Adult Children’s Intergenerational Mobility and Older Adults’ Self-Rated Health: A U.S.–China Comparison

Abstract

Objectives

This study examines whether and how adult children’s educational mobility is associated with the self-rated health of older adults aged 50 and above in China and the United States.

Methods

The analytic sample included 12,445 Chinese respondents from the 2011 to 2013 China Health and Retirement Longitudinal Study, and 17,121 US respondents from the 2010 to 2012 Health and Retirement Study. Multinomial logistic regression was employed to examine the relationship between children’s educational mobility and parents’ self-rated health, and the Karlson-Holm-Breen-method was used for mediation analysis.

Results

Adult children’s upward mobility was associated with their parents’ better health in both countries. This association was mediated by child-to-parent economic support, as well as parents’ social engagement and depressive symptoms in China; in the United States, parents’ depression was the only significant mediator.

Discussion

This study is among the first to empirically show the benefit of adult children’s upward mobility for their parents’ health. The cross-national differences in the mediating paths suggest that the cross-over effect of children’s intergenerational mobility on their parents’ health is embedded within specific sociocultural contexts.

Cross-national comparison, Intergenerational relationships, Later-life health, Social mobility

Existing research has shown that the socioeconomic achievement of adult children is a family-level resource that has the potential to benefit older adults’ health (Friedman & Mare, 2014). Prior studies mainly focused on how children’s socioeconomic status (e.g., education, occupation, and income) affected their parents’ health, showing that children’s higher social status contributed to parents’ better health (Elo et al., 2018; Jiang, 2019; Pei et al., 2020). In comparison, little is known whether and how adult children’s intergenerational mobility is associated with parents’ health. Intergenerational mobility—individuals’ social status relative to that of their parents—is commonly used to capture individual achievement in the context of one’s family of origin (Song et al., 2020). Understanding the role of children’s intergenerational mobility is important given the declining trend of mobility in many countries (Breen, 2019) as well as the theoretical ambiguity in the relationship between mobility and health. On the one hand, offspring’s upward mobility may benefit parents’ health because upwardly mobile children are in a better position to support their parents. On the other hand, social mobility may be accompanied by alienation from one’s family of origin (Hadjar & Samuel, 2015), and as such, children’s upward mobility might not benefit or may even harm their parents’ health. Testing these alternative hypotheses is therefore important to advance the understanding of intergenerational relationships and their health implications.

The association between offspring’s social mobility and older adults’ health, as well as the mechanisms underlying this association, are likely embedded within specific social and cultural contexts. This study draws on a comparison between China and the United States to reveal social and cultural norms that shape intergenerational relationships. Chinese older adults tend to have more reliance on adult children, given China’s lower level of economic development, relatively underdeveloped social welfare, and the strong filial norms (Cheng, 2017). By contrast, American older adults have stronger independence because of the highly developed economy and the individualistic culture in the United States (Klinenberg, 2012). These cross-national differences lead naturally to the question of whether the association between adult children’s social mobility and parents’ health, and the mechanisms underlying this association, are contingent on social contexts such as standards of living and family cultures.

Drawing on China Health and Retirement Longitudinal Study (CHARLS) and Health and Retirement Study (HRS), the current study investigates whether and how adult children’s educational mobility is associated with the self-rated health of adults aged 50 and above in China and the United States, as well as whether the mechanisms underneath this association differ between the two countries. In addition to promoting the understanding of the relationship between children’s intergenerational mobility and older adults’ health in different social contexts, this study contributes to policymaking and social practices by shedding light on how to improve older adults’ health, an especially important task given recent trends of declining social mobility in many countries including the United States (Chetty et al., 2017).

Prior Studies on Social Mobility, Intergenerational Relations, and Older Adults’ Health

Decades of studies at the intersection of social mobility, intergenerational relations, and older adults’ health have contributed to two major lines of inquiry. One emerging body of research investigates the relationship between social mobility and older adults’ health. A general finding is that upwardly mobile people had better health outcomes in older adulthood compared with nonmobile and downwardly mobile individuals (Faul et al., 2021; Houle & Martin, 2011; Malhotra et al., 2013; Pudrovska & Anikputa, 2014), even as some research showed that upward mobility could also have negative impacts on individual health (Simandan, 2018). By contrast, less attention is paid to whether and how individual health in later life is affected by offspring’s social mobility, even as lives are linked—children’s life circumstances may well predict the life chances of their parents’ (Elder et al. 2003).

This “linked lives” view characterizes the second strand of research, which uses an intergenerational perspective to examine the relationship between adult children’s achievement and their parents’ health outcomes. However, the major focus of these studies was on the impact of adult children’s absolute levels of socioeconomic status (e.g., education, occupation, and income), showing that children’s higher socioeconomic status (SES) was associated with parents’ better health (Elo et al., 2018; Friedman & Mare, 2014; Pei et al., 2020; Wolfe et al., 2018). What remains unclear is whether adult children’s intergenerational mobility would make a difference for parents’ health. Indeed, two adult children with the same SES level may well have differential intergenerational mobility patterns (as their parents’ SES may differ). Offspring’s intergenerational mobility thus has the potential to shape parents’ health independently of the absolute level of SES.

To the best of the author’s knowledge, only one recent study examined the consequence of children’s social mobility on parents’ health using a sample of Swedish people aged 76 and above. Results showed that adult children’s social mobility (either upward or downward) was associated with parents’ worse physical functioning (Jørgensen et al., 2019). However, that study did not examine the mechanisms underlying the association between offspring’s social mobility and parents’ health. It is also unknown whether the finding based on Sweden, a highly egalitarian country with distinct intergenerational mobility patterns (Fors & Lennartsson, 2008), may generalize to other contexts. Extending Jørgensen et al.’s work, this study investigates how adult children’s educational mobility affects parents’ health in older adulthood with a cross-national comparison between China and the United States, two countries with differential family cultures and levels of economic development.

Adult Children’s Intergenerational Mobility and Older Adults’ Health

Existing theories and empirical studies point to two possible relationships between adult children’s educational mobility and older adults’ health. One possibility is that adult children’s upward mobility benefits their parents’ health (Hypothesis 1). Three pathways may account for this positive relationship. First, adult children’s upward mobility may enhance their parents’ health through economic support provision. Social foreground theory argues that children attaining higher SES can improve their parents’ health and life expectancy, with financial assistance a crucial pathway through which offspring’s success benefits their parents’ health (Torssander, 2013). Applying this theory to the relationship between children’s social mobility and parents’ health, children moving upward in the social ladder may have a stronger ability to support their parents economically, thereby preventing older adults from health problems arising from financial strain (Kahn & Pearlin, 2006).

Second, adult children’s upward mobility may benefit their parents’ health by fostering social engagement. Children’s downward mobility may be perceived as “failure” at the end of the parents and pose threats to parents’ self-image (Scarnier et al., 2009). The stress and shame resulting from such perception may discourage older adults from social engagement (Consedine & Magai, 2003), a risk factor for older adults’ health (Cornwell & Waite, 2009). Adult children’s upward mobility, by contrast, likely increases older adults’ willingness to participate in social activities and subsequently benefits older adults’ health.

Third, children’s social mobility may be linked to parents’ health through a psychological pathway. Negative network events such as children’s downward mobility and the resulting lack of social support can impose stress on older adults (Milkie et al., 2008; Pearlin et al., 1981), which is harmful to older adults’ general health. By contrast, adult children’s upward mobility can be a source of pride and satisfaction, contributing to parents’ better health.

Altogether, to the extent that adult children’s upward mobility benefits parents’ health, this relationship could be mediated by child-to-parent economic support (economic pathway), social engagement (social pathway), and mental health (psychological pathway) (Hypothesis 2).

On the other hand, adult children’s upward mobility may be harmful to parents’ health (Hypothesis 3). Upwardly mobile children may live farther away from home to capitalize on educational and work opportunities, resulting in loneliness and other mental health problems among “empty nest” parents (Wu et al., 2010). Also, upwardly mobile children tend to adapt themselves to new norms and hold new values that are different from their parents’, which may bring about intergenerational conflicts (Guo et al., 2021). This negative interaction may distress parents and undermine their health (Song et al., 2021). Indeed, Jørgensen et al. (2019) found that adult children’s upward mobility was associated with parents’ poorer physical functioning in Sweden.

National Contexts: China and the United States

Social contexts, such as levels of economic development and family cultures, can shape the flow of resources from children to parents and thereby alter the association between offspring’s social mobility and older adults’ health. Given the different patterns of intergenerational relationships between China and the United States, the relationship between offspring’s social mobility and parents’ health and the underlying mechanisms may well differ between the two countries.

First, if adult children’s upward mobility is associated with parents’ better health, the mediating role of economic support might be more salient in China than in the United States (Hypothesis 4). Compared with their U.S. counterparts, Chinese older adults rely more on their adult children for economic support, given China’s lower gross domestic product per capita, underdeveloped social welfare, and the strong filial norms that emphasize children as key sources of support for aging parents (LaFave, 2017). In comparison, the highly developed economy and the individualistic culture in the United States may have made it less essential for older adults to depend on their adult children for economic support (Klinenberg, 2012).

Second, if adult children’s upward mobility is associated with parents’ worse health, this association is more likely to appear in the United States than in China (Hypothesis 5). Influenced by the Confucian culture, China has strong filial norms that stress closeness between adult children and their parents, as well as the important role of adult children in supporting their aging parents (LaFave, 2017). These norms, still prevalent in China, can prevent the relationship between upwardly mobile children and their parents from being estranged. The United States, in comparison, does not have such strict moral guidelines, and adult children’s support to their parents are relatively optional and voluntary (Streib, 1987). Combined with the prevalent U.S. individualism (Klinenberg, 2012) that further weakens the connectedness between parents and children, the upward mobility of adult children is less likely to benefit the health of American (vs Chinese) older adults.

Method

Data

This study draws on data from the 2011 to 2013 CHARLS and the 2010 to 2012 HRS. CHARLS is a Chinese national survey focusing on individuals aged 45 and above as well as other individuals up to 45 years old living in the same family. HRS is a U.S. national survey targeted at Americans aged 50 and above, along with their spouses or partners meeting the same age requirement in the same household. I chose these two surveys because of their national representativeness and similar design. Both surveys include important variables that are of key interest to this study, such as older adults’ self-rated health, adult children’s educational attainment, and child-to-parent economic support.

The specific waves of the two surveys are chosen for two reasons. First, the 2011 wave is the first wave of CHARLS, and the 2010 wave of HRS, for the first time, includes a wide range of cohorts (from Boomers to those born before 1924). Second, the 2011 CHARLS and the 2010 HRS are close in time and therefore suitable for comparison. I did not use more recent waves because doing so would lead to unequal gaps between the two data sets (CHARLS: 2015–2018; HRS: 2016–2018), which may complicate the interpretation of the results.

Sample

For CHARLS, 17,708 respondents living in 10,257 households participated in the baseline survey in 2011, with a response rate of 80.5% at the household level; 15,770 respondents were followed in 2013, and 2,834 new respondents were added. For HRS, 22,032 respondents participated in the 2010 survey with a response rate of 81.0%, and 20,554 respondents were followed in 2012. I selected people aged 50 and above (n = 13,683 for CHARLS and n = 19,582 for HRS), an age group covered by both CHARLS and HRS. I further excluded the following cases from the analytic sample: (a) respondents who did not report any children in either wave, (531 in CHARLS and 1,456 in HRS); (b) respondents who did not report their self-rated health in the second wave (102 in CHARLS and 19 in HRS); (c) respondents whose oldest child was younger than 25 years old when surveyed (247 in CHARLS and 861 in HRS) because their children may have not finished education when surveyed; and (d) respondents who had missing values on some crucial variables, such as age, education, and individual-level weights (358 in CHARLS and 125 in HRS). The final analytic sample included 12,445 and 17,121 respondents in CHARLS and HRS, respectively.

Dependent Variable

Self-rated health

Self-rated health, collected by both surveys, has been found to be effective in assessing health conditions (Jylhä, 2009). In HRS, respondents were asked, “Would you say your health is excellent, very good, good, fair, or poor?” In CHARLS, a portion of respondents were randomly selected to answer the question “Would you say your health is excellent, very good, good, fair, or poor?” And the remaining were asked, “Would you say your health is very good, good, fair, poor or very poor?” To facilitate comparison between surveys, I created a three-category variable that distinguished poor (the reference group), fair, and excellent/very good/good health.

Independent Variable

Adult children’s educational mobility

I focused on educational attainment to assess intergenerational mobility. Educational mobility is widely used in the social mobility literature and is closely linked with other types of intergenerational mobility such as mobility in income (Narayan et al., 2018). Practically, the differential measurements of occupation and income in HRS and CHARLS made it difficult to construct comparable measures of intergenerational mobility in occupation or income between the two countries.

I employed relative instead of absolute mobility to measure intergenerational mobility. Absolute mobility is the difference between children’s and parents’ education in absolute terms, while relative mobility considers individuals’ rankings of educational attainment within their birth cohort. Given the considerable educational expansion over the past decades in many countries (Hannum & Buchmann, 2003), most of the younger generation in my sample had acquired more education compared with their parents in the absolute sense. Relative mobility, therefore, provided a more refined and meaningful measure to assess adult children’s educational mobility.

Educational attainment was measured as years of schooling (0–17) in HRS and as levels of education in CHARLS (from “no formal education” to “Ph.D. degree”). Following prior research (Gugushvili et al., 2019), I first categorized respondents’ and their children’s educational attainment into low, middle, and high groups (1 = low, 2 = middle, and 3 = high) based on their tertiles in the distribution of education within each birth cohort (e.g., birth year 1950, 1951,…). I used this strategy to adjust for possible educational inflation over time. Then, I subtracted respondents’ ranking from their children’s ranking to create a continuous measure of relative mobility (ranging from −2 to 2). A positive difference indicated upward mobility and a negative difference indicated downward mobility. For respondents with more than one child, I selected the child with the highest educational ranking (Pei et al., 2020), which facilitated detecting children’s upward mobility. For robustness check, I created an alternative measure using the child with the lowest educational ranking, finding similar results (Supplementary Appendix Table 1). I also tried using the proportion of children moving upward, categorical relative mobility (no mobility was the reference group; upward mobility and downward mobility were distinguished), and absolute mobility as independent variables, and the results remained similar (Supplementary Appendix Tables 2–5).

Mediators

Child-to-parent economic support

The 2012 HRS asked respondents about the amount of economic support they received from all of their children during the past 2 years. Similarly, the 2013 CHARLS asked respondents how much economic support—both monetary and in-kind support—they received from all of their noncoresident children during the past year. I doubled the amount of economic support in CHARLS to approximate the amount of economic support received in the past 2 years, the time frame used by HRS. The amount of child-to-parent transfer was log-transformed to deal with skewness. I also conducted a sensitivity analysis in which the top 1% and the bottom 1% of child-to-parent transfer were trimmed, finding similar results (Supplementary Appendix Table 6).

Social engagement

Respondents in the 2012 HRS and 2013 CHARLS were asked how frequently they participated in social activities, such as interacting with friends, volunteering, and going to a club (complete items are presented in Supplementary Appendix Table 7). Respondents participating in at least one such social activity once a week or more frequently were coded as active social engagement (= 1).

Depressive symptoms

Both HRS and CHARLS used the Center for Epidemiologic Studies Depression scale (CES-D) to measure depressive symptoms, although the specific items differ between the two surveys (see Supplementary Appendix Table 8; Cronbach’s alpha = 0.81 in HRS and 0.76 in CHARLS). HRS asked respondents whether they had eight depressive symptoms much of the time during the past week (0 = no, 1 = yes), while CHARLS used a 10-item scale, with responses including rarely or none of the time, some or a little of the time, occasionally or a moderate amount of the time, and most or all of the time. I used the imputed CES-D scores provided by both surveys (ranging from 0 to 8 in HRS and 0 to 30 in CHARLS) and standardized them using z scores.

Control Variables

For both surveys, I controlled for respondents’ age, gender (0 = male, 1 = female), marital status (0 = separated, divorced, widowed, or never married; 1 = married or cohabiting), cohort-specific educational ranking (0 = low, 1 = middle, 2 = high), employment status (0 = unemployed or out of the labor force, 1 = working full-time or part-time), number of children, whether living with children (0 = no, 1 = yes), and lagged self-rated health (0 = poor, 1 = fair, 2 = good). Following prior cross-national research (Cheng, 2017), I also controlled for hukou (0 = nonagricultural hukou, 1 = agricultural hukou), a strong indicator of one’s social status in China (Wu, 2019), and in the United States analysis, race and ethnicity (0 = non-Hispanic Whites, 1 = non-Hispanic Blacks, 2 = Hispanics, 3 = non-Hispanic other races), an important determinant of SES and health in the United States (Priest & Williams, 2018).

Analytic Strategy

Regression analysis included two steps. First, I used multinomial logistic regression to estimate the relationship between children’s educational mobility and parents’ health while controlling for covariates measured in the second wave. Next, I added self-rated health measured in the first wave as a control variable to deal with possible endogeneity between adult children’s social mobility and respondents’ health. This lagged dependent variable approach accounts for baseline differences in the dependent variable, as well as persistent heterogeneity and serial correlation between waves (Kelly et al., 2011). For mediation analysis, I employed the Karlson-Holm-Breen (KHB)-method (Breen et al., 2013; Kohler & Karlson, 2019), a decomposition method that is unaffected by any rescaling bias when comparing nonlinear models.

I used multiple imputation chained equations to deal with missing values. Missing data ranged from 1.3% (economic support from children) to 6.0% (CES-D scores) in HRS and from 2.0% (children’s educational mobility) to 12.4% (lagged self-rated health) in CHARLS. All models were estimated using 20 multiply imputed data sets and weighted with the individual-level weights variables provided by HRS and CHARLS.

Results

Descriptive Statistics

Table 1 presents weighted means/percentages and standard deviations for the variables used in the analysis. Compared with U.S. respondents who tended to report good health (74% in wave 2 and 75% in wave 1), only one in four respondents in China rated their health as good (23% in wave 2 and 25% in wave 1). This difference may reflect a true difference in health conditions and/or cultural differences in assessing health between the two countries. Adult children’s intergenerational mobility was at a comparable level between the two countries (0.4 in China and 0.6 in the United States, representing moderate upward mobility). The mean of economic transfer was 7,490 RMB (approximately $1,200 USD) in China and $200 in the United States. Older adults in China were more likely to engage in social activities compared with their American counterparts (44% vs 24%). The average CES-D score was 7.7 (ranging from 0 to 30) for Chinese older adults and 1.43 (ranging from 0 to 8) for American older adults.

Table 1.

Descriptive Statistics of Respondents Aged 50 and Older in China and the United States

	China		United States
	(N = 12,445)		(N = 17,121)
	Mean/percent	SD	Mean/percent	SD
Self-rated health in the second wave
Good	22.82%		73.60%
Fair	49.30%		18.74%
Poor	27.88%		7.66%
Self-rated health in the first wave
Good	24.71%		75.27%
Fair	45.19%		18.09%
Poor	30.10%		6.63%
Adult children’s educational mobility	0.40	0.95	0.61	0.97
Child-to-parent economic support	7.49	23.29	0.20	1.90
Active social engagement	44.06%		24.27%
Depressive symptoms (CES-D scores before z-standardization)	7.70	5.71	1.43	2.01
Age	64.67	8.86	67.41	10.19
Female	51.36%		55.85%
Married/cohabiting	82.46%		67.44%
Educational ranking
Low	43.76%		49.00%
Middle	30.12%		18.72%
High	26.12%		32.28%
In labor force	54.89%		41.23%
Number of children	2.90	1.48	3.22	1.83
Coreside with offspring	50.78%		25.33%
Agricultural hukou	69.93%
Race
Non-Hispanic Whites			77.60%
Non-Hispanic Blacks			10.35%
Hispanics			8.94%
Non-Hispanic other races			3.11%

Notes: All results are weighted and based on nonimputed data. Child-to-parent economic support is in 1,000 RMB and 1,000 dollars for China and the United States, respectively. More detailed information on respondents’ educational ranking is shown in Supplementary Appendix Table 12.

Adult Children’s Educational Mobility and Their Parents’ Self-Rated Health

Table 2 presents results on the relationship between adult children’s social mobility and parents’ self-rated health in China and the United States. Model 1 shows that among Chinese older adults, one unit increase in children’s social mobility was associated with 13% (p < .05) and 24% (p < .001) increases in the odds of reporting fair health and good health (as opposed to poor health), respectively. After controlling for lagged self-rated health in Model 2, one unit increase in adult children’s social mobility was still linked to 9% (p < .1) and 16% (p < .01) increases in the odds of reporting fair health and good health (as opposed to poor health), respectively. The next two models show parallel results for the U.S. sample. Model 3 shows that one unit increase in children’s educational mobility increased the odds of reporting good health as opposed to poor health by 46% (p < .001). This association remained significant after controlling for lagged self-rated health in Model 4: one unit increase in children’s educational mobility increased the odds of reporting good health as opposed to poor health by 33% (p < .001). The effect size of children’s social mobility in both countries was small because the odds ratios (1.13 and 1.24 in China; 1.08 and 1.46 in the U.S.) were smaller than 1.68 (Chen et al., 2010). Supplementary Appendix Table 9 shows the average marginal effects of children’s social mobility, the magnitude of which was also small.

Table 2.

Odds Ratios from Multinomial Logistic Regression Models on Self-Rated Health in China and the United States

	China (Base: poor health)				United States (Base: poor health)
	Model 1		Model 2		Model 3		Model 4
	Fair health	Good health	Fair health	Good health	Fair health	Good health	Fair health	Good health
Adult children’s educational mobility	1.13**	1.24****	1.09*	1.16***	1.08	1.46****	1.05	1.33****
Age	0.99**	1.00	0.99	1.00	1.01**	1.01***	1.00	0.99*
Female	0.78****	0.75****	0.82***	0.81***	1.02	1.17**	0.97	1.11
Married/cohabiting	0.86	0.84*	0.88	0.92	1.29***	1.74****	1.17	1.38***
Educational ranking (Ref. = low)
Middle	1.28****	1.33***	1.17**	1.16	0.94	1.98****	0.83	1.45***
High	1.63****	2.14****	1.34**	1.58****	1.27*	3.95****	1.12	2.52****
In labor force	1.88****	2.30****	1.65****	1.91****	3.45****	8.93****	2.29****	4.22****
Number of children	0.94**	0.91***	0.95*	0.93**	0.98	0.95***	0.97	0.96**
Coreside with offspring	1.00	1.07	0.96	1.01	1.08	0.92	1.10	0.97
Agricultural hukou	0.60****	0.70***	0.68****	0.81*
Race (Ref. = non-Hispanic Whites)
Non-Hispanic Blacks					1.42***	0.92	1.52****	1.26*
Hispanics					1.29**	0.53****	1.30*	0.75*
Non-Hispanic other races					0.62**	0.55***	0.73	0.85
Self-rated health in the first wave (Ref. = poor)
Fair			4.05****	6.02****			5.79****	8.24****
Good			6.99****	29.88****			6.89****	103.48****
Observations	12,445				17,121

Note: Results presented are exponentiated coefficients. 95% confidence intervals are shown in Supplementary Appendix Table 11.

*p < .10.

^**  p < .05.

^***  p < .01.

^****  p < .001.

Taken together, adult children’s upward mobility was beneficial to their parents’ health in both countries, supporting Hypothesis 1 but not Hypothesis 3 (which expected a negative association between children’s upward mobility and parents’ health). Hypothesis 5 that anticipated the effects of children’s educational mobility to be of different directions in China and the United States was also rejected.

The Mediating Roles of Child-to-Parent Transfer, Social Engagement, and Depression

Table 3 presents results from the mediation analysis. In China, adding the mediator of child-to-parent economic support reduced the effect of children’s social mobility on the log odds of reporting good health (vs poor health) from 0.14 (p < .01, total effect) to 0.13 (p < .01), leaving an indirect effect of 0.01 (p < .05). The pathway through social engagement showed the same pattern for Chinese parents. The mediating effect of depressive symptoms was much larger: Adding the mediator of depressive symptoms reduced the effect of children’s social mobility on the log odds of reporting good health (vs poor health) from 0.15 (p < .01, total effect) to 0.07 (p > .1), leaving an indirect effect of 0.08 (p < .001). Of the three mediators, examining standardized coefficients and the contribution of each mediator to the total effect also suggested that the psychological pathway (depressive symptoms) was more important than the economic and social pathways. Combined, these findings support Hypothesis 2 that child-to-parent transfer, social engagement, and mental health mediate the relationship between offspring’s social mobility and parents’ health.

Table 3.

Estimates from KHB Mediation Analysis of Child-to-Parent Economic Support, Social Engagement, and Depressive Symptoms

	China (Base: poor health)		United States (Base: poor health)
	Fair health	Good health	Fair health	Good health
Child-to-parent economic support (log-transformed)
Total effect	0.10**	0.14***	0.02	0.18****
	(0.04)	(0.05)	(0.05)	(0.05)
Direct effect	0.10**	0.13***	0.02	0.18****
	(0.04)	(0.05)	(0.05)	(0.05)
Indirect effect	0.01*	0.01**	−0.00	−0.00
	(0.00)	(0.00)	(0.00)	(0.00)
Social engagement
Total effect	0.10***	0.14***	0.02	0.18****
	(0.04)	(0.05)	(0.05)	(0.05)
Direct effect	0.10**	0.13***	0.02	0.18****
	(0.04)	(0.05)	(0.05)	(0.05)
Indirect effect	0.01**	0.01**	0.00	0.00
	(0.00)	(0.00)	(0.00)	(0.00)
Depressive symptoms
Total effect	0.11**	0.15***	0.01	0.18****
	(0.04)	(0.05)	(0.05)	(0.05)
Direct effect	0.07	0.07	−0.01	0.13**
	(0.04)	(0.05)	(0.05)	(0.05)
Indirect effect	0.04****	0.08****	0.02****	0.06****
	(0.01)	(0.02)	(0.00)	(0.01)
Observations	12,445		17,121

Notes: (a) All models have controlled for respondents’ age, gender, marital status, education, work status, number of children, coresidence with children, lagged self-rated health, hukou (only China), and race and ethnicity (only the United States). (b) The indirect effect is a product of (i) the path from adult children’ educational mobility to the mediator and (ii) the path from the mediator to respondents’ self-rated health. When the indirect effect is positive, these two paths have the same sign (both positive or both negative); when the indirect effect is negative, these two paths are of opposite signs. (c) Results presented are log odds with standard errors in parentheses.

*p < .10.

^**  p < .05.

^***  p < .01.

^****  p < .001.

The last two columns of Table 3 show the corresponding results for American older adults. Contrary to the results in China, neither child-to-parent economic support nor social engagement was a significant mediator for American older adults. Nevertheless, the pathway through depressive symptoms was significant: Adding the mediator of depression reduced the effect of children’s social mobility on the log odds of reporting good health (vs poor health) from 0.18 (p < .001, total effect) to 0.13 (p < .05), leaving an indirect effect of 0.06 (p < .001). The significant mediating role of child-to-parent economic support in China rather than the United States supported Hypothesis 4.

Conclusion and Discussion

Drawing on data from the 2011 to 2013 CHARLS and the 2010 to 2012 HRS, this study examines how children’s social mobility is associated with individual health in China and the United States. In both countries, having upwardly mobile children was associated with older adults’ better health, and this association was mediated by depressive symptoms in later life. In China but not the United States, however, child-to-parent economic support and social engagement were also significant mediators.

Contrary to a prior Swedish study that found a negative association between children’s upward mobility and parents’ physical functioning (Jørgensen et al., 2019), this study suggests that children’s upward mobility is beneficial to parents’ health in both China and the United States. Consistent with Jørgensen et al.’s finding, however, this study found that children’s downward mobility was harmful to parents’ health in both China and the United States. These results are also consistent with prior findings that adult children’s greater achievement predicted parents’ better health (Elo et al., 2018; Ma, 2019; Zimmer et al., 2016).

This study also contributes to the literature by theorizing and testing the economic, social, and psychological pathways that connect children’s social mobility with parents’ health. First, it provides empirical evidence to the hypothesis based on the social foreground theory (Torssander, 2013), which predicts that children’s social achievement benefits their parents’ health through economic support provision. However, only in the Chinese sample did child-to-parent economic support emerge as a significant mediator. This is possibly because older adults are more dependent on adult children in China (LaFave, 2017), in contrast to the United States where economic support is more likely to be from parents to adult children (Friedman & Mare, 2014). Second, social engagement is another mediator in the association between offspring’s social mobility and parents’ health, although it is also only significant in China. It is possible that children’s social achievement matters more for Chinese parents’ perceived social image (Stipek, 1998), which may make children’s social mobility more influential on their social engagement and health. Combined, the cross-national differences in the mediating paths suggest that the cross-over effect of children’s intergenerational mobility on their parents’ health is embedded within specific sociocultural contexts.

Third, depression is the major pathway in the association between adult children’s social mobility and parents’ health in both countries, providing support to the hypothesis based on the stress process theory (Pearlin et al., 1981). Specifically, children’s upward mobility reduced parents’ depressive symptoms and consequently benefited parents’ health. To better establish the direction between depressive symptoms and self-rated health, I used adult children’s social mobility and respondents’ depressive symptoms measured in the 2013 CHARLS and the 2012 HRS, as well as respondents’ self-rated health measured in the 2015 CHARLS and the 2014 HRS to re-conduct mediation analysis, finding similar results (Supplementary Appendix Table 10).

These findings also have important practical implications. To improve later-life health, policymakers, and social practitioners need to provide more support to older adults whose adult children are moving downward in the social ladder. Additionally, for younger parents whose children are still receiving education, more effort is needed to improve children’s opportunities of upward mobility, which may have long-term benefits for the parents’ health.

This study has some limitations. First, given data availability and comparability of HRS and CHARLS, this study only uses educational mobility as an indicator of adult children’s social mobility. Although education is strongly associated with occupation and income (Domina et al., 2019), it remains unclear whether using other measurements of social mobility would yield different findings, an important question left for future investigation. Second, this study focuses on the mediating roles of child-to-parent economic support, social engagement, and depressive symptoms, even as other possible channels (e.g., healthcare access and affordability) exist connecting children’s intergenerational mobility and older adults’ health that future research may explore. Third, preliminary analysis showed that the relationship between children’s social mobility and parents’ health did not differ across gender, hukou, or racial groups, but the heterogeneous health effect of children’s social mobility may well exist along other dimensions, which awaits future research to fully understand.

Despite these limitations, this study takes one of the first steps to examine the role of children’s intergenerational mobility in parents’ health, a question that is all the more important to understand in view of the declining social mobility in many countries such as the United States (Chetty et al., 2017). As both aging and declining social mobility are becoming global challenges, this research shows that enhancing the younger generation’s social mobility could have a collateral benefit of improving the older generation’s health.

Acknowledgments

The author thanks Dr. Wen Fan, Dr. Sara Moorman, Dr. Felix Elwert, Dr. Natalia Sarkisian, Dr. Deborah Carr, Boston-Area Medical Sociology Meeting participants, and three anonymous reviewers for their helpful feedback.

Funding

None.

Conflict of Interest

None declared.