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REM sleep alterations associated with the sleeping arrangement. (A) Co-sleep (red bars) is associated with an approximately 10% higher amount of relative REM duration (23 ± 0.9% vs. 21 ± 0.8%) as compared to sleeping alone (blue bars). No other sleep stage shows significant alterations associated with the sleeping arrangement. Given are means ± SEM. REM sleep is less fragmented under the co-sleep condition [red bar, panel (B)] which results in markedly longer undisturbed continuous REM sleep sequences (C). Boxes represent first and third quartile (upper and lower margins) and median (bold horizontal line). N = 24, significance: ** < 0.01; *** < 0.001.
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Background/Objectives
Sharing the bed with a partner is common among adults and impacts sleep quality with potential implications for mental health. However, hitherto findings are contradictory and particularly polysomnographic data on co-sleeping couples are extremely rare. The present study aimed to investigate the effects of a bed partner's pres...
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Purpose
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Citations
... Sleep is a social and interdependent process, as most adults have a bed partner and nearly 90% of couples share a bed at least occasionally. [1][2][3][4] Thus, sleep occupies a major proportion of a couple's existence and time together. Moreover, relationship dynamics between cosleepers are associated with sleep outcomes. ...
Objective
The purpose of this study was to evaluate the psychometric properties of the Couples' Sleep Conflict Scale, a new measure designed to identify the extent of conflict around sleep in romantic relationships.
Methods
Data from an individual sample (N = 158) and dyadic sample (N = 143 mixed-gender couples) in romantic relationships were used to examine the psychometric properties of the Couples' Sleep Conflict Scale, including internal consistency, convergent and divergent validity, and whether the factor structure differed between couples with concordant and discordant chronotypes.
Results
Results revealed that the Couples' Sleep Conflict Scale fit a 1-factor solution of 5 items, a summed or mean score can be used, and that it is reliable for both men and women. In addition, more relational sleep conflict was associated with both their own and their partners’ poorer sleep hygiene, worse sleep quality, and more daytime sleepiness as well as more general relationship conflict, lower relationship satisfaction, and higher anxious and avoidant attachment. Finally, we found partial measurement invariance for factor loadings, intercepts, and latent variable variances between couples with concordant vs. discordant chronotypes.
Conclusion
The Couples' Sleep Conflict Scale is a brief measure that can be used in both research and in health care settings to examine how sleep-related conflict can affect both sleep and relationship quality among couples.
... Mothers and fathers in the same couple multi-trajectory group exhibited similar sleep patterns. A crosssectional laboratory study showed that couples sleeping together had more synchronized sleep stages than those sleeping individually, 44 which suggests similar sleep characteristics. However, the distribution between individual and couple multitrajectory groups exhibited larger differences for maternal than paternal sleep multi-trajectory groups, so mothers might be more likely to adapt their sleep to their partner's sleep or synchronize their sleep with their partner's. ...
Objective
We investigated maternal and paternal sleep evolution from 3 to 36 months postpartum, their interrelations and predictors in the SEPAGES cohort.
Methods
Sleep information (night sleep duration [NSD], weekend daytime sleep duration [DSD] and subjective sleep loss [SSL]) was collected by self-administered questionnaires at 3, 18, 24 and 36 months postpartum in the SEPAGES French cohort that included 484 mothers and 410 fathers. Group-based multi-trajectory modelling was used to identify maternal, paternal and couple sleep multi-trajectory groups among 188 couples reporting sleep data for at least 2 time points. Multinomial logistic regression was used to assess associations between parental sleep multi-trajectories and early characteristics such as sociodemographic, chronotypes, child sex, birth seasonality or breastfeeding duration.
Results
We identified three maternal (M1-M3), paternal (F1-F3) and couple (C1-C3) sleep multi-trajectory groups with similar characteristics: a group with short NSD and high SSL prevalence (M1, F2, C2), a group with long NSD but medium SSL prevalence (M2, F3, C3) and a group with long NSD and low SSL prevalence (M3, F1, C1). Mothers with the shortest NSD (M1) were less likely to have a partner with long NSD (F2). As compared with long NSD and low SSL prevalence (C1), couples with short NSD and high SSL prevalence (C2) were less likely to have had a first child born in the autumn and fathers in C2 had a later chronotype.
Conclusion
We identified distinct sleep multi-trajectory groups for mothers, fathers and couples from 3- to 36-month postpartum. Sleep patterns within couples were homogeneous.
... 7 Indeed, the recent use of these technologies has revealed that sleep neurophysiology and behavior are plastic and modulated by internal and ecological demands. 17,18 Various species, including humans, 19 baboons, 13 gulls, 20 and laboratory mice, 16 exhibit coordination in the timing of sleep and wake episodes between co-living individuals. Recent studies have also uncovered coordination in brain oscillatory patterns between awake interacting individuals in humans, 21 bats, 22 and mice. ...
... There is growing interest in the effects of intimate relationships on sleep [1][2][3][4] . However, much of the hitherto research has focused on personal factors (e.g., personality traits, attachment styles) or relational functioning (e.g., marital satisfaction, inter-partner conflict; for review see Rogojanski et al. (2013) 1 . ...
Objectives: To investigate intimate partners’ impact on sleep hygiene with focus on the temporal dimension and differential predictors of sleep hygiene in co-sleepers and individual sleepers. Material and Methods: Habitual co-sleepers and individual sleepers (n=102) completed a cross- sectional, self-report, in-lab, digital survey on sleep hygiene, habitual sleeping arrangement, self- control, depressiveness, and sociodemographic parameters. Results: The relationship between sleeping arrangement and sleep hygiene in co-sleepers was time-dependent with an initial steep incline and a subsequent plateau at approximately one year of co-sleeping routine. Co-sleepers with more than one year of unaltered sleeping arrangement had significantly better sleep hygiene than co-sleepers with less than one-year or individual sleepers. More than one-year continuity of the sleeping arrangement moreover robustly predicted sleep hygiene in co-sleepers whereas self-control was the dominant predictor in individual sleepers. Conclusion: Amongst others, our findings support the idea that insomnia treatment could be improved by becoming sensitive to the habitual sleeping arrangement.
Keywords: Sleep Hygiene; Co-sleep; Bed-sharing; Self-control; Social Control; CBTI.
... Moreover, for people living in a shared environment, their physical and mental states are closely related and even synchronized. For instance, Drews et al. [5] revealed that two people sleeping in the same room had a similar sleep staging. It was therefore considered that in addition to monitoring one's own physiological signal, measuring the data on the interacting partner can also help predict the individual's mental state. ...
... Second, we did control if athletes slept alone or in couple, and it is widely known that these 2 different conditions can have an impact on sleep quality and architecture. 33 However, none of the athletes slept in shared rooms with colleagues during the experimental procedures, and no training camps were scheduled in that period. 34 Third, 3 athletes spent one night, during the sleep monitoring period, in a hotel for different reasons (eg, small travels, family or business affairs, etc), and this could have modified their sleep behavior. ...
Purpose:
Few data are available on sleep characteristics of elite track-and-field athletes. Our study aimed to assess (1) differences in sleep between sexes and among different track-and-field disciplines, (2) the effect of individualized sleep-hygiene strategies on athletes' sleep parameters, and (3) daytime nap characteristics in track-and-field athletes.
Methods:
Sleep characteristics of 16 elite Olympic-level track-and-field athletes (male: n = 8; female: n = 8) were assessed during the preseason period, at baseline (T0), and during the in-season period, after the adoption of individualized sleep-hygiene strategies (T1). Sleep parameters were objectively monitored by actigraphy for a minimum of 10 days, for each athlete, at both T0 and T1. A total of 702 nights were analyzed (T0 = 425; T1 = 277).
Results:
Female athletes displayed better sleep efficiency (88.69 [87.69-89.68] vs 91.72 [90.99-92.45]; P = .003, effect size [ES]: 0.44), lower sleep latency (18.99 [15.97-22.00] vs 6.99 [5.65-8.32]; P < .001, ES: 0.65), higher total sleep time (07:03 [06:56-07:11] vs 07:18 [07:10-07:26]; P = .030, ES: 0.26), earlier bedtime (00:24 [00:16-00:32] vs 00:13 [00:04-00:22]; P = .027, ES: 0.18), and lower nap frequency (P < .001) than male athletes. Long-distance runners had earlier bedtime (00:10 [00:03-00:38] vs 00:36 [00:26-00:46]; P < .001, ES: 0.41) and wake-up time (07:41 [07:36-07:46] vs 08:18 [08:07-08:30]; P < .001, ES: 0.61), higher nap frequency, but lower sleep efficiency (88.79 [87.80-89.77] vs 91.67 [90.95-92.38]; P = .013, ES: 0.44), and longer sleep latency (18.89 [15.94-21.84] vs 6.69 [5.33-8.06]; P < .001, ES: 0.67) than athletes of short-term disciplines. Furthermore, sleep-hygiene strategies had a positive impact on athletes' total sleep time (429.2 [423.5-434.8] vs 451.4 [444.2-458.6]; P < .001, ES: 0.37) and sleep latency (14.33 [12.34-16.32] vs 10.67 [8.66-12.68]; P = .017, ES: 0.19).
Conclusions:
Sleep quality and quantity were suboptimal at baseline in Olympic-level track-and-field athletes. Large differences were observed in sleep characteristics between sexes and among different track-and-field disciplines. Given the positive effect of individualized sleep-hygiene strategies on athlete's sleep, coaches should implement sleep education sessions in the daily routine of top-level athletes.
... To the authors' knowledge, no studies examining relations between sibling sleep behaviors have considered characteristics of the sleeping environment, such as room-sharing. This is an important gap, as previous research among parent and infant dyads [20] and young adult couples [21,22] suggest that individuals can influence one another's sleep markedly, especially when sleeping in the same room. Moreover, in their study examining parent and adolescent sleep habits, Fuligni et al. [7] found that household size was associated with greater concordance in sleep duration and wake time. ...
... Specifically, relations between DZ-os twins' average sleep duration were nonsignificant in the main effect models; thus, exploring room-sharing as a moderator allowed for the discovery of a subgroup of DZ-os twins for whom sleep duration was concordant (i.e., those who shared rooms). Results from this aim complement existing work on room sharing during sleep among infant-parent and young adult couple dyads [20][21][22], offering additional evidence that individuals may influence one another's sleep more drastically in shared sleep environments. These results also support the line of thinking by Fuligni et al., 2015 [7], who hypothesized that concordance between the sleep of family members may be stronger due to shared sleeping quarters. ...
... A significant coupling of REM sleep cycles was observed when couples slept in the same bed. REM sleep may contain feedback to the surrounding environment [47]. Therefore, it is of great significance to monitor the physiological information during REM sleep. ...
Sleep is an essential physiological activity, accounting for about one-third of our lives, which significantly impacts our memory, mood, health, and children’s growth. Especially after the COVID-19 epidemic, sleep health issues have attracted more attention. In recent years, with the development of wearable electronic devices, there have been more and more studies, products, or solutions related to sleep monitoring. Many mature technologies, such as polysomnography, have been applied to clinical practice. However, it is urgent to develop wearable or non-contacting electronic devices suitable for household continuous sleep monitoring. This paper first introduces the basic knowledge of sleep and the significance of sleep monitoring. Then, according to the types of physiological signals monitored, this paper describes the research progress of bioelectrical signals, biomechanical signals, and biochemical signals used for sleep monitoring. However, it is not ideal to monitor the sleep quality for the whole night based on only one signal. Therefore, this paper reviews the research on multi-signal monitoring and introduces systematic sleep monitoring schemes. Finally, a conclusion and discussion of sleep monitoring are presented to propose potential future directions and prospects for sleep monitoring.
... Partnered (married or cohabiting) participants at the time of the sleep study had better sleep quality, while sleep impairment was substantially correlated with loneliness. These results correspond to the findings of previous studies, which have demonstrated that co-sleeping with a partner is related to an improvement in sleep quality as well as a reduction in the daily manifestations of insomnia [42][43][44]. ...
Background: The COVID-19 pandemic put considerable strain on individual mental health. The current study aimed to determine the prevalence and severity of insomnia symptoms among students and employees during this period. Methods: This paper is a cross-sectional analysis using convenience sampling. A web-based anonymous survey was developed and included questions about socio-demographic characteristics, contact with COVID-19, and the Athens Insomnia Scale. Results: 620 participants, 331 students, and 289 employees were included in the final sample. According to the current findings, 21.29% (n = 132) of participants met the criteria for insomnia, and 39.03% (n = 242) met the criteria for mild sleep disturbances. Conclusions: Although respondents reported an increased prevalence of sleep disorders, these changes were not directly related to the presence or severity of the infection but rather to a variety of socio-demographic and lifestyle-related variables. Students associated more frequently with the next-day consequences of insomnia (overall functioning and sleepiness during the day), while for employees, the most prevalent were awakenings during the night and early morning awakenings. Furthermore, sleep difficulties were more prevalent in women, single people, sedentary people, and those with psychiatric disorders.
... In terms of marital status, MEFCs who were married were more likely to report good sleep quality than those without a spouse, which was consistent with the previous study [53], although it was not significant in the last model. A possible reason was that loneliness caused by sleeping alone increases the stress hormone cortisol, leading to disrupted sleep and poorer sleep quality [54]. ...
Few studies have focused on the sleep quality among migrant elderly following children (MEFC). This study aimed to investigate the effects of chronic disease and mental health on the sleep quality of MEFC in Weifang, China. A cross-sectional study was conducted by multi-stage cluster random sampling, and in total 613 participants were enrolled. Sleep quality and mental health were assessed by the Pittsburgh Sleep Quality Index (PSQI) and the Depression, Anxiety, and Stress Scale (DASS-21), respectively. Chronic disease was assessed by the question “how many chronic diseases do you have?” A descriptive analysis and chi-square test were used to describe participants’ sociodemographic variables, chronic disease, mental health, and sleep quality. The relationship between chronic disease, mental health, and sleep quality was explored by establishing binary logistic regression models. The results showed that 18.3% of MEFC’s sleep quality was poor. MEFCs who were male were more likely to report good sleep quality. MEFCs who have similar monthly family income compared with others around, with multimorbidity, depression, and anxiety were more likely to report poor sleep quality. Nearly 1/5 of MEFCs were having poor sleep quality in this study. Results indicated that chronic diseases, depression, and anxiety were risk factors for the sleep quality of MEFC. Implications for the government, communities, and families of MEFC were given for improving their sleep quality.
