Sleep Profile Research Articles

Sleep profiles as a longitudinal predictor for depression magnitude and variability following the onset of COVID-19

The coronavirus disease 2019 (COVID-19) has disrupted multiple domains of life including sleep. The present study used a longitudinal dataset (N = 671) and a person-centered analytic approach – latent profile analysis (LPA) – to elucidate the relationship between sleep and depression. We used LPA to identify profiles of sleep patterns assessed by Pittsburg Sleep Quality Index (PSQI) at the beginning of the study. The profiles were then used as a predictor of depression magnitude and variability over time. Three latent profiles were identified (medicated insomnia sleepers [MIS], inefficient sleepers [IS], and healthy sleepers [HS]). MIS exhibited the highest level of depression magnitude over time, followed by IS, followed by HS. A slightly different pattern emerged for the variability of depression: While MIS demonstrated significantly greater depression variability than both IS and HS, IS and HS did not differ in their variability of depression over time. Medicated insomnia sleepers exhibited both the greatest depression magnitude and variability than inefficient sleepers and healthy sleepers, while the latter two showed no difference in depression variability despite inefficient sleepers’ greater depression magnitude than healthy sleepers. Clinical implications and limitations are discussed.

Do Children of Patients with Bipolar Disorder have a Worse Perception of Sleep Quality?

IntroductionThe offspring of bipolar parents (BO) is a high-risk population for inheriting the bipolar disorder (BD) and other early clinical manifestations, such as sleep disturbances. ObjectiveTo compare the presence of psychiatric disorders and sleep disturbances of BO versus offspring of control parents (OCP). MethodsA cross-sectional analytical study was conducted that compared BO versus OCP. The participants were assessed using valid tools to determine the presence of psychiatric symptoms or disorders. The “Sleep Evaluation Questionnaire” and “School Sleep Habits Survey” were used to determine sleep characteristics and associated factors. Sleep records (7-21 days) were also obtained by using an actigraphy watch. ResultsA sample of 42 participants (18 BO and 24 OCP) was recruited. Differences were found in the presentation of the psychiatric disorder. The BO group showed a higher frequency of major depression disorder (MDD; P = .04) and Disruptive Mood Dysregulation Disorder (DMDD; P = .04). The OCP group showed a higher frequency of Attention Deficit and Hyperactivity Disorder (ADHD; P = .65), and Separation Anxiety Disorder (SAD; P = .46). Differences were also found in sleep by using subjective measurements. Compared to the OCP group, BO had a worse perception of quality of sleep (P = .02), a higher frequency of nightmares (P = .01), a shorter total sleep time, and a higher sleep latency. Nevertheless, no differences were found between groups in the actigraphy measurements. ConclusionsThe BO group had a higher frequency of Mood Disorders, and at the same time a higher number of sleep disturbances in the subjective measurements. It is possible that there is an association between mood symptoms, sleep disturbances, and coffee intake. No differences were found in the sleep profile by using actigraphy.

Sleep in Psychotic Disorders: Results From Nationwide SUPER Finland Study.

Characterizing sleep in patients with schizophrenia, schizoaffective disorder, bipolar disorder, and psychotic depression. This cross-sectional questionnaire study is based on the SUPER study sample, which is part of the Stanley Global Neuropsychiatric Genomics Initiative. The study is a multicentre, nationwide Finnish study consisting of patients (N = 8 623) both in primary and specialized health care. The main measurements were sleep duration, difficulties initiating sleep, early morning awakenings, and fatigue. These results were compared with a nationally representative sample of the Finnish population from the Health 2000 survey (N = 7 167) with frequency and logistic regression analyses. Patients had more sleep problems compared with the general population, especially young and middle-aged patients (Difficulties initiating sleep in young patients odds ratio = 12.3, 95% CI 9.8-15.4). Long sleep duration was the most deviating property of the sleep characteristics, being particularly common among young patients with schizophrenia (odds ratio = 27.9, 95% CI 22.1-35.2, 47.4% vs 3.3% prevalence). All sleep problems were associated with worse subjective health. We also conducted a latent class analysis, resulting in a cluster relatively free of sleep problems (58% of patients), an insomnia symptom cluster (26%), and a hypersomnia symptom cluster (15%). In our sample, patients with psychotic disorders have more sleep problems-especially long sleep duration but also insomnia symptoms-compared with the general population. The patients can in a latent class analysis of their sleep symptoms be divided into groups with differing sleep profiles.

Objective sleep profile in LGI1/CASPR2 autoimmunity.

Rapid eye movement (REM) sleep behavior disorder (RBD) and other sleep disturbances are frequent in leucine-rich, glioma inactivated protein 1-IgG (LGI1) and contactin-associated protein 2-IgG (CASPR2) autoimmunity, yet polysomnographic analyses of these disorders remain limited. We aimed to characterize clinical presentations and analyze polysomnographic manifestations, especially quantitative REM sleep without atonia (RSWA) in LGI1/CASPR2-IgG seropositive (LGI/CASPR2+) patients. We retrospectively analyzed clinical and polysomnographic features and quantitative RSWA between LGI1+/CASPR2+ patients and age-sex matched controls. Groups were compared with Wilcoxon rank-sum and chi-square tests. Combined submentalis and anterior tibialis (SM + AT) RSWA was the primary outcome. Among 11 (LGI1+, n = 9; CASPR2+, n = 2) patients, Morvan syndrome sleep features were present in seven (63.6%) LGI1+/CASPR2+ patients, with simultaneous insomnia and dream enactment behavior (DEB) in three (27.3%), and the most common presenting sleep disturbances were DEB (n = 5), insomnia (n = 5), and sleep apnea (n = 8; median apnea-hypopnea index = 15/hour). Median Epworth Sleepiness Scale was nine (range 3-24; n = 10), with hypersomnia in four (36.4%). LGI1+/CASPR2+ patients had increased N1 sleep (p = .02), decreased REM sleep (p = .001), and higher levels of SM + AT any RSWA (p < .001). Eight of nine (89%) LGI1+ exceeded RBD RSWA thresholds (DEB, n = 5; isolated RSWA, n = 3). RSWA was greater in AT than SM. All 10 LGI1+/CASPR2+ patients treated with immunotherapy benefitted, and 5/10 had improved sleep disturbances. LGI1/CASPR2-IgG autoimmunity is associated with prominent dream enactment, insomnia, RSWA, sleep apnea, and shallower sleep. Polysomnography provides objective disease markers in LGI1+/CASPR2+ autoimmunity and immunotherapy may benefit associated sleep disturbances.

Identification of Latent Sleep Profiles in Middle-Aged Adults and Connections to Well-Being

For middle-aged adults, achieving adequate sleep is a challenge but essential for long-term health. The present study identified latent sleep profiles to clarify how multiple sleep variables (i.e., regularity, satisfaction, alertness, timing, efficiency, and duration) cooccur within middle-aged adults and the implications these holistic sleep experiences have for well-being. Three profiles emerged within the Midlife in the United States II dataset (MIDUS; N=4030, Mage=56.23 years): (i) good sleepers, (ii) nappers/poor night sleepers, and (iii) sufficient but irregular sleepers. Generally, good sleepers reported the best well-being, sufficient/irregular sleepers reported comparatively moderate well-being, and nappers/poor night sleepers reported the worst well-being across a variety of indicators (i.e., chronic health conditions, life satisfaction, positive affect, negative affect, and psychological well-being) after adjusting for sociodemographic characteristics. Age moderated these associations. Our findings advance understanding of sleep health as a multifaceted construct and of its connection to well-being in middle-aged adults.

Novel Approaches Examining Sleep Health as a Marker of Successful Aging

Sleep is a modifiable determinant of health. It changes with advancing age and in response to diverse contexts (e.g., related to work or one’s health). Previous studies have often used single measures of sleep duration or sleep quality. However, a recent paradigmatic shift towards multidimensional sleep health emphasizes the importance of examining how multiple sleep measures are simultaneously associated with health. This approach presents many opportunities for understanding sleep phenotypes and their potential contributions to health. Yet it also presents methodological challenges in analyzing multidimensional sleep data. This symposium showcases the most recent approaches and novel ideas examining the role of sleep health in successful aging. Paper 1 examines sleep profiles (i.e., latent groups with varying sleep characteristics) in middle-aged adults and their linkages to psychological well-being and chronic conditions with differences by age groups. Paper 2 investigates 24-hour patterns of sleep-activity rhythms and their associations with physical functioning performance in older men and women. Paper 3 showcases the utility of a sleep health composite score in examining sleep disparities and their drivers in middle- and later-adulthood. Paper 4 examines whether and how a composite sleep health measure based on actigraphy data is associated with specific characteristics of adult bipolar disorder patients. These papers use different cohorts, such as the Midlife in the United States Study, Osteoporotic Fractures in Men study, and Multi-Ethnic Study of Atherosclerosis. At the end, Dr. Wallace will discuss key findings from these studies, their methodological contributions and implications for aging, and directions for future research.

Association of Sleep, Neuropsychological Performance, and Gray Matter Volume With Glymphatic Function in Community-Dwelling Older Adults.

The glymphatic system, which is robustly enabled during some stages of sleep, is a fluid-transport pathway that clears cerebral waste products. Most contemporary knowledge regarding the glymphatic system is inferred from rodent experiments and human research is limited. Our objective is to explore the associations between human glymphatic function, sleep, neuropsychological performance, and cerebral gray matter volumes. This cross-sectional study included individuals 60 years or older who had participated in the Integrating Systemic Data of Geriatric Medicine to Explore the Solution for Health Aging study between September 2019 and October 2020. Community-dwelling older adults were enrolled at 2 different sites. Participants with dementia, major depressive disorders, and other major organ system abnormalities were excluded. Sleep profile was accessed using questionnaires and polysomnography. Administered neuropsychological test batteries included Everyday Cognition (ECog) and the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Battery (CERAD-NB). Gray matter volumes were estimated based on MRI. Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index was used as the MRI marker of glymphatic function. A total of 84 participants (mean [SD] age 73.3 [7.1] years, 47 [56.0%] women) were analyzed. Multivariate linear regression model determined that age (unstandardized β, -0.0025 [SE 0.0001]; p = 0.02), N2 sleep duration (unstandardized β, 0.0002 [SE 0.0001]; p = 0.04), and the apnea-hypopnea index (unstandardized β, -0.0011 [SE 0.0005]; p = 0.03) were independently associated with DTI-ALPS. Higher DTI-ALPS was associated with better ECog language scores (unstandardized β, -0.59 [SE 0.28]; p = 0.04) and better CERAD-NB word list learning delayed recall subtest scores (unstandardized β, 6.17 [SE 2.31]; p = 0.009) after covarying for age and education. Higher DTI-ALPS was also associated with higher gray matter volume (unstandardized β, 107.00 [SE 43.65]; p = 0.02) after controlling for age, sex, and total intracranial volume. Significant associations were identified between glymphatic function and sleep, stressing the importance of sleep for brain health. This study also revealed associations between DTI-ALPS, neuropsychological performance, and cerebral gray matter volumes, suggesting the potential of DTI-ALPS as a biomarker for cognitive disorders.

Association between fatigue and sleep disturbances during treatment for pediatric acute lymphoblastic leukemia and posttreatment neurocognitive performance.

Survivors of pediatric acute lymphoblastic leukemia (ALL) are at increased risk of neurocognitive weakness in the areas of attention, executive function, and processing speed. Although fatigue and sleep disturbances are frequent complications of ALL therapy and associated with cognitive functions, the impact of fatigue and sleep profiles during active ALL treatment on posttreatment neurocognitive performance has received limited attention. Pediatric patients (n=120) with ALL (diagnosed 2011-2016) who completed fatigue and sleep questionnaires at four time points during active treatment were enrolled in a study of neurocognitive performance. Latent class growth analysis identified subgroups of patients with similar sleep and fatigue profiles during treatment. Neurocognitive performance collected >6months post treatment on 40 participants was compared between latent classes using multivariable linear regression models. Participants (57.5% male and 79.1% Hispanic or non-Hispanic White) were classified into one of two fatigue and sleep profiles: Class 1 characterized by mild fatigue and sleep disturbances during treatment (50.8%), and Class 2 characterized by higher levels of fatigue and sleep disturbances (49.2%). Posttreatment cognitive performance was in the normal range for most measures, but significantly below normative means for executive function, verbal short-term memory, attention, and distractability measures. Compared to Class 1, Class 2 demonstrated significantly (p<.05) poorer posttreatment neurocognitive performance, particularly in measures of attention. Our findings indicate that fatigue and sleep disturbances during the first year of pediatric ALL therapy may impact long-term neurocognitive performance. Sleep and fatigue may be targets for intervention to preserve cognitive functioning in survivors.

Validation of Somno-Art Software, a novel approach of sleep staging, compared with polysomnography in disturbed sleep profiles.

Integrated analysis of heart rate (electrocardiogram [ECG]) and body movements (actimetry) during sleep in healthy subjects have previously been shown to generate similar evaluation of sleep architecture and continuity with Somno-Art Software compared to polysomnography (PSG), the gold standard. However, the performance of this new approach of sleep staging has not yet been evaluated on patients with disturbed sleep. Sleep staging from 458 sleep recordings from multiple studies comprising healthy and patient population (obstructive sleep apnea [OSA], insomnia, major depressive disorder [MDD]) was obtained from PSG visual scoring using the American Academy of Sleep Medicine rules and from Somno-Art Software analysis on synchronized ECG and actimetry. Inter-rater reliability (IRR), evaluated with 95% absolute agreement intra-class correlation coefficient, was rated as "excellent" (ICCAAAvg95% ≥ 0.75) or "good" (ICCAAAvg95% ≥ 0.60) for all sleep parameters assessed, except non-REM (NREM) and N3 sleep in healthy participants (ICCAAAvg95% = 0.43, ICCAAAvg95% = 0.56) and N3 sleep in OSA patients (ICCAAAvg95% = 0.59) rated as "fair" IRR. Overall sensitivity, specificity, accuracy, and Cohen's kappa coefficient of agreement (κ) on the entire sample were respectively of 93.3%, 69.5%, 87.8%, and 0.65 for wake/sleep classification and accuracy and κ were of 68.5% and 0.55 for W/N1+N2/N3/rapid eye movement (REM) classification. These performances were similar in healthy and patient population. The present results suggest that Somno-Art can be a valid sleep-staging tool in both healthy subjects and patients with OSA, insomnia, or MDD. It could complement existing non-attended techniques measuring sleep-related breathing patterns or be a useful alternative to laboratory-based PSG when this latter is not available.

Examining differences across sleep profiles in late middle‐aged adults: Results from the Wisconsin Registry for Alzheimer's Prevention (WRAP)

AbstractBackgroundPrevious studies suggest associations between self‐reported poor sleep and relevant health markers and AD‐related outcomes including cognition and AD pathology. It is important to understand how sleep, a modifiable risk factor, may be related to cognition and other measures of aging in late midlife when AD pathology may be accruing. The study objectives included examining whether sleep profiles were associated with concurrent health and cognition, and positron emission tomography (PET) measures of amyloid.MethodsDementia‐free participants from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) who had completed sleep questionnaires were eligible (n=619); questionnaires included the Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), and Medical Outcomes Study Sleep Scale (MOS). K‐means clustering analysis identified three clusters. We compared concurrent health markers (e.g., depression and insulin resistance) and cognitive composite scores across the sleep profile clusters. In the subset with Pittsburgh Compound B (PiB; n=107) PET imaging, we also compared amyloid measures (estimated global PiB distribution volume ratio (DVR), PiB chronicity, and PiB(+) (DVR&gt;=1.2) at sleep assessment. Significant omnibus tests (p&lt;.05) were followed with pairwise comparisons.ResultsMean(sd) sample baseline age was 62.6(6.7). Cluster analysis identified 3 groups: Healthy Sleepers (HS, n=262(42.3%)), Intermediate Sleepers (IS, n=229(37.0%)), and Poor Sleepers (PS, n=128(20.7%); Fig. 1, Fig. 2, Table 1). All omnibus tests comparing demographics and health measures across sleep groups were significant except age, gender, and APOE e4 carriers; the PS group was worse than HS and/or IS on all other measures, including self‐reported depression, health, and memory complaints (Table 2). PS performed worse than HS and/or IS on measured body mass index, waist‐hip ratio and insulin resistance (Fig. 3a); and after adjusting for covariates, PS performed worse on all cognitive outcomes except working memory (Fig. 4). There were no differences between sleep groups on measures of amyloid (Fig. 3b).ConclusionSleep profiles were associated with differences in additional modifiable risk factors and concurrent cognition, but not amyloid. Further analysis was needed in the association between the sleep constructs and amyloid clearance/accumulation. Management of sleep and related factors may provide an opportunity for early intervention that could ultimately delay or prevent clinical impairment.

Sleep patterns differ across Alzheimer's disease phenotypes: Implications for selective vulnerability and customized treatment.

Sleep-wake disturbances are a prominent feature in Alzheimer's Disease (AD), negatively impacting patients and caregivers' quality of life. Growing evidence suggests that sleep-wake dysregulation happens early in AD due to the AD-tau degeneration of the arousal system (i.e., locus coeruleus). However, whether the pattern of sleep-wake dysfunction is different among AD clinical variants and how it is different remains unclear. It is an unmet gap of high importance because these differing patterns may require tailored treatment strategies. Since AD phenotypes with different clinical profiles have distinct regional patterns of cortical tau, we hypothesized that AD variants may also have differential sleep patterns. Therefore, we aim to contrast the behavioral sleep features within AD variants. A cohort of 24 patients, including 8 amnestic AD and 16 non-amnestic AD (7 lvPPA, 9 PCA), with a neuropathological or biomarker based diagnosis of AD, underwent an overnight EEG monitoring. Sleep stages were evaluated by PRANA software and confirmed by REM Logic spectral analyses. We performed nonparametric analyses to study group differences in the amount of each sleep stage as a percent of total sleep time. Additionally, we performed linear regression models adjusting by the age of onset, MMSE, and CDR Total. There were no differences between amnestic AD, lvPPA, and PCA groups in gender, age of onset (59±11, 55±6, 59±8, respectively), global cognition (MMSE 21±7, 23±3, 21±5), or functional performance (CDR Total 0.9±0.5, 0.7±0.3, 1±0.4). Compared to non-amnestic AD, amnestic AD had more REM sleep (p<0.05) and a trend toward lower NREM sleep stages 1 and 3. In the same line, this pattern was still observed when comparing the three clinical variants (amnestic AD, lvPPA, and PCA) (p<0.05). Regression models confirmed that clinical AD variants accounted for differences in REM sleep (p<0.01). We are continuing to evaluate additional AD participants and age-matched healthy controls. Preliminary results suggest that sleep profiles might differ between AD variants. The existence of specific sleep-wake profiles would suggest differential degeneration patterns of the arousal system within AD phenotypes, which would open the door to uncover the selective vulnerability of subcortical structures for the first time.

Deep sleep predicts the cognitive evolution of mild‐moderate Alzheimer’s disease patients

AbstractBackgroundTo investigate the association between sleep and the cognitive evolution of mild‐moderate Alzheimer’s disease patients.MethodObservational, prospective, single‐center study, including consecutive patients diagnosed with mild‐moderate Alzheimer’s disease (NCT02814045). The individuals were submitted to overnight polysomnography, followed by neuropsychological evaluations at baseline and after 12 months of follow‐up. Principal component analysis characterized the sleep architecture of the cohort into two main types: individuals with a propensity to deepen their sleep (deep sleepers) and individuals who spent most of the time in the lighter sleep stage (light sleepers).ResultThe cohort included 125 subjects with a median [IQR] of 75.0 [72.0;80.0] years. The mean difference (95% CI) in the Mini‐mental state examination score at 12 months between deep and light sleepers was ‐1.51 (95% CI: ‐2.47 to ‐0.54; p‐value = 0.002). Accordingly, sleep depth and cognitive evolution presented a dose‐response relationship (p‐for‐trend = 0.02). Regarding the specific cognitive subdomains, we observed differences related to the processing speed, demonstrated by the Stroop words test (‐1.48; 95% CI: ‐2.58 to ‐0.38; p‐value = 0.009), and to the executive function, demonstrated by the Verbal fluency test (‐1.70; 95% CI: ‐2.85 to ‐0.55; p‐value = 0.004).ConclusionConsidering that light sleepers presented an increased cognitive decline, the sleep profile may have a predictive role in the cognitive evolution of mild‐moderate Alzheimer’s disease patients. The modifiable nature of sleep sets this behavior as a possible useful intervention for the improvement of cognitive evolution.

Objective home sleep profiles differentiate Alzheimer disease from α‐synucleinopathies

AbstractBackgroundNeurodegenerative disease (NDD) is associated with sleep disturbances, including decreased stage N3 and REM sleep and reduced spindle activity. Further, supine sleep position may impact NDD risk by altering glymphatic clearance. This study evaluated conventional and exploratory sleep metrics in the differentiation of subjects with normal cognition (NC) and patients with Alzheimer’s disease dementia (AD) and alpha‐synucleinopathies (α‐Syn).MethodHome sleep data were acquired across multiple study sites using the self‐applied Sleep ProfilerTM, including 44 NC subjects (age=69+5.0), 22 patients diagnosed with AD (age=75+7.1) and 25 with α‐Syn (Parkinson’s disease=14, Parkinson’s disease with Dementia or Dementia with Lewy Bodies=11; age=69+6.9). Recordings were auto‐staged and technically reviewed, with 86% of the records having two‐night averages. Logistic regression and Mann‐Whitney U tests were used to characterize group differences based on age, conventional sleep metrics (i.e., sleep efficiency, sleep onset (SO), awakenings, percent of sleep time (%) in REM,N1, N2 and N3, and sleep spindles) and exploratory sleep measures [i.e., % supine, % Light N2 (L2=N2 epochs absent of spindles with K‐complexes and/or alpha or EMG (&gt;40 Hz) intrusion), % NREM sleep with hypertonia (NRSH=&gt;4 consecutive epochs with persistently elevated EMG power relative to delta and theta power) and % atypical N3 (AN3=epochs staged N3 with low theta and sigma power relative to delta, alpha, beta and EMG)].ResultAD were older than both NC and α‐Syn patients (p&lt;0.005). Both AD and α‐Syn had lower %REM and greater %supine than NC (p&lt;0.005), and %NRSH was greater in α‐Syn than NC or AD (p&lt;0.005). Based on logistic regression, AD was differentiated from NC based on age, %REM, %L2 (p&lt;0.05) and %supine (p=0.06). α‐Syn was distinguished from NC using both conventional (%N3 and SO, p&lt;0.05) and exploratory sleep metric (%AN3 and %NRSH, p&lt;0.05; %supine, p=0.06). Age (p=0.05) and %NRSH (p&lt;0.01) were the only metrics that differentiated α‐Syn from AD.ConclusionObjective home sleep profiles hold promise for differentiating NDD patients from NC. The sleep metrics that provided the greatest distinction between NDD and NC were %REM, %supine and NRSH, while only NRSH distinguished AD from α‐Syn patients. Further confirmatory studies are underway.

Validation of technology to monitor sleep and bed occupancy in older men and women

AbstractBackgroundNocturnal disturbance is frequently observed in dementia and is a major contributor to institutionalisation. Unobtrusive technology that can quantify sleep/wake and determine bed occupancy during the major nocturnal sleep episode may be beneficial for long‐term clinical monitoring and the carer. Such technologies have, however, not been validated in older people. Here we assessed the performance of the Withings Sleep Mattress (WSM) in a heterogenous older population to ensure external validity.MethodEighteen participants (65 – 80 years, 10M:8F) completed 7‐12 days of sleep/wake monitoring at home prior to an overnight laboratory session. WSM performance was compared to gold‐standard (laboratory polysomnography [PSG] with video) and silver standard (actiwatch [AWS] and sleep diary at home). WSM data were downloaded from a third party API and the minute‐to‐minute sleep/wake timeseries extracted and time‐ordered to create a sleep profile. Discontinuities in the timeseries were labelled as ‘missing data’ events.ResultsParticipants contributed 107 nights with WSM and PSG or AWS data. In the laboratory, the overall epoch to epoch agreement (accuracy) of sleep/wake detection of WSM compared to PSG was 0.71 (sensitivity 0.8; specificity 0.45) and to AWS was 0.74 (sensitivity 0.77; specificity 0.53). Visual inspection of video recordings demonstrated that 20 of 21 ‘missing data’ events were true ‘out of bed’ events. These events were always associated with an increase in activity (AWS). At home, all 97 WSM ‘missing data’ events that occurred within the major nocturnal sleep episode defined by sleep diary data, were associated with an increase in activity levels in the AWS data and 36 of these events were also associated with an increase in light levels, indicating that the participant had left the bed. In several participants, data recorded by the WSM during daytime coincided with reported naps in the sleep diary.ConclusionAlthough WSM cannot reliably distinguish between sleep and wake, the presence/absence of data in WSM seem to be an accurate representation of whether older people are in or out of bed (bed occupancy). Thus, in dementia, this contactless, low‐burden technology may be able to provide information about nocturnal disturbances and daytime naps in bed.

Actigraphy-Derived Sleep Profiles of Children with and without Attention-Deficit/Hyperactivity Disorder (ADHD) over Two Weeks-Comparison, Precursor Symptoms, and the Chronotype.

Although sleep problems are common in children with ADHD, their extent, preceding risk factors, and the association between neurocognitive performance and neurobiological processes in sleep and ADHD, are still largely unknown. We examined sleep variables in school-aged children with ADHD, addressing their intra-individual variability (IIV) and considering potential precursor symptoms as well as the chronotype. Additionally, in a subgroup of our sample, we investigated associations with neurobehavioral functioning (n = 44). A total of 57 children (6–12 years) with (n = 24) and without ADHD (n = 33) were recruited in one center of the large ESCAlife study to wear actigraphs for two weeks. Actigraphy-derived dependent variables, including IIV, were analyzed using linear mixed models in order to find differences between the groups. A stepwise regression model was used to investigate neuropsychological function. Overall, children with ADHD showed longer sleep onset latency (SOL), higher IIV in SOL, more movements during sleep, lower sleep efficiency, and a slightly larger sleep deficit on school days compared with free days. No group differences were observed for chronotype or sleep onset time. Sleep problems in infancy predicted later SOL and the total number of movements during sleep in children with and without ADHD. No additional effect of sleep problems, beyond ADHD symptom severity, on neuropsychological functioning was found. This study highlights the importance of screening children with ADHD for current and early childhood sleep disturbances in order to prevent long-term sleep problems and offer individualized treatments. Future studies with larger sample sizes should examine possible biological markers to improve our understanding of the underlying mechanisms.

Identifying diverse forms of (un)healthy sleep: Sleep profiles differentiate adults' psychological and physical well-being

RationaleSleep health is best described by the co-occurrence of various dimensions (e.g., regularity, daytime alertness, satisfaction, efficiency, duration) but is rarely measured this way. Information is needed regarding common within-person patterns of sleep characteristics among adults and their relative healthiness. ObjectiveTo deepen understanding of healthy and unhealthy sleep, the present study aimed to uncover multidimensional sleep profiles in adults and their associations with a variety of psychological and physical well-being outcomes. MethodsSurvey data from 4622 adults who participated in the Midlife in the United States (MIDUS) project was used to identify latent sleep profiles across five core sleep dimensions. Adjusting for individual sleep dimensions and sociodemographic covariates, General Linear Models were used to test the associations of sleep profile membership with hedonic and eudemonic well-being and chronic physical conditions. ResultsFour latent sleep profiles were revealed, good sleepers, sufficient but irregular sleepers, nappers, and short, dissatisfied, and inefficient sleepers. The profiles differentially related to well-being outcomes above and beyond individual sleep dimensions and sociodemographic covariates. Good sleepers generally reported the best outcomes, and short, dissatisfied, and inefficient sleepers generally reported the worst outcomes. ConclusionFour common sleep profiles describe adults' holistic sleep experiences and predict a variety of well-being outcomes beyond other known predictors. In adulthood, healthy sleep may involve sufficient sleep across all dimensions whereas unhealthy sleep may involve insufficient sleep across three key dimensions: duration, satisfaction, and efficiency.

A Latent Profile Analysis of Sleep, Anxiety, and Mood in Youth with Craniopharyngioma

ABSTRACT Craniopharyngioma is a histologically benign brain tumor that arises in the suprasellar region affecting critical neurovascular structures including the hypothalamic-pituitary-adrenal axis and optic pathways. Children with craniopharyngioma often experience excessive daytime sleepiness (EDS) which may be compounded by anxiety and depression. The current study investigated disparate sleep profiles to better understand psychological adjustment among children diagnosed with craniopharyngioma. Method: Actigraphs recorded nightly sleep data, including measures of sleep onset latency (SOL) and wake after sleep onset (WASO), in a cohort of 80 youth between the ages of 2 and 20 years (median age = 9). Parent reports of behavioral and emotional functioning were included in the analysis. A latent profile analysis examined disparate sleep profiles, and a multinomial logistic regression examined differences of anxiety and depression among the sleep profiles. Results: The latent profile analysis revealed three sleep profiles: “healthy sleepers” (68.8%), “night wakers” (21.3%), and “prolonged onset sleepers” (10.0%). Contrary to expectations, sleep profiles were not associated with daytime anxiety (β = 2.26–4.30, p > .05) or depression (β = −5.87–4.74, p > .05). Conclusions: Youth with craniopharyngioma demonstrate poor sleep and EDS. Those with delayed SOL and prolonged WASO are particularly vulnerable to disrupted nighttime sleep, which may significantly compound EDS. Disrupted sleep was not associated with anxiety or depression, which may be related to the overall poor sleep and daytime sleepiness or to timing, as patients were early in their treatment course. Further study should evaluate the factors underlying sleepiness and daytime function in patients with craniopharyngioma.

Autism Spectrum Disorder and Intellectual Disability: A Pilot Study Exploring Associations between Child Sleep Problems, Child Factors and Parent Factors.

Sleep problems are common in children with autism spectrum disorder (ASD). However, few studies have undertaken group comparisons of sleep profiles and factors associated with poorer sleep between children with ASD without intellectual disability (ID; hereafter referred to as ASD) and ASD with co-occurring ID (hereafter referred to as ASD + ID). This study aimed to (1) compare child (sleep problems and emotional and behavioural problems (EBPs)) and parent factors (parenting stress and mental health) for children with ASD compared to children with ASD + ID, and (2) examine the associations between sleep problems and child and parent factors in both groups. Parents of 56 children with ASD (22 ASD, 34 ASD + ID) aged 6–13 years took part in the study. No statistically significant differences in sleep problems were found between children with ASD compared to children with ASD + ID. However, total EBPs were independently associated with child sleep problems in both groups. Further, ‘Self-Absorbed’ and ‘Communication Disturbance’ EBPs were significantly greater in the ASD + ID compared to the ASD group. Overall treatment outcomes for children with ASD may be further improved if consideration is given to the specific types of EBPs being experienced by the child and their association with sleep problems.

The association of the quality of sleep with proinflammatory cytokine profile in inflammatory bowel disease patients

BackgroundThe role of circadian rhythm abnormalities in patients with inflammatory bowel disease (IBD) remains relatively unknown. The aim of this study was to identify the inflammatory cytokine profile in the IBD patients and its relationship with the quality of sleep.MethodsProspective, single-center observational cohort study was performed. In all enrolled adult IBD patients, the disease activity was assessed using Crohn’s Disease Activity Index (CDAI) for Crohn’s disease (CD) and Partial Mayo Score for ulcerative colitis (UC), respectively. To assess the quality of sleep, all patients were asked to respond to a questionnaire to define Pittsburgh Quality Sleep Index (PSQI). From all enrolled patients, 15 ml venous blood was taken to determine serum inflammatory cytokine levels and perform standard laboratory tests.ResultsFifty-two IBD patients were enrolled in the study: 32 with CD and 20 with UC. The poor sleep was noted in 69.4% of patients with clinically active and in 6.3% of patients with inactive disease. In the group of IBD patients with poor sleep, the significantly higher level of serum IL-6, IL-17, and IL-23 were observed. In IBD patients with exacerbation, the significantly higher level of serum IL-6, IL-17, and IL-23 were recorded.ConclusionsThe relationship between quality of sleep and proinflammatory cytokine profile may show us a predisposition for the development of inflammatory intestinal lesions in IBD patients with sleep disturbances. This knowledge may allow the pharmacological and behavioral therapies of circadian rhythm abnormalities to become new significant targets in IBD patients.

Do self-ratings of the Pittsburgh Sleep Quality Index reflect actigraphy recordings of sleep quality or variability? An exploratory study of bipolar disorders versus healthy controls.

Sleep disturbances are typical symptoms of acute episodes of bipolar disorder (BD) and differentiate euthymic BD cases from healthy controls (HC). Researchers often employ objective recordings to evaluate sleep patterns, such as actigraphy, whilst clinicians often use subjective ratings, such as the Pittsburgh Sleep Quality Index (PSQI). As evidence suggests the measures may disagree, we decided to compare subjective (PSQI) and objective (3weeks of actigraphy) sleep profiles in BD cases and HC (n=154). We examined whether a dimensional approach helps to illustrate different patterns of sleep disturbances and whether the concordance between subjective and objective recordings varies according to clinical status (BD versus HC). Principal component analysis (PCA) extracted two factors from the PSQI, and separate PCAs of actigraphy recordings extracted two factors for mean values of sleep parameters and one factor for intra-individual variability. Correlational and linear regression analyses of PCA-derived dimensions demonstrated that, in both BD and HC, a PSQI "Sleep duration-efficiency" factor was significantly correlated with an actigraphy "Sleep initiation-duration" factor. Furthermore, in BD cases only, the PSQI total score and a PSQI "Sleep Impairments" factor were each significantly correlated with an actigraphy "Sleep Variability" factor. Overall, we found that subjective experiences of sleep may be modulated by different components of objectively recorded sleep in BD compared with HC. Also, the use of PCA enabled us to consider the multi-dimensional nature of subjective sleep, whilst the inclusion of intra-individual sleep variability afforded a more subtle evaluation of objective sleep.