Abstract Objectives Sleep problems increase in later life. Studies have linked sleep with marital satisfaction, yet mechanisms, such as mood, have not been explored. The current study is innovative in examining sleep and marital interactions among older couples in a daily context, exploring mood as a potential mediator. Method Data were taken from the Life and Family Legacies Daily Experiences Study, involving 191 older couples surveyed across 14 days. Multivariate (dyadic) multilevel models were used to address our research questions. Results Findings indicated significant associations between daily sleep hours, sleep quality, and feeling rested with daily marital interactions. These associations were most consistent for wives. Mediation analyses indicated that positive mood was a common mechanism linking sleep with marital interactions. Also, in some cases, spouse sleep and mood reports were associated with partner marital interactions. Discussion Improving sleep quality among older couples could lead to better daily marital interactions through changes in mood. Affect, Daily diary, Marriage, Sleep It is estimated that more than one third of Americans experience unhealthy sleep (Seixas et al., 2015). Sleep deprivation is linked with various negative cognitive, biological, and relational outcomes (Acheson, Richards, & de Wit, 2007; Hori et al., 2011; Kahn-Greene, Lipizzi, Conrad, Kamimori, & Killgore, 2006). Adults tend to report changes in sleep patterns as they age, and aging is linked with higher prevalence rates of insomnia, and to lower sleep time, efficiency, quality, and night-to-night consistency (Moraes et al., 2014; Nau, McCrae, Cook, & Lichstein, 2005; Neikrug & Ancoli-Israel, 2010). It may be that such aging-related sleep changes impact marital interactions. Among married couples, sleep is an important correlate of marital quality (Chen, Waite, & Lauderdale, 2015; Strawbridge, Shema, & Roberts, 2004). Various assessments of sleep quality, disturbances, disorders, and spousal sleep pattern congruence have been linked to marital interactions (Hasler & Troxel, 2010; Rauer & El-Sheikh, 2012; Strawbridge et al., 2004). Most recently, Gordon and Chen (2014) found that conflict in a romantic relationship increased on days following a poor night’s sleep. They also found that couples more often resolved conflicts when they reported feeling well rested. Although associations between sleep and marital quality have been established, few studies have examined the mechanisms involved when sleep problems affect marital interactions. Mood may act as a mechanism to explain the association between sleep and marital quality, given that poor sleep quality has been related to emotional distress (Acheson et al., 2007) and that emotional distress has been linked with subsequent marital quality (Pruchno, Wilson-Genderson, & Cartwright, 2009). The current study addresses these associations using daily diary survey data from 191 older couples across 14 days. Background The Model of Dynamic Association Between Relationship Functioning and Sleep that was developed by Troxel, Robles, Hall, and Buysse (2007) presents a bio/psycho/social model that helps to explain links between sleep, mood, and marital interactions. The model provides a holistic framework in which to examine marital interactions and sleep by considering contextual factors that could influence associations including psychopathology, personality, socioeconomic/occupational factors, stressful life events, and gender. Specifically, the associations between relationship functioning and sleep occur through a series of chronobiological, behavioral, psychological, and physiological pathways that are bidirectional (see Hasler & Troxel, 2010; Troxel et al., 2007). Consistent with the Relational Functioning and Sleep model, recent evidence identifies reciprocal pathways to and from sleep. Although there is evidence that, at times, marital quality may predict sleep (Chen et al., 2015), there may also be times when sleep problems are not brought on by marital distress, but then impact later marital interactions (Gordon & Chen, 2014). We leverage the design of a daily diary study to focus on one direction of these relationships: the relationship between sleep predicting relationship functioning among married couples, with mood representing a psychological pathway through which sleep may affect relationship interactions. We also consider gender within marriage as a contextual factor, using both actor pathways (e.g., wife sleep predicting her own mood and her own assessment of marital interactions), as well as partner pathways (e.g., wife sleep predicting her own mood and her husband’s assessment of marital interactions). Although not our central focus, we also test an alternative model, with mood and marital interactions predicting sleep. Sleep, Marital Quality, and Mood Few studies have addressed joint links between sleep, mood, and marital quality. Examining literature for each bivariate association among these three constructs provides support for linking the three. Regarding sleep and marital quality, studies have consistently identified sleep as an important predictor of marital outcomes (e.g., Gordon & Chen, 2014). Strawbridge and colleagues (2004) found in 405 older adult couples that a one-point increase in self-reported sleep problems correlated with a 12% and 15% increase, respectively, in individual and spousal measures of marital unhappiness. Similarly, Hasler and Troxel (2010) explored associations between couples’ nighttime sleep efficiency and daytime relationship functioning. They found that in men, higher sleep efficiency predicted less negative partner interaction during the next day, and for women, lower sleep onset concordance or wrist actigraphy measures predicted fewer positive and more negative partner interactions. Other studies indicate that formal sleep disorders (e.g., obstructive sleep apnea) correlate negatively with marital quality (Cartwright & Knight, 1987); and variations in sleep time and sleep disruptions accompanying the transition to parenthood are also linked with decreased marital satisfaction (Insana, Costello, & Montgomery-downs, 2011). Finally, research demonstrated that sleep disturbances were related to more intimate partner violence (IPV) and that more IPV predicts greater sleep disturbances (Rauer & El-Sheikh, 2012). Research suggests a consistent link between sleep and marital quality, although less is known about why or how sleep is linked with marriage. Mood may account for the association between sleep and marital interactions, as poor sleep may affect mood in important ways. At its extremity, sleep deprivation and/or its disturbance has been shown to positively relate to the development of pervasive mood disorders such as depression (Baglioni et al., 2011). For example, Roberts, Shema, Kaplan, and Strawbridge (2000) found in a prospective analysis that sleep disturbances were specifically correlated with later depression in older adults (>50 years old) and also predicted future major depression. Evidence from multiple neurobiological studies implicate the brain’s serontological system as the primary neurological control pathway that, when disrupted, is linked to the development of depression (Cryan & Leonard, 2000; Stockmeier, 2003). Accordingly, Roman, Walstra, Luiten, and Meerlo (2005) explored the effects of sleep restriction on mammalian serotonergic sensitivity, reporting that chronic partial sleep deprivation in rats resulted in a significant decrease in serotonin-1A receptor sensitivity after 8 days. These data suggest that in a relatively short period of time, mood states have the potential to undergo substantive physiologic changes in response to sleep disturbance. In 2005, Haack and Mullington used a daily assessment approach to evaluate sleep deprivation and mood directly, demonstrating a significant, progressive decline in positive affective states (i.e., optimism, happiness, etc.) in bihourly surveys over 16 days. Given sleep’s relationship to both macro changes in mood states and the development of mood disorders it follows that variation in a night’s sleep may also be significantly associated with daily mood states on the next day. To link sleep with marital interactions, mood would need to be associated independently with marital processes. Studies related to health have associated mood with marital satisfaction, in one direction or the other (Choi & Marks, 2008; Pruchno et al., 2009; Yorgason, Booth, & Johnson, 2008; Yorgason, Almeida, Neupert, Spiro, & Hoffman, 2006). Specifically, Pruchno and colleagues (2009) found that individual and partner depression symptoms were linked to marital satisfaction of both partners among a sample of 315 couples wherein one spouse had end stage renal disease. Other studies give evidence that mood and marriage are linked by examining both partners’ mood in the context of marriage (Burr, Hubler, Larzelere, & Gardner, 2013) and mood as an outcome of marital arguments (Almeida, McGonagle, Cate, Kessler, & Wethington, 2002). A primary focus of the current study is to examine ways daily fluctuations in mood relate to daily marital outcomes among older adult couples. Current Study The current study addresses an important gap in research literature by examining novel aspects of relationships between sleep, mood, and marital interactions for husbands and wives. If sleep is predictive of marital interactions, then couples could be aware of increased relationship needs after a poor night’s sleep. Where links between sleep and marital interactions are accounted for by mood, increased regulation of emotional processes (Monin, 2016) may buffer effects of poor sleep. Drawing on trends from prior studies (Hasler & Troxel, 2010; Strawbridge et al., 2004), we use data from both partners to address both self-reports (actor effects) and partner reports (partner effects) of sleep on individual and spousal marital outcomes. Examining dyadic associations expands the Relationship Functioning and Sleep model (Troxel et al., 2007) by addressing within- and between-person nuances of psychological pathways linking sleep with relationships. Because husbands and wives often report different experiences with regard to daily mood (Almeida & Kessler, 1998) and marriage relationships (Boerner, Jopp, Carr, Sosinsky, & Kim, 2014), we examine effects for both husbands and wives. Also, data come from a sample of older couples that report on sleep, mood, and marital interactions for 14 consecutive days, providing a micro snapshot of daily older couple experiences. Based on prior research, we hypothesized that (a) increases in daily reports of hours slept, sleep quality, and feeling rested would be related to higher daily positive and lower daily negative marital events and to higher daily marital satisfaction, (b) daily positive mood would be associated with better daily marital outcomes, and daily negative mood would be associated with poorer daily marital outcomes, (c) the sleep to marital outcome associations would be mediated by reports of positive and negative mood, and (d) individual reports of sleep and mood would be linked with partner reports of marital outcomes. Data and Methods Sample Participants were taken from the Life and Family Legacies Daily Experiences Study (DES), which comprises a smaller part of the Life and Family Legacies Study, a longitudinal examination of 6,729 individuals that began in 1966 with high school students (Call, Otto, & Spenner, 1982). Follow-up surveys were conducted with the same sample in 1980 and again in 2010. The daily experiences sample targeted married couples and was stratified by health (good vs poor), urban/rural status, and veteran (vs nonveteran) status. From the larger study, 1,928 participants had responded in 2010 who were eligible for the daily experiences study based on being married, living in the United States, and having full data on stratification variables. From this group, 559 participants with valid addresses were randomly identified to be recruited into the study. Surveys from 191 heterosexual couples wherein both spouses participated (382 individuals) were completed across 14 days (drawing a response rate of 34%). One same-sex couple was excluded from the current analysis due to the research questions and analysis involving distinguishable dyads (Olsen & Kenny, 2006). Couple surveys were matched by day for 5,196 surveys, with the average number of survey days per respondent being 13.6. Respondents participated via U.S. mail and were compensated $30 for each spouse who completed the study. Courtesy reminder phone calls were made to the couples each night of the study (14 nights) to encourage compliance with survey instructions and answer participants’ questions. Participants were instructed to not discuss their answers with their spouse until the study was completed and to seal each survey in a provided daily envelope. Approval for the study was obtained from the appropriate human subjects institutional review board. Respondents to the DES ranged in age from 60 to 64 years (mean = 62.43, SD = 0.74). Age of spouses was not assessed. The average education level in the sample was 3 years of college (15% of the sample had only a high school education and 28% had graduate training). The average income of the sample was between $80,000 and $89,000/year (SD = $43,000). Fifty-eight percent of the sample were in their first marriage. All DES participants were Caucasian, reflecting the larger sample from which respondents were drawn. Table 1 includes descriptive statistics, mean difference tests across gender, and correlations between the main study variables. Table 1. Correlations and Descriptive Properties of Study Variables (N = 382 Individuals from 191 Couples) Variables 1 2 3 4 5 6 7 8 1. Sleep duration .20* .11*** .29*** .11*** −.07*** .07*** .02 .05** 2. Sleep quality .06** .11 .18*** .11*** −.04* .02 −.04* .04* 3. Feeling rested .21*** .23*** .22** .44*** −.28*** .20*** −.10*** .26*** 4. Positive mood −.02 .13*** .40*** .30*** −.43*** .34*** −.14*** .31*** 5. Negative mood .04* −.08*** −.19*** −.28*** .11 −.11*** .28*** −.20*** 6. Positive marital events .01 .06** .14*** .43*** −.11*** .55*** −.25*** .61*** 7. Negative marital events .02 −.01 −.03 −.15*** .22*** −.21*** .21* −.34*** 8. Daily marital satisfaction .01 .13*** .25*** .40*** −.19*** .48*** −.33*** .49*** Husband M (SD) 7.47 (1.54) 1.98 (0.89) 3.73 (1.30) 8.17 (3.99) 1.32 (2.18) 3.70 (2.29) 0.28 (0.59) 4.39 (1.22) Wife M (SD) 7.65 (1.43) 1.93 (0.91) 3.76 (1.43) 8.69 (4.04) 1.69 (2.62) 3.85 (2.30) 0.27 (0.57) 4.38 (1.27) t Values 4.69*** −2.00* 1.02 5.55*** 5.68*** 3.33*** −0.92 −0.71 Variables 1 2 3 4 5 6 7 8 1. Sleep duration .20* .11*** .29*** .11*** −.07*** .07*** .02 .05** 2. Sleep quality .06** .11 .18*** .11*** −.04* .02 −.04* .04* 3. Feeling rested .21*** .23*** .22** .44*** −.28*** .20*** −.10*** .26*** 4. Positive mood −.02 .13*** .40*** .30*** −.43*** .34*** −.14*** .31*** 5. Negative mood .04* −.08*** −.19*** −.28*** .11 −.11*** .28*** −.20*** 6. Positive marital events .01 .06** .14*** .43*** −.11*** .55*** −.25*** .61*** 7. Negative marital events .02 −.01 −.03 −.15*** .22*** −.21*** .21* −.34*** 8. Daily marital satisfaction .01 .13*** .25*** .40*** −.19*** .48*** −.33*** .49*** Husband M (SD) 7.47 (1.54) 1.98 (0.89) 3.73 (1.30) 8.17 (3.99) 1.32 (2.18) 3.70 (2.29) 0.28 (0.59) 4.39 (1.22) Wife M (SD) 7.65 (1.43) 1.93 (0.91) 3.76 (1.43) 8.69 (4.04) 1.69 (2.62) 3.85 (2.30) 0.27 (0.57) 4.38 (1.27) t Values 4.69*** −2.00* 1.02 5.55*** 5.68*** 3.33*** −0.92 −0.71 Notes: Wife correlations above diagonal, husband correlations below the diagonal, and husband–wife correlations on the diagonal (bolded). t values based on husband/wife paired sample t tests (df not shown). *p ≤ .05. **p ≤ .01. ***p ≤ .001. View Large Predictor Measures Feeling rested was reported by respondents each day of the survey (Penrod et al., 2007). Responses ranged from 0 (not at all) to 6 (extremely). Sleep duration was assessed by participants indicating the number of hours slept in the last 24-hour period (rounded to the nearest whole number). Quality of sleep was assessed by respondents rating how well they slept the previous night. Responses ranged from 0 (not well at all) to 4 (extremely well). Positive and negative mood were assessed using the Thomas and Diener (1990) scale of positive and negative emotions. Respondents reported daily on how strongly they experienced four positive mood states (happy, joyful, pleased, and enjoyment/fun) and five negative mood states (depressed/blue, unhappy, frustrated, angry/hostile, and worried/anxious). Responses ranged from 0 (not at all) to 4 (extremely). Items were summed for positive and negative mood, respectively, with higher scores indicating higher positive or negative mood. Positive mood and negative mood were examined separately, following the bivariate view of positive and negative affect (Reich, Zautra, & Davis, 2003). Demographic characteristics including education, income, and number of times married were reported by initial 2010 respondents, representing household/couple level variables. Education levels ranged from 1 (11th grade or less) to 8 (graduate degree). Total household income in 2009 was measured by respondents selecting income categories ranging from “less than $10,000” to “$150,000 or more” a year, and responses were coded to reflect the midpoint of the interval selected (e.g., “$10,000–$14,999” was re-coded to “$12,500”). Marital history was measured with one item that asked the number of times respondents had been married. Health limitations were measured with five items that assessed the degree to which respondents accomplished less, spent less time working, felt limitations, or had difficulty performing tasks due to physical health. Four items were modified from the SF-36 health survey (Hays, Sherbourne, & Mazel, 1993), framing them within the last 24 hours and broadening response options. The last item addressed limitations caused by medication side effects. Responses to all items ranged from 0 (no) to 3 (yes, very much), with higher scores indicating higher activity limitations (scale reliability = .86). Outcome Measures Positive and negative marital events were each measured using modified versions of the daily perceptions of spousal support and negative spousal behavior scales (Neff & Karney, 2005). The scales were modified by changing the reference person to “partner” and by adding five marital events to the original list. Positive items addressed a spouse helping with something important, saying something that made them feel loved, a spouse listened to or comforted them, sharing physical intimacy, enjoying leisure together, and providing care for one’s spouse. Negative items included having an argument with a spouse, a spouse letting them down or breaking a promise, being criticized by a spouse, and not being able to spend desired time with one’s spouse. Participants indicated whether each event had happened to them that day (1 = Yes and 0 = No), and a count of positive and negative events comprised the two scales. Seven items from a scale by McNulty and Karney (2001) assessed satisfaction with daily marital interactions. Respondents reported satisfaction with their spouse/partner in the areas of division of household labor, emotional support, amount of time together, disagreements, conversations, affection, and dependability. Responses ranged from 0 (very unsatisfied) to 6 (very satisfied). Statistical Analysis Multivariate multilevel models were estimated in SAS using the Proc Mixed procedure to predict outcomes of daily positive marital interaction, daily negative marital interaction, and satisfaction with daily marital interactions. Models were multivariate in that they estimated predicted values for multiple outcomes simultaneously within a single model (one for the husband and one for the wife), and in the process provide estimates of and account for the correlated nature of spousal data (Raudenbush, Brennan, & Barnett, 1995). These models also account for the longitudinal nature of the data (repeated measures across days). Variables in the current analysis had some missing data (all variables < 4% data missing, except the “income” variable which had < 8% data missing). SAS Proc Mixed handles missing data on outcome variables using full information maximum likelihood, yet excludes rows (days) of data where predictor variables are missing. Predictors in the models included main effects of daily sleep duration, sleep quality, and perceived daily reports of feeling rested, as well as covariates of age, education, income, health limitations, and marital history. The three measures of sleep are only modestly correlated with each other (r values = .06–.29), suggesting that they each represent unique aspects of the sleep experience. However, when all sleep predictors were included in the same model, results suggested issues of multicollinearity. As such, each measure of sleep was modeled separately (Table 2 and Supplementary Tables 1 and 2). Both within- and between-person predictors of sleep duration, quality, and feeling rested were included in the models (Bolger & Laurenceau, 2013). Specifically, a person-mean-centered, within-person predictor was included (one’s deviation on a given day from their personal average across the 14 days), as well as a grand-mean-centered, between-person predictor (a person’s average across the 14 days). Independent main effects of positive and negative mood on the outcome were first estimated (not shown; available upon request). Models 1–3 include main effects of individual predictors (e.g., sleep duration) on each marital outcome, as well as mediation variables with either positive or negative mood added to the model. Level 2 continuous predictors were centered at the grand mean to facilitate interpretation of the intercepts. Table 2. Unstandardized Estimates for Actor/Partner Links of Mood and Sleep with Daily Positive Marital Events (N = 191) Model 1 Model 2 Model 3 (a) (b) (c) (a) (b) (c) (a) (b) (c) Wives Intercept 3.94*** 3.96*** 3.97*** 3.93*** 3.95*** 3.96*** 3.94*** 3.95*** 3.97*** Within person Hours slept −0.00+P −0.02+P −0.01+P Sleep quality 0.02 −0.00 −0.01 Rested 0.11*** 0.08* 0.03a Negative mood −0.10***−P −0.10***−P −0.09***−P Positive mood 0.12*** 0.12*** 0.12*** Between person Hours slept 0.30* 0.29* 0.19 Sleep quality 0.13 0.14 −0.07 Rested 0.44*** 0.46*** 0.16b Negative mood −0.06 −0.07 0.00 Positive mood 0.23*** 0.24*** 0.21*** Husbands Intercept 3.77*** 3.79*** 3.79*** 3.76*** 3.77*** 3.77*** 3.76*** 3.77*** 3.79*** Within person Hours slept 0.05†+P 0.06*+P 0.05† Sleep quality 0.04+P 0.04+P 0.03+P Rested 0.12*** 0.10** 0.05 Negative mood −0.07*** −0.07*** −0.07*** Positive mood 0.13***+P 0.14***+P 0.13***+P Between person Hours slept 0.10 0.10 0.13 Sleep quality 0.13 0.12 −0.21 Rested 0.18 0.18 −0.31*c Negative mood −0.07 −0.05 −0.03 Positive mood 0.24*** 0.24*** 0.28*** No. of parms/No. of days 22/4,326 26/4,264 26/4,286 22/4,372 26/4,312 26/4,334 22/4,380 26/4,326 26/4,348 W: W/B variance 2.29/2.92 2.23/2.90 2.16/2.40 2.29/2.97 2.23/2.96 2.15/2.43 2.26/2.73 2.21/2.71 2.14/2.40 H: W/B variance 2.27/2.86 2.22/2.82 2.15/2.01 2.27/2.85 2.23/2.83 2.15/2.01 2.25/2.83 2.21/2.82 2.14/1.96 Model 1 Model 2 Model 3 (a) (b) (c) (a) (b) (c) (a) (b) (c) Wives Intercept 3.94*** 3.96*** 3.97*** 3.93*** 3.95*** 3.96*** 3.94*** 3.95*** 3.97*** Within person Hours slept −0.00+P −0.02+P −0.01+P Sleep quality 0.02 −0.00 −0.01 Rested 0.11*** 0.08* 0.03a Negative mood −0.10***−P −0.10***−P −0.09***−P Positive mood 0.12*** 0.12*** 0.12*** Between person Hours slept 0.30* 0.29* 0.19 Sleep quality 0.13 0.14 −0.07 Rested 0.44*** 0.46*** 0.16b Negative mood −0.06 −0.07 0.00 Positive mood 0.23*** 0.24*** 0.21*** Husbands Intercept 3.77*** 3.79*** 3.79*** 3.76*** 3.77*** 3.77*** 3.76*** 3.77*** 3.79*** Within person Hours slept 0.05†+P 0.06*+P 0.05† Sleep quality 0.04+P 0.04+P 0.03+P Rested 0.12*** 0.10** 0.05 Negative mood −0.07*** −0.07*** −0.07*** Positive mood 0.13***+P 0.14***+P 0.13***+P Between person Hours slept 0.10 0.10 0.13 Sleep quality 0.13 0.12 −0.21 Rested 0.18 0.18 −0.31*c Negative mood −0.07 −0.05 −0.03 Positive mood 0.24*** 0.24*** 0.28*** No. of parms/No. of days 22/4,326 26/4,264 26/4,286 22/4,372 26/4,312 26/4,334 22/4,380 26/4,326 26/4,348 W: W/B variance 2.29/2.92 2.23/2.90 2.16/2.40 2.29/2.97 2.23/2.96 2.15/2.43 2.26/2.73 2.21/2.71 2.14/2.40 H: W/B variance 2.27/2.86 2.22/2.82 2.15/2.01 2.27/2.85 2.23/2.83 2.15/2.01 2.25/2.83 2.21/2.82 2.14/1.96 Notes: Parms = number of parameters; W = wife; H = husband. Covariates include age, number of times married, health limitations, education, and income. +P and −P in superscripts indicate positive and negative partner effects (p ≤ .05; numerical values available upon request). aIndirect effect of W/P feeling rested through W/P positive mood on positive marital events: b = .01, z = 2.10, p = .036. bIndirect effect of B/P feeling rested through B/P positive mood on positive marital events: b = .37, z = 4.08, p = .000. cWhen positive mood was added to the model of feeling rested predicting positive marital events, the B/P feeling rested coefficient switched signs from positive to negative, indicating a suppressor effect. This finding appears to be an anomaly, as patterns throughout our findings are generally in expected directions. †p ≤ .10. *p ≤ .05. **p ≤ .01. ***p ≤ .001. View Large An example of the multivariate multilevel equation illustrates main effects from our analysis for husband and wife within-person reports of deviation in sleep duration (DSD) for a given person “i” on a given day “t”, and “between-person” average sleep duration (ASD) for a given person “i” across days predicting daily marital satisfaction: DailyMarSatit=(Husband)it[β0hi+β1hi(DSD)it+β2hi(ASD)i](Wife)it[β0wi+β1wi(DSD)it+β2wi(ASD)i]+eit Multilevel structural equation modeling in Mplus (Muthén & Muthén, 1998–2002) was used to examine follow-up models of indirect effects/mediation of daily mood between daily sleep and marital outcomes. Results Sleep and Marriage Findings from multivariate models provide some support for our first hypothesis, with general trends suggesting links between sleep variables and marital interactions (see column “a” of each Model in Table 2 and Supplementary Tables 1 and 2; within-person effects are abbreviated as “W/P” and between-person effects are abbreviated as “B/P”). Wife reports of sleeping longer on a given night relative to their study average were linked to increases in both the number of positive marital events reported on the next day (B/P: b = 0.30, p < .05) and wife marital satisfaction (B/P: b = 0.17, p < .05). Additionally, on days when wives reported better sleep quality than their study average, they endorsed less negative marital events on that day (W/P: b = −0.04, p < .01). Although husband reports of sleep duration were not significantly linked to marital outcomes, their reports of higher than the sample average sleep quality were related to higher daily marital satisfaction (B/P: b = 0.40, p < .01). Marital events and marital satisfaction were often predicted by daily reports of feeling rested (Table 2 and Supplementary Tables 1 and 2). For wives, feeling more rested than their own study average (W/P: b = 0.11, p < .001) and feeling more rested than the wife sample mean (B/P: b = 0.44, p < .001) were significantly related to more positive marital events and higher perceived daily marital satisfaction (W/P: b = 0.06, p < .001; B/P: b = 0.41, p < .001). Prior to controlling for health limitations, feeling rested was significantly linked to fewer negative marital events (see notes of Supplementary Table 1; W/P: b = −0.02, p < .05; B/P: b = −0.04, p < .05). After controlling for health limitations, feeling rested was only linked with fewer negative marital events at a trend level (see Model 3, Supplementary Table 1; W/P: b = −0.02, p < .10). Husbands’ higher than average daily feeling rested was significantly related to more positive marital events (W/P: b = 0.12, p < .001) and higher daily marital satisfaction (W/P: b = 0.06, p < .01; B/P: b = 0.33, p < .001). Mood and Marriage In support of our second hypothesis, husband and wife positive and negative mood were associated with each of the marital outcomes in the study (see columns “b” and “c” of each Model, Table 2 and Supplementary Tables 1 and 2; only wife results reported in-text; see husband results in Table 2 and Supplementary Tables 1 and 2). Specifically, wife and husband reports of higher negative mood were linked to lower reports of positive marital events (W/P: b = −0.10, p < .001), higher number of negative marital events (W/P: b = 0.05, p < .001; B/P: b = 0.06, p < .001), and decreases in marital satisfaction (W/P: b = −0.05, p < .001; B/P: b = −0.09, p < .05). Also, both wife and husband within- and between-person positive mood scores predicted, in expected directions, the incidence of positive marital events (W/P: b = 0.12, p < .001; B/P: b = 0.23, p < .001), negative marital events (W/P: b= −0.02, p < .001; B/P: b = −0.01, p < .10), as well as daily marital satisfaction (W/P: b = 0.05, p < .001; B/P: b = 0.13, p < .001). Mood Mediating Sleep to Marriage Link Our third hypothesis involved exploring how mood might mediate the associations between sleep and marital interactions. As a first step, we considered effects of sleep on marital outcomes that were originally statistically significant (see column “a” of each model in Table 2 and Supplementary Tables 1 and 2) and then became nonsignificant (p > .05) when positive or negative mood were included in the models (see columns “b” and “c” of each model in Table 2 and Supplementary Tables 1 and 2). For example, for wives in Table 2, the between-person predictor of hours slept was originally significant in column “a” of Model 1, but then became trend level (p < .10) or nonsignificant when positive mood was entered as a predictor in column “c” of the same model. We found similar patterns for (a) wife W/P and B/P feeling rested predicting positive marital events, (b) husband W/P feeling rested predicting positive marital events, (c) wife W/P and B/P feeling rested predicting negative marital events through positive and negative mood (albeit only when health limitations are not controlled), (d) wife B/P hours slept predicting daily marital satisfaction, (e) wife W/P feeling rested predicting daily marital satisfaction, (f) husband B/P sleep quality predicting daily marital satisfaction, and (g) husband W/P and B/P feeling rested predicting daily marital satisfaction. In 11 of these situations, positive mood played the role of mediator, whereas negative mood played that role twice. To confirm potential mediation, we then used Preacher, Zyphur, and Zhang’s (2010) method of testing indirect effects within a multilevel structural equation model. Of the above 13 potential mediation cases, five were confirmed to have significant indirect effects (see a summary of results in the notes of Table 2 and Supplementary Table 1). Among four of the five significant indirect effects, greater wife feeling rested was linked with greater wife positive mood and less negative mood, which were linked to wife reports of positive and negative marital events. In contrast, W/P wife feeling rested was positively linked with W/P negative mood, which was then associated with higher negative marital interactions. Each case of significant indirect effects was only found among wives, and the majority suggested that better sleep was linked with better mood, which was subsequently linked to better marital outcomes. Partner Effects Along with the actor effects described earlier (independent and dependent variables measured from same participant), we investigated partner effects (independent variables from one spouse being associated with dependent variables of the other spouse). As noted with a + or − “(P)” in Table 2 and Supplementary Tables 1 and 2, results indicated that significant partner effects linking sleep variables with marital outcomes did exist (coefficients not shown). Specifically, increases in wife W/P hours slept on a given day significantly predicted an increase in the number of positive marital events and marital satisfaction reported by their husband on that same day. Similarly, husband W/P hours slept and sleep quality were positively associated with wife reports of positive marital events. Higher wife W/P daily feeling rested was linked to less negative marital events reported by husbands. In contrast to other trends in the results, reports of higher husband B/P average feeling rested was associated with lower daily marital satisfaction in wives. Significant partner effects were also observed where positive and negative mood in husbands and wives predicted marital outcomes. For wives, on days where they reported higher W/P negative mood, husbands reported fewer positive and more negative marital interactions. For husbands, on days when they reported higher positive mood or higher negative mood, wives reported more positive marital interactions and higher negative marital interactions, respectively. Also, on days where wives reported higher W/P positive mood or lower W/P negative mood, husbands reported an increase in marital satisfaction. Links between husband positive and negative mood with wife marital satisfaction produced identical results (Supplementary Table 2). We found no clear patterns of mood acting as a mediator for partner effects of sleep on marital outcomes. Last, to address the question of endogeneity, we conducted some follow-up analyses where marital events and mood on a given day predicted sleep that night. Lagged models (t − 1 predictors) were used to predict sleep on a given night by marital events and mood reported that same day. Findings indicated that marital events did indeed predict sleep in a number of cases (W/P negative marital events predicted hours slept for husbands [b = −0.12, p < .05] and wives [b = −0.11, p < .05], and W/P marital satisfaction predicted feeling rested among husbands [b = 0.08, p < .05], B/P marital satisfaction predicted hours slept among wives [b = 0.14, p < .05], B/P marital satisfaction predicted sleep quality among husbands [b = 0.10, p < .01], B/P positive marital events and marital satisfaction predicted feeling rested for husbands [positive events: b = 0.08, p < .05, satisfaction: b = 0.29, p < .001] and wives [positive events: b = 0.15, p < .001, satisfaction: b = 0.37, p < .001]). Mood was also linked with sleep, yet only in a handful of cases (W/P negative mood predicted hours slept for wives [b = 0.05, p < .001]; B/P positive mood predicted sleep quality for husbands [b = 0.03, p < .05]; W/P positive and negative mood predicted feeling rested for wives [positive mood: b = −0.03, p < .01; negative mood: b = −0.03, p < .05]; B/P positive mood predicted feeling rested for husbands [b = 0.14, p < .001] and wives [b = 0.13, p < .001]). Follow-up analyses were generally in expected directions, with poorer marital interactions and mood linked with poorer sleep. Discussion Research has established links between sleep and marital satisfaction (Hasler & Troxel, 2010; Rauer & El-Sheikh, 2012; Strawbridge et al., 2004), between sleep patterns and mood fluctuations (Roberts et al., 2000), and between mood and marital satisfaction (Pruchno et al., 2009). The current study examined these relationships concurrently with results generally supporting the hypotheses; daily sleep was often significantly related to marital outcomes, positive and negative mood were consistently linked with marital outcomes, mood was sometimes a mediator between sleep measures and marital outcomes, and sleep and mood in one spouse were sometimes linked to marital interactions as reported by their partner. These results expand the Sleep and Relationship Functioning model (Troxel et al., 2007) to include dyadic associations, along with within- and between-person specific findings. Results from the study are particularly relevant in later life as sleep problems become more prevalent with age (Moraes et al., 2014) and may indicate an increased need for emotion regulation processes among older couples (Monin, 2016) when sleep is not optimal. Sleep and Marital Outcomes In support of past literature findings (Insana et al., 2011; Strawbridge et al., 2004), the current study indicated that increases in sleep quality and feeling rested were correlated with positive and negative marital events and daily marital satisfaction in expected directions. Moreover, the number of hours slept was significantly and positively related to marital outcomes, though only sporadically for both male and female spouses. Getting appropriate sleep appears to be an important element in fostering positive and lowering negative daily marital interactions. A possible reason for sparse links between number of hours slept and marital outcomes is that sleeping fewer hours may not relate to marital quality in immediate succession, but may manifest two or more days after a poor sleep night. Hasler and Troxel (2010) found results supporting the idea that lagged effects of sleep (2 or 3 days following) may be more consistent and salient than the day immediately following sleep deprivation. Thus, number of hours slept may be less important in marriage relationships on a given day than on future days. Although beyond the scope of the present study, future research should consider lagged effects of poor sleep, as well as marital interactions with the potential compounding effects of having multiple consecutive poor sleep nights. Also, as husband and wife sleep reports are modestly correlated (Table 1), paired sleep reports might be considered more directly in future research. Mood and Marital Outcomes As supported by prior research (Pruchno et al., 2009), both positive and negative mood were consistently predictive of marital outcomes for both husbands and wives. Although mean difference tests from the current study suggested gender differences in daily reports of mood, regression results supported the idea that mood is an important correlate of marital interactions for both husbands and wives. Prior research suggests that mood may influence the behavior of spouses toward each other, color the “lens” through which spouses view their marital interactions, or both (Durtschi, Fincham, Cui, Lorenz, & Conger, 2011; Larson & Almeida, 1999). Also, Choi and Marks (2008) suggest that mood and marital interactions may be associated reciprocally. Future research examining lagged effects across days or broader time points could further explore various temporal orderings of daily mood and daily marital interactions. That positive mood emerged with stronger connections to marital outcomes than negative mood is somewhat unexpected. In 2001, Baumeister, Bratslavsky, Finkenauer, and Vohs suggested that negativity produces stronger reactions than positivity; yet a recent study suggests that positive emotions are more commonly involved in crossover (transferring from one person to another) than negative ones (Westman, Shadach, & Keinan, 2013). Further, a focus on positive perceptions and emotions may become more salient in later years (Samanez-Larkin, Robertson, Mikels, Carstensen, & Gotlib, 2014). Consistent with the current study, it may be that positive emotions, compared with negative ones, are more strongly linked to daily sleep and to daily positive marital interactions. Alternatively, positive emotions may emerge in the current study because respondents endorsed negative mood less frequently. Future research could explore nuances of various aspects of both positive and negative mood states, as well as associations between sleep and marital interactions among persons with mood disorders. Sleep, Mood, and Marital Interactions Of primary interest in the current study are the mechanisms accounting for the link between sleep and marital interactions in later-life couples. Results provide evidence supporting the Dynamic Association Model, suggesting that sleep and marital interactions are linked through social and psychological processes (Troxel et al., 2007). Indeed, findings from the current study indicated that after controlling for mood, nearly all effects of sleep on marital interactions became nonsignificant, while mood effects maintained their statistical significance. Robust mediation analyses further indicated that indirect effects from sleep to marital interactions through mood were significant in a number of cases. Stronger patterns of mediation emerged for wives in the study, with positive mood most commonly acting as the mechanism. This gender-based finding is consistent with prior research suggesting that wives may experience greater fluctuations in daily distress levels than husbands (Almeida & Kessler, 1998), and they may also report more sleep problems than husbands (Krishnan & Collop, 2006). Research examining sleep associations with mood are consistent with the current findings and provide some insight into potential biological correlates. Neurophysiological mechanisms, such as changes in cortisol regulation (Hori et al., 2011), memory deficits (Gamaldo, Allaire, & Whitfield, 2010), prefrontal cortical functioning (Kamphuis, Meerlo, Koolhaas, & Lancel, 2012), and neurotransmitter desensitization (Roman et al., 2005), may help explain associations between sleep and mood. Although a complex interplay of bio, psycho, and social mechanisms likely link sleep to marital interactions, the current study provides unique evidence regarding mood fluctuations. Concerning partner effects, and consistent with the emotional transmission paradigm described by Larson and Almeida (1999), results from the current study show some evidence of sleep or mood in one spouse being related to marital outcomes in their partner, though not as consistently or saliently as “actor” effects observed. Although emotional transmission is addressed in numerous studies, the role that sleep may play in this process has received less attention. Clinical research consistently links improving sleep with beneficial health outcomes for individuals (Cappuccio, D’Elia, Strazzullo, & Miller, 2009). The current study adds further evidence supporting Strawbridge and colleagues’ (2004) suggestion that treating sleep problems will likely lead to better physical health among both spouses. Research examining physical, emotional, and relationship health outcomes among couples with interventions to improve partner sleep are needed and may be especially relevant to older adults who experience age-related health challenges. Two specific findings were counterintuitive: within-person wives’ feeling rested being positively linked with wife negative marital interactions through negative mood and higher husband between-person feeling rested being linked with lower marital satisfaction for wives. Feeling rested may at times be linked with greater awareness of negative experiences. As insufficient rest is linked with decreased cognitive and relationship functioning (Almklov, Drummond, Orff, & Alhassoon, 2015; Hasler & Troxel, 2010), sufficient rest may at times provide greater opportunity for disappointment or negative responses. Although this study has mainly focused on ways that sleep affects mood and marital interactions, some research suggests that marital interactions and mood can also impact sleep (Chen et al., 2015). Indeed, the Dynamic Association Model suggests reciprocal processes (Troxel et al., 2007). Results from follow-up analyses suggest that there may be links between marital interactions on a given day with sleep that night. In line with prior research, patterns in these results were evident, yet not as salient as when marital interactions were predicted by sleep. Furthermore, positive and negative mood on a given day were only linked to sleep that night in a few cases. Although mood may affect sleep more in certain populations (e.g., osteoarthritis patients; Song, Graham-Engeland, Mogle, & Martire, 2015), in the current sample it appears that sleep is the stronger precursor. Various complex interactions of moderation, mediation, and reciprocity between sleep, mood, and marital interactions could provide fruitful future research avenues. Limitations, Strengths, and Conclusion Limitations apply to the current study. First, length of marriage was not directly assessed and could not be computed for a portion of the sample (46 couples), and as a result it was omitted as a covariate. Accounting for length of marriage in future sleep and relationship research may provide additional insights, as sleep might impact relationships differently for those in short- versus long-term relationships (see Umberson, Williams, Powers, Chen, & Campbell, 2005). Second, only self-report, single-item measures of sleep were used. Although some research suggests that self-report measures of sleep, compared with objective measures, may be more commonly correlated with psychological distress (Caldwell & Redeker, 2009), future studies could provide additional evidence using multi-item and objective measures of sleep (e.g., polysomnography, wrist actigraphy). Third, there is little socioeconomic and racial/ethnic diversity in the current sample. Future research could address the role of cultural context in relation to sleep, mood, and marriage. Last, contextual factors such as employment might influence links between sleep and marriage. A growing number of studies have addressed interactions between employment and sleep quality (van Tienoven, Glorieux, & Minnen, 2014). Future research might examine couples in context of employment, sleep, and marital quality. Despite its limitations, this study has unique strengths in its microlongitudinal nature, considerable breadth of data (5,168 surveys) from nearly 200 later-life couples, across a 2-week period, and in utilizing data from both husbands and wives. Furthermore, the study employed multiple measures of sleep, mood, and marital interactions and included both within- and between-person associations. These strengths expand the Sleep and Relationship Functioning model in important ways, especially with regard to dyadic and within/between-person processes linking sleep to marital interactions through psychological pathways. These findings have important implications for the mood and marital quality among couples where one or both spouses experience sleep problems. Such couples may benefit by increased awareness and regulation of emotions on days with poor sleep. Supplementary Material Please visit the article online at http://gerontologist.oxfordjournals.org/ to view supplementary material. 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The Journals of Gerontology Series B: Psychological Sciences and Social Sciences – Oxford University Press
Published: Mar 1, 2018
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