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Introduction Insomnia is highly prevalent, but difficult to diagnose due to night-to-night sleep variability, and difficult to treat in part due to the lack of trained providers. Consumer sleep technology (CST) allows for longitudinal sleep monitoring in a natural environment. One such device, the Sleep Score Max (SleepScore Labs) combines longitudinal non-contact sleep tracking via radio-frequency biomotion sensor technology with an individualized sleep guide function, which provides tailored recommendations to improve sleep based on the user’s objectively measured sleep, bedroom environment, and self-reported daily activity. Focusing on sleep efficiency, we examined if level of engagement with the sleep guide is related to sleep improvement in chronic insomnia. Methods As part of a larger study, N=30 individuals with chronic insomnia (ages 38.7±14.9; 8 male) participated in an 8-week at-home sleep monitoring study. Enrollment criteria included being 18-65y old and meeting ICSD-3 criteria for chronic insomnia with no other clinically relevant condition contributing to sleep disturbance. Participants were instructed to track their sleep with the aforementioned device and engage with the sleep guide daily for 8 consecutive weeks. For observed sleep efficiency, means (characterizing sleep overall) and within-subject standard deviations (characterizing ­night-to-night variability) were assessed by week, and change scores from week 1 to week 8 were correlated with level of engagement with the sleep guide function (defined as percentage of days interacted with the guide within the 8-week period). Results From week 1 to week 8, mean sleep efficiency increased non-significantly (t[23]=0.83, p=0.42), but night-to-night variability decreased significantly (t[23]=-2.16, p=0.041). There was no significant relationship between change in mean sleep efficiency and level of engagement with the sleep guide (r=0.005, p=0.980), but there was a significant relationship between change in night-to-night variability and level of engagement (r=-0.48, p=0.018), such that night-to-night ­variability decreased more in those with greater engagement. Conclusion Night-to-night sleep variability is a chief complaint of people with chronic insomnia, and reduced night-to-night variability in sleep efficiency may indicate improvement. As such, engagement with an individualized sleep guide incorporated in a CST device may help individuals with chronic insomnia improve their sleep. Support (if any) NIH grant KL2TR002317; research devices provided by SleepScore Labs.

Introduction Individuals with insomnia report poor sleep quality and non-restorative sleep, and often exhibit irregular sleep patterns over time. First night effects and logistical challenges make it difficult to accurately measure these sleep characteristics in the laboratory. Also, sensitivity to sleep disruption from obtrusive devices confounds sleep measurements in people with insomnia in their naturalistic setting. Non-contact devices (NCDs) may address these issues and enable ecologically valid, longitudinal and unobtrusive characterization of sleep in individuals with insomnia. We present results from a NCD, previously validated against polysomnography, – SleepScore Max (SleepScore Labs) – assessing the sleep of individuals with chronic insomnia, compared to healthy sleeper controls, in their home setting. Methods A total of 112 individuals participated in an at-home sleep monitoring study including 83 with chronic insomnia (ages 19-65, 58 females) and 29 healthy sleeper controls (ages 19-54, 21 females). Enrollment criteria included being 18-65 years of age and, for the insomnia group, meeting International Classification of Sleep Disorders (3rd edition; ICSD-3) criteria for chronic insomnia with no other clinically relevant condition contributing to sleep disturbance. Participants used the NCD to record their sleep periods each night for 8 weeks. Sleep measurements were analyzed for group differences in both means (characterizing sleep overall) and within-subject standard deviations (characterizing night-to-night sleep variability), using mixed-effects regression controlling for systematic between-subject differences. Results On average, individuals with chronic insomnia exhibited increased total wake time, wake after sleep onset, and decreased sleep efficiency relative to healthy sleeper controls (F>6.8, p4.4, p Conclusion In our sample of individuals with chronic insomnia, a NCD naturalistically detected differences from healthy sleeper controls in multiple sleep parameters, both on average and in terms of night-to-night variability. Capturing night-to-night variability in the home setting adds an important dimension to our understanding of poor sleep and provides a more comprehensive, ecologically valid characterization of chronic insomnia as experienced in daily life. Support (If Any) NIH grant KL2TR002317; research devices provided by SleepScore Labs

STUDY OBJECTIVES We used quantitative genetic models to assess whether area-level deprivation as indicated by the Singh Index predicts shorter sleep duration and modifies its underlying genetic and environmental contributions. METHODS Participants were 4,218 adult twin pairs (2,377 monozygotic and 1,841 dizygotic) from the University of Washington Twin Registry. Participants self-reported habitual sleep duration. The Singh Index was determined by linking geocoding addresses to 17 indicators at the census-tract level using data from Census of Washington State and Census Tract Cartographic Boundary Files from 2000 and 2010. Data were analyzed using univariate and bivariate genetic decomposition and quantitative genetic interaction models that assessed A (additive genetics), C (common environment), and E (unique environment) main effects of the Singh Index on sleep duration and allowed the magnitude of residual ACE variance components in sleep duration to vary with the Index. RESULTS The sample had a mean age of 38.2 y (standard deviation [SD] = 18), and was predominantly female (62%) and Caucasian (91%). Mean sleep duration was 7.38 h (SD = 1.20) and the mean Singh Index score was 0.00 (SD = 0.89). The heritability of sleep duration was 39% and the Singh Index was 12%. The uncontrolled phenotypic regression of sleep duration on the Singh Index showed a significant negative relationship between area-level deprivation and sleep length (b = -0.080, P < 0.001). Every 1 SD in Singh Index was associated with a ∼4.5 min change in sleep duration. For the quasi-causal bivariate model, there was a significant main effect of E (b(0E) = -0.063; standard error [SE] = 0.30; P < 0.05). Residual variance components unique to sleep duration were significant for both A (b(0Au) = 0.734; SE = 0.020; P < 0.001) and E (b(0Eu) = 0.934; SE = 0.013; P < 0.001). CONCLUSIONS Area-level deprivation has a quasi-causal association with sleep duration, with greater deprivation being related to shorter sleep. As area-level deprivation increases, unique genetic and nonshared environmental residual variance in sleep duration increases.

STUDY OBJECTIVES To examine whether sleep duration modifies genetic and environmental influences on body mass index (BMI). DESIGN Genotype-environment interaction twin study. SETTING University of Washington Twin Registry. PATIENTS OR PARTICIPANTS A population-based sample of US twins (1,088 pairs, 604 monozygotic, 484 dizygotic; 66% female; mean age = 36.6 yr, standard deviation (SD) = 15.9 yr). INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Participants self-reported information on height, weight, and sleep. Mean BMI was calculated as 25.3 kg/m² (SD = 5.4) and mean habitual sleep duration was 7.2 hr/night (SD = 1.2). Data were analyzed using biometric genetic interaction models. Overall the heritability of sleep duration was 34%. Longer sleep duration was associated with decreased BMI (P < 0.05). The heritability of BMI when sleep duration was < 7 hr (h² = 70%) was more than twice as large as the heritability of BMI when sleep duration was ≥ 9 hr (h² = 32%); this interaction was significant (P < 0.05). CONCLUSIONS Shorter sleep duration is associated with increased BMI and increased genetic influences on BMI, suggesting that shorter sleep duration increases expression of genetic risks for high body weight. At the same time, longer sleep duration may suppress genetic influences on body weight. Future research aiming to identify specific genotypes for BMI may benefit by considering the moderating role of sleep duration.

OBJECTIVES: To compare sleep-spindle incidence (number of spindles per minute of non-rapid eye movement [NREM] stage 2 sleep) and duration, spindle wave time (seconds per epoch in NREM stage 2 sleep), spindle frequency activity, and pain measures (pressure pain threshold, number of tender points, skinfold tenderness) between midlife women with fibromyalgia (FM) and moderate to high pain to a control group of sedentary women without pain. A second goal was to explore the extent to which pain pressure thresholds, age, and depression explain the variance in spindle incidence. DESIGN: A cross-sectional descriptive study. SETTING: A university-based sleep research laboratory and a referral clinic for chronic fatigue and pain. PARTICIPANTS: Thirty-seven medication-free women with FM (mean age, 44.9 +/- 8 years) and 30 women with self-reported good sleep and no pain (mean age, 44.1 +/- 7.7 years) completed a psychiatric interview and the Beck Depression Inventory prior to 2 consecutive nights of polysomnography, with pain measures obtained in the morning. Time domain analysis of spindle incidence and spectral analysis of spindle frequency activity were conducted on night 2 of polysomnography recordings. INTERVENTIONS: NA. RESULTS: Women with FM had fewer mean spindles per minute of NREM stage 2 sleep and lower mean spindle time per epoch of NREM stage 2 sleep (both P values < .02), but mean spindle duration, although slightly shorter, was not statistically significantly different (P < .06) compared to control women. Women with FM had a lower mean pressure pain threshold, a higher average number of positive tender points, and higher skinfold tenderness compared to control women (all P values < .001). Group differences in spindle frequency activity were found after controlling for age, depression, and psychiatric diagnosis in a general linear model (P < .02). One-way analysis of variance revealed significantly lower spindle activity in the 3 frequency bins (12-12.5 Hz, 13-13.5 Hz, 14-14.5 Hz) at C3 (all P values < .04), Fz (all P values < .02), and Cz (all P values < .02). Finally, after controlling for age and depression, pain pressure threshold significantly predicted spindles per minute and spindle time per epoch of NREM stage 2 sleep (r2 = .26; P < .001). CONCLUSIONS: Women with FM and pain have fewer sleep spindles and reduced electroencephalogram power in spindle frequency activity compared to control women of similar age. These data imply that some aspect of thalamocortical mechanisms of spindle generation might be impaired in FM.

STUDY OBJECTIVES To examine the objective and subjective measures of insomnia in chronic fatigue syndrome (CFS). DESIGN Monozygotic co-twin control study. SETTING Academic medical center. PATIENTS OR PARTICIPANTS Twenty-two pairs of monozygotic twins where 1 member of the pair had CFS and the other did not. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Twenty-two CFS-discordant twin pairs completed a Sleep Disorders Questionnaire, overnight polysomnography, and a postpolysomnography sleep survey. Mean and percent differences in the sleep measures were compared between the CFS and healthy twins using matched-pair methods of analysis. Compared with their healthy co-twins, the CFS twins more frequently endorsed 8 subjective measures of insomnia and poor sleep (all p < or = 0.05). However, the CFS and healthy twins did not differ in objective polysomnographic measures of insomnia, including sleep latency, total sleep time, sleep efficiency, arousal number, arousal index, hypnogram awakenings, rapid eye movement (REM)-sleep latency, and percent stages 1, 2, and 3-4 (delta). Percent stage REM sleep was increased in the CFS twins compared with the healthy twins (27.7% vs. 24.4%, p < or = 0.05). On the postpolysomnography survey, CFS twins reported that they had slept fewer hours (6.2 vs. 6.7; p < or = 0.05), and were less well rested (p < or = 0.001) compared to their co-twins. CONCLUSIONS CFS patients had worse subjective sleep than their co-twins despite little objective data supporting this discrepancy, suggesting they suffer from an element of sleep-state misperception. The higher percentage of REM sleep in the CFS twins implies that REM sleep may play a role in this illness.

Objectives Chronic fatigue syndrome (CFS) has been associated with altered amounts of slow wave sleep, which could reflect reduced delta electroencephalograph (EEG) activity and impaired sleep regulation. To evaluate this hypothesis, we examined the response to a sleep regulatory challenge in CFS. Design The first of 3 consecutive nights of study served as laboratory adaptation. Baseline sleep was assessed on the second night. On the third night, bedtime was delayed by 4 hours, followed by recovery sleep. Total available sleep time was held constant on all nights. Setting A research sleep laboratory. Participants 13 pairs of monozygotic twins discordant for CFS. Interventions N/A. Measurements and results Power spectral analysis quantified slow wave activity (SWA) in the 0.5-3.9 Hz band in successive NREM periods (stage 2, 3, or 4) on each night. To ensure comparability, analyses were restricted to the first 4 NREM periods on each night. Data were coded for NREM period and twin pair. Repeated-measures analysis of variance (ANOVA) contrasted sleep delay effects across NREM periods between twin pairs. A second ANOVA calculated the SWA in each NREM period in recovery sleep relative to baseline SWA. The 2 groups of twins were similar on baseline SWA power. After sleep delay, CFS twins exhibited significantly less SWA power in the first NREM period of recovery sleep and accumulated a smaller percentage of SWA in the first NREM period than their co-twins. Conclusions CFS is associated with a blunted SWA response to sleep challenge, suggesting that the basic sleep drive and homeostatic response are impaired.

STUDY OBJECTIVES To better understand the relationships of insomnia, sleepiness, and obesity. DESIGN Classic twin study. SETTING A community-based twin registry in Washington State. PATIENTS OR PARTICIPANTS One thousand forty-two monozygotic and 828 dizygotic twin pairs participating in the University of Washington Twin Registry. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS Twins were, on average, 32 years old; 61% were women, and 19.5% were obese, defined as a body mass index > or = 28. Insomnia and sleepiness were endorsed by 19.3% and 3.7% of twins, respectively. Twin correlations were higher in monozygotic than dizygotic twins for insomnia (0.47 versus 0.15), sleepiness (0.37 versus 0.14), and obesity (0.82 versus 0.46). Heritability estimates were 57% for insomnia (p < .001; 95% confidence interval 47-63), 38% for sleepiness (p < .01; 95% confidence interval 16-46), and 73% for obesity (p < .001; 95% confidence interval 49-87). Multivariate genetic model fitting revealed that common additive genetic effects comprised 12.8% of the phenotypic correlation between insomnia and sleepiness (p < .01) and 10% of the phenotypic correlation between insomnia and obesity (p < .01). The phenotypic correlation between sleepiness and obesity was not due to common additive genetic effects. CONCLUSIONS Insomnia, sleepiness, and obesity are under strong genetic influence. Common genetic effects were observed between insomnia and both sleepiness and obesity, suggesting shared genetic contributions to these phenomena.