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Aging Couples: Benefits and Costs of Long Intimate Relations

Summary and Keywords

Aging does not occur in isolation, but often involves significant others such as spouses. Whether such dyadic associations involve gains or losses depends on a myriad of factors, including the time frame under consideration. What is beneficial in the short term may not be so in the long term, and vice versa. Similarly, what is beneficial for one partner may be costly for the other, or the couple unit over time. Daily dynamics between partners involving emotion processes, health behaviors, and collaborative cognition may accumulate over years to affect the longer-term physical and mental health outcomes of either partner or both partners across adulthood and into old age. Future research should move beyond an individual-focused approach to aging and consider the importance of and interactions among multiple time scales to better understand how, when, and why older spouses shape each other’s aging trajectories, both for better and for worse.

Keywords: couples, time-sampling, longitudinal, emotion, health behaviors, cognition, intraindividual variability, intracouple variation


Development does not occur in isolation. Social ties have long been recognized to be important for key outcomes, including health and well-being, throughout the adult lifespan and into old age (Uchino, 2009; Rook, Mavandadi, Sorkin, & Zettel, 2007), with marriage and romantic relationships being the closest and perhaps most influential ties (Johnson, Backlund, Sorlie, & Loveless, 2000; House, Landis, & Umberson, 1988). A wealth of research emphasizes the importance of partners to health and well-being outcomes, for better or worse, but studies are primarily based on individual reports about the respective partner’s behaviors, experiences, and feelings (Robles, Slatcher, Trombello, & McGinn, 2014). Such approaches provide highly valuable insight into what individuals observe their partners doing or feeling, but they are also limiting, in that they do not take into account each partner’s own perspective. Obtaining data from both partners advances our understanding of the social dynamics that characterize health and well-being in couples, as well as the mechanisms that link them to more or less favorable aging outcomes.

This article focuses on the role of spouses and how they shape each other’s aging outcomes, recognizing that marital relationships represent only one of several close ties that an individual has across the lifespan. The term marital relationships will be used in a broader sense to describe unions between two adults who are married or who have been living together for over 12 months. This definition is inclusive of same-sex and opposite-sex common-law relationships, and it distinguishes close long-term relationships from more casual ones. A conceptual framework is outlined for studying the spousal dynamics in aging couples to explore how partners can be important resources for each other, but at times also bring each other down (Holt-Lunstad, Birmingham, & Jones, 2008; Lewis & Rook, 1999). The discussion does not focus on major themes concerning aging couples, such as marital satisfaction, sexuality, childlessness, negativity, or caretaking issues (such as frailty and dementia) in older age. Rather, the importance of time is highlighted for understanding the dynamic interplay among processes that occur and evolve across different time scales, to elaborate how everyday-life processes accumulate to shape longer-term aging trajectories in couples. In doing so, the article brings together research from the broader stress, coping, and lifespan developmental literature.

To illustrate key concepts, an applied scenario will be used throughout the article based on Linda and Bill, a hypothetical older adult couple. Bill recently had a stroke and now needs to modify many of his everyday activities to promote recovery and reduce his future cardiovascular risk. Linda, who shares the same lifestyle as her husband, is Bill’s main source of support and tries to help him cope with life after stroke. She sees Bill’s stroke as a wake-up call for both of them to adopt healthier lifestyles. The sample case of a couple coping with stroke was selected because cardiovascular disease is a common condition in old age that not only affects the individual but often requires the involvement of close others, such as spouses, and also can be influenced by behavioral lifestyle factors (De Backer et al., 2003; Dimsdale, 2008; Godwin, Swank, Vaeth, & Ostwald, 2013; WHO, 2017a). In the following sections, the experiences of this hypothetical couple are examined to illustrate the value of taking a social-contextual approach to aging in order to better understand everyday spousal dynamics (i.e., regarding emotion, health behavior, and cognitive processes) and their longer-term outcomes at the individual and couple levels.

A Social-Contextual Approach to Aging

National statistics across the Western world show that the majority of adults are coupled (Copen, Daniels, Vespa, & Mosher, 2012; European Commission, 2015; Statistics Canada, 2013). Married individuals overall enjoy better physical and mental health than unmarried or divorced individuals (Johnson, Backlund, Sorlie, & Loveless, 2000; Robles & Kiecolt-Glaser, 2003). In contrast, being in a strained marriage has been associated with worse health outcomes compared to single and divorced individuals (Hawkins & Booth, 2005; Holt-Lunstad, Birmingham, & Jones, 2008; Umberson, Williams, Powers, Liu, & Needham, 2006). In other words, the association of marriage with physical and mental health does not seem to be ubiquitously beneficial; rather, it depends upon the characteristics of the relationship.

Aging couples often share a long history of relationship experiences. Relationships are not randomly formed, and the early years of marriage can set couples on various trajectories into old age. Partners tend to share a variety of characteristics when they meet (i.e., assortative mating; Trombello, Schoebi, & Bradbury, 2015). There is a rich body of literature addressing how early marriage influences later relationship outcomes (Karney & Bradbury, 1995). For example, examining couples who divorced, Gottman and Levenson (2002) found that partners who approached conflicts with high expressivity of anger and negativity were also more likely to divorce earlier (on average, after 8–9 years of marriage), whereas partners who responded with less anger and negativity were likely to stay together longer (15–16 years).

Links between early strategies to cope with conflict and later divorce outcomes may operate through the small everyday “bids” that partners put forth, where everyday moments of intimacy and affection (or lack thereof) pile up to influence later relationship outcomes (Driver & Gottman, 2004). Whether a couple ends up staying together, as well as the way that partners influence each other in old age, are assumed to be rooted deeply in their everyday social exchanges. The reoccurring spousal dynamics that accumulate over time are expected to set them up for more or less favorable long-term outcomes.

By the time partners reach old age, they share a long history of joint experiences that uniquely position them to support each other when confronted with age-normative stressors such as health problems (Berg & Upchurch, 2007). A number of theoretical frameworks in the stress, coping, and lifespan developmental literatures offer conceptual insights into how couples cope during difficult times (Baltes & Carstensen, 1999; Berg & Upchurch, 2007; Hoppmann & Gerstorf, 2016; Preece & DeLongis, 2005). Inherent in all of these is a recognition that partners have the potential to share their resources and engage in strategies that help each other to accomplish what would not be possible alone, but that they also have the potential to bring each other down (Schoebi, 2008; Umberson, Crosnoe, & Reczek, 2010; Weldon & Bellinger, 1997). The Selective Optimization with Compensation model (Baltes & Baltes, 1990) posits that development goes along with gains and losses. Such gain-loss dynamics have been fruitfully extended to dyads (Baltes & Carstensen, 1999; Hoppmann & Gerstorf, 2016). For example, gains and losses in partnerships can take intricate forms in situations where what is beneficial for one partner ends up hurting the other partner or the couple as a whole, and vice versa (Baltes & Carstensen, 1999).

Using these dyadic frameworks as a stepping stone, this article emphasizes the need to unpack the temporal gain-loss dynamics and specific mechanisms that differentiate couples who are likely to embark on more favorable aging trajectories from couples who are likely to embark on less favorable ones. Aging by definition involves the passage of time. A lifespan is formed through a collection of moments that form days, eventually shaping longer-term aging trajectories that unfold on a scale of years (Gerstorf, Hoppmann, & Ram, 2014). Seminal work by DeLongis, Coyne, Dakof, Folkman, and Lazarus (1982) has focused attention on the associations of everyday processes (specifically, daily hassles) with longer-term health outcomes. The idea that short-term, within-person fluctuations are systematically linked with longer-term aging outcomes occurring on a larger time scale is also reflected in Nesselroade’s (1991) seminal work and has gained huge momentum over the past decade, as exemplified by the increasing popularity of measurement-burst designs (Sliwinski, 2008; Ram et al., 2014). Measurement-burst designs are especially ideal for integrating short-term processes that unfold over shorter time scales and within a couple with longer-term outcomes that evolve over longer time periods (Scott et al., 2015).

Recent theoretical and methodological advances have led to distinguishing net intraindividual variability from time-structured intraindividual variability (Ram & Gerstorf, 2009). Net intraindividual variability refers to fluctuations within a given person in behaviors and feelings that are not systematically ordered in time, thereby capturing phenomena such as lability, rigidity, robustness, and flexibility. For example, high intraindividual variability (i.e., extreme fluctuations within a short span of time) in affect can be a sign of worse psychological and physical health in older age, above and beyond average levels of affect (Ong & Ram, 2017). In contrast, time-structured intraindividual variability refers to fluctuations within a given person in behaviors and feelings that are systematically ordered in time, thereby capturing processes of adaptation, regulation, homeostasis, and differentiation (see also Wang, Hanmaker, & Bergeman, 2012).

Such notions may be fruitfully extended to research on couples, as illustrated in the guiding theoretical framework presented in Figure 1. Consider the case of Linda and Bill, where Bill is struggling as he recovers from his stroke. His recovery from the stroke has involved many challenges that make it harder for him to regulate his emotions (e.g., impaired cognitive function, disrupted daily routines, adjustment to new physical limitations), and so, on average, he experiences lower positive affect than his wife, but he also is more likely to have large positive-affect fluctuations (e.g., high net intraindividual variability, defined by a large intraindividual standard deviation). Bill’s wife, Linda, is generally able to maintain higher positive affect, and although she feels less positive affect when her husband is feeling down, her fluctuations in positive affect are not as extreme as his. Despite Bill’s own high intraindividual variability in positive affect, the fact that he is partnered with a generally stable and supportive wife has kept him on a better trajectory, despite this vulnerability.

Aging Couples: Benefits and Costs of Long Intimate RelationsClick to view larger

Figure 1. Conceptual framework for interrelated fluctuations of individuals contributing to health and well-being trajectories in couples, adapted from Nesselroade (1991) and Gerstorf et al. (2014). Each partner has his or her own daily fluctuations that are part of a daily couple dynamic, which in turn shapes the interrelated trajectory of the couple (black lines). Each unique partner also has his or her own unique trajectory beyond the couple (light grey lines). The solid lines depict individual and couple macro-time changes, while the dotted lines connect the zoomed-in micro-time “bubbles” to their respective points on the macro-timelines. Individual trajectories shape the direction of the couple trajectory, which in turn brings the individual either up or down through time.

Dyadic measurement-burst designs are special because they include the intraindividual fluctuations of two related individuals who may or may not be systematically linked (e.g., Hoppmann & Gerstorf, 2013), which in turn end up shaping longer-term outcomes at both the individual and couple levels. Intraindividual variability concepts involve couple-level phenomena such as synchrony, reactivity, and coregulation (Butler, 2015) and acknowledge that such phenomena both influence and are influenced by individual-level processes and can contribute to relationship functioning (Randall & Schoebi, 2015). Importantly, whether any dyadic associations in within-person fluctuations are beneficial or costly to the individual or the unit often depends on the time frame in question. For example, conflict avoidance limits negative affective responses in the moment, but they also can foreshadow future relationship issues (DeLongis & Zwicker, 2017; Gottman & Levenson, 2002). There may also be times when what benefits one partner may come at the cost of the other, or what helps the couple may involve costs for one of the individuals—but one or both partners may still be willing and motivated to make such investments because they might contribute to favorable aging outcomes down the road. Harking back to our hypothetical couple, it may be difficult for Linda to adjust her schedule to drive Bill to his appointments, and it may also be difficult for him to accept her support, but there is also an opportunity for both of them to coordinate in a way that makes them resilient and better able to successfully manage future challenges.

Of note, Figure 1 could be further extended to also take into consideration other important conceptualizations of time, such as the accumulation of pathology (Fauth, Gerstorf, Ram, & Malmberg, 2012, 2014), time to death (Gerstorf, Ram, Lindenberger, & Smith, 2013), and historical time (cohort-specific experiences; e.g., Badley, Canizares, Perruccio, Hogg-Johnson, & Gignac, 2015; Masarik et al., 2016), as well as notions related to whether something happens “on time” or “off time” (e.g., the social clock; Neugarten, 1979) relative to a couple’s position in life. Age itself has important implications for how one’s life is structured regarding interactions with others (Settersten, 2003). Again, consider the case of Linda and Bill, who are dealing with Bill’s stroke. Challenging as it may already be, their story would be completely different if Bill had had his stroke “off time” in his early forties, a generation ago, when there were fewer resources available for stroke management, or if his health already had been so poor that the stroke would have resulted in accelerated decline. At 75 years old, his stroke was terrifying for the entire family, but possibly less devastating than if it had occurred under different life circumstances. Taken together, a social-contextual approach to aging provides insights into the social dynamics that occur between partners, and it points to the everyday processes that can help unravel how and why they accumulate over time to set partners on better or worse individual and joint aging trajectories.

Long-Term Trajectories and Daily Life Processes in Aging Couples

This section focuses on a sample of everyday processes (e.g., emotion, health behaviors, cognition) and how they shape the path to longer-term aging outcomes in couples. The literature on aging couples is based on multiple methodological approaches that are not always well integrated. For example, there is accumulating evidence from long-term longitudinal studies that individual trajectories in a number of different life domains (e.g., cognition, depressive symptomology, happiness) influence and are influenced by spousal relationships (Gruber-Baldini, Schaie, & Willis, 1995; Kouros, Papp, & Cummings, 2008; Gerstorf, Hoppmann, Kadlec, & McArdle, 2009; Hoppmann, Gerstorf, Willis, & Schaie, 2011; Polenick, Brooks, & Birditt, 2017). There is also a growing body of couples studies using repeated daily-life assessments from both partners to address the social dynamics and everyday mechanisms that characterize marriage (Hülür et al., 2016; Lüscher et al., 2015; Wagner, Voelke, Hoppmann, Luszcz, & Gerstorf, 2017; Wilson, Martire, & Sliwinski, 2017). The aim of this section is to understand the everyday processes that accumulate over time to shape longer-term outcomes.

This article provides a selective overview of empirical evidence using repeated daily-life assessments obtained in three distinct, yet interconnected domains of functioning: affect, health behaviors, and cognition. The respective sections are structured to address (a) the role of age, (b) the role of partners and dyadic mechanisms, and (c) dyadic gain/loss dynamics. Our compilation is meant to highlight the innovation and potential of repeated daily-life assessments from adult samples, and with couples where possible. It is also meant to illustrate the unique insights that such designs have for furthering our understanding of linked aging trajectories while acknowledging complementary study designs (e.g., experimental, longitudinal, cross-sectional).

Affective Dynamics in Couples

The Role of Age

Prominent aging models propose that older adults are better at regulating their emotions than young adults, in part due to future time perspective-related shifts in goals and priorities that optimize well-being (Carstensen, Fung, & Charles, 2003; Carstensen, Isaacowitz, & Charles, 1999). This may be particularly true when older adults draw on their past experience with overcoming stressors, but otherwise older adults seem to be just as vulnerable (or even more vulnerable) to stress than young adults because of age-related wear-and-tear in their biological stress systems (Charles, 2010).

Recent findings dovetail with this idea and show that older adults’ improved emotion regulation takes time, and that individuals across the adult lifespan are vulnerable to experiencing negative affect immediately after the occurrence of a stressor (Scott, Ram, Smyth, Almeida, & Sliwinski, 2017). Furthermore, older adults respond with less negative affect to an accumulation of stressors over a one-week period than younger adults, although like younger adults, they react with high negative affect to acute stressors (Schilling & Diehl, 2014). Taken together, older adulthood may be characterized by improved emotion regulation, but older adults still respond at least as strongly as young adults to acute stressors.

The Role of Partners and Dyadic Mechanisms

Emotions are not experienced in a social vacuum. Emotional experiences, particularly negative affect, can be contagious and spread across partners. For example, there may be crossover between the way that one spouse feels earlier in the day and how the partner feels subsequently (Larson & Almeida, 1999). Furthermore, individuals in close relationships have been shown to converge in their emotional experiences, expressions, and responses over time (Anderson, Keltner, & John, 2003). Time-varying modulations by the social context are paramount in understanding the everyday emotional dynamics in couples.

Taking a social-contextual approach to understanding emotional responses across the adult lifespan is particularly enlightening (Berg, Sewell, Hughes Lansing, Wilson, & Brewer, 2016). In many cases, the spouse can act as a first line of defense for coping with stressors (Berg & Upchurch, 2007). For example, responding with empathy buffers the impact of spousal depressive symptoms on disability and marital quality among rheumatoid arthritis patients (Stephenson, DeLongis, Esdaile, & Lehman, 2014). Furthermore, partners who characteristically share in each other’s soft affect (e.g., sad–depressed, upbeat–content) are also more likely to score higher in perspective taking, while crossover of hard affect (e.g., angry–calm) is more likely for those who have greater interpersonal insecurity (Schoebi, 2008). The connection between health outcomes and marriage may at least in part come from the affective processes within a couple and being attuned to one’s partner’s emotions (Slatcher & Schoebi, 2017).

Dyadic Gain/Loss Dynamics

In addition to such time-varying dyadic processes, stable, traitlike characteristics can drive the everyday emotional dynamics between partners. For example, we and others have shown that older adult partnerships characterized by high levels of support and collaboration are associated with tighter dyadic linkages in negative affect, but not positive affect, in everyday life (Berg, Wiebe, & Butner, 2011; Michalowski, Hoppmann, & Gerstorf, 2016). This points to an interesting gain–loss dynamic. Although spousal support has been associated with lower overall negative affect and higher overall positive affect, it also goes along with an increased likelihood of picking up negative affect from one’s partner (Michalowski et al., 2016). Sensitivity to negative stimuli is generally stronger than to positive stimuli (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001), but when it comes to gain–loss dynamics in couples, such findings suggest further nuance depending on timescale: although the individual is more vulnerable to the partner’s negative experience in the moment, perhaps the benefits of being in a positive relationship outweigh such costs. This raises important questions regarding the long-term consequences of affect covariation. Initial evidence from middle-aged couples shows that responding with positive affect to one’s partner’s positive affect decreases psychological distress one year later, whereas findings regarding susceptibility to partner negative affect are less clear (Randall & Schoebi, 2015). Hence, the everyday emotional dynamics in couples may have ramifications for longer-term outcomes.

Future research should consider the time frame in which relevant emotional processes occur—what is negative in a short slice of time may not necessarily be maladaptive down the road. For example, as Linda and Bill cope with the aftermath of Bill’s stroke, it is hard for Linda to see her partner suffer, but it is adaptive for both partners to understand how the other feels and to strengthen each other in their coping strategies. Not every couple will respond to challenges in the same way. Key couple-level differences affect how older adults respond when seeing their respective spouse suffer (Monin et al., 2010). Furthermore, personality differences and spousal matches in personality characteristics shape how couples respond to the problems in everyday life (Lay & Hoppmann, 2014; Roberts, Smith, Jackson, & Edmonds, 2009). Overall, the characteristic way that partners respond to each other’s emotional states forms patterned dynamics that differ by couple and circumstance, systematically shaping the path of their individual and joint aging trajectories.

Health Behavior Dynamics in Couples

The Role of Age

Health behaviors encompass both health-enhancing activities that can benefit health and be challenging to maintain (e.g., physical activity) and health-compromising activities that are harmful to health and difficult to quit (e.g., smoking; Taylor & Sirois, 2012). Importantly, health behaviors vary across days, and partners can bring each other up or down in small yet meaningful ways that ultimately may shift health and disease outcomes. Physical activity and smoking have been shown to be particularly susceptible to social-contextual factors (Lüscher, Berli, & Scholz, 2017).

Older adults are less likely than younger adults to regularly engage in physical activity (Sun, Norman, & While, 2013), and although more older adults are meeting physical activity guidelines in recent years as compared to two decades ago, it remains the case that less than half meet guidelines (Keadle, McKinnon, Graubard, & Troiano, 2016). On the flip side, older adults show the lowest rates of smoking across age groups (CDC, 2016; Statistics Canada, 2015). Smoking cessation earlier in adulthood translates into the highest gains in life expectancy, but individuals at any age experience health benefits from quitting, with individuals who quit even after a heart attack cutting in half their chances of having another heart attack (WHO, 2017b).

The Role of Partners and Dyadic Mechanisms

Physical activity and smoking showcase the potential of dyadic approaches to health behaviors in old age. Close others like spouses can promote both health-enhancing (e.g., joining the respective partner on a walk) and health-compromising (e.g., lighting a cigarette after dinner) behaviors (Lüscher et al., 2017). Daily process approaches have helped identify key underlying mechanisms that highlight what is helpful and what is less helpful in promoting healthy lifestyles in old age. There is solid evidence on the important role of spousal support for health outcomes (Stephens et al., 2009). Findings from daily diary research on middle-aged, dual-smoker couples during a quit attempt indicate that partners smoked less on days characterized by greater support provision and receipt than on days characterized by little support (Lüscher, Stadler, & Scholz, 2017).

Dyadic Gain/Loss Dynamics

Not all spousal behaviors work out as intended. For example, unsolicited support prompts unpleasant affect and can undermine self-esteem by communicating doubt about the recipient’s capability to cope on her or his own (Smith & Goodnow, 1999). Another example of the potentially double-edged nature of spousal contributions comes from the social control literature (Lewis & Rook, 1999). Health-related social control within marriage is an interdependent communal process with strategies that can range from coercive to persuasive (Lewis, Butterfield, Darbes, & Johnston-Brooks, 2004). Evidence from a sample of type II diabetes patients shows that spousal pressure and persuasion elicit both positive and negative emotions, but only persuasion effectively facilitates dietary change (August & Sorkin, 2010).

The dual-effects hypothesis suggests that health-related social control can be effective for changing health behaviors in a partner, but it also emphasizes that there may be costs to well-being (Hughes & Gove, 1981). Support for the latter notion comes from a sample of older adults recovering from knee osteoarthritis surgery, where both positive (e.g., motivating) and negative (e.g., pressuring) spousal control strategies had negative effects on patients’ well-being over time (Fekete, Stephens, Druley, & Greene, 2006). On the other hand, spousal control strategies involving pressure and persuasion were linked with better adherence to medical recommendations (including daily physical therapy and increased physical activity) in another sample of older adults after knee surgery, although pressure met with more negative emotions, and persuasion with more positive ones (Stephens et al., 2009).

Considering social control in the context of chronic illness, it has been shown that type II diabetes patients react with less resistance and hostility to spousal control when patients expect their spouses to be involved in illness management (Rook, August, Stephens, & Franks, 2011). Recalling our sample couple coping with life post stroke, Linda is trying to help Bill set up an exercise routine, but how Bill responds to such efforts depends on how he perceives her involvement and what his expectations are of Linda’s behavior toward him. Even though such efforts may be well intentioned, if not executed or perceived in a way that motivates the patient, they can hurt both partners and their relationship.

Future research needs to take such gain–loss dynamics seriously and search for a nuanced understanding of the interpersonal processes that affect everyday health behaviors in older couples, so as to better understand how well-intentioned spouses can translate their intentions into meaningful and positive health outcomes for the respective other. Considerations of the time-ordered couple support and control dynamics can further elucidate how spouses can achieve their health behavior goals together, rather than hindering each other or negatively affecting other domains of functioning.

Collaborative Cognition Dynamics in Couples

The Role of Age

Many of the processes that underlie daily emotion regulation and health behaviors in old age draw on cognitive resources, including planning, coping, and problem solving. Yet cognitive resources, especially fluid abilities such as working memory, decline with age (Baltes, 1997; Schaie, Willis, & Caskie, 2004). Research using repeated daily-life assessments of middle-aged and older people indicates that self-reported memory failures were less likely to occur on days when individuals engaged in increased physical activity (Whitbourne, Neupert, & Lachman, 2008), a health-promoting behavior. In addition, lapses in prospective memory have been related to same- and next-day increases in negative affect (Mogle, Muñoz, Hill, Smyth, & Sliwinski, 2017).

Furthermore, weeks characterized by many stressors relate to having more prospective memory lapses, but only for individuals with greater cognitive decline over the preceding 10 years (Rickenbach, Almeida, Seeman, & Lachman, 2014). Dovetailing with the time-sampling literature surrounding memory lapses, lower working memory in daily life is related to arousal (i.e., feeling nervous) in middle-aged and older adults, specifically when momentary heart rate is also high (Riediger et al., 2014). Taken together, cognitive processes in middle and older adulthood fluctuate in everyday life and often covary between partners, and potential pathways may lie within the realm of dynamic social contexts and dyadic mechanisms.

The Role of Partners and Dyadic Mechanisms

Given this evidence, there is a push toward combining experimental approaches and repeated daily-life assessments to provide a more thorough understanding of how older spouses may draw on each other’s support to accomplish together what may be difficult to do alone (Berg & Upchurch, 2007; Hoppmann & Gerstorf, 2016). Collaborative cognition involves cognitive processes unfolding within an interaction between individuals, but the specific characteristics of such interactions can take many shapes (Dixon, 1999). The pathways through which such characteristics are formed have been mainly explored in cross-sectional studies using lab settings.

Experimental cognitive collaboration paradigms point to the important role of partner familiarity for cognitive performance by demonstrating that familiarity reduces attentional load and increases task focus (Brennan & Enns, 2015). Collaboration can compensate for age-related decreases in fluid abilities (Rauers, Riediger, Schmiedek, & Lindenberger, 2011), and it is perceived as more satisfying when completed with a spouse rather than with an unfamiliar partner (Margrett & Marsiske, 2002). Hence, evidence using experimental paradigms points to partner familiarity as an important factor that may help older couples optimize their resources and improve cognitive outcomes, although how exactly such processes unfold over time would be enriched by intensive repeated within measures and longitudinal approaches.

Dyadic Gain/Loss Dynamics

Not all couples benefit from cognitive collaboration (Harris, Barnier, Sutton, Keil, & Dixon, 2017). Communication style and frequency have been linked with cognitive performance (Brennan & Enns, 2015; Margrett, Reese-Melancon, & Rendell, 2011). Furthermore, couples with high affiliative exchanges (e.g., cooperative and obliging conversations) tend to engage in superior problem solving compared to couples with low affiliative exchanges (Berg, Johnson, Meegan, & Strough, 2003). There are also circumstances under which collaboration can actually hamper cognitive performance, resulting in collaborative inhibition (Weldon & Bellinger, 1997) or retrieval disruption (Harris, Peterson, & Kemp, 2008). Hence, there are potential costs and benefits to collaborating with a significant other.

Aging Couples: Benefits and Costs of Long Intimate RelationsClick to view larger

Figure 2. Dynamics of emotion, health behaviors, and cognition represented as daily processes that are interrelated, but also exist within daily couple dynamics. These daily processes in turn accumulate to affect long-term health and well-being outcomes, which themselves are interrelated processes. Long-term outcomes are not necessarily end points. Daily processes will also differ, depending on current life circumstances.

Although there is promising time-sampling evidence on the temporal dynamics of cognitive processes in everyday life, and a significant body of experimental work that has explored mechanisms underlying collaborative cognition, future research would benefit from integrating the two methodologies. Time-sampling research combined with a dyadic experimental approach would be well suited to thoroughly answer questions such as how (going back to our hypothetical couple) Linda and Bill can optimize each other’s cognitive performance in their daily lives while avoiding bringing each other down, especially in the face of Bill’s stroke. Even more interesting would be to connect how such efforts could shape longer-term cognitive outcomes down the road.

Taken together, emotional, behavioral, and cognitive processes each unfold across micro–time frames, and each has the potential to influence long-term, macro–time frame aging outcomes. It is pivotal to recognize that these processes occur both within a given person and within a social relationship context (see Figure 2). The challenge for future research lies in the appreciation of the complexity of such interrelationships, not only regarding different domains of functioning within an individual but also with respect to the couple context. Ultimately, such considerations can further our understanding of how key social partners, such as spouses, can be harnessed to build favorable long-term aging trajectories.

Conclusion and Outlook

The main goal of this article was to describe key factors underlying interrelated aging trajectories in couples, the costs and benefits of these interrelations, and the importance of time as an element. Emotional experiences, health behaviors, and cognition were used to illustrate how couple dynamics unfold in daily life, ultimately influencing long-term outcomes. In pointing out the dynamic nature of such processes, the challenge put forth to the field is to push for better understanding of the mechanisms of how older couples may facilitate each other’s aging, both in an everyday-life context and in the long run. Several sets of factors are laid out next that future research should take into account to push forward such an understanding.

First, marriage is undoubtedly a significant relationship across the adult lifespan (Berg & Upchurch, 2007). A high-quality marriage can confer unique health benefits (Holt-Lunstad, Birmingham, & Jones, 2008). Much less is known though about the role of other close ties. For example, friendships are an important source of social support (Holt-Lunstad, 2017), and sibling bonds can last a lifetime (Cicirelli, 1982). Future research needs to disentangle if and how findings emanating from one close tie generalize to others.

Second, it is also important to recognize the increasingly heterogeneous nature of couple relationships (Copen, Daniels, Vespa, & Mosher, 2012; Statistics Canada, 2013). It is not a given that older couples are married, nor that they have been married for a long time (Statistics Canada, 2013). Furthermore, same-sex marriage is historically a recent accomplishment, and the circumstances of same-sex couples likely differ from the normative paths of heterosexual couples (Zdaniuk & Smith, 2016). As societal definitions of long-term intimate partnerships shift, so must conceptualizations in research on aging couples.

Third, it is important to recognize that marriage becomes fragile in middle and older adulthood due to increased morbidity and mortality risks. For example, taking on a caregiving role profoundly alters couple dynamics. The health risks associated with caregiving are well documented, but there may also be positive aspects to providing care for a loved one (Vitaliano, Zhang, & Scanlan, 2003; Zarit, 2012). Spousal death is a very potent stressor, but widows and widowers differ in psychosocial resources, leading to individual differences in health after bereavement (Boerner, Schulz, & Horowitz, 2004; Infurna & Luthar, 2017; Ong, Fuller-Rowell, & Bonanno, 2010). Widowhood research integrating multiple timescales (e.g., Pitzer & Bergeman, 2014; Carnelley, Wortman, Bolger, & Burke, 2006) has high potential to extend our understanding of widowhood.

Perhaps one of the most profound changes in partnerships over the past decades is the increased likelihood of divorce (Stevenson & Wolfers, 2007), which currently peaks in midlife, but the divorce rate for older adults has particularly risen with the number of aging baby boomers (Statistics Canada, 2013; U.S. Census Bureau, 2015). Divorce has long been recognized as detrimental to health (Rabkin & Struening, 1976; Manzoli, Villari, Pirone, & Boccia, 2007). However, remaining in a poor-quality marriage also has adverse effects on health (Holt-Lunstad, Birmingham, & Jones, 2008; Williams, 2003), and remarriage can involve complicated stepfamily dynamics (DeLongis & Zwicker, 2017).

Another exciting avenue for future research is the rise of new statistical tools that allow precise tests of important conceptual ideas (see Boker et al., 2011, for multilevel structural equation models, and Burkner, 2017, for multilevel Bayesian modeling). Beyond multilevel modeling approaches, Ferrer, Steele, and Hsieh (2012) developed an algorithm that identifies periods of stability and variability at both the individual and couple levels, particularly for the examination of affective dynamics in couples. Grid-sequence analysis models within-couple dynamics from within-day repeated assessments, which conceptually addresses questions concerning not only synchrony within couples, but also what is happening subsequently within a given person (Brinberg, Ram, Hülür, Brick, & Gerstorf, 2016). Modeling how dynamic short-term fluctuations are intertwined with long-term trajectories in long-term intimate relationships is complex, but it is certainly a conceptually rich undertaking.

One of the most challenging and long-standing directions for research concerning social relationships and development is the simultaneous inclusion of social context and relevant time scales. Theory development on relevant time frames and including multiple network members is needed to advance the field (Ram et al., 2014). Even when dynamic processes are considered on appropriate timescales, such processes are rarely integrated with social-contextual approaches, resulting in a somewhat disjointed literature on interpersonal dynamics (Butler, 2015). Processes within a social context do not unfold at a single point in time. The lifespan and most days do not occur independently from others.

Further, lifespan developmental models (e.g., Berg & Upchurch, 2007) offer an especially informative picture of social interrelationships that is not only useful for theory building, but also guides real-world interventions. Such research builds conceptual models that acknowledge the social context within which development unfolds. Similarly, policymakers and practitioners must also recognize that what works for a young single adult may not be effective for a middle-aged parent. For example, coping with chronic illness often requires lifestyle changes in daily life, and partners can be a resource if they are being recognized as key players in patient health.

Finally, even the most well-intentioned partner may not be able to help without the right tools. Developmental-contextual models inform what needs to go into such toolkits, so that clinicians and partners can support each other to facilitate patient recovery. It is also important to recognize that spousal dynamics are not ubiquitously positive, and a recognition of this fact will help distill effective strategies. Gains and losses are intertwined processes that shape the interdependence of couple developmental trajectories and represent a promising direction for future research (Kiecolt-Glaser & Wilson, 2017).

To close, the purpose of this article was to illustrate the value of considering time carefully and to highlight the importance of the spousal partner for shaping everyday patterns that accumulate into long-term trajectories. Focusing on time-sampling and longitudinal research, while recognizing the complementary insights gained from other methodologies, everyday dynamics and long-term outcomes were explored through a sample of factors that play out between partners: emotions, health behaviors, and cognition.

The next steps include a push toward better understanding how couple dynamics shape longer-term outcomes, to integrate repeated assessments on multiple time scales, and to use data sets that take the perspective of both partners into account. In other words, an integration of the dyadic with the dynamic is a promising route toward understanding and maximizing the potential of interrelations between partners across adulthood and old age.


Victoria Michalowski gratefully acknowledges support from the Social Sciences and Humanities Research Council. Christiane Hoppmann gratefully acknowledges the support of the Michael Smith Foundation for Health Research and the Canada Research Chairs Programme. Denis Gerstorf’s and Christiane Hoppmann’s work on this article was supported by the German Research Foundation (Grant GE 1896/3-1, GE 1896/6-1, and GE 1896/7-1).


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