Janice K. Kiecolt-Glaser, Institute for Behavioral Medicine Research, Department of Psychiatry and Behavioral Health, The Ohio State University College of Medicine, Columbus, OH, USA, ude.cmuso@resalG-tloceiK.ecinaJ;
Corresponding Author: Janice K. Kiecolt-Glaser, Institute for Behavioral Medicine Research, The Ohio State University College of Medicine, 460 Medical Center Drive, Columbus, OH 43210 USA, ude.cmuso@resalG-tloceiK.ecinaJ
The publisher's final edited version of this article is available at Annu Rev Clin PsycholThis review highlights recent advances in research addressing intimate partner relationships and health. Consideration of the strong mutual influences that the members of a couple have on each other's mental and physical health trajectories provides a new way to view the health implications of couples’ convergence or interdependence; marital closeness can have a clear downside when one partner has mental or physical health problems. Couples’ interconnectedness can also be leveraged to promote better treatment outcomes. Major themes addressed include the pivotal role of depression, as well as the importance of gender differences in the pathways from the marital relationship to physiological functioning and health. The health risks and benefits of support are weighed. Additionally, two prominent emerging paths from marital distress to poor health are emphasized: sleep problems, and metabolic alterations that promote obesity and its comorbidities.
Keywords: marriage, depression, convergence, interdependence, sleep, metabolismMarried people have better mental and physical health than unmarried people, on average (Kiecolt-Glaser and Newton, 2001, Robles et al., 2014). Morbidity and mortality are reliably lower for the married than the unmarried across a variety of acute and chronic conditions, including such diverse health threats as cancer, heart attacks, and surgery (Aizer et al., 2013, Neuman and Werner, 2015, Engstrom et al., 2006).
However, the simple presence of a spouse is not necessarily protective; a troubled marriage is itself a prime source of stress, and simultaneously limits the partner's ability to seek support in other relationships (Coyne and DeLongis, 1986). Indeed, the relationship between life satisfaction and marital quality is stronger than life satisfaction’s ties to either one's job or one’s health (Heller et al., 2004). Marital quality clearly colors one’s overall sense of well-being, and marital distress elevates health risks (Kiecolt-Glaser and Newton, 2001, Robles et al., 2014).
A recent meta-analysis reported that the relationships between marital quality and various health outcomes had effect sizes similar in magnitude to the reported effects of diet and exercise on clinical health endpoints (Robles et al., 2014). Although the number of studies for specific health problems limited the conclusions that could be drawn, a notable finding was the lower risk for mortality associated with better marital quality, with the largest relationships found in studies addressing chronic illnesses (Robles et al., 2014).
In this paper we highlight advances in research addressing intimate partner relationships and health. To complement and extend the extensive reviews that have documented marital discord's negative health consequences (Kiecolt-Glaser and Newton, 2001, Robles et al., 2014), we discuss how couples mutually influence each other's mental and physical health trajectories; we consider the health and treatment implications of couples’ convergence or interdependence in health behaviors as well as in their mental and physical health. We address marital functioning’s indirect influences on health outcomes through depression and health behaviors. Following up on major themes that we have addressed previously, we emphasize the importance of differentiating positive and negative dimensions of marital functioning, specifically examining the health risks and benefits of support, as well as gender differences in the pathways from the marital relationship to physiological functioning and health (Kiecolt-Glaser and Newton, 2001). We highlight two prominent emerging paths from marital distress to poor health: sleep problems, and metabolic alterations that promote obesity, metabolic syndrome, and diabetes. Additionally, we focus on evidence that more satisfying or closer marital relationships also increase health risks; marital closeness can have a clear downside when one spouse has mental or physical health problems.
Distressed marital relationships and depression often travel in tandem. Both syndromal depression and depressive symptoms are strongly associated with marital distress (Beach, 2014). The strength of the tie is sizable, e.g., one study found a 10-fold increase in risk for depressive symptomatology associated with marital discord (O'Leary et al., 1994); similarly, data from a large epidemiological study demonstrated that unhappy marriages were a potent risk factor for major depressive disorder for both men and women, associated with a 25-fold increase over untroubled marriages (Weissman, 1987). The relationship is bidirectional: distressed marriages enhance depressive symptoms, and depression promotes poorer marital quality (Beach, 2014). The stress generation model illustrates how this association emerges: depression contributes to marital discord, which enhances other stressors and serves to maintain or exacerbate symptoms (Foran et al., 2015).
The association of marital distress with depression has important implications for physical functioning. Depression alters multiple biological systems (e.g., endocrine, immune, cardiovascular, metabolic, neurocognitive), and these alterations are sufficient to enhance a variety of health threats, including premature mortality (Hughes et al., 2016, Jaremka et al., 2013). Depression promotes inflammation, one central pathway to poor health (Kiecolt-Glaser et al., 2015a). Heightened inflammation characterizes a number of disorders and systemic diseases including cardiovascular disease, diabetes, metabolic syndrome, rheumatoid arthritis, asthma, multiple sclerosis, chronic pain, and psoriasis; each of these also features an elevated risk for depression (Shelton and Miller, 2010, Slavich and Irwin, 2014). In addition to physiological alterations, depressed individuals are also more likely to have poorer health habits including a greater propensity for alcohol and drug abuse, inadequate sleep and nutrition, and less exercise, all of which have negative health influences in their own right (Kiecolt-Glaser et al., 2010).
Furthermore, depression can sensitize the inflammatory response, thus effectively promoting larger cytokine increases in response to stressors or pathogens (Glaser et al., 2003, Fagundes et al., 2013). Together, depression and stress contribute to a greater risk for infection, prolonged infectious episodes, and delayed wound healing; all processes that can fuel sustained proinflammatory cytokine production (Glaser and Kiecolt-Glaser, 2005).
By promoting depression and emotional stress responses, marital distress can effectively modulate secretion of proinflammatory cytokines both directly (via CNS/neural/endocrine/immune biobehavioral pathways), and indirectly, through behavioral changes. Through these pathways, depression and stressful marital experiences contribute to both acute and chronic proinflammatory cytokine production (Kiecolt-Glaser et al., 2005, Kiecolt-Glaser et al., 2003).
A growing literature addresses how couples mutually influence each other’s mental and physical health trajectories (Hoppmann et al., 2011a). As depicted in Figure 1 , couples' health and health behaviors are often similar and tend to converge over time (Leong et al., 2014). This occurs in part because of assortative mating: people typically choose a partner who is similar in terms of attitudes and demographics, as well as health-related behaviors like diet, physical activity, smoking, alcohol consumption, and BMI (Leong et al., 2014, Jackson et al., 2015). The shared resources hypothesis speculates that concordance may be a function of the fact that couples share a lifestyle as well as common stressors; spouses typically have a common living environment, they pool resources, they eat together, and they share a social network. Shared major and minor life events contribute to behavioral convergence. Spouses’ daily life activities are intertwined, and each partner's personal attributes--mood, attitudes, behavior, health, stresses, and lifestyle--affect both spouses. Thus, couples’ mutual influence can be beneficial or harmful to health behaviors and health (Meyler et al., 2007).
Conceptual framework summarizing the pathways by which partners’ health may converge over time. Partners influence each other’s health behaviors and eventual development of disease directly through interaction, emotion transmission, and shared behavior and experience. Partners’ level of closeness, their marital satisfaction, and age may modify their degree of convergence.
In accord with lifespan theories, the links between partners’ happiness trajectories across 35 years were substantially stronger than those observed in random pairs of women and men (Hoppmann et al., 2011b). Furthermore, spouses’ joint happiness explained much of the inter-individual differences in happiness.
Survey data from aging adults showed that wives’ and husbands’ quality of life traveled together over time; furthermore, each partner’s self-reported physical health and cognition predicted their spouses’ baseline quality of life, even after controlling for their own health and cognition (Bourassa et al., 2015b). In turn, better quality of life scores were related to longer-term health outcomes including better cardiovascular health, better sleep, and lower all-cause mortality (Bourassa et al., 2015b). Indeed, interdependence in couples' quality of life can persist even after a partner's death; among couples in which one spouse had died, the surviving partner’s later quality of life was associated with the deceased’s prior life quality (Bourassa et al., 2015a).
Researchers have documented strong spousal associations in exercise, smoking, alcohol consumption, and diet (Jackson et al., 2015). For example, a diary study showed that on days when spouses took more steps, osteoarthritis patients were more physically active as well (Martire et al., 2013b). Convergence on such key health behaviors has implications for other health indices; a systematic review reported positive spousal concordance for major coronary risk factors including diastolic blood pressure, triglycerides, total and low-density lipoprotein cholesterol, smoking, body mass index, and waist/hip ratio (Di Castelnuovo et al., 2009).
In addition, changes in one spouse’s behavior can prompt change in their partner. Couples in the English Longitudinal Study of Ageing, a population-based study of middle-aged and older adults in the United Kingdom, were more likely to stop smoking, increase physical activity, and lose 5% or more of their weight if their partner made the same positive change (Jackson et al., 2015). The impact on health behaviors can be substantial; longitudinal data show that when one spouse becomes obese, their partner’s risk for obesity almost doubles (Cobb et al., 2015). In fact, couples who live together for longer time periods become more similar in obesity-related behaviors, including low levels of physical activity and high rates of sedentary behavior (The and Gordon-Larsen, 2009).
Moreover, one spouse can benefit from an intervention delivered to their partner, a “ripple effect” (Gorin et al., 2008). For example, in a trial that evaluated how intentional weight loss affected cardiovascular outcomes in overweight people with type 2 diabetes, spouses of intervention group participants lost more weight than the partners of usual care condition participants, and the spouses’ weight loss was significantly correlated (Gorin et al., 2008). Similarly, husbands of women in the low-fat intervention arm of the Women’s Health Trial reduced their body fat and weight more than the husbands of control arm women (White et al., 1991).
Not surprisingly, spouses’ health behavior concordance can translate into disease risks (Monserud and Peek, 2014, Hoppmann et al., 2011a, Gerstorf et al., 2009). When one partner has a history of diabetes, spousal risk for diabetes is increased 26%; a spousal history of either diabetes or prediabetes confers a two-fold risk for the partner (Leong et al., 2014). When one spouse has metabolic syndrome, his or her spouse has roughly a 30% greater chance of also having metabolic syndrome (Kim et al., 2006). Among older Mexican American couples, a history of hypertension, arthritis, or cancer was associated with higher odds that the spouse would have the same condition. For example, having a partner with arthritis almost tripled the spouse's odds for arthritis (Stimpson and Peek, 2005). People whose partners have asthma, peptic ulcer disease, or depression have a 70% or greater increased risk themselves for these conditions, even after controlling for partners’ age, smoking, and obesity (Hippisley-Cox et al., 2002). Spouses of hypertensive patients have a two-fold increased risk of hypertension even when age, BMI, and diabetes are controlled (Hippisley-Cox and Pringle, 1998).
A large population-based, nested case-control study showed that the risk for developing physician-diagnosed hay fever was more than twice as great in people who lived with a partner with hay fever compared to people living with an unaffected partner. Furthermore, the longer the partners lived together, the greater the risk: compared to couples who had lived together for 1–11 years, the odds ratio for those who were together 12–23 years rose to 1.8, increasing to 7.4 for 24–35 years, and then rapidly escalating to 13.7 for those in the longest term relationships, 36–54 years (Schafer et al., 2004).
Married couples’ behavior patterns influence both spouses, a key assumption of interdependence theory, and one partner’s functioning can influence both spouses (Kelly and Thibaut, 1978). Crossover or spillover effects can arise in one partner following a spouse’s negative experience, particularly when one member of the couple is experiencing health problems (Bourassa et al., 2015b). In a diary study, patients diagnosed with both diabetes and osteoarthritis had heightened blood glucose problems and arthritis severity on days when their disease-free spouses reported worse physical symptoms (Yorgason et al., 2012). Relatedly, emotional transmission happens when a partner’s own personal experiences provoke emotional responses and behaviors, which, in turn, affect the spouse (Larson and Almeida, 1999). Indeed, both mood convergence and emotional contagion hypotheses suggest that the interdependence of life with a partner promotes shared emotions.
Marital contagion of depressive symptoms and distress has been extensively documented. Living with a depressed spouse clearly alters the partner's mood. Higher levels of depressive symptoms in one spouse are associated with higher levels of depressive symptoms in his or her partner; this reciprocal relationship has been a consistent theme throughout a number of studies. Furthermore, longitudinal studies suggest that increases in one partner's depressive symptoms over time are associated with increments in the spouse's symptoms (Pruchno et al., 2009, Monin et al., 2016). Diary studies suggest that negative and high-arousal emotions are particularly contagious between partners (Schoebi, 2008, Saxbe and Repetti, 2010).
Major and minor life events that happen to one spouse can influence the mental health of both partners; for example, research has confirmed convergence following such health events as a cancer diagnosis and treatment, cardiomyopathy, heart failure, coronary heart disease, erectile dysfunction, and infertility, as well as nonhealth events like job loss (Meyler et al., 2007). Data from both cross-sectional and longitudinal studies show that depressive symptoms among older adults experiencing vision loss (Strawbridge et al., 2007), prostate cancer (Berg et al., 2011), and arthritis (Stephenson et al., 2014) are also experienced by their spouse. Lung cancer patients’ declining physical function predicted increases in spouse depressive symptoms over one year (Lyons et al., 2014). Similarly, longitudinal data from the National Survey of Families and Households addressed the effects of a spouse's illness on depressive symptoms in middle-aged and older married adults. People whose spouse had become ill or stayed ill because of a chronic disease or physical disability reported higher levels of depressive symptoms at the 10 year follow-up; in contrast, depressive symptoms were lower at follow-up than at baseline among those whose spouses’ health improved (Bookwala, 2014).
Depressive symptoms and the ability to perform activities of daily living have reciprocal influences on each other among older adults; functional limitations increase risk for depression, and depression increases the risk for functional limitations (Hoppmann et al., 2011a). For example, frailty, characterized by weakness, slowness, and exhaustion, presages elevated risks for depression, disability, falls, hospitalization, and early mortality (Monin et al., 2016). Over time, people’s depression predicted their own later frailty, and frailty predicted subsequent depression (Monin et al., 2016). In couples, frailty in one spouse predicted frailty in their partner; moreover, higher levels of depressive symptoms in one spouse predicted greater depressive symptoms in the partner (Monin et al., 2016). Similarly, longitudinal data from older Mexican American couples showed that functional limitations in one spouse were linked with higher levels of depressive symptoms in their partner (Monserud and Peek, 2014). Mechanistically, both depression and frailty have inflammatory correlates, and chronic inflammation has been suggested as one key biological mechanism that may fuel declines in physical function that lead to frailty, disability, and, ultimately, death (Ershler and Keller, 2000).
Self-rated health -- how healthy one feels -- predicts physical disability, inflammation, and mortality (Pruchno et al., 2009, Christian et al., 2011). In a longitudinal study of self-rated health and depressive symptoms in patients with end-stage renal disease, changes in the patient's self-rated health increased the spouse's depressive symptoms, and these effects were greater for the spouse than changes in his or her own self-rated health (Pruchno et al., 2009).
Surprisingly, little of the research has addressed how either marital satisfaction or relationship closeness impacts convergence-related risk. The limited data described below speak to their importance.
Marital satisfaction moderates the dynamic links between partners’ health. The health of people in higher-quality marriages may be at greater risk when their partner is suffering (Hoppmann and Gerstorf, 2009). In longitudinal data from community-dwelling older couples, husbands’ cognitive impairment was associated with subsequent poorer health and well-being among their wives, but only for the 52% of wives who reported few or no marital problems (Strawbridge et al., 2009). Global marital satisfaction may serve as an interpretive backdrop, altering the partner’s appraisals of the impaired spouse’s behaviors, and thereby their functional significance for the partner’s health (Turk et al., 1992).
Marital satisfaction is moderately correlated with relationship closeness (Aron et al., 1992), another important relational dimension that may alter spillover and health convergence. Closer relationships may involve greater involvement in the spouse's daily activities compared to relationships that are not as close. Also, feeling close to one’s partner can promote more empathic responding as well as greater contagion of negative affect (Berg et al., 2008, Cialdini et al., 1997); consequently, adverse health changes in one spouse may have a particularly strong impact on close partners. For example, in a sample of osteoarthritis patients and their spouses, greater knee pain during the day predicted partner’s poorer sleep quality that night, and these effects were strongest among couples in closer relationships (Martire et al., 2013a). Other data from this cohort showed that greater relationship closeness exacerbated the impact of increased patient illness severity on their partner’s positive affect and depressive symptoms over six months (Polenick et al., 2015), consistent with previous studies that showed stronger transmission of depressive symptoms in closer couples (Tower and Kasl, 1995, Tower and Kasl, 1996).
Exposure to a partner’s disease-related pain can function as a potent stressor, influencing the spouse’s physical and psychological health (Schulz et al., 2009). For example, spouses were adversely affected by witnessing their partner’s pain; the spouse’s blood pressure increased more in response to arthritis patient’s suffering than to a stranger’s pain (Monin et al., 2010).
These studies illustrate how even close and satisfying relationships can have a clear downside, because the very fact that spouses are close and happy means that one spouse's mental or physical health problems are more likely to impact their partner, perhaps through more time spent together, greater willingness to engage the ill spouse despite stressors, and more intimate emotional connection to the ill spouse’s suffering. Among prostate cancer patients and their wives, negative affect was heightened when couples had managed daily stressors together, which underscores the risk of negative emotion transmission when both partners are closely involved (Berg et al., 2011). The closer the relationship, the greater the potential loss, and the greater the risk for the unimpaired partner’s mental and physical health.
Older adults are at greatest risk when a spouse is ill for several reasons. Older adults typically put more time and energy into close personal relationships rather than broader social networks (Charles and Carstensen, 2010), and thus partner functioning would have a greater impact than among younger people. Among older couples, social-activity trajectories are interrelated, strengthened by the partner's cognitive, physical, and affective resources (Hoppmann et al., 2008). Concordance is likely to be greater in longer-term marriages; couples have learned to function as a team throughout their history of joint experiences (Gerstorf et al., 2009). Compared to younger adults, older adults' marriages are typically closer (Hoppmann and Gerstorf, 2009). Older couples in longer-term marriages have survived many challenges, they have a long history of shared experiences and joint roles such as parenthood through their decades together (Hoppmann and Gerstorf, 2009). This interdependence can be problematic when adverse changes arise for one partner (Gerstorf et al., 2009). Greater spousal closeness in the face of one partner’s health crisis may thus spread poorer health, particularly among older couples.
Certainly, the pathways linking marital processes to health are complex. While partners may expose each other to health risks via shared health behaviors and emotion transmission, they may also influence health outcomes by exchanging support.
Supportive behaviors of one spouse may lessen symptoms in their partner; for example, greater satisfaction with the partner's behavior was related to lower pain ratings in arthritis patients (Holtzman and Delongis, 2007). Arthritis patients whose partners had more confidence in their illness management improved more in their physical function, disease severity, and activity levels compared to those with less confident spouses, in part through changes in partner responses to patient pain (Hemphill et al., 2016, Gere et al., 2014).
On the other hand, support that inadvertently undermines independence and self-efficacy to maintain healthy behaviors can have poor health consequences. For example, male osteoarthritis patients reduced their physical activity on days when wives pressured them to be more active (Martire et al., 2013b). Also, patients who received more unwanted spouse support reported worse arthritis management (Martire et al., 2002). Support delivered in a critical, controlling, or coercive way can also have negative results: a diary study found that on days when spouses used coercion in the absence of encouragement Type 2 diabetes patients were less physically active (Khan et al., 2013).
In addition to influencing health behaviors, partner support may directly alter physiological reactivity to stressors. For instance, people who received more encouragement and validation from their partner after a stressor experienced faster reductions in cortisol levels than those who were met with less sensitive and more hostile responses (Meuwly et al., 2012). In a neuroimaging study, neural reactions to a painful stimulus were less pronounced when participants held their spouse’s hand instead of a stranger’s, and maritally satisfied people reacted even less than dissatisfied participants (Coan et al., 2006).
Beyond the effects of discrete support behaviors, perceiving one’s spouse as generally responsive may confer health benefits. Perceived partner responsiveness--the extent to which people feel that their partner understands, cares for, and validates them—has emerged as a predictor of health in recent studies. For example, higher mortality rates were associated with more received partner emotional support among those who described their partner as low on responsiveness (Selcuk and Ong, 2013). However, having a partner described as very responsive protected people from the mortality risk associated with higher received partner support. Likewise, in a representative sample of 1078 married or cohabiting adults, greater perceived partner responsiveness at baseline was related to higher awakening cortisol and steeper diurnal cortisol slopes 10 years later, but not total cortisol production (Slatcher et al., 2015). However, a prospective study of osteoarthritis patients found that perceived partner responsiveness did not explain improvements in post-surgical knee recovery associated with partner support (Khan et al., 2009). Understanding the interplay of support behaviors and the general impressions that shape their interpretation represents a promising avenue for future work.
Spouses’ response to positive events, or capitalization support, should also be further examined as a candidate mechanism of marriage’s health effects. Among romantic partners in a lab study, partners’ supportive responses increased positive emotions and facial expressions but not skin conductance responses (Monfort et al., 2014). Future studies might expand the range of physiological outcomes to determine the scope of capitalization’s effects.
We have focused on depression as a key pathway between marital distress and health. In this context, the consistent finding that women have higher rates of depression than men has multiple implications for marriage-related health outcomes. As described earlier, depression has close ties to inflammation (Kiecolt-Glaser et al., 2015a); this link may be particularly relevant for women for several reasons. First, inflammation-induced mood and behavior changes appear to be more prominent among women than men. For example, women respond to transient elevations in inflammation with stronger feelings of loneliness and social disconnection than men, a characteristic that likely contributes to the 2:1 ratio of women to men in depressive disorders (Moieni et al., 2015). Additionally, prior depression, somatic symptomatology, interpersonal stressors, childhood adversity, obesity, and physical inactivity are all factors that elevate inflammation, and women have disproportionately higher representation than men in each of these domains (Derry et al., 2015). Relationship-related distress has stronger ties to inflammation among women than men (Derry et al., 2015), and the relationship between depression and marital quality is stronger among women than men (Whisman, 2001). Accordingly, there are multiple reasons to believe that these gender-related differences in depression lead to greater health risks for women than for men in marriage.
Some evidence suggests that husbands' cognitive functioning can predict changes in wives' cognition, but not the reverse (Gerstorf et al., 2009, Strawbridge et al., 2009). One hypothesis used to explain this unidirectional effect suggests that the increasing time demands that would lead the wife to curtail social and other activities that provide cognitive stimulation in favor of more time at home (Gerstorf et al., 2009).
Auditory and visual impairments become increasingly prevalent with age. Hearing impairments in one spouse also affect the partner's health and well-being. As with cognitive functioning, wives were more negatively affected by their husbands' hearing loss than vice versa (Wallhagen et al., 2004).
Vision impairments can lead to poor problems in communication, as well as broader difficulties with psychosocial functioning (Strawbridge et al., 2007). In longitudinal data with older adults from the Alameda County Study, impaired vision in one spouse adversely impacted his or her own depression, physical functioning, and well-being, and the partner’s data showed negative changes on these same dimensions. After adjusting for the impact of one's own visual impairment, the spousal consequences for physical functioning, depression, and well-being were greater among wives than husbands (Strawbridge et al., 2007).
Within the dementia caregiving literature, spousal caregivers’ stress has been well-documented. Women suffer greater adverse effects when caregiving for a husband with dementia than men experience when they become caregivers (Hagedoorn et al., 2001). Although such intensive caregiving substantially increases health risks (Glaser and Kiecolt-Glaser, 2005), the data reviewed above suggest that even nondisabling conditions can raise the stakes.
A meta-analysis of distress in couples coping with cancer reported a moderate correlation of .29 between patients and partners. Nonetheless, regardless of whether they were the person with cancer or the person’s partner, women consistently reported greater distress than men (Hagedoorn et al., 2008).
Husbands' high blood pressure and stroke history were related to higher levels of depressive symptoms among their wives; however wives' health problems were not related to husbands' depressive symptoms (Ayotte et al., 2010).
Similarly, among a community-based sample of 995 older couples in which neither, one, or both partners had a chronic disease, women’s psychological distress was linked with both her own and her husband’s condition, whereas men’s distress was only related to his own health (Hagedoorn et al., 2001). Moreover, despite the fact that male patients reported fewer physical problems than female patients, the husband’s health status augmented wives’ distress, but wives’ health problems did not increase husbands’ distress.
Individuals with chronic pain often rate their pain and disability differently than their partner. Women’s perceptions of their husbands' thoughts and feelings better matched husbands’ responses compared to husbands' ratings of wives' thoughts and feelings (Cano et al., 2005).
These findings echo the gender differences we have highlighted previously (Kiecolt-Glaser and Newton, 2001). As discussed elsewhere, past studies show that wives respond more to the husband’s chronic illness than vice versa, and this greater influence means that wives are also more likely to be affected (Berg and Upchurch, 2007). However, the origin of this gender-based vulnerability is unclear; this area of research must continue to be reevaluated as new cohorts of couples marry and divorce, and as the demographic face of marriage evolves (Amato et al., 2007, Cherlin, 2010).
