Impact of Upper and Lower Body Functional Ability on Affect in Older Couples

Abstract

Objective: We explore how upper and lower body functional ability of older adults and their partners relate to affect in later life. Methods: Data regarding own and partner’s upper and lower body functional abilities were reported by 1767 married/partnered persons aged 57–83. Using multilevel modeling to account for nesting within couples, we examined the impact of a respondent’s own functional abilities, their perception of their partner’s abilities, and the interaction of respondent’s and perceived partner’s abilities on respondent’s positive and negative affect. Results: Higher upper and lower body ability of both respondents and partners were associated with higher positive and lower negative affect. Moderating effects demonstrated a protective role of respondents’ ability on affect when their partners experienced lower ability. Discussion: There is a potential compensatory relationship between older couples adapting to functional changes; it is important to support the functional abilities of both partners in couples to maximize psychological well-being.

Keywords

positive affect negative affect psychological well-being older adults

As individuals age, they experience biological declines that can result in varying levels of functional decline (i.e., inability to walk and limited reach; Deeg et al., 2013; Holstein et al., 2007; Plant et al., 2005). Such change can be debilitating for older adults, limiting their ability to complete basic activities of daily living and negatively impacting their quality of life (Muramatsu et al., 2010; Robb et al., 2008). Older adults experiencing such limitations must increasingly rely on the support of others and/or modify their environment to maximize well-being (Lawton & Nahemow, 1973).

Individuals living with a spouse or significant other are in a unique position to support each other as they cope with such change (Kiecolt-Glaser & Newton, 2001). As one older partner loses one type of ability (i.e., lower or upper body mobility/strength), the other partner may be able to help compensate for this loss. For example, if an older woman is unable to reach up over her head to pull a dish down, she may be able to adapt to her limitation because her partner may be able to do this task for her. Similarly, if an older man has trouble grasping small objects, he may be able to adapt to his loss because his partner is able to help with this task. The adaptive partnership, whereby one partner compensates for the other’s loss may be protective for positive well-being outcomes (i.e., affect). Conversely, if both partners simultaneously experience losses in the same functional domain, this may reduce well-being. The analyses that follow fill a gap in the literature by examining how upper and lower body functional abilities of individuals and of their partners affect well-being.

Developmental and Dyadic Theory

According to Baltes’ (1997) developmental theory on the incomplete architecture of human ontogeny, as individuals age, they experience declines in biological plasticity that are attributed to evolutionary selection benefits. Biological changes are partnered with an increased need for cultural support, yet a decreased efficacy of culture (Baltes, 1997). As the disablement process proposes, biological decline and disease can result in impairments and lead to functional limitations and disability in an unsupportive environment (Verbrugge & Jette, 1994).

The built and social environment play a vital role in supporting older adults’ ability to continually function in their homes or physical spaces (Lawton & Nahemow, 1973). According to Lawton’s ecological theory of aging, the changing level of competence brought on by biological declines interacts with environmental press (i.e., demands of the environment) to ultimately impact a person’s well-being (Lawton & Nahemow, 1973). When there is a lack of fit between a person’s abilities and the environment, the person will experience decreased well-being (Lawton & Nahemow, 1973). Social support can serve as an environmental support to the older individual, mitigating environmental press. Social support can also serve as a moderating factor that prevents an impairment from becoming a disability (Warner & Kelley-Moore, 2012).

Dyadic coping theory posits that partners work together to cope with stressors in their lives, such as functional decline (Berg & Upchurch, 2007). Couples may engage collaboratively or be uninvolved, supportive, controlling, protective, buffering, or overprotective when facing a stressor. For example, empirical evidence indicates that spouses help to manage health-based stressors and health challenges including knee osteoarthritis (Martire et al., 2013), diabetes (Khan et al., 2013), or functional disability (Bisschop et al., 2003).

Interdependent Experience of Functional Ability

Mounting evidence has demonstrated the interdependence of health outcomes within older couples. It is established, for example, that one partner’s physical (i.e., chronic illness) or emotional health (i.e., depression) can impact his or her partner’s health and/or well-being (Bourassa et al., 2015; Goodman & Shippy, 2002; Polenick et al., 2019; Pruchno et al., 2009a, 2009b; Ruthig et al., 2012; Siegel et al., 2004; Stephenson et al., 2014; Valle et al., 2013). However, less understood is the interdependence and/or potential compensatory effects of functional abilities on psychological well-being within couples. Functional ability is a unique developmental outcome of aging because of its interdependence on social context (Schulz & Williamson, 1993 as cited in Robb et al., 2008; Warner & Kelley-Moore, 2012). It is not wholly dependent upon genetic or biological factors. When each partner is experiencing the biological decrements of aging that impact functional capacity, it is likely that their social dependence will mean that their joint experience of functional decline will impact each other’s well-being.

In fact, within coresident partnerships, evidence suggests that greater frailty in a person is associated with greater frailty in their partner (Kang et al., 2020; Monin et al., 2016) and that partnership can have protective effects on decline of physical functioning for older people without chronic illnesses (Bisschop et al., 2003). Furthermore, a partner’s lower functional ability has been found to be associated with increased depression, loneliness, and lower well-being for both men and women (Hoppmann et al., 2011; Korporaal et al., 2008; Monin et al., 2016; Monserud & Peek, 2014; Robb et al., 2008). Some research suggests that the magnitude of this association differs by gender (Ruthig et al., 2012).

Spousal support can also result in better functional ability, while spousal strain can reduce functional ability (Adams, 2016; Ryan et al., 2014). Marital quality of both spouses is associated with disability; seeing oneself as supportive or one’s spouse as supportive has positive effects on functional ability (Choi et al., 2016). One explanation for this finding is that higher relationship quality or levels of support may be associated with better perception of what a partner needs which results in concretely supporting the partner in achieving a functional goal (i.e., becoming a social resource for adapting to disability; Verbrugge & Jette, 1994). For example, in the osteoarthritis context, when an individual perceives the pain of a partner accurately, that person can offer support more in line with what his or her partner wants (Martire et al., 2006). This empathic response from a spouse may buffer against negative effects of spouse depression on functional ability (Stephenson et al., 2014).

Not understood, however, is how a respondent’s functional ability and that of a partner work in concert with one another to impact well-being. While there may be a direct effect of a partner’s functional ability on a respondent’s well-being, this association may be moderated by the respondent’s own functional ability. Said another way, the impact of a partner’s functional ability on a respondent’s well-being may be dependent upon how the respondent is functioning. If an older individual retains functional capacity, the loss of a partner’s ability may not have as strong of an impact on well-being than if both individuals have lost functional ability.

Functional Ability and Positive and Negative Affect

Research to date primarily focuses on the impact of functional ability and health within couples on depression (i.e., Ruthig et al., 2012; Siegel et al., 2004). However, when we look to Lawton’s ecological theory of aging, we see that affective well-being (positive and negative affect) is posited as the outcome when there is a lack of fit between a person (competence) and the surrounding environment (environmental press; Lawton & Nahemow, 1973). When a person is in a maladaptive state (i.e., there is a lack of fit between capacities and demands within the environment), negative affect is experienced. When a person is at or near adaptation level (i.e., the theoretical mean for adaptive functioning at a given level of competence), he experiences positive affect (Lawton & Nahemow, 1973). Thus, an individual’s level of functional ability is likely to directly impact his affect, whereby higher ability is associated with greater positive affect and less negative affect. Further, his partner’s functional ability, which is an aspect of his environment that could act as a resource or a stressor, is likely to impact his affect. Yet, research has not fully examined the impact of functional ability of both partners in a couple on an individual’s affect.

With this, research has found that positive and negative affect can operate as independent outcomes of constructs with distinct correlates associated with each (Emmons & Diener, 1985). Additional research at the individual level demonstrates unique associations of functional ability with positive and negative affect (Choi et al., 2020; Ostir et al., 2015; Wahl et al., 2014). It is critical, therefore, to understand how the functional ability of older adult couples impacts both positive and negative affect.

Present Study

The analyses that follow extend the current literature by using reports of one older adult in a partnership to examine how their own reports of functional ability and their perceptions of partner’s functional ability impact the positive and negative affect of the respondent. Particularly novel is the focus on testing the moderating association of perceived partner’s functional ability on one’s own affect. The moderation tested here determined if there was a buffering or compensatory effect present, whereby when the respondent experienced low levels of functional ability, high levels of perceived partner’s ability sustained levels of well-being for the respondent (positive and negative affect).

While most dyadic studies on functional ability measure ability as a single outcome (i.e., Korporaal et al., 2008; Robb et al., 2008; Ruthig et al., 2012), some work in individuals separates upper and lower body functional ability to develop a more nuanced perspective of how functional ability by domain impacts outcomes (Schootman et al., 2009; Simonsick et al., 2001). We extend the literature examining functional ability in couples by testing the associations of upper and lower body functional ability separately. Conceptually, this allows for the testing of a possible compensatory effect within couples; if a respondent lacks upper body ability, but a partner has upper body ability, there is an opportunity for compensation. Likewise, a similar association may be present for lower body ability.

Analyses drew upon data from a large representative panel of older adults living in New Jersey and addressed the following hypotheses: (1) Higher levels of respondent’s functional ability (upper and lower body functioning) would be associated with respondent’s higher positive affect and lower negative affect. (2) Higher levels of perceived partner’s functional ability (upper and lower body functioning) would be associated with respondent’s higher positive affect and lower negative affect. (3) The impact of respondent’s functional ability on affect would be moderated by the level of perceived partner’s functional ability, by functional domain. Specifically, if the respondent reported lower levels of upper body functioning, but their partner was perceived to retain high levels of upper body functioning, the respondent would not experience decrements in positive affect or increases in negative affect. A similar pattern was expected for lower body functioning.

Models accounted for covariates with known associations with support and functional ability, including age, race, gender (Ruthig et al., 2012), and relationship quality (Kiecolt-Glaser & Newton, 2001; McPheters & Sandberg, 2010).

Methods

Participants and Procedures

ORANJ BOWL^TM (Ongoing Research on Aging in New Jersey) is a large-scale representative longitudinal panel study of older adults in New Jersey developed to understand issues related to successful aging. It includes 5688 individuals who were interviewed at age 50–74 at baseline (November 2006–April 2008). Panelists were recruited by cold calling using list-assisted random digit-dialing (LA-RDD) procedures. The demographic characteristics of the target sample made coverage loss due to the growing incidence of cellphone only households small. ORANJ BOWL^TM response rates were consistent with or higher than the average rates in other RDD health surveys at the time (e.g., New Jersey BRFSS). Demographic characteristics of panelists mirrored those of New Jersey, including only slightly more women and individuals with more education. Individuals of Hispanic origin are underrepresented in the sample given English-only telephone surveys (see Pruchno et al., 2010 for sample details).

When panelists verbally consented to the baseline interview, they agreed to be contacted in the future for annual interviews thereafter and were verbally re-consented or consented in writing at each wave. As of 2020, panelists participated in up to seven waves of data collection: Wave 1 (baseline; 2006–2008), Wave 2 (2007–2008; N = 1594 completed a personality assessment), Wave 3 (2011; N = 3387), Wave 4 (2014–2015; N = 3608), Wave 5 (2015–2017; N = 3076), Wave 6 (2017–2019; N = 3137), and Wave 7 (2020, post-COVID-19 pandemic onset; N = 2458). Data for the analyses that follow are drawn from baseline (Wave 1; demographics) and Wave 5 (marital/living status, relationship length, relationship quality, respondent functional ability, partner functional ability, and respondent positive and negative affect).

At Wave 5, panelists were asked to report on their current relationship status. Data for the analyses presented here were limited to those respondents that endorsed being married and living with their spouse or living with someone/partner in a committed relationship. Of panelists who completed Wave 5, 55% were married and living with their spouse (n = 1678) and 3% were living with someone in a committed relationship (n = 89). We include all variations of self-reported romantic partnership as we would expect the associations tested here to exist in all couple configurations. Thus, total sample size for these analyses included 1767 respondents.

Respondents included in this subsample reported higher levels of education (t(5673) = −16.74, p < .001) and income (t(5020) = −28.63, p < .001) than those not included. Respondents included here were also significantly younger (t(5686) = 10.93, p < .001), more likely to be male (X²(1, N = 5688) = 94.15, p < .001), and less likely to be African American (X²(1, N = 5688) = 145.73, p < .001) than those who were not included. All procedures were approved by the UMDNJ and Rowan University Institutional Review Boards.

Measures

Demographics and covariates

Covariates included age, gender, race, education, and length and quality of relationship. At baseline (Wave 1), respondents reported their gender as 0 (male) or 1 (female), race as 0 (non–African American) or 1 (African American), and education from 1 (less than high school) to 9 (doctoral/professional degree). At Wave 5, respondents reported their current relationship status. As specified above, analyses were restricted to those respondents who indicated at Wave 5 that they were married (and living in the same household) or living with someone in a committed relationship. For those panelists currently in a relationship, respondents were asked “In what month and year did you get married to your spouse?” or “In what month and year did you become involved with your partner?” Length of relationship was determined by computing the number of years from the date of relationship inception to date of survey completion. Respondents were also asked to rate “How close is your relationship with your current (spouse/partner)?” from 1 (not at all close) to 4 (very close).

Independent variables: functional ability

At Wave 5, panelists engaged in a relationship with a partner reported the extent of difficulty they themselves had and the perception their partners had with nine indicators of functional limitations (walk a 1/4 mile; walk up 10 steps without resting; stand or be on your feet for about 2 hours; sit for about 2 hours; stoop, bend, or kneel; reach up over your head; use your fingers to grasp or handle small objects; lift or carry something as heavy as 10 lbs.; and push or pull large objects like a living room chair) using a 5-point Likert scale ranging from 1 (can’t do it at all) to 5 (not at all difficult). These items were developed for the National Health Interview Survey and have been used by others (Guralnik & Ferrucci, 2003; Long & Pavalko, 2004).

To be able to consider a buffering or compensatory effect of functional ability by domain, we split functional ability items for the respondent and the partner into two subscores: lower body functional ability and upper body functional ability. Items reflecting lower body ability included Walk a 1/4 mile; Walk up 10 steps without resting; Stand or be on your feet for about 2 hours; and Stoop, bend, or kneel (Schootman et al., 2009). Items reflecting upper body ability aligned with those used in prior work (Simonsick et al., 2001) and included Reach up over your head, Use your fingers to grasp or handle small objects, Lift or carry something as heavy as 10 lbs. (such as a full bag of groceries), and Push or pull large objects like a living room chair. The item of Push or pull large objects like a living room chair could be considered an upper or lower body ability item; we tested models with a scale for upper body ability that included and did not include this item. Results presented below did not change with the exclusion of this item, so we opted to retain the item in the upper body scale due to greater construct reliability with its inclusion. In addition, the functional ability item of Sit for about 2 hours was excluded as it was not clear whether it reflected a lower or upper body ability. Mean item total scores were computed for each construct; higher scores indicated greater ability. The resultant data preparation produced four key independent variables: (1) respondent lower body functional ability (α = .86; range = 4–20), (2) respondent upper body functional ability (α = .77; range = 5–20), (3) respondent report of perceived partner’s lower body functional ability (α = .92; range = 4–20), and (4) respondent report of perceived partner’s upper body functional ability (α = .86; range = 4–20).

Dependent variables: affect

At Wave 5, respondents reported on their own positive and negative affect (Lawton et al., 1992). Respondents rated in the past week how often they felt happy, warm-hearted, interested, content, energetic, irritated, sad, annoyed, worried, and depressed on a scale of 0 (never) to 4 (nearly always). Positive affect was computed as a mean item total score of 5 items: happy, warm-hearted, interested, content, and energetic (α = .82). Negative affect was computed as a mean item total score of 5 items: irritated, sad, annoyed, worried, and depressed (α = .82). Higher scores indicated greater positive or negative affect.

Analytic Strategy

First, descriptive statistics and correlations were computed for all key variables (see Tables 1 and 2). Second, we created cross-sectional multilevel (2-level) models to examine the associations between respondent and perceived partner upper and lower body functional ability and the positive and negative affect of the respondent. Level one is the dependent variables measured at the level of the couple, and level two includes the covariates that explain couple-level variability. Separate models were created positioning respondent positive and negative affect as the dependent variables, accounting for the fact that reports were nested within couples’ nature (reports by the respondent for both respondent’s own functional ability and his/her partner’s functional ability) of the data. Covariates included age, gender, education, race, length of the relationship, and quality of the relationship. Education and relationship quality, however, were removed from all models reported due to nonsignificance.

Table 1.

Sample Demographics (N = 1767).

	M(SD)/%(N)
Demographics and Covariates
Age	68.32(6.46)
Gender (female)	54%(962)
Race (African American)	4%(67)
Education	4.73(2.15)
Relationship length (years)	36.00(14.38)
Relationship quality	3.73(.57)
Predictor variables
Respondent lower body functional ability	17.13(3.40)
Respondent upper body functional ability	18.65(2.25)
Partner lower body functional ability	16.87(4.14)
Partner upper body functional ability	18.20(3.01)
Outcome variables
Respondent positive affect	15.32(3.30)
Respondent negative affect	7.08(3.12)

Table 2.

Bivariate Correlations among Key Constructs.

	1	2	3	4	5	6	7	8	9	10	11	12
1. Age	—
2. Gender (1 = female)	−.05*	—
3. Race (1 = African American)	.00	.01	—
4. Education	.06*	−.10***	−.06*	—
5. Relationship length	.45***	.06*	−.02	−.10***	—
6. Relationship quality	.10***	−.02	−.03	.01	.07**	—
7. Respondent lower body functional ability	−.19***	−.10***	−.01	.19***	−.13***	.05*	—
8. Respondent upper body functional ability	−.13***	−.18***	−.01	.14***	−.09***	.03	.65***	—
9. Partner lower body functional ability	−.24***	−.08***	−.03	.14***	−.18***	.08**	.19***	.16***	—
10. Partner upper body functional ability	−.22***	.06*	−.03	.12***	−.16***	.08**	.14***	.15***	.76***	—
11. Respondent positive affect	.08**	.08**	.02	.07**	.07**	.29***	.29***	.22***	.13***	.16***	—
12. Respondent negative affect	−.07**	.14***	−.05*	−.07**	−.06*	−.23***	−.22***	−.23***	−.11***	−.13***	−.57***	—

*p < .05, **p < .01, ***p < .001.

Two sets of models were computed: one included the mean-centered independent variables of respondent’s lower body functional ability and perceived partner’s lower body functional ability, and the other included respondent’s upper body functional ability and perceived partner’s upper body functional ability. Final models included the interaction of respondent’s and perceived partner’s lower body ability and upper body ability, respectively. The process yielded four sets of models: positive and negative affect X upper body and lower body function. Model fit was evaluated using −2 Res Log Likelihood, AIC, and BIC estimates, all for which lower scores indicate better fit. Models were developed using SAS 9.4 PROC MIXED.

Results

Cross-sectional multilevel model results indicated that greater age was associated with more positive affect and less negative affect; women reported higher levels of both positive and negative affect, and African Americans reported less negative affect (no differences on positive affect). In addition, individuals in relationships of longer duration reported more positive affect and less negative affect. Table 3 (Models 1A and 2A) and Table 4 (Models 3A and 4A) show effects of covariates in each of the four sets of models.

Table 3.

Multilevel Modeling Results for Lower Body Functional Ability.

	Positive Affect		Negative Affect
	Model 1A	Model 1B	Model 2A	Model 2B
	B(SE)	B(SE)	B(SE)	B(SE)
Intercept	9.15(.85)***	9.11(.85)***	10.50(.83)***	10.56(.83)***
Age	.08(.01)***	.08(.01)***	−.05(.01)***	−.05(.01)***
Gender (1 = female)	.82(.15)***	.82(.15)***	.70(.15)***	.71(.15)***
Race (1 = African American)	.45(.38)	.46(.38)	−.91(.37)*	−.94(.37)*
Relationship length	.01(.01)*	.01(.01)*	−.02(.01)**	−.02(.01)**
Respondent lower body functional ability	.31(.02)***	.31(.02)***	−.20(.02)***	−.20(.02)***
Partner lower body functional ability^a	.10(.02)***	.10(.02)***	−.08(.02)***	−.08(.02)***
Respondent lower body functional ability* partner lower body functional ability	—	n.s.	—	−.01(.01)*
Dyad covariance estimate	9.46	9.46	8.96	8.94
−2 Res Log Likelihood	8939.8	8947.2	8855.2	8859.9
AIC	8943.8	8951.2	8859.2	8863.9
BIC	8954.8	8962.1	8870.1	8874.9

n.s. = not significant. *p < .05, **p < .01, ***p < .001; N = 1767

^aData regarding partner abilities were reported by the study respondent.

Table 4.

Multilevel Modeling Results for Upper Body Functional Ability.

	Positive Affect		Negative Affect
	Model 3A	Model 3B	Model 4A	Model 4B
	B(SE)	B(SE)	B(SE)	B(SE)
Intercept	10.03(.86)***	9.95(.86)***	10.27(.82)***	10.33(.81)***
Age	.06(.01)***	.07(.01)***	−.04(.01)***	−.04(.01)***
Gender (1 = female)	.76(.15)***	.77(.15)***	.70(.15)***	.70(.15)***
Race (1 = African American)	.48(.39)	.54(.39)	−.95(.37)*	−1.00(.37)**
Relationship length	.01(.01)*	.01(.01)*	−.01(.01)*	−.01(.01)*
Respondent upper body functional ability	.34(.03)***	.36(.04)***	−.28(.03)***	−.30(.03)***
Partner upper body functional ability^a	.17(.03)***	.18(.03)***	−.14(.02)***	−.15(.02)***
Respondent upper body functional ability* partner upper body functional ability	—	.03(.01)*	—	−.02(.01)*
Dyad covariance estimate	9.87	9.84	8.89	8.87
−2 Res Log Likelihood	8996.4	8997.7	8825.0	8827.9
AIC	9000.4	9001.7	8829.0	8831.9
BIC	9011.3	9012.7	8839.9	8842.9

*p < .05, **p < .01, ***p < .001; N = 1767.

^aData regarding partner abilities were reported by the study respondent.

Regarding lower body functional ability, greater respondent functional ability was associated with greater positive affect and less negative affect (Table 3, Models 1A and 2A). Likewise, greater perceived partner lower body functional ability was also associated with greater positive affect and less negative affect (Table 3, Models 1A and 2A). However, the impact of respondent’s lower body functional ability on negative affect was moderated by the level of perceived partner’s lower body functional ability (Table 3, Model 2B). When the respondent retained greater lower body ability, the impact of the partner’s lesser lower body ability was less on negative affect. The respondent’s retained lower body abilities were able to protect or buffer against the detriment of the perceived partner’s failing lower body ability regarding negative affect (see Figure 1(a)). Negligible change was found in fit indices for positive and negative affect with lower body functional ability as model complexity increased from Model A to Model B.

Figure 1.

Moderation effect of (a) respondent’s lower body functional ability on the association of partner’s lower body functional ability with negative affect, (b) respondent’s upper body functional ability on the association of partner’s upper body functional ability with positive affect, and (c) respondent’s upper body functional ability on the association of partner’s upper body functional ability with negative affect, modeled at high (+1 SD) and low (−1 SD) levels of functional ability for exemplifying purposes.

Similarly, considering upper body functional ability, greater respondent upper body ability was associated with greater positive affect and less negative affect (Table 4, Models 3A and 4A). Likewise, greater perceived partner upper body functional ability was also associated with greater positive affect and less negative affect (Table 4, Models 3A and 4A). However, the impact of respondent upper body functional ability on positive and negative affect was moderated by the level of perceived partner’s upper body functional ability (Table 4, Models 3B and 4B). When the respondent retained greater levels of upper body ability, the impact of the partner’s lesser upper body ability was less on positive and negative affect. The respondent’s retained upper body abilities were able to protect against the detriment of the partner’s perceived failing upper body ability regarding positive (see Figure 1(b)) and negative affect (see Figure 1(c)). Again, negligible change was found in fit indices as model complexity increased.

Discussion

This study examined the effects of respondents’ and perceived partners’ functional ability within older adult couples on respondents’ positive and negative affect. Analyses examined if there was an interaction between respondents’ and perceived partners’ functional ability on respondent’s affect. Results are consistent with the literature such that respondents’ and perceived partners’ functional ability were associated with positive and negative affect. However, findings extend the literature by demonstrating that the impact of respondent’s functional ability on affect was moderated by a partner’s perceived functional ability. Implications for intervention and future research are discussed.

Findings are consistent with prior literature that documents the interdependent experience of functional ability in older adult couples. Similar to work on depression and loneliness (Hoppmann et al., 2011; Korporaal et al., 2008; Monserud & Peek, 2014; Robb et al., 2008), greater respondent and perceived partner functional ability (upper and lower body) were associated with greater positive affect and less negative affect. These results are also consistent with theoretical expectations. The disablement model tells us that the experience of functional disability is a mismatch between personal competence and environmental supports (i.e., a physical impairment is only a disability when there is a limitation of capacity in social context; Verbrugge & Jette, 1994), and Lawton’s ecological model of aging suggests that when there is a lack of person x environment fit this is associated with decreased affective well-being (Lawton & Nahemow, 1973). Considering the impact of perceived partner’s functional ability on respondent’s affect, functional decline may serve as a unique stressor for older couples to manage that carries implications for emotional well-being (Robb et al., 2008). As contagion theory proposes, the interdependent nature of marriage or romantic partnerships may mean that whatever impacts one person’s affect also likely impacts the other person’s affect (Ruthig et al., 2012). Thus, if one partner is experiencing a direct effect of functional ability on affective well-being, then the other partner will feel that effect too. These findings suggest that by increasing person x environment fit for an individual or his/her partner (i.e., by decreasing environmental press when competence declines), affective well-being may also be improved for the couple. Further, dyadic interventions that jointly target both partners’ functional ability and coping responses to the stressor (Berg & Upchurch, 2007) may improve affective well-being for both individuals in older couples. Sustaining functional ability and affective well-being may further support the ability of older individuals in a couple to remain in a community setting, rather than need additional long-term supports and services (Nuotio et al., 2003; Peng & Wu, 2015).

Second, findings extend the current literature by demonstrating an interactive effect of perceived partners’ functional ability on affect in older couples. When an older adult is experiencing functional decline in lower or upper body ability, if his/her partner is perceived to retain that ability, decrements in affective well-being are less. Said another way, when an older adult’s partner is experiencing functional decline in lower body or upper body ability, retaining ability in that domain is protective for affective well-being. This finding suggests that there may be a compensatory response to disability happening. For example, if an older woman’s partner can no longer reach up over her head to grasp small objects (i.e., decrements in upper body ability) this can result in decreased affective well-being. However, if she retains this ability, while her partner loses it, decrements in positive and increases in negative affect may be lessened. Interventions that support the functional well-being of a given individual, such as those supporting function-focused care in the community (see Pretzer-Aboff et al., 2011), have the potential to impact both the affective well-being of the individual and his or her partner.

Results presented here are strengthened by their use of reports on functional ability and affect from a large sample of older adults. However, findings are not without limitation. Panelists included in this subsample reported higher levels of education and income, were significantly younger, were more likely to be male, and were less likely to be African American than those from the panel who were not included in analyses. While some of these differences may indicate selection tendencies of those that remain married or in partnerships, they bias interpretation of findings to those that share these attributes, and results should be interpreted with this limitation in mind. Second, the sample was relatively high functioning; despite that or because of that, we see a moderating effect of perceived partner’s ability. However, future work should examine whether these associations hold in a sample experiencing higher levels of disability. Further, the interaction estimate, while significant, was modest and future efforts should evaluate further what would be considered meaningful change in the context of disability within couples. Third, because reports were only collected from one member of each couple, we are only able to examine the impact of respondents’ perceptions of partners’ ability on affect. Further work should examine if associations hold when partners themselves are asked to rate their functional ability. Similarly, because reports of affect were only collected from respondents, a full actor–partner model could not be specified. Additional work should examine the joint impact of functional ability of older couples on partner’s affective well-being as well. Fourth, final models did not include an indicator of relationship quality, only relationship length. Our single-item report of relationship quality did not explain any additional variance above and beyond relationship length. While relationship length likely proxies for relationship quality, as those in dysfunctional relationships are less likely to be still married or living together in a partnership, a more thorough examination of the impact of relationship quality within these models with a more comprehensive scale should be used. Fifth, further work is needed to look beyond the presence of a partner and his or her functional capacity and also consider the built environment. Person by environment fit theories purport that the physical space of an individual can impact well-being (Lawton & Nahemow, 1973) and that an older person’s rate of functional decline is influenced by a combination of person by environment characteristics (Christensen et al., 2002). It may be that modification of a physical space can also offer a similar buffering effect. Further research is needed to explore this additional factor. Finally, models here find a moderating effect of partner’s abilities on own abilities which suggest a possible compensatory effect between partners. However, additional research is needed to determine if the results found here are objectively due to a partner performing actions (i.e., reaching up over one’s head) on behalf of a partner or if the impact on affect is due to other explanatory variables.

Overall, the findings from this work demonstrate the interdependent nature of functional ability in older couples. Results highlight both the importance of a respondent’s and perceived partner’s functional capacity on respondent’s affect and the moderating effect of a partner’s functional ability on respondent’s affect. Intervention programs that target the functional ability of an older person have the potential to cause rippling effects for a partner. Findings support the use of function-based interventions for older adults in the community (i.e., Pretzer-Aboff et al., 2011) to sustain levels of psychological well-being.

Footnotes

Acknowledgments

The authors would like to thank the ORANJ BOWL participants for their time and efforts and the ORANJ BOWL project team at the New Jersey Institute for Successful Aging for their help in collecting the data.

Declaration of Conflicting Interests

The author(s) 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: National Institute on Aging (R01AG046463) and UMDNJ-SOM.

ORCID iD

Allison R. Heid

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