Sleep misestimation among older adults suffering from insomnia with short and normal objective sleep duration and the effects of cognitive behavior therapy

Sleep discrepancy and brain glucose metabolism in community-dwelling older adults

Sleep discrepancy (negative discrepancy reflects worse self-reported sleep than objective measures, such as actigraphy, and positive discrepancy the opposite) has been linked to adverse health outcomes. This study is first to investigate the relationship between sleep discrepancy and brain glucose metabolism (assessed globally and regionally via positron emission tomography), and to evaluate the contribution of insomnia severity and depressive symptoms to any associations. Using data from cognitively unimpaired community-dwelling older adults (N = 68), cluster analysis was used to characterise sleep discrepancy (for total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE)), and logistic regression was used to explore sleep discrepancy's associations with brain glucose metabolism, while controlling for insomnia severity and depressive symptoms. Lower glucose metabolism across multiple brain regions was associated with negative discrepancy for WASO and SE, and positive discrepancy for WASO only (large effect sizes; β ≥ 0.5). Higher glucose metabolism in the superior parietal and posterior cingulate regions was associated with negative discrepancy for TST (large effect sizes; β ≥ 0.5). These associations remained when controlling for insomnia severity and depressive symptoms, suggesting a unique role of sleep discrepancy as a potential early behavioural marker of brain health.

Sleep-wake state discrepancy among cancer survivors with insomnia symptoms

PURPOSE

To evaluate the discrepancy and correlation between sleep-wake measures (i.e., time in bed (TIB), total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE%)) reported on sleep diary and measured by actigraphy among cancer survivors with insomnia symptoms; and examine the influences of sociodemographic and clinical variables on these measurement differences.

METHODS

A heterogenous sample of cancer survivors with insomnia symptoms (n = 120; M age = 63.7 ± 10.1; female = 58.3%) was included. Seven consecutive days of sleep diary and actigraphic data were obtained along with information on demographic, sleep, and mental health symptoms. Bland-Altman plot, Pearson correlation coefficient, concordance correlation coefficient, and mixed linear model approach were used to conduct the analysis.

RESULTS

Self-reported TIB, SOL, and WASO were longer than measured by actigraphy (TIB: 8.6 min. (95% CI, 3.7, 13.5; p < .001); SOL: 14.8 min. (95% CI, 9.4, 20.2; p < .0001); and WASO: 20.7 min. (95% CI, 9.4, 20.2; p < .0001), respectively); and self-reported TST and SE% were shorter than measured by actigraphy (TST: 6.8 min. (95% CI, -18.7, 5.13); and SE%: 0.7% (95%CI, -3.0, 2.0), respectively), but were not statistically significant. Sex, higher insomnia severity, and poor sleep quality were associated with discrepancy between several sleep-wake measures.

CONCLUSION

Subjective and objective sleep-wake measures may present discrepant finding among cancer survivors with symptoms of insomnia. Future research is needed to validate appropriate sleep-wake assessment, and better understand factors that influence the discrepancy that exists between measures among this population.

CLINICAL TRIAL REGISTRATION

Clinical trials identifier: NCT03810365. Date of registration: January 14, 2019.

Epidemiology of insomnia disorder in older persons according to the Diagnostic and Statistical Manual of Mental Disorders: a systematic review and meta-analysis

PURPOSE

There is a scarcity of summarizing data on the epidemiology of insomnia in older persons, especially when diagnosed with international criteria. This study aimed to estimate the prevalence and correlates of insomnia disorder in older persons, according to the Diagnostic and Statistical Manual of Mental Disorders (DSM).

METHODS

Through PubMed/MEDLINE, EMBASE, and Web of Science (WoS), we searched for relevant articles published before June 28, 2023. The risk of bias was weighed using the Joanna Briggs Institute's (JBI's) critical appraisal checklist for studies reporting prevalence data. For our analyses, we used a random-effect model, with subgroup analyses, meta-regression, and sensitivity analyses to explore potential sources of heterogeneity. We followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement.

RESULTS

We included 18,270 participants across 16 studies. The male/female ratio was 0.89 (12 studies), and the mean age varied from 65.9 to 83.1 years (8 studies). The pooled prevalence of insomnia was 19.6% (95% CI = [12.3%; 28.3%]), with substantial heterogeneity. This prevalence fluctuated according to the sample size, the minimal age for inclusion, and the study quality, considering that the risk of bias was moderate for most of studies. There was a publication bias, with a very low level of certainty. Insomnia disorder was associated with the female gender, depression, anxiety, and somatic illnesses notably cardiovascular, respiratory, and painful ones.

CONCLUSION

Nearly one in every five old individuals was considered to have insomnia disorder, which was associated with the gender and the existence of mental health and/or somatic conditions.

REGISTRATION

We registered the protocol in the International Prospective Register of Systematic Reviews (PROSPERO) with registration number: CRD42022344675.

Reconsidering sleep perception in insomnia: from misperception to mismeasurement

So-called 'sleep misperception' refers to a phenomenon in which individuals have the impression of sleeping little or not at all despite normal objective measures of sleep. It is unknown whether this subjective-objective mismatch truly reflects an abnormal perception of sleep, or whether it results from the inability of standard sleep recording techniques to capture 'wake-like' brain activity patterns that could account for feeling awake during sleep. Here, we systematically reviewed studies reporting sleep macro- and microstructural, metabolic, and mental correlates of sleep (mis)perception. Our findings suggest that most individuals tend to accurately estimate their sleep duration measured with polysomnography (PSG). In good sleepers, feeling awake during sleep is the rule at sleep onset, remains frequent in the first non-rapid eye movement sleep cycle and almost never occurs in rapid eye movement (REM) sleep. In contrast, there are patients with insomnia who consistently underestimate their sleep duration, regardless of how long they sleep. Unlike good sleepers, they continue to feel awake after the first sleep cycle and importantly, during REM sleep. Their mental activity during sleep is also more thought-like. Initial studies based on standard PSG parameters largely failed to show consistent differences in sleep macrostructure between these patients and controls. However, recent studies assessing sleep with more refined techniques have revealed that these patients show metabolic and microstructural electroencephalography changes that likely reflect a shift towards greater cortical activation during sleep and correlate with feeling awake. We discuss the significance of these correlates and conclude with open questions and possible ways to address them.

Insomnia nosology: a systematic review and critical appraisal of historical diagnostic categories and current phenotypes

Insomnia nosology has significantly evolved since the Diagnostic and Statistical Manual (DSM)-III-R first distinguished between 'primary' and 'secondary' insomnia. Prior International Classification of Sleep Disorders (ICSD) nosology 'split' diagnostic phenotypes to address insomnia's heterogeneity and the DSM nosology 'lumped' them into primary insomnia, while both systems assumed causality for insomnia secondary to health conditions. In this systematic review, we discuss the historical phenotypes in prior insomnia nosology, present findings for currently proposed insomnia phenotypes based on more robust approaches, and critically appraise the most relevant ones. Electronic databases PsychINFO, PubMED, Web of Science, and references of eligible articles, were accessed to find diagnostic manuals, literature on insomnia phenotypes, including systematic reviews or meta-analysis, and assessments of the reliability or validity of insomnia diagnoses, identifying 184 articles. The data show that previous insomnia diagnoses lacked reliability and validity, leading current DSM-5-TR and ICSD-3 nosology to 'lump' phenotypes into a single diagnosis comorbid with health conditions. However, at least two new, robust insomnia phenotyping approaches were identified. One approach is multidimensional-multimethod and provides evidence for self-reported insomnia with objective short versus normal sleep duration linked to clinically relevant outcomes, while the other is multidimensional and provides evidence for two to five clusters (phenotypes) based on self-reported trait, state, and/or life-history data. Some approaches still need replication to better support whether their findings identify true phenotypes or simply different patterns of symptomatology. Regardless, these phenotyping efforts aim at improving insomnia nosology both as a classification system and as a mechanism to guide treatment.

Does providing feedback and guidance on sleep perceptions using sleep wearables improve insomnia? Findings from "Novel Insomnia Treatment Experiment": a randomized controlled trial

STUDY OBJECTIVES

Insomnia is a disorder diagnosed based on self-reported sleep complaints. Differences between self-reported and sensor-based sleep parameters (sleep-wake state discrepancy) are common but not well-understood in individuals with insomnia. This two-arm, parallel-group, single-blind, superiority randomized-controlled trial examined whether monitoring sleep using wearable devices and providing support for interpretation of sensor-based sleep data improved insomnia symptoms or impacted sleep-wake state discrepancy.

METHODS

A total of 113 (age M = 47.53; SD = 14.37, 64.9% female) individuals with significant insomnia symptoms (Insomnia Severity Index(ISI) ≥10) from the community were randomized 1:1 (permuted block randomization) to receive 5 weeks (1) Intervention (n = 57): feedback about sensor-based sleep (Fitbit and EEG headband) with guidance for data interpretation and ongoing monitoring, and (2) Control (n = 56): sleep education and hygiene. Both groups received one individual session and two check-in calls. The ISI (primary outcome), sleep disturbance (SDis), sleep-related impairment (SRI), depression, and anxiety were assessed at baseline and post-intervention.

RESULTS

In total, 103 (91.2%) participants completed the study. Intention-to-treat multiple regression with multiple imputations showed that after controlling for baseline values, compared to the Control group (n = 51), the Intervention group (n = 52) had lower ISI (p = .011, d = 0.51) and SDis (p = .036, d = 0.42) post-intervention, but differences in SRI, depression, anxiety, and sleep-wake state discrepancy parameters (total sleep time, sleep onset latency, and wake after sleep onset) were not meaningful (P-values >.40).

CONCLUSIONS

Providing feedback and guidance about sensor-based sleep parameters reduced insomnia severity and sleep disturbance but did not alter sleep-wake state discrepancy in individuals with insomnia more than sleep hygiene and education. The role of sleep wearable devices among individuals with insomnia requires further research.

CLINICAL TRIAL REGISTRATION

The Novel Insomnia Treatment Experiment (NITE): the effectiveness of incorporating appropriate guidance for sleep wearables in users with insomnia. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378452, Australia New Zealand Clinical Trials Registry: ACTRN12619001636145.

Treatment of insomnia based on the mechanism of pathophysiology by acupuncture combined with herbal medicine: A review

Insomnia is a sleep disorder which severely affects patients mood, quality of life and social functioning, serves as a trigger or risk factor to a variety of diseases such as depression, cardiovascular and cerebrovascular diseases, obesity and diabetes, and even increases the risk of suicide, and has become an increasingly widespread concern worldwide. Considerable research on insomnia has been conducted in modern medicine in recent years and encouraging results have been achieved in the fields of genetics and neurobiology. Unfortunately, however, the pathogenesis of insomnia remains elusive to modern medicine, and pharmacological treatment of insomnia has been regarded as conventional. However, in the course of treatment, pharmacological treatment itself is increasingly being questioned due to potential dependence and drug resistance and is now being replaced by cognitive behavior therapy as the first-line treatment. As an important component of complementary and alternative medicine, traditional Chinese medicine, especially non-pharmacological treatment methods such as acupuncture, is gaining increasing attention worldwide. In this article, we discuss the combination of traditional Chinese medicine, acupuncture, and medicine to treat insomnia based on neurobiology in the context of modern medicine.

Effects of Non-Pharmacological Sleep Interventions in Older Adults: A Systematic Review and Meta-Analysis

This study investigated the effects of non-pharmacological interventions on sleep in older people through a systematic review and meta-analysis. We conducted a literature search using eight electronic databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Participant characteristics, the contents of the evaluated interventions, and the measured outcomes were systematically reviewed for 15 selected studies. We performed a meta-analysis to estimate the effect size for overall, aggregated sleep outcomes. Due to the small number of studies available for each intervention, only the overall effectiveness of non-pharmacological sleep interventions was evaluated. The evaluated interventions included exercise, aromatherapy, acupressure, cognitive behavior therapy, and meditation. Our results demonstrated that non-pharmacological interventions showed statistically significant effects on sleep (effect size = 1.00, 95% confidence interval: 0.16, 1.85, I2 = 92%, p < 0.001). After confirming publication bias and removing outliers, we found no heterogeneity (I2 = 17%, p = 0.298), with a decrease in effect size to 0.70 (95% confidence interval: 0.47, 0.93). Non-pharmacological interventions are effective for improving sleep in older adults. Future studies should continue to investigate sleep problems and interventions addressing these problems in this demographic, particularly in older women. Objective measures should be used to follow-up on the evaluated sleep interventions over the long term.

Emerging applications of objective sleep assessments towards the improved management of insomnia

Self-reported sleep difficulties are the primary concern associated with diagnosis and treatment of chronic insomnia. This said, in-home sleep monitoring technology in combination with self-reported sleep outcomes may usefully assist with the management of insomnia. The rapid acceleration in consumer sleep technology capabilities together with their growing use by consumers means that the implementation of clinically useful techniques to more precisely diagnose and better treat insomnia are now possible. This review describes emerging techniques which may facilitate better identification and management of insomnia through objective sleep monitoring. Diagnostic techniques covered include insomnia phenotyping, better detection of comorbid sleep disorders, and identification of patients potentially at greatest risk of adverse outcomes. Treatment techniques reviewed include the administration of therapies (e.g., Intensive Sleep Retraining, digital treatment programs), methods to assess and improve treatment adherence, and sleep feedback to address concerns about sleep and sleep loss. Gaps in sleep device capabilities are also discussed, such as the practical assessment of circadian rhythms. Proof-of-concept studies remain needed to test these sleep monitoring-supported techniques in insomnia patient populations, with the goal to progress towards more precise diagnoses and efficacious treatments for individuals with insomnia.

Sleep duration of lactating mothers and its relationship with feeding pattern, milk macronutrients and related serum factors: A combined longitudinal cohort and cross-sectional study

Objective

Insufficient sleep is common in postpartum mothers. The main objectives of this study are to explore the sleep duration among Chinese lactating mothers and preliminarily investigate the relationship between sleep duration and feeding pattern. The secondary objectives are to investigate the relationships between sleep duration and milk macronutrients and between maternal-related indicators, including melatonin (MT), growth hormone (GH), ghrelin (GHRL), glucagon-like peptide-1 (GLP-1), prolactin (PRL), and cholecystokinin (CCK).

Methods

The present study comprises a longitudinal and a cross-sectional cohort from December 2019 to December 2021. Postpartum lactating women living in Shanghai were recruited through online and offline recruitment. The subjects were included in the longitudinal cohort or cross-sectional study based on their lactation period at the time of recruitment. The longitudinal cohort included a total of 115 mothers. Human milk and feeding pattern were measured and collected at 2–4 months and 5–7 months postpartum. At four predetermined follow-up time points, data on sleep duration was collected (at the time of recruitment, 2–4 months postpartum, 5–7 months postpartum, and 12–17 months postpartum). The cross-sectional study included 35 lactating mothers (2–12 months postpartum) who reported their sleep duration and provided blood samples. Mid-infrared spectroscopy (MIRS) method was used to analyze the macronutrients of breast milk, while MT, GH, GHRL, GLP-1, PRL, and CCK in maternal blood were determined by ELISA.

Results

The maternal sleep duration before pregnancy was 8.14 ± 1.18 h/d (n = 115), 7.27 ± 1.31 h/d (n = 113) for 2–4 months postpartum, 7.02 ± 1.05 h/d (n = 105) for 5–7 months postpartum, and 7.45 ± 1.05 h/d (n = 115) for 12–17 months postpartum. The incidence of insufficient sleep (<7 h/d) before pregnancy (12.17%) was significantly less than at any follow-up time after delivery (vs. 2–4 months postpartum, χ² = 10.101, p = 0.001; vs. 5–7 months postpartum, χ² = 15.281, p < 0.0001; vs. 12–17 months postpartum, χ² = 6.426, p = 0.011). The percentage of insufficient maternal sleep was highest at 5–7 months postpartum (34.29%). No significant difference was found between the incidence of insufficient sleep at 5–7 months postpartum, 2–4 months postpartum (29.20%, χ² = 0.650, p = 0.420), and 12–17 months postpartum (25.22%, χ² = 2.168, p = 0.141). At 2–4 months postpartum, the frequency of formula feeding per day is related to reduced maternal sleep duration (Standardization coefficient β = −0.265, p = 0.005, Adjusted R² = 0.061). At 2–4 months and 5–7 months postpartum, the relationship between macronutrients in breast milk and the mother's sleep duration was insignificant (all p > 0.05). Other than the positive correlation found between maternal GHRL and sleep duration (r = 0.3661, p = 0.0305), no significant relationship was observed between sleep duration and other indexes (all p > 0.05).

Conclusions

Postpartum mothers generally sleep less, but there is no correlation between insufficient sleep and the macronutrient content of breast milk. Formula feeding may be related to the mother's sleep loss, while breastfeeding (especially direct breastfeeding) may be related to increased maternal sleep duration. The findings suggest that sleep duration is related to maternal serum GHRL. More high-quality studies are needed to clarify the mechanism of these findings and provide a solid theoretical basis and support references for breastfeeding.

Differences between subjective and objective sleep duration according to actual sleep duration and sleep-disordered breathing: the Nagahama Study

STUDY OBJECTIVES

Since subjective sleep duration (SSD) is considered to be longer than objective sleep duration (OSD), results of SSD minus OSD (SSD-OSD) might always be thought to be positive. Some recent reports showed different results, but exact results have not been obtained. The difference between SSD and OSD may change according to OSD. We investigated this difference and its association with sleep-disordered breathing (SDB) or nonrestorative sleep.

METHODS

This cross-sectional study evaluated 6,908 community residents in Nagahama, Japan. SSD was determined by self-administered questionnaire. OSD was measured by wrist actigraphy and sleep diary. SDB was assessed according to the 3% oxygen desaturation index adjusted for OSD.

RESULTS

Worthy of notice was that SSD was shorter than OSD for those with SSD longer than 6.98 hours in all participants, 7.36 hours in males, and 6.80 hours in females. However, SSD was longer than OSD (mean ± SD: 6.49 ± 1.07 vs 6.01 ± 0.96; P < .001) overall, as SSD is considered to be longer than OSD. In patients with SDB, the difference between SSD-OSD was greater when OSD was shorter. The difference also depended on SDB severity. The degree of positivity between OSD and SSD was a significant factor in nonrestorative sleep (odds ratio: 2.691; P < .001).

CONCLUSIONS

When OSD was slightly less than 7 (6.98) hours, participants reported or perceived SSD > OSD. When OSD was > 6.98 hours, participants reported or perceived SSD < OSD. Patients with SDB reported longer SSD than OSD according to severity of SDB. Evaluating SSD, OSD, and their differences may be useful for managing sleep disturbances, including nonrestorative sleep.

CITATION

Takahashi N, Matsumoto T, Nakatsuka Y, et al. Differences between subjective and objective sleep duration according to actual sleep duration and sleep-disordered breathing: the Nagahama Study. J Clin Sleep Med. 2022;18(3):851-859.

Subtypen der Insomnie – exemplarische Ansätze und offene Fragen

Verschiedene Autorinnen und Autoren nehmen an, dass es klinisch nützlich und wissenschaftlich erkenntnisbringend sein könnte, Subtypen der Insomnie zu identifizieren, um diese spezifisch und damit möglicherweise effektiver zu behandeln, als dies derzeit geschieht. Im vorliegenden Beitrag werden folgende exemplarisch ausgewählte Ansätze zur Einteilung der Insomnie in Subtypen vorgestellt: 1) Einteilungen nach klinischen Symptomen; 2) Primäre vs. sekundäre Insomnie; 3) Subtypen nach ICSD‑2; 4) Insomnie mit und ohne objektiv messbare kurze Schlafdauer; 5) Subtypen aus der Netherlands Sleep Registry. Anschließend werden die Stabilität der Zuordnung von einzelnen Patienten zu den verschiedenen Subtypen sowie die klinische Relevanz der Einteilungen kritisch diskutiert.