Self-perceptions of aging and domain-specific health outcomes among midlife and later-life couples

Abstract

Objectives: This study places the self-perceptions of aging (SPA)-health link in the couple context and examines how changes in one’s own and spouse’s SPA influence multiple health domains and how such associations differ by gender. Methods: Fixed-effects regression models were estimated. Data were drawn from the Health and Retirement Survey (N = 5972). Results: For both husbands and wives, almost all health domains declined when their own SPA became more negative. The spouse’s SPA were associated with one’s self-rated health, regardless of gender. Gender differences existed in some cross-spousal health effects; while the husband’s SPA were associated with his wife’s depressive symptoms, the wife’s SPA were associated with her husband’s physical disability, functional limitations, and chronic diseases. Discussion: The SPA–health association extends beyond the individual in married persons, demonstrating intertwined health trajectories in older couples. The detrimental effects of ageism might be underestimated if the spillover effects were not considered.

Keywords

ageism healthy aging age stereotype attitudes toward aging

Introduction

Ageism has been defined in multiple ways. In this study, it is defined as “negative or positive stereotypes, prejudice and/or discrimination against (or to the advantage of) elderly people based on their chronological age, or based on a perception of them as being ‘old’ or ‘elderly’” (Iversen et al., 2009, p. 15). When ageism is directed at oneself in old age, it can be conceived as self-perceptions of aging (SPA, Levy, 2009). Ageism has potential economic costs. Levy et al. (2020) find that the one-year health-care cost of ageism—operationalized as negative age stereotypes, discrimination against older people, and negative SPA—is $63 billion, or one of every seven dollars spent on health conditions. Among the three components of ageism, negative SPA have the highest excess health-care cost.

Research to date on the relationship between SPA and health is extensive and mostly consistent, showing that negative SPA adversely affect older adults’ health outcomes across time and geography. The current literature has several limitations. First, although numerous studies reveal strong associations between one’s own SPA and health, most studies only focus on one single health domain, which is limited in scope. Second, prior research has suggested differential effects of the SPA on cognitive performance by gender (Siebert, Wahl, & Schröder, 2018), but few studies have examined whether this is the case for other health domains. Third, while most studies have investigated how one’s own SPA affect their health, few have considered the spillover effects of the SPA; that is, whether the spouse’s SPA have an effect on one’s health. Finally, few studies have explored whether the health of husbands and wives is differently affected by their partner’s SPA.

Building on this background, our study examined associations of both one’s own and spouse’s SPA with multiple domain-specific health outcomes. By examining multiple health outcomes, we aim to obtain a broader picture with regard to the role of SPA in older adults’ health. To explore how gender operates within intimate relationships, this study compares how husbands and wives differ in the association between partner’s SPA and one’s health outcomes. With a gender-specific perspective in a couple context, this study adds to the literature on SPA and health in two aspects: (1) it advances our understanding of an understudied topic by exploring the existence and magnitude of spillover effects of SPA among married couples in their midlife and later life, and (2) it sheds light on gender differences in the spillover effects of SPA.

Self-Perceptions of Aging and Health

SPA are a lens through which age-related changes are interpreted. These interpretations can affect future health outcomes. There is evidence to support that SPA are less a result, but rather a cause, of health changes (Wurm et al., 2013). One way that SPA affect later life health is through self-fulfilling prophecy. Negative beliefs can evoke psychological, cognitive, and behavioral processes. As a result, these beliefs may become a reality. Regarding the detrimental health consequences of negative SPA, the psychological process is the most studied, with perceived control (Levy, Slade, & Kunkel, 2002), self-efficacy (Tovel et al., 2019), and will-to-live (Levy, Slade, Kunkel, & Kasl, 2002) having been identified to be involved. Standard measurements for the behavioral process include physical activities (Li et al., 2013) and health-promoting behaviors (Kim, 2009). The relatively understudied is the physiological process, which has been assessed by C-reactive protein (a marker of stress-related inflammation) in past research (Levy & Bavishi, 2018).

Empirical studies have shown that negative SPA adversely affect domain-specific health outcomes of older adults. These health outcomes include, but are not limited to, disease (Siebert, Wahl, & Degen, 2018), mortality (Sargent-Cox et al., 2014), physical health (Moser et al., 2011), mental health (Schroyen et al., 2017), cognitive health (Smith et al., 2018), self-rated health (Levy, Slade, & Kunkel, 2002), quality of life (Kiarsipour et al., 2017), and health behaviors (Sun & Smith, 2017). Systematic reviews and meta-analyses provide strong evidence for this point (Chang et al., 2020; Horton et al., 2008; Meisner, 2012; Westerhof et al., 2014). To illustrate, recently, Chang et al. (2020) published a comprehensive systematic review that covered 11 health domains conducted in 45 countries with more than seven million older adults. Their study revealed a strong and consistent link between ageism and adverse health outcomes—ageism caused significantly worse health outcomes in 95.5% of the studies and that 74.0% of the 1159 ageism–health associations were significant (Chang et al., 2020).

Several recent studies have examined whether the relationship between SPA and health differs between men and women. For instance, drawing on a national sample from the Interdisciplinary Longitudinal Study of Adult Development and Aging that covered a 12-year interval, Siebert, Wahl, and Schröder (2018) investigated to what extent the association between attitudes toward one’s own aging and fluid functioning differed by gender. They reported that such an association was stronger for men than for women even after controlling for other health conditions and education. However, we do not know if women are at a disadvantage when negative SPA are linked to other domain-specific health outcomes and whether negative SPA cause more negative consequences for women. The differential gender effects in the SPA–cognitive performance relationship deserve to be further examined in other health domains.

Self-Perceptions of Aging, Intimate Relationships, and Health

Although growing attention has been paid to the relationship between SPA and health, most existing research focuses simply on the effect of individual’s own SPA on their health. Relatively little research has examined the association between the spouse’s SPA and one’s own health. In short, previous studies have ignored the partner effect of SPA. In the following, we refer to the well-established thesis in the marriage and health literature; namely, intimate relationships (e.g., marriage) can have both beneficial and detrimental effects on health, and these effects are gendered. Intimate relationships operate through multiple pathways to influence the spouse’s health. In this study, we suggest that attitude toward aging is one pathway.

Research has shown that the members of a couple have strong influence on the physical and mental health trajectories of each other (Kiecolt-Glaser & Wilson, 2017). For example, health problems of one member of the couple have spillover health effects on the other (Bourassa et al., 2015). More recent research suggests that psychological attributes of their partners are related to individuals’ health outcomes (Drewelies et al., 2018; Kim et al., 2014; Roberts et al., 2009). For example, partners’ higher levels of mastery and optimism are associated with better health trajectories including fewer functional limitations, fewer chronic conditions, better self-rated health, and more physical activity (Drewelies et al., 2018; Kim et al., 2014). To our knowledge, only one study to date has examined partner effects of SPA on older adults’ health (Momtaz et al., 2013). Using an actor–partner interdependence model, the researchers examined the dyadic effects of attitude toward aging on the psychological well-being of 300 older couples in Malaysia. They found that one’s own attitude toward aging was correlated with the spouse’s attitude toward aging and that other than their own attitude effects, spousal attitude toward aging also affected older adults’ psychological well-being, regardless of gender. This study only used psychological well-being as the outcome. It is not known if partners’ SPA also affect other health domains such as physical heath and cognitive health.

In addition, how the relationship between the spouse’s SPA and individual’s health differs between husbands and wives has been rarely investigated. There are reasons to expect gender differences in the effects of spouse’s SPA on health. Numerous studies during the past decades have shown that the health benefits of marriage are gendered; that is, men usually enjoy more health benefits from marriage than women (Gove, 1972, 1973; Reczek et al., 2016). One explanation of the differential marriage benefits is related to gender differences in emotion and caring work (Calasanti & Bowen, 2006; Calasanti & King, 2007). Women typically act as the “health expert” and “emotion expert” in intimate relationships, engaging in more preventive health care, healthy behavior, social connection, and emotional support for the family than men (Umberson, 1992). Based on this reasoning, husbands’ health should be more affected by wives’ SPA than vice versa, as the wife’s SPA may affect her psychological resources (e.g., self-efficacy), health behavior (e.g., physical activity), and physiological state (e.g., inflammation) which affect not only her own health but also her ability to perform the caring and emotion work that benefits the husband.

However, there is also evidence that women are more negatively affected by marital conflict and their spouses’ health problems than men (Ayotte et al., 2010; Berg & Upchurch, 2007; Whisman, 2001). Some suggest that women’s vulnerability is related to their more relationally interdependent self-representations (Kiecolt-Glaser & Newton, 2001). Others argue that women’s subordinate position relative to their husbands is a reason for women’s greater reactivity (Wanic & Kulik, 2011). According to this line of research, women are more likely than men to be affected by their spouse’s SPA.

Given that no empirical studies have examined gender differences in the spillover effects of SPA in a couple context, we take an exploratory approach to the issue. Specifically, we will examine the spillover effects of SPA on different health outcomes for husbands and wives, respectively. The health outcomes include physical disability, functional performance, chronic disease, depressive symptoms, cognitive functioning, and self-rated health. This range of health indicators can help to better understand gender differences in response to their partner’s SPA. The literature has suggested that women have higher rates of depression than men, and that women are more emotionally and psychologically reactive to marital distress and health issues of their spouses than men (Kiecolt-Glaser & Wilson, 2017; Platt et al., 2020; Rosenfield et al., 2014). Hence, we expect the SPA spillover effects on depressive symptoms to be more salient in wives than in husbands.

The present study contributes to the SPA–health research in multiple ways. First, we examine how both older people’s own negative SPA and their spouse’s SPA are related to their health. Such cross-partner effect of SPA has been rarely examined in the prior literature. Second, unlike prior gender-blind research, we take a gender perspective and test if the SPA–health links differ between men and women. Third, we argue that SPA is one way that intimate relationships operate through to generating health benefits. We use a broad range of health measures to test if the marital benefits due to SPA differ across health domains, echoing prior research findings on gender differences in marital advantages in different health domains. Fourth, drawing on panel data from a general population survey, we estimate fixed-effects regression models which are considerably less prone to bias due to omitted confounding variables than multilevel and cross-sectional approaches (explained in detail later).

Methods

Data and Sample

This study was based on the Health and Retirement Study (HRS), a national panel study of individuals over age 50 years and their spouses of any age. The HRS was designed to investigate the population aging process. It was approved by the Institutional Review Board at the University of Michigan. The first wave of the HRS took place in 1992, with later waves conducted biannually. As SPA have been measured consistently across waves only since 2008 in the Participant Lifestyle Questionnaire in addition to the HRS core content, this study used five waves of HRS data that were collected biannually between 2008 and 2016. Key variables of interest, like health and SPA of the partner, were not directly measured but could be obtained when respondents were married, and their spouse also participated in the HRS. Therefore, this study focused on married individuals. Given our research aims, the sample was further restricted to heterosexual married couples in which both partners answered the Participant Lifestyle Questionnaire, were aged 51 and older, and had occurred at least twice in the panel. Missing values differed by health outcomes. To reduce sample selectivity, we did not use a joint sample that had information on all health outcomes. Instead, we included all observations that provided information on a given health outcome in the analyses, resulting in different sample sizes across health outcomes. The final analytic sample included 2669 couples comprising 5972 couple-year observations.

There were some differences between the included sample and the excluded sample. Compared to the respondents included in this study, the excluded respondents were more likely to be younger (mean _husband = 66.53 vs. 69.71, t = −12.90; mean _wife =63.66 vs. 66.82, t = −13.38), hold higher negative SPA (mean _husband = 25.70 vs. 25.09, t = 3.37; mean _wife = 24.99 vs. 24.42, t = 3.10), and report more physical disabilities (mean _husband = .54 vs. .36, t = 5.86; mean _wife = .49 vs. .31, t = 6.10), depressive symptoms (mean _husband = 1.17 vs. .84, t = 7.85; mean _wife = 1.36 vs. 1.07, t = 6.14), cognitive impairment (mean _husband = 11.13 vs. 10.52, t = 6.35; mean _wife = 9.61 vs. 9.05, t = 6.07), and worse self-rated health (mean _husband = 2.89 vs. 2.73, t = 5.94; mean _wife = 2.82 vs. 2.63, t = 6.45). However, the two groups’ health conditions were not significantly different in functional performance and chronic disease. Considering that the excluded sample holds more negative SPA and is in worse health conditions than the study sample, estimates of the associations between negative SPA and health outcomes derived from the study sample might be underestimated.

Measures

The dependent variables involve six health domains: physical disability, functional performance, chronic disease, depressive symptoms, cognitive functioning, and self-rated health. The former three have often been used as indicators of physical health. The latter three are indicators of mental, cognitive, and subjective health, respectively. We purposefully chose these health outcomes because (a) these health measures involve adults’ physical capability, physiological health, psychological well-being, and cognitive health; (b) prior literature suggests different gender disparities across health domains (Kiecolt-Glaser & Wilson, 2017); and (c) these six health outcomes are among the most frequently explored measures in the recent healthy aging literature, as suggested by one recent systematic review (Lu et al., 2019). However, even if we have included multiple health outcomes, we acknowledge that this study only covers some of the aspects in the SPA–health literature.

Physical disability was measured by the count of difficulty with five activities of daily living (e.g., dressing and eating; Katz et al., 1963) and five instrumental activities of daily living (e.g., shopping for grocery and managing money; Lawton & Brody, 1969).

Functional performance was measured by the count of difficulty with 12 tasks, such as walking several blocks, jogging one mile, sitting for about 2 hours, and getting up from a chair after sitting for long periods (Rosow & Breslau, 1966).

Chronic disease was measured by a count of eight chronic conditions that respondents have been diagnosed with, including hypertension, diabetes, cancer, lung disease, heart disease, stroke, psychiatric problems, and arthritis.

Depressive symptoms were measured by the widely used 8-item Center for Epidemiologic Studies Depression scales (CES-D, Radloff, 1977). The psychometric properties of the CES-D scale have been established in prior studies (Steffick, 2000). Participants were asked to respond either “yes” or “no” to statements about their feelings in the week before the interview. An example of the typical item was “much of the time during the past week, you felt that everything was an effort.”

Cognitive functioning was assessed by immediate and delayed recalls, in line with recent research using the same dataset (Chen et al., 2019). Respondents were randomly read 10 words and were asked to recall the words immediately and after a delay of about five minutes. We recoded the original measure and summed the wrong answers in the two recalls.

Self-rated health measured the respondents’ self-reported general health status on a 5-point scale (1 = excellent to 5 = poor). This single-item self-rating measure has been widely used in prior studies (Idler & Benyamini, 1997).

SPA were measured by an 8-item scale derived from the Philadelphia Morale Scale and the Berlin Aging Study (Lawton, 1975; Liang & Bollen, 1983). Respondents were asked to report their feelings about their age and the things that happened as they got older on a 6-point scale (1 = strongly disagree to 6 = strongly agree). Cronbach’s α of this scale across waves ranged from .813 to .818. To construct the SPA variable, all responses were summed up, with scores ranging from 0 to 48, where 48 indicated the most negative SPA.

As suggested by the stereotype embodiment theory (Levy, 2009), older adult’s SPA were associated with individual’s own age. Also, age was widely known as being associated with health outcomes. By adding controls of the wife’s and husband’s age, we estimated the effects of changes in the wife’s and husband’s SPA on health outcomes net of age effects. Age was measured in 10-year intervals and top coded at 89 years old. The four age categories, 50–59, 60–69, 70–79, and 80–89, could also be referred to as “middle-aged,” “young–old,” “middle–old,” and “old–old.” This categorical approach allowed for nonlinearity in the age trajectory of health outcomes and took self-relevancy of SPA into account.

Statistical Analyses

To examine the effects of SPA on health outcomes, we used fixed-effects panel regression models (Allison, 2009). Fixed-effects panel regression models focus only on within-person change over time. By removing the effect of those time-invariant characteristics and relating temporal variation in the outcome variables only to temporal variation in the independent variables, the net effect of the predictors on the outcome variables can be assessed. The estimated coefficients of fixed-effects models cannot be biased in that fixed-effects models control for all omitted time-invariant differences between the individuals (e.g., differences in education and race/ethnicity). Thus, all time-constant variables would be dropped out of the equation, and only time-varying variables were in the models, rendering both observed and unobserved time-constant heterogeneity unimportant.

Changes in one’s own and spouse’s SPA were modeled as predictors of change in own and spousal health conditions across the five study waves. The analyses were conducted separately for men and women, given the gendered nature of health changes within married couples. Thus, it is likely that the SPA may have different effects on health outcomes for men and women. We estimated a total of 12 models. The first set of six models pertained to physical health, assessing changes in wife’s and husband’s physical disability, functional performance, and chronic disease. The second set of six models pertained to mental health, cognitive health, and self-rated health.

A concerning issue in health studies is sample attrition by a loss to follow-up and mortality, which may produce biased parameter estimates and weaken the representativeness of longitudinal surveys over time. Nonetheless, the reinterview response rates are high in the HRS, and the cross-wave attritions are low. To date, the HRS has collected 13 waves of data between 1992 and 2016, with the baseline response rate ranging from 47.4% to 81.3% across study entry cohorts (an average of 73.0%) and reinterview response rates ranging from 68.8% to 92.3% (Health and Retirement Study, 2017). Also, to reduce sample selectivity, we did not restrict the sample to individuals having no missing information on all health outcomes. Nonetheless, attrition might underestimate the relationships between SPA and health outcomes if the likelihood of attrition related to the SPA was more significant for those who dropped out from the analyses than those who remained in the panel. Sensitivity tests were conducted to assess the robustness of the results. The results of the sensitivity analyses were mostly consistent with the findings reported in the main analyses. All analyses were performed using Stata 16.

Results

Descriptive Results

Table 1 shows weighted descriptive statistics for the main variables for wives and husbands. Wives were relatively younger than their husbands. The average age was 64.24 years (SE = .13) for wives and 66.80 years (SE = .14) for husbands. Most wives belonged to the young-old group (43.18%) and middle-aged group (32.14%), and most husbands belonged to the young-old group (43.45%) and middle-old group (26.33%). Husbands reported higher negative SPA (24.66) than their wives (23.92). This provides preliminary evidence that wife’s more positive attitude toward aging than their husband’s may operate as one source of marital benefits. As years passed by, there was a general upward trend of negative SPA. Husbands reported worse health status in terms of physical disability, chronic disease, cognitive functioning, and self-rated health than their wives. Wives reported lower functional performance and more depressive symptoms than their husbands. A correlation matrix is presented in Supplementary Table A1.

Table 1.

Weighted Descriptive Statistics by Gender.

	Wives		Husbands
	%	Mean (SE), n (%)	%	Mean (SE), n (%)	Range
Age (years)		64.24 (.13)		66.80 (.14)	51–85
Age categories (years)
50–59	32.14		21.45
60–69	43.18		43.45
70–79	20.08		26.33
80–89	4.60		8.77
Self-perceptions of aging		23.92 (.12)		24.66 (.11)	0–48
Physical disability		.25 (.01)		.29 (.01)	0–10
Functional performance		2.77 (.05)		2.35 (.04)	0–12
Chronic disease		1.81 (.02)		1.96 (.02)	0–8
Depressive symptoms		1.04 (.03)		.82 (.03)	0–8
Cognitive functioning		8.65 (.05)		10.00 (.05)	0–20
Self-rated health		2.54 (.02)		2.62 (.02)	1–5

Fixed-effects Regression Models

The main results are presented in Tables 2 and 3, and Figures 1 and 2. Table 2 shows estimates of one’s own and spouse’s SPA predicting changes in physical health (including physical disability, functional performance, and chronic disease) for wives and husbands. Figure 1 presents the marginal effects of changes in the health outcomes associated with changes in one’s own and spouse’s SPA along with 95% confidence intervals when all covariates were fixed at their means. Table 3 shows estimates of one’s own and spouse’s SPA predicting depressive symptoms, cognitive functioning, and self-rated health for wives and husbands. Figure 2 also presents the marginal effects of one’s own and spouse’s SPA on these health outcomes.

Table 2.

Main Effects of Self-Perceptions of Aging and Age Predicting Physical Disability, Functional Performance, and Chronic Disease For Husbands and Wives. Unstandardized Estimates from Fixed-Effects Regression Models.

	Physical disability		Functional performance		Chronic disease
	Wife	Husband	Wife	Husband	Wife	Husband
	Estimates	Estimates	Estimates	Estimates	Estimates	Estimates
Wife’s self-perceptions of aging	.02***	.01*	.05***	.03***	.01***	.01***
Wife’s self-perceptions of aging	(.00)	(.00)	(.01)	(.01)	(.00)	(.00)
Husband’s self-perceptions of aging	.00	.02***	.01	.04***	.00	.01***
Husband’s self-perceptions of aging	(.00)	(.00)	(.01)	(.01)	(.00)	(.00)
Age (years) (reference 50–59: middle-aged)
60–69 (young-old)	.03	.06	.24**	.33***	.46***	.40***
60–69 (young-old)	(.04)	(.05)	(.09)	(.10)	(.03)	(.04)
70–79 (middle-old)	.14*	.24***	.65***	.86***	.94***	.96***
70–79 (middle-old)	(.06)	(.06)	(.12)	(.13)	(.04)	(.05)
80–89 (old-old)	.41***	.60***	1.15***	1.68***	1.42***	1.42***
80–89 (old-old)	(.08)	(.08)	(.17)	(.16)	(.06)	(.06)
Constant	−.37***	−.42***	1.17***	.32	1.06***	.96***
Constant	(.09)	(.10)	(.20)	(.20)	(.07)	(.08)
Number of couples	2669	2669	2669	2669	2669	2669

Note. Standard errors in parentheses. *** p < .001, ** p < .01, * p < .05.

Table 3.

Main Effects of Self-Perceptions of Aging and Age Predicting Depressive Symptom, Cognitive Functioning, and Self-Rated Health for Husbands and Wives. Unstandardized Estimates from Fixed-Effects Regression Models.

	Depressive symptom		Cognitive functioning		Self-rated health
	Wife	Husband	Wife	Husband	Wife	Husband
	Estimates	Estimates	Estimates	Estimates	Estimates	Estimates
Wife’s self-perceptions of aging	.04***	.00	.02*	.02	.02***	.01**
Wife’s self-perceptions of aging	(.00)	(.00)	(.01)	(.01)	(.00)	(.00)
Husband’s self-perceptions of aging	.01*	.03***	.01	.01	.01**	.02***
Husband’s self-perceptions of aging	(.00)	(.00)	(.01)	(.01)	(.00)	(.00)
Age (years) (reference 50–59: middle-aged)
60–69 (young-old)	−.03	−.15*	.28	.33	.11***	.08*
60–69 (young-old)	(.07)	(.07)	(.16)	(.17)	(.03)	(.04)
70–79 (middle-old)	−.03	−.13	.83***	.71**	.27***	.23***
70–79 (middle-old)	(.10)	(.09)	(.21)	(.23)	(.05)	(.05)
80–89 (old-old)	.02	−.14	1.49***	1.87***	.52***	.47***
80–89 (old-old)	(.14)	(.12)	(.31)	(.29)	(.07)	(.07)
Constant	−.14	.12	7.77***	9.27***	1.88***	1.82***
Constant	(.16)	(.15)	(.33)	(.36)	(.08)	(.09)
Number of couples	2658	2625	2656	2615	2669	2669

Note. Standard errors in parentheses. *** p < .001, ** p < .01, * p < .05.

Figure 1.

Changes in wife’s and husband’s physical disabilities, functional limitations, and chronic diseases. Marginal effects are shown, and covariates are fixed at their means. Estimates were based on the models shown in Table 2.

Figure 2.

Changes in wife’s and husband’s depressive symptoms, cognitive impairment, and self-rated health. Marginal effects are shown, and covariates are fixed at their means. Estimates were based on the models shown in Table 3.

Figures 1 and 2 illustrate changes in wife’s health in the upper plots and husband’s corresponding changes in the lower plots. We found that for wives, all six domain-specific health conditions declined when their own negative SPA increased. As wife’s negative SPA increased by one unit, wife’s physical disability increased by .02 unit, functional limitation increased by .05 unit, chronic disease increased by .01 unit, depressive symptoms increased by .04 unit, cognitive impairment increased by .02 unit, and self-rated health increased by .02 unit.

In terms of the spillover effects of SPA, wife’s negative SPA were positively related to changes in her husband’s physical disabilities (b = .01, p < .05), functional limitations (b = .03, p < .05), chronic diseases (b = .01, p < .05), and self-rated health (b = .01, p < .05), but were not related to her husband’s depressive symptoms (b = .00, p = .83) and cognitive impairment (b = .02, p = .08). Overall, wife’s own SPA affected her health more strongly than it affected her husband’s health.

In addition, compared with the middle-aged group, although young-old wives’ health declined only in terms of functional performance (b = .24, p < .05), chronic disease (b = .46, p < .05), and self-rated health (b = .11, p < .05), for both middle-old and old-old wives, all health conditions but depressive symptoms (b_middle–old = −.03, p = .75; b_old–old = −.02, p = .90) deteriorated. In other words, as age increased, the wife’s depression level seemed rather stable.

For husbands, we found that, first, his SPA affected all health conditions except cognitive functioning (b = .01, p = .39). When husband’s negative SPA increased by one unit, his physical disability increased by .02, functional limitation increased by .04, chronic disease increased by .01, depressive symptoms increased by .03, and self-rated health increased by .02. Second, husband’s SPA were only associated with his wife’s depressive symptoms (b = .01, p < .05) and self-rated health (b = .01, p < .05), and were not associated with his wife’s physical disability (b = .00, p = .27), functional limitation (b = .01, p = .14), chronic disease (b = .00, p = .10), and cognitive health (b = .01, p = .25). Similar to what has found for the wife’s spillover effect, husband’s own SPA had greater effects on his health than on his wife’s health. Third, compared with middle-aged husbands, young-old husbands’ health declined except physical disabilities (b = .06, p = .19) and cognitive health (b = .33, p = .06). However, compared with middle-aged husbands, all health conditions but depressive symptoms (b_middle–old = −.13, p = .16; b_old–old = −.14, p = .25) exacerbated among both middle–old and old–old husbands.

In addition to the fixed-effects models, we also estimated random-effects models for all health outcomes, after which we performed Hausman tests (Andreß et al., 2013) to determine whether the fixed-effects models were to be preferred over the random-effects models. Hausman tests examined whether the unique errors were correlated with the regressors and revealed that fixed-effects models were to be preferred over random-effects models in all 12 situations (Supplementary Table B1). Results of the random-effects largely confirmed the main conclusions obtained from the smaller sample size, despite that overall, the magnitudes were more substantial and that both own, and spousal effects of SPA in all random-effects models were significant (Supplementary Tables B2 and B3).

Discussion

This study addresses several research gaps in the SPA–health research. Previous empirical research on the SPA–health link left out the couple context and thus ignored the potential spillover effect. In light of these limitations, this study used nationally representative data from the United States to provide a comprehensive examination of how one’s own and spouse’s SPA are associated with domain-specific health outcomes and how such associations differed between men and women. The multiple health measures involved physical disability, functional performance, chronic disease, depressive symptoms, cognitive functioning, and self-rated health.

Results from fixed-effects regression models yielded several main findings. First, for both husbands and wives, almost all their health conditions declined when their own SPA became more negative. These results should not be surprising, given that numerous studies have shown that negative SPA predict decline in physical, mental, cognitive, and subjective health (Gu et al., 2016; Levy, Slade, & Kunkel, 2002; Mendoza-Núñez et al., 2018; Mohammadpour et al., 2018; Moser et al., 2011; Seidler & Wolff, 2017). Further, the recent comprehensive review indicates that among the three components of ageism, the prevalence of significant relationships with health was the highest when ageism was operationalized as negative SPA as opposed to age stereotypes and age discrimination (Chang et al., 2020). Our findings obtained from the more recent national data lend support to these early findings.

Second, unlike previous gender-blind studies that treat men and women as one entity, this study employs a gender perspective in the SPA–health research. For both men and women, partners’ SPA affected their own self-rated health. However, there are also substantial gender differences in terms of the spouse’s SPA–health associations. While the husband’s SPA predicted his wife’s future depressive symptoms, the wife’s SPA predicted her husband’s physical health, indicated by physical disability, functional limitation, and chronic disease. To our knowledge, these findings have not been reported in previous SPA–health research.

The gendered pattern of the cross-spousal influence of SPA on health outcomes might be linked to the long-standing gendered institutional forces (Reczek & Umberson, 2012). Women overwhelmingly act as health workers who take responsibility for health promotion of other family members, and men are overwhelmingly inattentive to their own and their spouse’s health (Calasanti, 2004). Women who hold less negative SPA are more likely to promptly and diligently adopt health-promotion behavior themselves, and thus may also likely act as the health expert and encourage their husbands to seek health care and adhere to medical treatment. When women hold higher negative SPA, they are less likely to do the health-care work for themselves and for other family members. Consequently, their husband’s health, particularly physical health, is negatively affected. The fact that the husband’s SPA are not associated with their wife’s physical health further supports that it is usually women doing the health-care work within the couple context. However, wife’s depressive symptoms are more reactive to their partner’s SPA than husband’s. Such findings are in line with prior research about gender-related differences in associations between marital quality and depression (Whisman, 2001), and between their spouse’s health problems and depression (Ayotte et al., 2010). Future research is needed to replicate the gender differences in the SPA spillover effects reported here and to investigate the reasons for the differences.

Extensive laboratory and field research showed that negative SPA are modifiable and can be made more positive with interventions (Levy et al., 2014). Previous meta-analyses (e.g., Horton et al., 2008) found that the priming techniques in changing stereotypes of aging can alter older adults’ memory performance, with an overall effect size of .38. The nuanced gender differences in the spousal SPA–health link are important because they inform us that social service programs should pay attention to partner effects when designing programs to promote adults’ well-being and improve health outcomes. For instance, when husbands face great challenges in physical health, interventions to boost their own as well as their wife’s SPA may be helpful. Likewise, when wives display depressive symptoms, interventions should include strategies to lessen their own and their husband’s negative SPA. Many adult men are reluctant to admit their health problems or seek help, which might be due to the perception that their masculinities are threatened by the health concerns (Calasanti, 2004). For these men, efforts to engage their wives may be a feasible approach and are beneficial to both the husbands and wives.

The question of whether the health decline that adults experience as they age is because of the natural aging process or because of SPA is important. Our study provides evidence for both sides. Other than reporting the evidence for the social determinants of health outcomes, this study also shows that aging is a biological inevitability. We found robust evidence for the distinct role of aging in different health trajectories. For both husbands and wives, when they transitioned from the middle-aged to the middle–old and old–old stages, nearly all health conditions deteriorated. Nonetheless, both men’s and women’s depression levels seemed rather stable when the adult’s age increased. This point suggests that adults, particularly women, might have already shown depressive symptoms in an early stage (when they were younger than 50 years). Indeed, prior research suggests that the age pattern of depressive symptoms is characterized by a U-shaped curve, with highest levels in young adulthood, lowest levels in midlife, and increasing levels in later life (Clarke et al., 2011; Mirowsky & Ross, 1992). Moreover, given that ageism was associated with the onset of and lifetime depression (Chang et al., 2020), the timely detection of negative SPA and corresponding treatment programs are necessary.

Further, although adult’s physical performance and cognitive functioning began to decline around 70 years or so, adult’s functional performance, chronic conditions, and self-rated health began to deteriorate at a much earlier time (about 60s). These dissimilar aging trajectories of different health dimensions suggest the need to disentangle health outcomes when analyzing the role of aging and the need to attend to changes in the population age structure when designing health programs.

Limitations and Future Research

Several limitations should be acknowledged. The first limitation is that the study sample was limited to heterosexual, married couples, which limits the generalizability of the findings. Minority stress theory suggests that same-sex couples face additional stressors and stigma which are detrimental to health (LeBlanc et al., 2018; Meyer, 2003). How the partner’s SPA affect one’s health might be more complex for homosexual unions. On the one hand, there is a growing consensus of the marital advantage in both the heterosexual and same-sex couples (Reczek, 2020). On the other hand, it is possible that our findings that heterosexual husband’s SPA predicted wife’s mental health, and heterosexual wife’s SPA predicted husband’s physical health might not apply to same-sex couples. There is fairly strong evidence showing that same-sex couples are less subject to the gendered social scripts (e.g., women as nurturing and men as not nurturing), more likely to have an egalitarian household division of labor (Reczek, 2020), more concordant in health behavior (Holway et al., 2018), and more balanced in attending to their spouse’s health than heterosexual couples (Reczek et al., 2020; Reczek & Umberson, 2012). Nonetheless, emerging research also reveals that although relationship dynamics within sexual minority couples might diverge from heterosexual couples, gay and lesbian couples both uphold and challenge these social scripts (Thomeer et al., 2015). Future research investigating similar processes in same-sex couples is warranted.

Second, this study did not establish the causality between SPA and older adults’ health. Although prior research supports that SPA affect older adults’ health rather than the other way around (Levy et al., 2020), it is possible that the SPA–health relationship is reciprocal (Wurm et al., 2007) and that older adults’ health conditions might affect their SPA. Nonetheless, recent research has also shown that the impact of SPA on health is more significant than the reverse relationship (Sargent-Cox et al., 2012; Wurm et al., 2007).

Third, given that fixed-effects models are designed to study the causes of changes within a person, fixed-effects models are not well suited to investigate time-invariant causes of the dependent variables. Several factors, such as self-efficacy (Levy, Slade, & Kunkel, 2002; Tovel et al., 2019) and health behavior (Kim, 2009; Yeom, 2014), were reported to contribute to the persisting health inequalities in old age. Future studies are warranted to investigate these possibilities.

The fourth limitation concerns the attrition issue in longitudinal analyses. Given that early research revealed that negative SPA increased mortality hazards (Kotter-Grühn et al., 2009; Sargent-Cox et al., 2014), our results of the associations between one’s own and spouse’s SPA and adult’s health outcomes might be underestimated. Also, our study only examined the health influence of negative SPA. The interrelated nature of the three operationalizations of ageism (i.e., age discrimination, age stereotypes, and negative SPA) suggests that future studies may benefit from the inclusion of the other two ageism measures.

Conclusions

This study used panel data from a nationally representative sample and fixed-effects regression models, which account for time-constant observed and unobserved confounders, to present less biased and more consistent estimates concerning the SPA–health relationship. Consistent with prior research, we found that individual’s own negative SPA predicted future health deteriorations, regardless of gender. We contributed to the existing SPA–health literature by showing that the cross-spousal influence of SPA on health outcomes depend on gender, such that wife’s SPA have an evident influence on her husband’s physical health, and husband’s SPA have a clear influence on his wife’s mental health. Thus, the detrimental effects of ageism might be underestimated if the spillover effects were not considered. This study shows that intimate relationships operate through multiple pathways to influence health, and that attitude toward aging of one’s partner is one pathway.

Supplemental Material

Online_Supplementary_Material – Supplemental Material for Self-perceptions of aging and domain-specific health outcomes among midlife and later-life couples

Supplemental Material, Online_Supplementary_Material for Self-perceptions of aging and domain-specific health outcomes among midlife and later-life couples by Meng Sha Luo, Lydia W. Li and Rita Xiaochen Hu in Journal of Aging and Health

Footnotes

Ethical Approval

Data collection for the Health and Retirement Study (HRS) was conducted by the University of Michigan. The HRS was approved by the Institutional Review Board at the University of Michigan (IRB Protocol HUM00061128), and all participants provided informed consent.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Social Science Foundation of China (Grant No. 20CRK007).

ORCID iDs

Meng Sha Luo

Lydia W. Li

Supplemental Material

Supplemental material for this article is available online.

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