortality above and beyond other objective health measures and identified risk factors, particularly among older adults (Idler & Benyamini, 1997). During Waves 2 to 8, participants were asked to rate their health on a four-point scale from 1 (Excellent) to 4 (Poor) using one item (“Compared to people your own age, how would you rate your overall physical health at the present time?”). The scale was reverse-coded, with higher scores indicating better health.

Positive emotions

Five items from the Bradburn Affect Balance Scale (Bradburn, 1969) were used to measure positive emotions in Waves 2 to 8. Participants were asked if they felt “particularly excited or interested in something,” “proud because someone complimented you on something you had done,” “pleased about having accomplished something,” “on top of the world,” and “that things were really going your way” in the past few weeks. Each item had a score of 1 (Yes) or 0 (No). Item scores were summed, with higher scores indicating more positive emotions. This measure demonstrated acceptable internal reliability from Waves 2 to 8 (KR-20 coefficients = .64–.78).

Depression

Emotional distress was measured using the 20-item Center for Epidemiologic Studies Depression scale (CES-D; Radloff, 1977) from Waves 2 to 8. Participants were asked if they experienced depressed mood, feelings of worthlessness, helplessness and hopelessness, and somatic symptoms in the past week. Each item was rated on a four-point scale from 0 (Never) to 3 (Always). These items were summed after reversing the positive affect items, with a score ranging of 0 to 60. A score of 16 and above was suggestive of clinical depression. The CES-D demonstrated good internal reliability from Waves 2 to 8 (Cronbach’s α = .87–.93).

Covariates

Age and gender (0 = Male, 1 = Female) were included in all analyses. As socioeconomic status (SES) may explain some of the variability in parental support and cumulative advantage/disadvantage, we included race and household income as proxies of SES. Because of the low frequencies of other ethnic groups and ambiguous categories like “other hyphenated identity,” we dichotomized race into 0 (Non-Hispanic white) and 1 (Non-white). Annual household income in 1971 was assessed by an ordinal-scale item with $1,999 increments from 1 ($3,000–$4,999) to 16 (> $50,000).

Data analysis

We used LGC models to test our hypotheses. To reduce model complexity, each outcome was tested in a separate model. We used mixed-effects models with a random effect accounting for participants from the same family. Maximum likelihood algorithm with robust standard errors (MLR) was used to derive parameter estimates with standard errors and chi-square statistics that were robust to non-normality in complex data (Muthén & Muthén, 1998–2011). MLR utilizes a full information maximum likelihood algorithm that estimates model parameters based on the assumption that data are missing at random. It uses information from all observed data, including the mean and variance of missing portions of the variable given the observed portions of other variables.

Unconditional LGC models estimated the stability and change of self-rated health, positive emotions, and depressive symptoms from Wave 2 to 8. Because attrition could bias the sample, LGC analysis included all possible respondents with all missing patterns (McArdle & Hamagami, 1992). Most LGC analyses define the intercept as the earliest measurement. Given our interest in well-being in midlife, the intercept of the estimated LGC was fixed at Wave 8, with time loadings of −6, −5, −4, −3, −2, −1, and 0 from Wave 2 to 8. Significant variances in the average level and slope of each outcome would imply notable inter-individual differences, making the prediction of their trajectories with parental emotional support meaningful.

Evaluation of model fit was based on a root mean square error of approximation (RMSEA) of .06 or less; and a comparative fit index (CFI) and Tucker-Lewis index (TLI) of .95 or above (Hu & Bentler, 1999). The Satorra-Bentler scaled chi-square difference was calculated using the scaling score and adjusted chi-square values generated by MPlus 6.1 (Muthén & Muthén, 1998–2011) to evaluate nested models. When the chi-square change was non-significant, the conceptually-more parsimonious model with more degrees of freedom would be deemed a better fit to the data.

Results

Descriptive findings

Selective attrition

Logistic regression revealed that female participants were more likely to remain in the study in Wave 8 (Odds Ratio = 1.88, 95% CI = 1.22–2.90, p = .004). Being older (Odds Ratio = 1.00, 95% CI = .88–1.13, p = .97), non-white (Odds Ratio = .94, 95% CI = .54–1.65, p = .83), or having more income (Odds Ratio = 1.01, 95% CI = .94–1.10, p = .72) in 1971 did not predict attrition. Greater maternal (Odds Ratio = .90, 95% CI = .72–1.13, p = .37) and paternal emotional support (Odds Ratio = .94, 95% CI = .77–1.15, p = .50) also did not predict attrition. Accordingly, non-representativeness as a result of selective attrition was not a serious concern in our sample.

Table 1 presents correlations among study variables. LGC models of self-rated health, positive emotions, and depressive symptoms had excellent statistical fit to the data (See Table 2). When we constrained the slopes of self-rated health and positive emotions to zero, model fit deteriorated, suggesting the presence of significant linear changes. When we constrained the slope of depressive symptoms to zero, the model continued to demonstrate excellent statistical fit. The Satorra-Bentler scaled chi-square difference between the LGC model and the no-slope model was non-significant for depression (Adjusted χ² = 4, df = 3, p < .30). The no-slope model with more degrees of freedom was chosen, suggesting relatively stable and low level of depressive symptoms over time.

Table 1.

Correlation matrix of study variables (n = 337).

	1	2	3	4	5	6	7	8	9	10	11	12
1. Age (Wave 1)	–
2. Gender (1 = Female)	−.06	–
3. Race (1 = Non-white)	.12*	−.10	–
4. Income (Wave 1)	.10	−.11	.00	–
5. Maternal support (Wave 1)	.16**	.04	.04	−.09	–
6. Paternal support (Wave 1)	.19***	.09	.02	−.06	.77***	–
7. Self-rated health (Wave 2)	.02	.00	.08	.15	.13	.10	–
8. Self-rated health (Wave 3)	.03	.01	.03	.03	.28***	.29***	.53***	–
9. Self-rated health (Wave 4)	.03	−.03	.03	.01	.21**	.19**	.52***	.69***	–
10. Self-rated health (Wave 5)	.00	−.04	−.05	−.13	.22**	.30***	.52***	.59***	.73***	–
11. Self-rated health (Wave 6)	.02	.09	−.04	.03	.27***	.35***	.53***	.55***	.65***	.74***	–
12. Self-rated health (Wave 7)	.02	−.02	−.02	.05	.14	.21**	.42***	.52***	.59***	.65***	.77**	–
13. Self-rated health (Wave 8)	−.04	.08	−.14	.02	.16*	.18*	.47***	.54***	.64***	.60***	.68***	.66***
14. Positive emotions (Wave 2)	−.10	.10	−.02	.00	.05	.05	.09	.17*	.19*	.13	.17*	.11
15. Positive emotions (Wave 3)	−.00	.04	.00	.00	.05	.08	.10	.34***	.31***	.23**	.33***	.24**
16. Positive emotions (Wave 4)	−.08	−.01	.01	−.14	.17*	.06	.09	.25**	.31***	.22**	.22**	.13
17. Positive emotions (Wave 5)	−.08	.02	.06	.−07	.05	.00	.25**	.17*	.31***	.28***	.21*	.14
18. Positive emotions (Wave 6)	−.07	−.07	.08	.01	.12	.08	.09	.13	.17*	.22**	.21*	.14
19. Positive emotions (Wave 7)	−.06	−.03	.08	−.07	.13	.06	.07	.08	.16*	.22**	.26**	.15*
20. Positive emotions (Wave 8)	−.01	.03	.02	−.09	.05	.00	.09	.21*	.24**	.23**	.30***	.17*
21. Depression (Wave 2)	−.08	.05	−.02	−.12	−.15*	−.15*	−.31**	−.30***	−.24**	−.21*	−.19*	−.11
22. Depression (Wave 3)	−.02	.08	−.05	−.09	−.17*	−.21**	−18*	−.34***	−.29***	−.23**	−.25**	−.20*
23. Depression (Wave 4)	−.04	.00	−.11	−.03	−.19**	−.17*	−.23**	−.35***	−.40***	−.31***	−.30***	−.18*
24. Depression (Wave 5)	−.03	−.05	−.07	.04	−.18*	−.18*	−.15	−.31***	−.31***	−.37***	−.24**	−.24**
25. Depression (Wave 6)	−.02	.05	−.07	−.15	−.13	−.21**	−.14	−.20*	−.27**	−.26**	−.35***	−.21**
26. Depression (Wave 7)	−.07	.07	−.05	.00	−.17*	−.22**	−.16*	−.17*	−.33***	−.35***	−.35***	−.31***
27. Depression (Wave 8)	−.05	−.08	.02	.10	−.12	−.14	−.26**	−.27**	−.33***	−.29***	−.35***	−.23**

Note. *p < .05; **p < .01; ***p < .001.

Table 1.

(Continued)

	13	14	15	16	17	18	19	20	21	22	23	24	25	26
14. Positive emotions (Wave 2)	.01	–
15. Positive emotions (Wave 3)	.26*	.50***	–
16. Positive emotions (Wave 4)	.15	.40***	.51***	–
17. Positive emotions (Wave 5)	.14	.36***	.41***	.48***	–
18. Positive emotions (Wave 6)	.18*	.38***	.37***	.46***	.61***	–
19. Positive emotions (Wave 7)	.19*	.28**	.43***	.47***	.41***	.56***	–
20. Positive emotions (Wave 8)	.19*	.29**	.29***	.31***	.39***	.50***	.42***	–
21. Depression (Wave 2)	−.11	−.29**	−.27**	−.17*	−.20*	−.22**	−.21**	−.14	–
22. Depression (Wave 3)	−.27**	−.17***	−.45***	−.32***	−.25**	−.21*	−.13	−.13	.48***	–
23. Depression (Wave 4)	−.20*	−.21**	−.34***	−.57***	−.31***	−.28***	−.15	−.14*	.39***	.53***	–
24. Depression (Wave 5)	−.31***	−.11	−.24**	−.28***	−.42***	−.22**	−.16	−.17*	.39***	.49***	.53***	–
25. Depression (Wave 6)	−.23**	−.22**	−.28***	−.31***	−.36***	−.49***	−.21**	−.26**	.38***	.49***	.45***	.49***
26. Depression (Wave 7)	−.26**	−.02	−.22**	−.27**	−.24**	−.24**	−.35**	−.17*	.35***	.38***	.46***	.50***	.56***
27. Depression (Wave 8)	−.37***	−.08	−.21**	−.21**	−.26**	−.22**	−.24**	−.38***	.42***	.40***	.41***	.50***	.39***	.58***

Note. *p < .05; **p < .01; ***p < .001.

Table 2.

Goodness of model fit statistics.

Hypothesis 1	CFI	TLI	RMSEA (90% CI)
Self-rated health LGC model	.97	.98	.05 (.02–.08)
No slope model***	.92	.93	.08 (.06–.11)
Positive emotions LGC model	.96	.97	.04 (.00–.07)
No slope model**	.88	.90	.07 (.04–.09)
Depressive symptoms LGC model	.99	.99	.02 (.00–.06)
No slope model	.98	.98	.03 (.00–.06)
Hypothesis 2
Self-rated health (Conditional LGC)	.97	.96	.04 (.01–.05)
Positive emotions (Conditional LGC)	1.0	.99	.01 (.00–.04)
Depressive symptoms (No slope)	.99	.99	.01 (.00–.04)

Note. Satorra-Bentler scaled chi-square difference: **p < .01; ***p < .001.

The estimated level of self-rated health and positive emotions were significantly greater than zero, whereas the level of depressive symptoms was below the clinical cutoff of 16 (Radloff, 1977). There were significant inter-individual variations in these three variables in Wave 8. Significant variations in the rate of change were observed in self-rated health and positive emotions only (See Table 3). Conditional LGC models were performed on self-rated health and positive emotions to determine if parental support explained inter-individual differences in their levels and trajectories. For depressive symptoms, the slope was constrained to zero to test if mothers’ and father’s support were associated with depression in adulthood.

Table 3.

Unstandardized parameter estimates from unconditional LGC models.

	Self-rated health		Positive emotions		Depression
	Level	Slope	Level	Slope	Level	Slope
Mean	2.98 (.06)***	−.03 (.01)**	3.60 (.09)***	−.05 (.02)**	10.71 (.62)***	.05 (.12)
Variance	.58 (.07)***	.01 (.001)**	1.22 (.18)***	.02 (.01)**	47.90 (9.12)***	.56 (.32)
Level and slope	.04 (.01)***		.10 (.03)**		2.53 (1.45)

Note. Robust standard errors are in parentheses. **p < .01; ***p < .001.

Effects of parental emotional support

Partially supporting Hypotheses 1, fathers’ emotional support was positively associated with self-rated health (β = .32, SE = .10, p < .01) and negatively with depression (β = −.24, SE = .11, p < .05). Mothers’ support was positively associated with more positive emotions (β = .27, SE = .13, p < .05; see Table 4). Partially supporting Hypothesis 2, paternal support had a positive association with the linear trajectory of self-rated health from early to middle adulthood (β = .37, SE = .17, p < .05). Baby Boomers who reported more paternal support during emerging adulthood experienced better health and less depression in midlife, as well as a slower decline in self-rated health. Baby Boomers who reported more maternal support during emerging adulthood experienced more positive emotions in midlife. Post-hoc analysis that included the interaction terms between mothers’ or fathers’ emotional support and participants’ gender revealed statistically non-significant interaction effects. The influence of mothers’ and fathers’ emotional support on later well-being did not differ between daughters and sons.

Table 4.

Standardized parameter estimates from conditional models.

	Self-rated health		Positive emotions		Depression
	Level	Slope	Level	Slope	Level
Age (Wave 1 in years)	−.03 (.08)	−.04 (.12)	−.07 (.08)	.06 (.11)	−.02 (.06)
Gender (1 = Female, 0 = Male)	.11 (.13)	.11 (.13)	−.02 (.08)	−.08 (.12)	.06 (.07)
Race (1 = Non-white, 0 = Non-Hispanic white)	−.02 (.08)	−.09 (.15)	.12 (.09)	.14 (.14)	−.01 (.08)
Household income (Wave 1)	−.02 (.08)	−.15 (.13)	−.07 (.09)	−.11 (.12)	−.02 (.07)
Maternal support (Wave 1)	−.05 (.12)	−.29 (.19)	.27 (.13)*	.24 (.18)	−.02 (.11)
Paternal support (Wave 1)	.32 (.10)**	.37 (.17)*	−.12 (.12)	−.22 (.17)	−.24 (.11)*

Note. Robust standard errors are in parentheses. *p < .05; **p < .01.

Discussion

The purpose of this study was to examine the role of parental emotional support during the life-course transition of emerging adulthood in impacting later well-being among the Baby Boom generation. This study extended previous research in several ways. First, the longitudinal nature of available data allowed for analysing actual well-being trajectories that spanned more than three decades since emerging adulthood. Second, inclusion of male and female participants and emotional support from both parents made possible the investigation of the respective influence of mothers’ and fathers’ support during emerging adulthood. Third, this study linked two contemporary interests in developmental research by exploring the impact of parental emotional support during emerging adulthood on middle-aged Baby Boomers. Not only were findings consistent with previous research on the influence of early parental emotional support on later well-being, but they also shed light on the role of maternal and paternal support during critical life transitions through the process of cumulative advantage and reliance on positive past examples to guide current coping.

Cumulative advantage or recollection of the past?

Greater paternal emotional support in emerging adulthood attenuated the decline in self-rated health through midlife, supporting the cumulative advantage perspective that individuals would be on a better health trajectory if they experienced more emotional support from their father early in life. Parental emotional support is associated with academic success and emotional well-being in adolescence (Roth et al., 2009). These psychosocial resources can yield even more health-promoting resources in emerging adulthood and beyond, namely better knowledge of and access to healthcare. Accumulation of these resources may buffer the aging-related decline in health. The absence of increasingly divergent trajectories of positive emotions and depression as a function of parental emotional support may be due to the different nature of physical and emotional well-being. Unlike physical health deterioration that involves irreversible wear and tear, emotional well-being across the life-course is more responsive to resilience-promoting factors in adulthood (Pitzer & Fingerman, 2010), making the cumulative advantage/disadvantage phenomenon in positive emotions and depression less apparent. Alternatively, non-significant findings may be a result of having a restricted range of depression scores among a generally healthy sample.

Developmental processes other than cumulative advantage/disadvantage may be present to explain significant prospective associations between greater paternal support and better self-rated health and less depression, and between greater maternal support and more positive emotions in midlife. Similar to emerging adulthood, midlife is characterized by identity explorations and the need to balance autonomy with interdependence (Fingerman et al., 2012). A unique feature of our study is that we examined the effects of parental support during one life transition on well-being during another life transition 35 years later. Supplementary analysis suggested that Baby Boomers in this study had biological children who were emerging adults during the two most recent study waves (Average age of their children in Wave 7 = 17.99, SD = 4.78). As these Baby Boomers moved through midlife, memories of their parents’ emotional support during their own emerging adulthood might affect their identity explorations as aging adults, parents to emerging adults, and caregivers to their aging parents. Our findings may be a reflection of the association between memories of positive parent-child relations and midlife well-being (Davey, Tucker, Fingerman, & Savla, 2009).

Differences in maternal and paternal emotional support

Despite increasingly egalitarian beliefs regarding women and men in the latter half of the 20th century, the notion of nurturing and involved fathers only gradually began to grow in the late 1960s (Yeung, Sandberg, David-Kean, & Hofferth, 2001). The roles of parents often remained distinct, with fathers acting as providers and mothers as caregivers (e.g., Grossmann et al., 2002). If fathers were perceived as the ones with greater authority within the family because of their status as breadwinners, Baby Boomers who felt trusted, respected, and treated with fairness by the stronger parental figure during the transition from adolescence to adulthood may have developed a stronger self-image than when the same feelings were coming from their mothers only. Affirmation from fathers but not mothers may have a greater contribution to greater self-esteem, because it may be regarded as recognition for good performance, rather than love that is blindly given and generally expected from mothers (Fields, 1983). This may explain why paternal emotional support during emerging adulthood is significantly associated with better self-rated health, which is a reflection of self-esteem.

In our analysis, maternal emotional support was only prospectively associated with positive emotions in midlife. At least one study also finds that recalled childhood maternal affection is associated with higher positive affect in adulthood (Davey et al., 2009). Historically, mothers were more involved in providing care and affection to their off-springs, spouses, relatives, and friends. Prospective associations between parental emotional support in emerging adulthood and well-being in midlife may in part be driven by current challenges among Baby Boomers responsible for helping their aging parents and emerging adult children. They may look to positive memories of their nurturing mothers as their role models when coping with interpersonal and caregiving stress (Poon & Knight, 2012).

Limitations

Although our study allowed for the estimation of the rate of change in well-being to examine the cumulative advantage phenomenon, several limitations need to be considered. First, we were unable to determine the impact of ongoing availability and quality of parental–child relationships across the lifespan, because parental emotional support was not routinely measured at each wave in the LSOG. Current parent–child dynamics may negate or amplify the positive and negative effects of earlier parent–child experiences, such as when an adult child is now caring for their ailing parents. Second, we did not systematically investigate cohort or socioeconomic differences in explaining patterns of cumulative advantage. Parenting behaviors, such as limited warmth from one’s father, may be more appropriate among certain cohorts or social groups. Although the LSOG included participants from four generations, key variables during the three decades between emerging adulthood and midlife were only measured in the Baby Boom cohort. Exploration of the influence of SES on cumulative advantage by adding race and income to the models did not yield significantly different findings. Income distribution was limited by drawing the sample from an HMO with relatively homogenous socioeconomic backgrounds. There may be other unmeasured social and structural variables that promote cumulative advantage/disadvantage within the entire cohort. For example, income may have varied over time. In addition, our study only included Baby Boomers who lived with both parents during emerging adulthood. Findings cannot be generalized to single-parent families that may be impacted by different socioeconomic challenges. Finally, although we were able to overcome the bias associated with the use of retrospective data, this limited the opportunity to compare the relative influence of actual past parent-child experiences and current recollection or reconstruction of past experiences (Davey et al., 2009).

Conclusions

The current study revealed different effects of mothers’ and fathers’ emotional support during emerging adulthood on well-being in midlife, but no significant variation between daughters and sons. Despite a growing emphasis on gender-specific effects within the parent–child dyad in research on parental support, consistent patterns were not observed across studies (Mallers et al., 2010; Poon & Knight, 2012). Additional research on mother– and father–child relations across the lifespan is needed to advance our understanding of longitudinal and life-stage specific mechanisms through which paternal and maternal emotional support may impact health and adjustment in a changing world.

The experiences of emerging adults in the 1970s were very different from those in the early 21st century. In the 1970s, median age of first marriage was 21 and 23 years for women and men, respectively. A few decades later, the median age rose to 25 and 27 (Arnett, 2000). In fact, the term emerging adulthood came into existence at the turn of this century to describe young people aged around 18–25 years. Instead of being defined by a specific age-range, emerging adulthood is characterized by identity explorations during the transition from adolescence to adulthood. Midlife also presents similar developmental challenges to redefine one’s identity while preparing for the transition into old age. Economic uncertainties and changing social norms imply that more time and resources may be needed before one can become self-reliant young adults. Middle-aged parents from cohorts that come after the Baby Boomer may play an even bigger part in their emerging adult children’s identity development. As life expectancy continues to rise, additional challenges such as caring for one’s aging parents may also contribute to shifting trajectories of parent–child support and well-being during overlapping periods of life transitions, warranting the development of social and healthcare policies that can meet the needs of future intergenerational families.

Footnotes

Acknowledgments

Waves 1 to 7 data of the LSOG was obtained from the Inter-University Consortium for Political and Social Research () database (http://www.icpsr.umich.edu/). Wave 8 data were obtained from the LSOG research team. The authors wish to thank Jessica Lendon, PhD, and anonymous reviewers for feedback on an earlier draft of this manuscript.

Funding

The LSOG data collection was originally supported by the National Institute on Aging [grant number: NIA R56 AG007977]. However, the current research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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