Sleep and cognitive performance: cross-sectional associations in the UK Biobank

Lifetime depression, sleep disruption and brain structure in the UK Biobank cohort

Whether depression and poor sleep interact or have statistically independent associations with brain structure and its change over time is not known. Within a subset of UK Biobank participants with neuroimaging and subjective and/or objective sleep data (n = 28,351), we examined associations between lifetime depression and sleep disruption, and their interaction with structural neuroimaging measures, both cross-sectionally and longitudinally. Sleep variables were: self-reported insomnia and difficulty getting up; actigraphy-derived short sleep (<7 h); sustained inactivity bouts during daytime (SIBD); and sleep efficiency. Imaging measures were white matter microstructure, subcortical volumes, cortical thickness and surface area of 24 cortical regions of interest. Individuals with lifetime depression (self-reported, mental health questionnaire or health records) were contrasted with healthy controls. Interactions between depression and difficulty getting up for i) right nucleus accumbens volume and ii) mean diffusivity of forceps minor, reflected a larger negative association of poor sleep in the presence vs. absence of depression. Depression was associated with widespread reductions in white matter integrity. Depression, higher SIBD and difficulty getting up were individually associated with smaller cortical volumes and surface area, particularly in the frontal and parietal lobes. Many regions showed age-related decline, but this was not exacerbated by either depression or sleep disturbance. Overall, we identified widespread cross-sectional associations of both lifetime depression and sleep measures with brain structure. Findings were more consistent with additive rather than synergistic effects - although in some regions we observed greater magnitude of deleterious associations from poor sleep phenotypes in the presence of depression.

About Digitalisation and AI, Data Protection, Data Exchange, Data Mining-Legal Constraints/Challenges Concerning Sleep Medicine

The revolution of artificial intelligence (AI) methods in the scope of the last years has inspired a deluge of use cases but has also caused uncertainty about the actual utility and boundaries of these methods. In this overview, we briefly introduce their main characteristics before focusing on use cases in sleep medicine, discriminating four main areas: Measuring sleep state, advancing diagnostics, advancing research and general advances. We then outline the current European legal framework on AI and the related topic of data sharing.

Sleep Health and White Matter Integrity in the UK Biobank

Many people experience impaired sleep health, yet knowledge about its neurobiological correlates is limited. As previous studies have found associations between white matter integrity and several sleep traits, white matter integrity could be causally implicated in poor sleep health. However, these studies were often limited by small sample sizes. In this study, we examine associations between multiple indices of white matter integrity and sleep health in 29,114 UK Biobank participants. Late chronotype, daytime sleepiness, insomnia symptoms and, most extensively, long sleep duration were independently associated with diffusion MRI markers of reduced white matter integrity. Previous findings showing an association between insomnia symptoms and decreased fractional anisotropy (FA) in the anterior internal capsule could not be replicated. To our knowledge, the current analysis is the first study to find an association between long sleep duration and impaired microstructural white matter integrity. Previous assumptions concerning the role of white matter integrity for insomnia are challenged.

Effects of Sleep-Disordered Breathing on Daytime Brain Activity in Community-Dwelling Older Adults

Introduction  Sleep-disordered breathing (SDB) is associated with an increased risk of cardiovascular diseases. The present study aimed to examine the influence of SDB on daytime brain activity in the community-dwelling older adults. Material and Methods  Eighty one consecutive volunteers aged 60 years or older (mean age 70.5 ± 4.8 years) participated in the present study. Daytime brain activity was assessed by measuring the peak cortical oxygenated hemoglobin (OxyHb) levels and area under the near-infrared spectroscopy (NIRS) curve. The respiratory event index (REI) and 3% oxygen desaturation index (3%ODI) were evaluated using a home sleep-apnea test. Results  The peak OxyHb and area under the NIRS curve were significantly lower in the participants with REI ≥ 15/h than those with REI < 15/h. The body mass index (BMI), REI, 3%ODI, and Epworth sleepiness scale (ESS) scores were significantly correlated with peak OxyHb levels (BMI: r  = -0.202, p  = 0.035; REI: r  = -0.307, p  = 0.003; 3%ODI: r  = -0.321, p  = 0.002; and ESS score: r  = -0.287, p  = 0.005). Also, the BMI, REI, and 3%ODI were significantly correlated with the area under the NIRS curve (BMI: r  = -0.306, p  = 0.002; REI: r  = -0.326, p  = 0.002; and 3%ODI: r =-0.322, p  = 0.002), and BMI was a significant factor associated with the area under the NIRS curve. Conclusions  Brain activity during wakefulness was associated with severities of SDB and obesity. A simple NIRS may yield unique information for characterizing the decline in daytime brain activity of the community-dwelling older adults.

Social Determinants of Health Predict Sleep-Wake Disturbances Among Patients Living With Primary Brain Tumors: A Cross-Sectional Analysis

INTRODUCTION

Sleep disturbance (SD) and sleep-related impairment (SRI) significantly impact the lives of primary brain tumor (PBT) patients. We aimed to describe the prevalence of SD and SRI in this population, determine the reliability of the PROMIS-SD and PROMIS-SRI instruments, and identify predictive factors to support the development of targeted interventions for at-risk individuals.

METHODS

This cross-sectional study evaluated SD and SRI in PBT patients enrolled in a Natural History Study who completed 1-year follow-up questionnaires (N = 229). Demographic, clinical, and socioeconomic data were analyzed to identify factors associated with SD and SRI. Descriptive statistics were used to report the prevalence of sleep problems, and linear regression analysis was conducted to identify predictive factors. The reliability of sleep-related instruments was calculated using Cronbach's alpha.

RESULTS

Fifteen percent of PBT participants reported clinically significant SD and 20% reported clinically significant SRI, which were associated with financial toxicity (p < 0.001), being unemployed (p ≤ 0.02), and taking psychotropic medication (p ≤ 0.002). Good internal consistency was demonstrated by the SD (0.923) and SRI (0.925) questionnaires in this population.

CONCLUSIONS

In this study, social factors such as financial toxicity and employment status were associated with SD and SRI. Psychotropic medications also impacted SD and SRI in PTB survivors, but less so than financial toxicity. Social factors and other medications may impact sleep more strongly in PBT survivors than their previous treatment courses.

IMPLICATIONS FOR CANCER SURVIVORS

SD and SRI can be impacted by multiple factors, including those not related to PBT treatment, which should be considered by their providers.

The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks

STUDY OBJECTIVES

Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN).

METHODS

We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores.

RESULTS

Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD.

CONCLUSIONS

We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

Memory performance mediates subjective sleep quality associations with cerebrospinal fluid Alzheimer's disease biomarker levels and hippocampal volume among individuals with mild cognitive symptoms

Sleep disturbances are prevalent in Alzheimer's disease (AD), affecting individuals during its early stages. We investigated associations between subjective sleep measures and cerebrospinal fluid (CSF) biomarkers of AD in adults with mild cognitive symptoms from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study, considering the influence of memory performance. A total of 442 participants aged >50 years with a Clinical Dementia Rating (CDR) score of 0.5 completed the Pittsburgh Sleep Quality Index questionnaire and underwent neuropsychological assessment, magnetic resonance imaging acquisition, and CSF sampling. We analysed the relationship of sleep quality with CSF AD biomarkers and cognitive performance in separated multivariate linear regression models, adjusting for covariates. Poorer cross-sectional sleep quality was associated with lower CSF levels of phosphorylated tau and total tau alongside better immediate and delayed memory performance. After adjustment for delayed memory scores, associations between CSF biomarkers and sleep quality became non-significant, and further analysis revealed that memory performance mediated this relationship. In post hoc analyses, poorer subjective sleep quality was associated with lesser hippocampal atrophy, with memory performance also mediating this association. In conclusion, worse subjective sleep quality is associated with less altered AD biomarkers in adults with mild cognitive symptoms (CDR score 0.5). These results could be explained by a systematic recall bias affecting subjective sleep assessment in individuals with incipient memory impairment. Caution should therefore be exercised when interpreting subjective sleep quality measures in memory-impaired populations, emphasising the importance of complementing subjective measures with objective assessments.

Causal relationship between sleep disorders and the risk of Alzheimer's disease: A Mendelian randomization study

BACKGROUND AND OBJECTIVE

Epidemiological studies have shown that sleep disorders are risk factors for Alzheimer's disease (AD), but the causal relationship between sleep disorders and AD risk is unknown. We aim to assess the potential genetic causal association between sleep characteristics and AD, which may contribute to early identification and prediction of risk factors for AD.

METHODS

Seven sleep-related traits and the outcome phenotype AD were selected from published genome-wide association studies (GWASs). These sleep-related characteristics and instrumental variables (IVs) for AD were extracted. Two-sample and multivariate Mendelian randomization (MR) analyses were performed to assess the causal relationships between sleep characteristics and AD. The inverse variance weighted (IVW), weighted median (WME), weighted mode (WM), MR-Egger regression (MR-Egger) and simple mode (SM) models were used to evaluate causality. The existence of pleiotropy was detected and corrected by MR-Egger regression, MR pleiotropy residuals and outliers.

RESULTS

A two-sample MR study revealed a positive causal association between sleep duration and the onset of AD (OR = 1.002, 95 % CI: 1.000-1.004), and the risk of AD increased with increasing sleep duration. The MR-Egger regression method and MR-PRESSO were used to identify and correct pleiotropy, indicating that there was no horizontal pleiotropy. Heterogeneity was evaluated by Cochran's Q, which indicated no heterogeneity. In a multivariate MR study with seven sleep characteristics corrected for each other, we found that sleep duration remained causally associated with AD (OR = 1.004, 95 % CI: 1.000-1.007). Moreover, we found that after mutual correction, daytime napping had a causal relationship with the onset of AD, and daytime napping may reduce the risk of AD (OR = 0.995, 95 % CI: 0.991-1.000).

CONCLUSION

This study is helpful for the early identification and prediction of risk factors for AD, long sleep durations are a risk factor for AD, and daytime napping can reduce the risk of AD.

Exploring the relationship between response time sequence in scale answering process and severity of insomnia: A machine learning approach

Utilizing computer-based scales for cognitive and psychological evaluations allows for the collection of objective data, such as response time. This cross-sectional study investigates the significance of response time data in cognitive and psychological measures, with a specific focus on its role in evaluating sleep quality through the Insomnia Severity Index (ISI) scale. A mobile application was designed to administer scale tests and collect response time data from 2729 participants. We explored the relationship between symptom severity and response time. A machine learning model was developed to predict the presence of insomnia symptoms in participants using response time data. The result revealed a statistically significant difference (p < 0.01) in the total response time between participants with or without insomnia symptom. Furthermore, a strong correlation was observed between the severity of specific insomnia aspects and the response times at the individual questions level. The machine learning model demonstrated a high predictive Area Under the ROC Curve (AUROC) of 0.824 in predicting insomnia symptoms based on response time data. These findings highlight the potential utility of response time data to evaluate cognitive and psychological measures.

Shorter sleep duration and lesser sleep efficiency are associated with poorer memory functions among non-demented, middle-aged, and older rural Indians

Introduction

Sleep is known to be involved in cognitive processes, such as memory encoding and consolidation, and poor sleep is a potential risk factor for dementia. This study aims to investigate the effect of sleep quality on memory functions among middle-aged and older adults from a rural Indian population.

Methods

Participants were non-demented, rural Indians (≥45 years) from an ongoing, prospective, aging cohort study, namely Srinivaspura Aging, NeuroSenescence, and COGnition (SANSCOG) study. Cross-sectional (baseline) data on seven sleep dimensions was obtained using the Pittsburgh Sleep Quality Index (PSQI). Memory functions were assessed using immediate recall, delayed recall, name-face association, and semantic association from a culturally validated, computerized, neurocognitive test battery. Linear regression models, unadjusted and adjusted for cognitive status, age, sex, and depression were used to analyze the association between each sleep dimension and the memory tests.

Results

A total of 1195 participants, with a mean age of 57.10 years, were included. Out of the seven sleep dimensions of the PSQI, only two dimensions, namely sleep duration and sleep efficiency, were significantly associated with memory functions. In the fully adjusted model, shorter sleep duration was significantly associated with poorer performance in delayed recall, and lesser sleep efficiency was significantly associated with poorer delayed recall and semantic association performance.

Conclusions

Specific sleep characteristics appear to influence memory functions in aging Indians well before the onset of dementia. In the backdrop of the non-availability of a definitive treatment for dementia, promptly identifying and addressing these problems could be an effective, community-level strategy for preventing dementia.

Sleep duration, chronotype, health and lifestyle factors affect cognition: a UK Biobank cross-sectional study

Objective

To explore the nuanced relationship between sleep patterns, chronotype, quality and the influence of health and lifestyle factors on cognitive performance.

Design setting participants

This cross-sectional analysis used ordinary least squares regression within the UK Biobank database, assessing 26 820 participants aged 53-86 years, categorised into two cohorts: Cohort 1 (10 067 participants, 56% female; completed all four cognitive tests of Fluid Intelligence/reasoning, Pairs Matching, Reaction Time and Prospective Memory) and Cohort 2 (16 753 participants, 56% female; completed only two cognitive assessments of Pairs Matching and Reaction Time).

Exposures

Participant's self-reported sleep duration, chronotype and quality. Cognitive function was assessed through standardised computerised tests. The analysis was adjusted for demographic and comorbidity covariates.

Main outcomes and measures

Cognitive performance scores were evaluated against sleep parameters and health and lifestyle factors including sex, age, vascular and cardiac conditions, diabetes, alcohol intake, smoking habits and body mass index.

Results

The regression highlighted a positive association between normal sleep duration (7-9 hours) and cognitive scores in Cohort 1 (β=0.0567, 95% CI 0.0284 to 0.0851), while extended sleep duration negatively impacted scores across both cohorts (Cohort 1: β=-0.188, 95% CI -0.2938 to -0.0822; Cohort 2: β=-0.2619, 95% CI -0.3755 to -0.1482). Chronotype distinctions, particularly intermediate and evening types, were linked to superior cognitive function. Gender, age, angina, high blood pressure, diabetes, alcohol intake and smoking emerged as significant cognitive influencers.

Conclusions and relevance

The study delineates a multifaceted and nuanced relationship between sleep variables, health and lifestyle factors in determining cognitive outcomes. These findings highlight the vital role of sleep quality on cognitive health.

Long Objective Sleep Duration is a Marker of Cognitive Impairment in Older Adults: Findings from the Cretan Aging Cohort

 We examined associations between objective sleep duration and cognitive status in older adults initially categorized as cognitively non-impaired (CNI, n = 57) or diagnosed with mild cognitive impairment (MCI, n = 53). On follow-up, 8 years later, all participants underwent neuropsychiatric/neuropsychological evaluation and 7-day 24-h actigraphy. On re-assessment 62.7% of participants were cognitively declined. Patients who developed dementia had significantly longer night total sleep time (TST) than persons with MCI who, in turn, had longer night TST than CNI participants. Objective long sleep duration is a marker of worse cognitive status in elderly with MCI/dementia and this association is very strong in older adults.

Association of Sleep Status With Cognitive Functions in Centenarians: Evidence From Hainan Centenarian Cohort

OBJECTIVES

This study aimed to analyze the association between sleep quality, sleep duration, and cognitive functions among centenarians.

METHODS

The baseline data of the China Hainan Centenarians Cohort Study served as the foundation for this study. Logistic regression was utilized to demonstrate the relationship between sleep status and cognitive impairment. Moreover, a canonical correlation analysis was performed to analyze the correlation between these variables.

RESULTS

A total of 994 centenarians were included. After adjustment, poor sleep quality centenarians had an odds ratio of 1.77 (95% confidence interval [CI]: 1.00-3.09) for cognitive impairment when compared to centenarians with normal sleep quality. Centenarians who slept for more than 9 hr had a stronger association with severe cognitive impairment, indicated by an odds ratio of 1.41 (95% CI: 1.02-1.96), compared to those who slept for 7-9 hr. Additionally, the canonical correlation analysis results revealed that the linear combination of sleep quality V1, primarily determined by sleep latency, daytime dysfunction, and subjective sleep quality, was associated with cognitive function; the linear combination of cognitive function W1, mainly determined by orientation, attention and calculation, and memory.

DISCUSSION

There exists a correlation between poor sleep quality and cognitive impairment in centenarians, as well as a correlation between sleep duration >9 hr at night and severe cognitive impairment. The primary cognitive domains associated with sleep quality are orientation, calculation, and memory. It is imperative to monitor and safeguard the cognitive functions linked to poor sleep quality in the older individuals, with attention to orientation, calculation, and memory.

Shorter self-reported sleep duration is associated with worse virtual spatial navigation performance in men

Sleep has been shown to impact navigation ability. However, it remains unclear how different sleep-related variables may be independently associated with spatial navigation performance, and as to whether gender may play a role in these associations. We used a mobile video game app, Sea Hero Quest (SHQ), to measure wayfinding ability in US-based participants. Wayfinding performance on SHQ has been shown to correlate with real-world wayfinding. Participants were asked to report their sleep duration, quality, daytime sleepiness and nap frequency and duration on a typical night (n = 766, 335 men, 431 women, mean age = 26.5 years, range = 18-59 years). A multiple linear regression was used to identify which self-reported sleep variables were independently associated with wayfinding performance. Shorter self-reported sleep durations were significantly associated with worse wayfinding performance in men only. Other self-reported sleep variables showed non-significant trends of association with wayfinding performance. When removing non-typical sleepers (< 6 or > 9 h of sleep on a typical night), the significant association between sleep duration and spatial navigation performance in men was no longer present. These findings from U.S.-based participants suggest that a longer self-reported sleep duration may be an important contributor to successful navigation ability in men.

Sleep duration, insomnia and cognitive performance in the Elsa-Brasil cohort: a cross-sectional analysis

OBJECTIVE

To investigate the single and combined associations between sleep disturbances (sleep duration, insomnia symptoms in the last 30 nights, and daytime tiredness) and performance in cognitive tests.

METHODS

Cross-sectional analysis of data from visit 2 (2012-2014) of the Longitudinal Study of Adult Health from a cohort of active and retired civil servants from six Brazilian capitals. Polynomial regression with quadratic term and multiple linear regression models were performed to assess single and combined associations between sleep disturbances and memory performance, fluency, executive functions, and global cognition.

RESULTS

A total of 7,248 participants were included, with a mean age of 62.7 years (standard deviation [SD]=5.9), and 55.2% were women. Inverted U-shaped associations were observed between sleep duration and performance on all cognitive abilities, suggesting that durations shorter or longer than seven hours are associated with worse performance, regardless of age. Reported insomnia was associated with worse executive function (β: -0.08; 95% confidence interval [CI]: -0.15 to -0.01), and the magnitudes of associations were higher for individuals with insomnia at two or more moments (β: -0.12; 95%CI -0.19 to -0.05) or, especially, insomnia combined with short sleep (β: -0.18; 95%CI -0.24 to -0.11). Insomnia in two or more periods was also associated with lower memory and global cognition. There was no association between any sleep disturbance tested and verbal fluency. Isolated daytime tiredness was not associated with performance in the evaluated tests.

CONCLUSION

The results suggest that extreme sleep durations are detrimental to almost all cognitive abilities investigated, whereas insomnia appears to affect more severely the executive function.

Association between sleep hours and changes in cognitive function according to the morningness-eveningness type: A population-based study

OBJECTIVE

The aim of this study was to investigate proper sleep hours to reduce the risk of cognitive decrease considering morningness-eveningness type.

METHODS

The Korean Community Health Survey was used, which includes adults aged over 19 years old. These data were obtained from a cross-sectional study and assessed sleep hours using questionnaire of Pittsburgh Sleep Quality Index. Based on the wake-up time of each participant, they were classified into the morningness, intermediate, eveningness, and none groups. The change in cognitive function was determined by a single question about memory loss experience.

RESULTS

A total of 224,714 participants were included in the analysis. Of the participants, 55.6 % and 5.0 % of whom had morningness and eveningness, respectively. The risk of cognitive decline was significantly different by sleep hours and morningness-eveningness type. Without considering sleep quality, the intermediate and eveningness groups showed a higher risk of cognitive decline than the morningness group, and the risk was lowest in those with 7-9 sleep hours. However, when sleep quality showing significant effect was included in the analysis, sleep hours showing the lowest risk were different among morningness, intermediate, eveningness groups, and it was the shortest in the morningness type at 5-6 h and the longest in the eveningness type at 7-8 h.

CONCLUSION

Proper sleep hours to decrease the risk of cognitive decline may be different by morningness-eveningness types. However, when considering sleep quality, sleep duration had little influence on cognitive decline. Future studies investigating healthy sleep hours need to consider sleep quality as well as the habitual sleep schedules.

LIMITATIONS

The morningness-eveningness types were classified based on wake-up time not morningness-eveningness types. The morningness-eveningness types in this study would be interpreted as habitual sleep schedule rather than chronotype.

Impact of subjective sleep quality on objective measures of neurocognitive dysfunction in patients with major depressive disorder

Background

Sleep disturbances are prevalent in major depressive disorder (MDD). MDD and sleep disturbances are both linked to cognitive impairments. Studies exploring the mechanisms and impact of sleep disturbances on neurocognitive functioning in depressed patients are lacking and proper assessment and therapeutic interventions for sleep disturbances are not part of clinical management of MDD.

Aim

We investigated the association between subjective sleep quality and neurocognitive dysfunction in patients with MDD.

Materials and Methods

Patients with moderate MDD episode were matched and assigned to two groups with poor and good sleep quality. We used Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality. To measure frontotemporally mediated cognitive functioning, following tests were administered: Wisconsin Card Sorting Test (WCST) and degraded continuous performance test (CPT-DS). Two-tailed independent samples t tests or Mann-Whitney U tests and Pearson's correlation coefficient were performed for the statistical analysis of sleep latency, sleep duration, overall sleep quality, CPT d' value, WCST correct answers, errors, and perseverative errors.

Results

Participants with MDD and poor sleep quality performed worse on cognitive tests compared to patients with MDD and good sleep quality. Scores of subjective sleep on PSQI positively correlated with WCST errors (r (60) =0.8883 P = .001) and negatively correlated with WCST correct answers (r (60) = -.869 P = .001) and measures of CPT-DS d' value (r (60) = -.9355 P = .001).

Conclusions

Poor sleep quality, notably sleep duration and sleep latency, worsens the neurocognitive impairments of MDD patients. As these impairments are found to be associated with treatment outcomes, sleep disturbances should be additionally assessed and treated in MDD episode.

Content analysis of insomnia questionnaires: A step to better evaluate the complex and multifaceted construct of insomnia disorder

Insomnia disorder is a mental disorder that includes various types of symptoms (e.g., insomnia initiating, worries, mood disturbances) and impairments (e.g., distress related to sleep alterations). Self-report questionnaires are the most common method for assessing insomnia but no systematic quantified analysis of their content and overlap has been carried out. We used content analysis and a visualization method to better identify the different types of clinical manifestations that are investigated by nine commonly used insomnia questionnaires for adults and the Jaccard index to quantify the degree to which they overlap. Content analysis found and visualized 16 different clinical manifestations classified into five dimensions ("Insomnia symptoms", "Insomnia-related symptoms", "Daytime symptoms", "Insomnia-related impairments", "Sleep behaviors"). The average Jaccard Index was 0.409 (moderate overlap in content). There is a lack of distinction between symptoms and impairments, and the assessment of sleep duration and hyperarousal symptoms remains overlooked. This preliminary analysis makes it possible to visualize the content of each of the nine questionnaires and to select the most appropriate questionnaire based on the issue to be addressed. Suggestions are made regarding the development of future questionnaires to better distinguish symptoms and impairments, and the different phenotypes of insomnia disorder.

The relationship between cognitive reserve focused on leisure experiences and cognitive functions in bipolar patients

Bipolar disorder (BP) is characterized by cognitive decline. Individual differences exist in maintaining cognitive function due to daily physical activity and sleep. We examined the relationship between leisure experiences as proxies for cognitive reserve (CR) and cognitive function in patients with bipolar disorder after adjusting for daily physical activity and sleep. The CR of patients with BP (n = 24) and healthy study controls (HC) (n = 24) was assessed using premorbid IQ, years of education, and leisure activity history. Performance-based neuropsychological tests were performed to evaluate cognitive function. A self-reported scale was used to assess resilience. Physical activity and sleep were measured using an activity meter. Verbal fluency, story memory, and verbal memory were significantly positively correlated with the kinds of leisure experiences in patients with BP. A hierarchical regression analysis accounting for confounding factors showed that verbal fluency and memory were associated with the kinds of leisure experiences. Neither years of education nor resilience were significantly associated with neuropsychological scores. Various leisure experiences in patients with BP are associated with higher language-related cognitive functioning. Engaging in various leisure experiences may affect higher cognitive functions related to language.

Sleep Duration and Executive Function in Adults

PURPOSE OF REVIEW

To review the literature examining the relationship between sleep and cognition, specifically examining the sub-domain of executive function. We explore the impact of sleep deprivation and the important question of how much sleep is required for optimal cognitive performance. We consider how other sleep metrics, such as sleep quality, may be a more meaningful measure of sleep. We then discuss the putative mechanisms between sleep and cognition followed by their contribution to developing dementia.

RECENT FINDINGS

Sleep duration and executive function display a quadratic relationship. This suggests an optimal amount of sleep is required for daily cognitive processes. Poor sleep efficiency and sleep fragmentation are linked with poorer executive function and increased risk of dementia during follow-up. Sleep quality may therefore be more important than absolute duration. Biological mechanisms which may underpin the relationship between sleep and cognition include brain structural and functional changes as well as disruption of the glymphatic system. Sleep is an important modifiable lifestyle factor to improve daily cognition and, possibly, reduce the risk of developing dementia. The impact of optimal sleep duration and sleep quality may have important implications for every ageing individual.

The Interactive Role of Sleep and Circadian Rhythms in Episodic Memory in Older Adults

Adequate sleep is essential for healthy physical, emotional, and cognitive functioning, including memory. However, sleep ability worsens with increasing age. Older adults on average have shorter sleep durations and more disrupted sleep compared with younger adults. Age-related sleep changes are thought to contribute to age-related deficits in episodic memory. Nonetheless, the nature of the relationship between sleep and episodic memory deficits in older adults is still unclear. Further complicating this relationship are age-related changes in circadian rhythms such as the shift in chronotype toward morningness and decreased circadian stability, which may influence memory abilities as well. Most sleep and cognitive aging studies do not account for circadian factors, making it unclear whether age-related and sleep-related episodic memory deficits are partly driven by interactions with circadian rhythms. This review will focus on age-related changes in sleep and circadian rhythms and evidence that these factors interact to affect episodic memory, specifically encoding and retrieval. Open questions, methodological considerations, and clinical implications for diagnosis and monitoring of age-related memory impairments are discussed.

Social Isolation, Sleep Disturbance, and Cognitive Functioning (HRS): A Longitudinal Mediation Study

BACKGROUND

Social isolation is prevalent and associated with dementia, yet the directionality and mechanisms are less understood. This study examined the association between social isolation and cognitive functioning and explored the mediating role of sleep disturbance on the social isolation-cognition relationship.

METHODS

Data from 5 753 dementia-free Americans aged ≥50 of 2006 (T1), 2010 (T2), and 2014 (T3) waves of the Health and Retirement Study. Social isolation was measured by the Steptoe Social Isolation Index. Cognitive functioning was measured by the Telephone Interview of Cognitive Status. Sleep disturbance was measured with the modified Jenkins Sleep Scale. We used cross-lagged panel models to determine the associations between social isolation, sleep disturbance, and cognitive functioning.

RESULTS

Social isolation is significantly associated with subsequent cognitive functioning (T1 to T2: β = -0.055, standard error [SE] = 0.014, p < .001; T2 to T3: β = -0.044, SE = 0.016, p < .001). Lower cognitive functioning is significantly associated with greater subsequent social isolation (T1 to T2: β = -0.101, SE = 0.020, p < .001; T2 to T3: β = -0.058, SE = .011, p < .001). Sleep disturbance at T2 partially mediated the effect of social isolation (T1) on cognitive functioning (T3), accounting for 6.2% of the total effect (β = -0.003, SE = 0.001, p < .01).

CONCLUSIONS

Social isolation may deteriorate cognitive functioning and vice versa. The association between social isolation and cognition is partially explained by sleep disturbance.

Remote evaluation of sleep to enhance understanding of early dementia due to Alzheimer's Disease (RESTED-AD): an observational cohort study protocol

BACKGROUND

Sleep and circadian rhythm disorders are well recognised in both AD (Alzheimer's Disease) dementia and MCI-AD (Mild Cognitive Impairment due to Alzheimer's Disease). Such abnormalities include insomnia, excessive daytime sleepiness, decreased sleep efficiency, increased sleep fragmentation and sundowning. Enhancing understanding of sleep abnormalities may unveil targets for intervention in sleep, a promising approach given hypotheses that sleep disorders may exacerbate AD pathological progression and represent a contributory factor toward impaired cognitive performance and worse quality of life. This may also permit early diagnosis of AD pathology, widely acknowledged as a pre-requisite for future disease-modifying therapies. This study aims to bridge the divide between in-laboratory polysomnographic studies which allow for rich characterisation of sleep but in an unnatural setting, and naturalistic studies typically approximating sleep through use of non-EEG wearable devices. It is also designed to record sleep patterns over a 2 month duration sufficient to capture both infradian rhythm and compensatory responses following suboptimal sleep. Finally, it harnesses an extensively phenotyped population including with AD blood biomarkers. Its principal aims are to improve characterisation of sleep and biological rhythms in individuals with AD, particularly focusing on micro-architectural measures of sleep, compensatory responses to suboptimal sleep and the relationship between sleep parameters, biological rhythms and cognitive performance.

METHODS/DESIGN

This observational cohort study has two arms (AD-MCI / mild AD dementia and aged-matched healthy adults). Each participant undergoes a baseline visit for collection of demographic, physiological and neuropsychological information utilising validated questionnaires. The main study period involves 7 nights of home-based multi-channel EEG sleep recording nested within an 8-week study period involving continuous wrist-worn actigraphy, sleep diaries and regular brief cognitive tests. Measurement of sleep parameters will be at home thereby obtaining a real-world, naturalistic dataset. Cognitive testing will be repeated at 6 months to stratify participants by longitudinal disease progression.

DISCUSSION

This study will generate new insights particularly in micro-architectural measures of sleep, circadian patterns and compensatory sleep responses in a population with and without AD neurodegenerative change. It aims to enhance standards of remotely based sleep research through use of a well-phenotyped population and advanced sleep measurement technology.

Accelerometer-derived sleep measures in idiopathic dystonia: A UK Biobank cohort study

BACKGROUND

Sleep disturbance is an increasingly recognized non-motor trait in dystonia, with varying findings reported to date. Here, we examine sleep in a UK Biobank derived dystonia cohort using subjective self-reported sleep symptoms and objective accelerometer-derived sleep measures, with comparison to a control population.

METHODS

A total of 241 dystonia cases were compared to 964 matched controls in analysis of self-reported sleep symptoms and changes in sleep architecture using wrist-worn triaxial accelerometers.

RESULTS

Dystonia participants had poorer self-reported sleep patterns compared to controls. Accelerometery measurements demonstrated later sleep times, reduced time in bed, and shifts in circadian rhythm. No association was observed with pain, and only limited relationships with psychiatric symptoms.

DISCUSSION

This study demonstrates the utility of accelerometers in longer term evaluation of sleep in dystonia, for measurement of disturbance and response to treatment. Compared to controls, altered sleep and circadian rhythm were more common in dystonia patients which may contribute to the clinical phenotype.

Association of Subjective Sleep Pattern with Self-reported Diabetes in China

There is limited research investigating the relationship between self-reported diabetes mellitus and subjective sleep patterns. Our study aims to explore this association by analyzing trends in a cohort study conducted in China using data from the China Health and Nutrition Survey longitudinal research (CHNS). We used multilevel logistic regression models to analyze the relationship. Our findings indicate that the prevalence of self- reported diabetes in China increased from 1.10% in 2004 to 3.36% in 2015, with an increase in the prevalence of short-term sleep from 7.03-10.24%. The prevalence of self-reported diabetes increased with increasing BMI levels (Normal and below: 0.67-2.16%, Overweight: 1.58-4.35%, Obesity: 2.68-6.57%, p < 0.01). The short-term sleep subgroup had the highest prevalence (2.14-5.64%). Additionally, we found significant associations between age, education level, ethnicity, coffee, smoking, drinking and the self-reported diabetes. Interestingly, the risk ratios for self-reported diabetes differed between sleep durations. With 6-8hours as the reference group, the risk ratios for self-reported diabetes in the short-term, and long-term sleep subgroups were 1.80 (95% CI: 1.23-2.63), and 1.41 (95%CI: 1.01-1.96), respectively. Raising awareness about the impact of irregular sleep duration on diabetes risk is essential, and these initiatives may serve as effective policies for diabetes control.

The association of previous night's sleep duration with cognitive function among older adults: a pooled analysis of three Finnish cohorts

STUDY OBJECTIVES

Sleep duration has been shown to associate with cognitive function, but little is known about the short-term effect of sleep duration on the previous night. This study examines how usual sleep duration and previous night's sleep duration are associated with cognitive function in older adults.

METHODS

The study population consisted of 2949 adults aged 59-92 years (mean 72.6, SD 5.7) derived from three Finnish cohorts. Participants' self-reported usual sleep duration was categorized into short (< 7 h, 19%), mid-range (7- < 9 h, 64%), and long (≥ 9 h, 17%). Self-reported sleep duration on the night prior to cognitive testing was categorized into shorter (59%), same (35%), and longer (5.9%) than usual sleep duration. Computerized Cambridge Neuropsychological Test Automated Battery (CANTAB®) was used to assess: (1) learning and memory, (2) working memory, (3) information processing, and (4) reaction time.

RESULTS

Participants with self-reported long, but not short, usual sleep duration had poorer learning and memory (p = .004), information processing (p = .003), and reaction time (p = .006) when compared to those with mid-range sleep duration. Those who slept more than usually the night prior to cognitive testing had poorer information processing (p = .019) than those sleeping the same as usually, while sleeping less than usually was not associated with cognitive function.

CONCLUSIONS

This study suggests that while long sleep duration was associated with worse cognitive function, sleeping more than usually the night prior to cognitive testing was only associated with information processing, and sleeping less than usually is not associated with cognitive function.

Correlates of cognition among people with chronic heart failure and insomnia

PURPOSE

This study aimed to describe cognitive characteristics and their associations with demographic and clinical factors among adults with chronic heart failure (HF) and insomnia.

METHODS

We performed a cross-sectional analysis of baseline data from the HeartSleep Study (NCT#02,660,385), a randomized controlled trial designed to evaluate the effects of cognitive-behavioral therapy for insomnia. Demographic characteristics and health history were obtained. We measured sleep characteristics with the Insomnia Severity Index, the PROMIS Sleep Disturbance Questionnaire, and wrist actigraphy. Sleepiness, stress, and quality of life were measured with validated questionnaires. Measures of cognition included frequency of lapses on the psychomotor vigilance test and the PROMIS cognitive abilities scale where ≥ 3 lapses and a score of ≤ 50, respectively, suggested impairment. These variables were combined into a composite score for multivariable analyses.

RESULTS

Of a sample that included 187 participants (58% male; mean age 63.1 [SD = 12.7]), 77% had New York Heart Association class I or II HF and 66% had HF with preserved ejection fraction. Common comorbidities were diabetes (35%), hypertension (64%), and sleep apnea (54%). Impaired vigilant attention was associated with non-White race, higher body mass index, less education, and more medical comorbidities. Self-reported cognitive impairment was associated with younger age, higher body mass index, and pulmonary disease. On adjusted analysis, significant risk factors for cognitive impairment included hypertension (OR 1.94), daytime sleepiness (OR 1.09), stress (OR 1.08), and quality of life (OR 0.12).

CONCLUSIONS

Impaired cognition is common among people with chronic HF and insomnia and associated with hypertension, daytime sleepiness, stress, and poor quality of life.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: Insomnia Self-management in Heart Failure; NCT#02,660,385.

Physical activity and morningness: A helpful combination in improving the sleep quality of active Italian university students

University students are commonly described as having worsened sleep quality, especially when inactive and Evening-type (E-type) subjects. This study aimed to examine the interactions between physical activity and chronotype on sleep quality among a sample of active Sports Science university students. In November 2019, 433 participants (mean age: 19.7 ± 1.56 years; 70% males) completed the Pittsburgh Sleep Quality Index, the Godin-Shepard Leisure-Time Physical Activity Questionnaire (tertiles categorisation), and the Morningness-Eveningness Questionnaire. Females and E-type slept significantly worse than males and Neither-(N-types) and Morning-types (M-types), respectively. However, there were no significant differences in sleep quality based on physical activity levels. The three-way ANOVA revealed that sleep quality in N- and E-types appeared to be independent of physical activity, whereas M-types showed an improvement in sleep classification with increased physical activity. Moderation analysis indicated that physical activity significantly moderated the relationship between chronotypes and sleep quality. Specifically, M-types demonstrated a more pronounced improvement in sleep quality with increasing physical activity compared to the other chronotypes. In conclusion, M-type university students derived the greatest benefits from physical activity in improving sleep quality. Conversely, physical activity seemed to have a limited impact on sleep quality among active E-type university students.

Associations between sleep health and grey matter volume in the UK Biobank cohort (n = 33 356)

As suggested by previous research, sleep health is assumed to be a key determinant of future morbidity and mortality. In line with this, recent studies have found that poor sleep is associated with impaired cognitive function. However, to date, little is known about brain structural abnormalities underlying this association. Although recent findings link sleep health deficits to specific alterations in grey matter volume, evidence remains inconsistent and reliant on small sample sizes. Addressing this problem, the current preregistered study investigated associations between sleep health and grey matter volume (139 imaging-derived phenotypes) in the UK Biobank cohort (33 356 participants). Drawing on a large sample size and consistent data acquisition, sleep duration, insomnia symptoms, daytime sleepiness, chronotype, sleep medication and sleep apnoea were examined. Our main analyses revealed that long sleep duration was systematically associated with larger grey matter volume of basal ganglia substructures. Insomnia symptoms, sleep medication and sleep apnoea were not associated with any of the 139 imaging-derived phenotypes. Short sleep duration, daytime sleepiness as well as late and early chronotype were associated with solitary imaging-derived phenotypes (no recognizable pattern, small effect sizes). To our knowledge, this is the largest study to test associations between sleep health and grey matter volume. Clinical implications of the association between long sleep duration and larger grey matter volume of basal ganglia are discussed. Insomnia symptoms as operationalized in the UK Biobank do not translate into grey matter volume findings.

The association of night shift work with the risk of all-cause dementia and Alzheimer's disease: a longitudinal study of 245,570 UK Biobank participants

BACKGROUND

The purpose of this research was to investigate a possible link between night shift work and the development of all-cause dementia and Alzheimer's disease (AD), as well as determine the contribution of night shift work, genetic susceptibility to AD.

METHODS

This study was conducted using the UK Biobank database. 245,570 participants with a mean follow-up length of 13.1 years were included. A Cox proportional hazards model was used to investigate the link between night shift work and the development of all-cause dementia or AD.

RESULTS

We counted a total of 1248 participants with all-cause dementia. In the final multivariable adjusted model, the risk of dementia was highest in always night shift workers (HR 1.465, 95% CI 1.058-2.028, P = 0.022), followed by irregular shift workers (HR 1.197, 95% CI 1.026-1.396, P = 0.023). AD events were recorded in 474 participants during the follow-up period. After final multivariate adjustment of model, always night shift workers remained at the highest risk (HR 2.031, 95% CI 1.269-3.250, P = 0.003). Moreover, always night shift workers were associated with a higher risk of AD in both low, intermediate and high AD-GRS groups.

CONCLUSIONS

Always night shift work had a higher risk of developing all-cause dementia and AD. Irregular shift workers had a higher risk of developing all-cause dementia than no shift workers. Always night shift work had a higher AD risk, regardless of whether they had a high, intermediate or low AD-GRS.

Threshold effects of the relationship between physical exercise and cognitive function in the short-sleep elder population

BACKGROUND

It has been demonstrated that elderly people's cognitive capacities can be improved with exercise, and short sleep is linked to cognitive decline. However, the impact of physical exercise on cognitive performance in seniors who do not get enough sleep is largely unknown. This makes it an intriguing subject to explore further.

METHODS

This study consisted of elders (over 60 years old) who participated throughout the National Health and Nutrition Examination Survey's 2011-2014 cycle (NHANES). Weighted linear regression model and restricted cubic splines analysis were performed to evaluate the association between physical exercise and cognitive function. In the end, 1,615 samples were scrutinized and the total number of weighted respondents was 28,607,569.

RESULTS

Results showed that in the Animal Fluency test and the Digit Symbol Substitution test, a positive association was found between physical exercise volume and scores in the fully adjusted model. A two-piecewise linear regression model was then applied to explore the threshold effect of exercise on cognitive performance. Before 960 and 800 MET-minutes/week, there were consistent positive relationship between exercise and scores of the Animal Fluency test [ß (95% CI): 0.233 (0.154, 0.312), p < 0.001] and Digit Symbol Substitution test [β (95% CI): 0.555 (0.332, 0.778), p < 0.001], respectively. However, there was a saturation effect where physical exercise volume reached the two inflection points.

CONCLUSION

According to our research, the benefit of exercise did not always expand with the exercise volume increment under the short-sleep condition, which challenged existing knowledge. The short-sleep elder group could maintain cognitive performance with no more than 800 MET-minutes/week of physical exercise. Verification of these findings requires further biological investigations.

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank

BACKGROUND

Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes.

METHODS

Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC).

RESULTS

For MD vs. controls (n_(MD) = 24,229; n_(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67-0.69. Discrimination was reasonable for atypical vs. typical symptoms (n_(atypical) = 958; n_(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71-0.77) but poor for remaining models (AUCs 0.59-0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes.

LIMITATIONS

Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary.

DISCUSSION

Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features.

Understanding neuron-glia crosstalk and biological clocks in insomnia

According to the World Health Organization, about one-third of the population experiences insomnia symptoms, and about 10-15% suffer from chronic insomnia, the most common sleep disorder. Sleeping difficulties associated with insomnia are often linked to chronic sleep deprivation, which has a negative health impact partly due to disruption in the internal synchronisation of biological clocks. These are regulated by clock genes and modulate most biological processes. Most studies addressing circadian rhythm regulation have focused on the role of neurons, yet glial cells also impact circadian rhythms and sleep regulation. Chronic insomnia and sleep loss have been associated with glial cell activation, exacerbated neuroinflammation, oxidative stress, altered neuronal metabolism and synaptic plasticity, accelerated age-related processes and decreased lifespan. It is, therefore, essential to highlight the importance of glia-neuron interplay on sleep/circadian regulation and overall healthy brain function. Hence, in this review, we aim to address the main neurobiological mechanisms involved in neuron-glia crosstalk, with an emphasis on microglia and astrocytes, in both healthy sleep, chronic sleep deprivation and chronic insomnia.

Associations between insomnia symptoms and functional connectivity in the UK Biobank cohort (n = 29,423)

An increasing number of studies harness resting-state fMRI functional connectivity analysis to investigate the neurobiological mechanisms of insomnia. The results to date are inconsistent and the detection of minor and widely distributed alterations in functional connectivity requires large sample sizes. The present study investigated associations between insomnia symptoms and resting-state functional connectivity at the whole-brain level in the largest sample to date. This cross-sectional analysis used resting-state imaging data from the UK Biobank, a large scale, population-based biomedical database. The analysis included 29,423 participants (age: 63.1 ± 7.5 years, 54.3% female), comprising 9210 with frequent insomnia symptoms and 20,213 controls without. Linear models were adjusted for relevant clinical, imaging, and socio-demographic variables. The Akaike information criterion was used for model selection. Multiple comparisons were corrected using the false discovery rate with a significance level of q < 0.05. Frequent insomnia symptoms were associated with increased connectivity within the default mode network and frontoparietal network, increased negative connectivity between the default mode network and the frontoparietal network, and decreased connectivity between the salience network and a node of the default mode network. Furthermore, frequent insomnia symptoms were associated with altered functional connectivity between nodes comprising sensory areas and the cerebellum. These functional alterations of brain networks may underlie dysfunctional affective and cognitive processing in insomnia and contribute to subjectively and objectively impaired sleep. However, it must be noted that the item that was used to assess frequent insomnia symptoms in this study did not assess all the characteristics of clinically diagnosed insomnia.

Association of subclinical depressive symptoms and sleep with cognition in the community-dwelling older adults

BACKGROUND

/Purpose: This study aimed to explore the association of subclinical depressive symptoms and sleep with cognition in community-dwelling Taiwanese older adults.

METHODS

This four-year prospective cohort study (2015-2019) included 379 participants aged 65 years or older from the annual senior health checkup program at National Taiwan University Hospital who were followed up two years later. Global and domain cognitive functions were assessed using validated neuropsychological tests. Depressive symptoms were evaluated using the Center for Epidemiologic Studies Depression (CES-D) Scale. Sleep quality was evaluated using the Pittsburg Sleep Quality Index (PSQI). Excessive daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS). Generalized linear mixed models were used to explore the associations of subclinical depressive symptoms and sleep variables with cognition, adjusting for important covariates. Stratification analyses were performed using the sleep variables.

RESULTS

Over time, depressive symptoms were associated with poor performance of memory (βˆ = 0.24, P = 0.04) and executive function (βˆ = -0.24, P = 0.03). Poor sleep quality (elevated PSQI score) was associated with poor memory performance (βˆ = -0.04 to -0.03, P < 0.05). Excessive daytime sleepiness (elevated ESS score) was associated with poor performance of memory (βˆ = -0.02, P < 0.05) and executive function (βˆ = -0.02, P = 0.001). At baseline, better sleep quality and no excessive daytime sleepiness were associated with better memory performance over time.

CONCLUSION

Subclinical depressive symptoms, worse sleep quality, and excessive daytime sleepiness were differentially associated with impairment of cognitive domains (mainly memory and executive function).

Associations between sleep-related symptoms, obesity, cardiometabolic conditions, brain structural alterations and cognition in the UK biobank

OBJECTIVES

Sleep disturbances are increasingly recognized as adversely affecting brain health in aging. Our aim was to investigate interrelations between subjective sleep-related symptoms, obesity, cardiometabolic disorders, brain structure and cognitive decline in a population-based aging sample.

METHODS

Data were extracted from the UK Biobank for anthropometric and demographic information, self-reported sleep behaviours, cardiometabolic measures, structural brain magnetic resonance imaging and cognitive test scores. "Sleep-related symptoms" (SRS) were measured using four questionnaire items: loud snoring, daytime sleepiness, likelihood to nap and difficulty getting up in the morning. Associations were tested using a structural equation model (SEM), adjusted for confounders. Further, multiple regression analysis was used to test for direct relationships between SRS and specific cognitive domains.

RESULTS

Among 36,468 participants with an average age of 63.6 (SD 7.5) years and 46.7% male, we found that SRS were associated with obesity and several pre-existing cardiometabolic disturbances. In turn, cardiometabolic disorders were associated with increased white matter hyperintensities and cortical thinning, which were related to cognitive dysfunction. SRS were also directly related to several structural brain changes and to cognitive dysfunction. Regression analyses showed that SRS were directly associated with slower reaction times, and lower scores in fluid intelligence, working memory and executive function.

CONCLUSIONS

Self-reported sleep-related symptoms were associated with cognitive dysfunction directly and through pre-existing cardiometabolic disorders and brain structural alterations. These findings provide evidence that symptoms of sleep disturbances, here defined primarily by hypersomnolence and snoring, are important risk factors or markers for cognitive dysfunction in an aging population.

Associations between objectively measured sleep parameters and cognition in healthy older adults: A meta-analysis

Multiple studies have examined associations between sleep and cognition in older adults, but a majority of these depend on self-reports on sleep and utilize cognitive tests that assess overall cognitive function. The current meta-analysis involved 72 independent studies and sought to quantify associations between objectively measured sleep parameters and cognitive performance in healthy older adults. Both sleep macrostructure (e.g., sleep duration, continuity, and stages) and microstructure (e.g., slow wave activity and spindle activity) were evaluated. For macrostructure, lower restlessness at night was associated with better memory performance (r = 0.43, p = 0.02), while lower sleep onset latency was associated with better executive functioning (r = 0.28, p = 0.03). Greater relative amount of N2 and REM sleep, but not N3, positively correlated with cognitive performance. The association between microstructure and cognition in older adults was marginally significant. This relationship was moderated by age (z = 0.07, p < 0.01), education (z = 0.26, p = 0.03), and percentage of female participants (z = 0.01, p < 0.01). The current meta-analysis emphasizes the importance of considering objective sleep measures to understand the relationship between sleep and cognition in healthy older adults. These results also form a base from which researchers using wearable sleep technology and measuring behavior through computerized testing tools can evaluate their findings.

Factors associated with insomnia symptoms: A cross-sectional study during a Covid-19 fully restrictive lockdown

Insomnia is the most frequent sleep disorder and a public health concern that increased during the Covid 19 pandemic. Fully restrictive lockdowns during Covid are interesting periods to examine the impact of environmental and behavioural changes on the emergence of insomnia symptoms. In this cross-sectional study we aimed to (1) determine the main factors associated with insomnia symptoms during a Covid-19 fully restrictive lockdown examining the associated daily life alterations and (2) create a predictive model of insomnia symptoms. We used the data drawn from the "Covid-RythmE" study that reached volunteers from the general French population through an online survey during the last 2 weeks of the 2 month full lockdown. Associations with insomnia symptoms were tested and significant associations were entered in a Backward Stepwise Logistic Regression (BSLR) to assess the best combination to classify individuals with or without insomnia symptoms. From the 1624 participants, 50.64% suffered from mild to severe insomnia symptoms as assessed by the ISI. The best combination for explaining insomnia symptoms with 74.26% of accuracy included: age (OR = 1.15), females (OR = 1.26), smaller home sizes (OR = 0.77), environmental noises (OR = 1.59), anxiety symptoms (OR = 1.24), depressive symptoms (OR = 1.15), regularity of sleep-wake schedules (OR = 1.25), exposure to screen during the morning (OR = 1.13), and LED light during the evening (OR = 1.17). Thus, lifestyle schedule and exposure to natural synchronizers such as light, are primordial in considering in insomnia physiopathology, prevention and treatment, as well as the associated mental health status.

Identifying the Biomarker Profile of Pre-Frail and Frail People: A Cross-Sectional Analysis from UK Biobank

OBJECTIVE

This study aimed to compare the biomarker profile of pre-frail and frail adults in the UK Biobank cohort by sex.

METHODS

In total, 202,537 participants (67.8% women, aged 37 to 73 years) were included in this cross-sectional analysis. Further, 31 biomarkers were investigated in this study. Frailty was defined using a modified version of the Frailty Phenotype. Multiple linear regression analyses were performed to explore the biomarker profile of pre-frail and frail individuals categorized by sex.

RESULTS

Lower concentrations of apoA1, total, LDL, and HDL cholesterol, albumin, eGFRcys, vitamin D, total bilirubin, apoB, and testosterone (differences ranged from -0.30 to -0.02 per 1-SD change), as well as higher concentrations of triglycerides, GGT, cystatin C, CRP, ALP, and phosphate (differences ranged from 0.01 to 0.53 per 1-SD change), were identified both in pre-frail and frail men and women. However, some of the associations differed by sex. For instance, higher rheumatoid factor and urate concentrations were identified in pre-frail and frail women, while lower calcium, total protein, and IGF-1 concentrations were identified in pre-frail women and frail women and men. When the analyses were further adjusted for CRP, similar results were found.

CONCLUSIONS

Several biomarkers were linked to pre-frailty and frailty. Nonetheless, some of the associations differed by sex. Our findings contribute to a broader understanding of the pathophysiology of frailty as currently defined.

Insomnia and risk of dementia in a large population-based study with 11-year follow-up: The HUNT study

Despite evidence suggesting that insomnia is associated with the risk of dementia and cognitive dysfunction, studies have shown mixed results. Dementia has a long prodromal phase, and studies with long follow-up are required to avoid reverse causality. In our 11-year follow-up study, we assessed whether probable insomnia disorder (PID) based on diagnostic criteria, and insomnia symptoms were associated with risk of all-cause dementia, Alzheimer's disease (AD) and cognition, measured with the Montreal Cognitive Assessment scale. We also examined if Apolipoprotein E genotype modified any associations with dementia through interaction. We analysed data from 7492 participants in the Norwegian Trøndelag Health Study. PID was not associated with all-cause dementia (odds ratio = 1.03, 95% confidence interval = 0.74-1.43), AD (odds ratio = 1.07, 95% confidence interval = 0.71-1.60) or Montreal Cognitive Assessment score (regression coefficient = 0.37, 95% confidence interval = -0.06 to 0.80). The insomnia symptom "difficulties maintaining sleep" was associated with a lower risk of all-cause dementia (odds ratio = 0.81, 95% confidence interval = 0.67-0.98), AD (odds ratio = 0.73, 95% confidence interval = 0.57-0.93), and better Montreal Cognitive Assessment score, mean 0.40 units (95% confidence interval = 0.15-0.64). No interaction with Apolipoprotein E genotype was found. PID and insomnia symptoms did not increase the risk of dementia in our study. More research with longer follow-up is needed, and future studies should explore if the associations to dementia risk vary across insomnia subtypes.

Evaluation of an occupation-based sleep programme for people with Insomnia

BACKGROUND

Sleep problems are a health issue worldwide. Based on the Person-Environment-Occupation-Performance model, we developed an occupation-based sleep programme to promote awareness of sleep hygiene factors, promote an environment conductive to sleep, and restructure participation in daytime activities with a focus on occupational balance.

METHOD

This study uses a non-equivalent group design to evaluate the effectiveness of an occupation-based sleep intervention among community-dwelling adults with insomnia, when compared with a treatment-as-usual (TAU) group which focused on sleep hygiene, and relaxation.

RESULTS

When compared with the TAU group (n = 20), the intervention group (n = 22) had significant improvement in sleep duration, occupational balance, and reduction in mood symptoms at both post treatment and 1-month follow up.

CONCLUSION

The results demonstrated that an occupation-based programme is an effective treatment for insomnia disorder and demonstrated the role which occupational therapy could play in primary health care service.

Clinical and genotypic analysis in determining dystonia non-motor phenotypic heterogeneity: a UK Biobank study

The spectrum of non-motor symptoms in dystonia remains unclear. Using UK Biobank data, we analysed clinical phenotypic and genetic information in the largest dystonia cohort reported to date. Case-control comparison of dystonia and matched control cohort was undertaken to identify domains (psychiatric, pain, sleep and cognition) of increased symptom burden in dystonia. Whole exome data were used to determine the rate and likely pathogenicity of variants in Mendelian inherited dystonia causing genes and linked to clinical data. Within the dystonia cohort, phenotypic and genetic single-nucleotide polymorphism (SNP) data were combined in a mixed model analysis to derive genetically informed phenotypic axes. A total of 1572 individuals with dystonia were identified, including cervical dystonia (n = 775), blepharospasm (n = 131), tremor (n = 488) and dystonia, unspecified (n = 154) groups. Phenotypic patterns highlighted a predominance of psychiatric symptoms (anxiety and depression), excess pain and sleep disturbance. Cognitive impairment was limited to prospective memory and fluid intelligence. Whole exome sequencing identified 798 loss of function variants in dystonia-linked genes, 67 missense variants (MPC > 3) and 305 other forms of non-synonymous variants (including inframe deletion, inframe insertion, stop loss and start loss variants). A single loss of function variant (ANO3) was identified in the dystonia cohort. Combined SNP and clinical data identified multiple genetically informed phenotypic axes with predominance of psychiatric, pain and sleep non-motor domains. An excess of psychiatric, pain and sleep symptoms were evident across all forms of dystonia. Combination with genetic data highlights phenotypic subgroups consistent with the heterogeneity observed in clinical practice.

Associations Between Sleep Health and Amygdala Reactivity to Negative Facial Expressions in the UK Biobank Cohort

BACKGROUND

Sleep health (SH) is considered a key determinant of human physiological and psychological well-being. In line with this, previous studies have found that poor sleep is associated with various psychiatric disorders, in particular, with anxiety and depression. Although little is known about the neural mechanisms underlying these associations, recent findings suggest that essential dimensions of SH are associated with altered amygdala reactivity (AR); however, evidence to date is inconsistent and reliant on small sample sizes.

METHODS

To address this problem, the current preregistered study investigated associations between SH and AR to negative facial expressions in the UK Biobank cohort (25,758 participants). Drawing on a large sample size and consistent data acquisition, 5 dimensions of SH (insomnia symptoms, sleep duration, daytime sleepiness, chronotype, and sleep medication) were examined.

RESULTS

Exploratory analyses revealed that short sleep duration was associated with decreased AR. The remaining SH dimensions and a composite measure of all SH dimensions were not associated with AR.

CONCLUSIONS

To our knowledge, this is the largest study to test associations between SH and AR. Habitual short sleep duration may be associated with decreased AR, possibly indicating compensation for impaired prefrontal processes and hampered emotion regulation.

The nosological status of unipolar mania and hypomania within UK Biobank according to objective and subjective measures of diurnal rest and activity

BACKGROUND

There is uncertainty whether unipolar mania is a discrete sub-type of bipolar disorder. Disrupted rest/activity rhythms are a key feature of bipolar disorder (BD) but have not been well characterised in unipolar mania/hypomania (UM). We compared subjective and objective rest/activity patterns, demographic and mental health outcomes across BD, UM and control groups.

METHODS

UK residents aged 37-73 years were recruited into UK Biobank from 2006 to 2010. BD, UM and control groups were identified via a mental health questionnaire. Demographic, mental health and subjective sleep outcomes were self-reported. Accelerometery data were available for a subset of participants, and objective measures of sleep and activity were derived.

RESULTS

A greater proportion of males met UM criteria, and more females were in the BD group. Both BD and UM groups had poor mental health outcomes vs. controls. Objectively measured activity differed between all three groups: UM had highest levels of activity and BD lowest. The UM group had shorter sleep duration compared to controls. Subjective rest/activity measures showed that both mood disorder groups (compared to controls) had later chronotype preference, more disturbed sleep and increased difficulty getting up in the morning. However, the UM group were more likely to report an early chronotype compared to BD and control groups.

CONCLUSIONS

BD and UM share features in common, but key differences support the proposition that UM may be a distinct and more clinically homogenous disorder. UM was characterised by a higher proportion of males, early chronotype, increased activity and shorter sleep duration.

Evaluation of Sleep Habits and Disturbances Among US Adults, 2017-2020

IMPORTANCE

Unhealthy sleep behaviors and sleep disturbances are associated with higher risk of multiple diseases and mortality. The current profiles of sleep habits and disturbances, particularly the differences between workdays and free days, are unknown in the contemporary US.

OBJECTIVE

To comprehensively evaluate sleep habits on workdays and free days and the prevalence of sleep disturbances among US adults.

DESIGN, SETTING, AND PARTICIPANTS

This study is a cross-sectional analysis of US nationally representative data from the National Health and Nutrition Examination Survey (2017-2020) among adults aged 20 years or older. Data analysis was performed from February to May 2022.

MAIN OUTCOMES AND MEASURES

The main outcomes were means and/or distributions of sleep habits, including sleep duration and sleep-wake timing on workdays and free days, sleep debt (ie, the difference between sleep duration on free days and mean weekly sleep duration), and social jet lag (ie, the difference between the midpoint between sleep and wake time on workdays and free days). Prevalence of trouble sleeping (ie, participants told a doctor or other health professional that they have trouble sleeping) and daytime sleepiness (ie, self-reported feeling of being overly sleepy during the day ≥5 times per month) were also determined.

RESULTS

A total of 9004 individuals (mean [SE] age, 48.3 [0.53] years; 4635 women [51.9%]; 3158 non-Hispanic White [62.8%]) were included in the current study. The mean sleep duration was 7.59 hours (95% CI, 7.54 to 7.64 hours) on workdays and 8.24 hours (95% CI, 8.17 to 8.31 hours) on free days (difference, 0.65 hour). The mean sleep and wake times were at 11:02 pm (95% CI, 10:57 pm to 11:17 pm) and 6:41 am (95% CI, 6:36 am to 6:45 am), respectively, on workdays and 11:25 pm (95% CI, 11:21 pm to 11:35 pm) and 7:41 am (95% CI, 7:37 am to 7:46 am), respectively, on free days (differences, 0.23 hour for sleep time and 1.00 hour for wake time). On workdays, 23.1% (95% CI, 21.3% to 24.9%) of adults slept less than 7 hours and 25.4% (95% CI, 24.1% to 26.6%) went to sleep at midnight or later; the corresponding percentages changed to 12.9% (95% CI, 11.6% to 14.1%) and 40.9% (95% CI, 38.4% to 43.5%), respectively, on free days. Furthermore, the mean sleep debt was 0.73 hours (95% CI, 0.68 to 0.77 hours), and mean social jet lag was 1.10 hours (95% CI, 1.05 to 1.15 hours); 30.5% (95% CI, 26.8% to 33.3%) of adults experienced 1 hour or more of sleep debt, and 46.5% (95% CI, 42.6% to 50.3%) experienced 1 hour or more of social jet lag. The prevalence of trouble sleeping was 29.8% (95% CI, 28.2% to 31.5%), and that of daytime sleepiness was 27.2% (95% CI, 25.0% to 29.5%).

CONCLUSIONS AND RELEVANCE

In 2017 to 2020, US adults showed variability in sleep habits between workdays and free days, with longer sleep duration and later sleep-wake phases on free days, and high percentages of US adults experienced long-term sleep deprivation, chronic social jet lag, and frequent sleep disturbances. These findings provide evidence to further investigate potential approaches to optimize overall US sleep health.

Chronotype and cognitive function: Observational study and bidirectional Mendelian randomization

BACKGROUND

Association has been found between chronotype and cognitive function in conventional observational studies but whether this association is causal and if so, its direction, is uncertain. There are also concerns among people with later chronotype that their habits may be detrimental to cognitive function.

METHODS

We analyzed the association between chronotype (measured as sleep midpoint) and cognitive function (measured by Mini-Mental Status Examination (MMSE) and Delayed Word Recall Test (DWRT)) using multivariable linear regression on 14,582 participants in the Guangzhou biobank cohort study (GBCS) from 2008 to 2012. Using bidirectional Mendelian randomization, we used 207 single nucleotide polymorphisms (SNPs) associated with chronotype from the combination of UK Biobank and 23andMe (n = 697,828), and 127 SNPs associated with cognitive function from the combination of UK Biobank and COGENT consortium (n = 257,841).

FINDINGS

Observationally in GBCS, later chronotype was associated with better cognitive function (MMSE scores: β = 0.14 per hour; 95% confidence interval (CI), 0.09-0.19; DWRT scores: β = 0.07 per hour; 95% CI, 0.04-0.11). Bidirectional MR showed genetic predisposition to early, versus later, chronotype was not associated with cognitive function using inverse-variance weighted (β = -0.02; 95% CI, -0.05 to 0.01). However, better cognitive function was associated with decreased odds of early chronotype (UK Biobank: odds ratio = 0.88 per standardized score; 95% CI, 0.83-0.93; 23andMe: 0.87 per standardized score; 95% CI, 0.80-0.95).

INTERPRETATION

It is a reassuring finding for adults with later chronotype who may be concerned if such a habit has a negative impact on cognitive function.

FUNDING

The National Natural Science Foundation of China; Natural Science Foundation of Guangdong; The University of Hong Kong Foundation for Educational Development and Research; The Health Medical Research Fund in Hong Kong; The University of Birmingham, UK.

The Effect of Sleep Quality and Mental Fatigue on the Learning Rate of Shift Workers with Fast Shift Work Rotation

Background

Modern industrial societies are always prone to errors and accidents due to complex devices, multitasking, and shift work jobs. Therefore, behavioral tests in learning and memory are necessary to evaluate employees' perceptions to examine the brain's information processing and the physiological and psychological aspects of memory disorders.

Materials and Methods

In this study, the effect of fast shift rotation, sleep quality, and mental fatigue on individuals' learning and memory was investigated using a maze device. Participants were divided into two groups (regular daytime workers and shift workers). The quality of sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI), and the rate of mental fatigue was evaluated using a checklist published by the Japan Industrial Safety and Health Association.

Results

Learning time and the number of learning errors at the beginning and end of the morning shifts and night shifts had a significant relationship (P value <0.0001). However, there was no meaningful relationship between sleep quality and time and the number of learning errors in day workers and shift workers.

Conclusion

The results indicated that although shift workers experience rapid shift rotation, they are still exposed to this circadian sleep change's side effects such as general physical fatigue, sensory-neurological fatigue, poor perceived sleep quality, daily dysfunction, difficulty in learning, and memory. They show a significant difference compared to people working on a regular workday.

Sleep duration, genetic susceptibility, and Alzheimer's disease: a longitudinal UK Biobank-based study

BACKGROUND

Alzheimer's disease (AD) is the most frequently occurring type of dementia. Concurrently, inadequate sleep has been recognized as a public health epidemic. Notably, genetic and environmental factors are now considered contributors to AD progression.

OBJECTIVE

To assess the association between sleep duration, genetic susceptibility, and AD.

METHODS AND RESULTS

Based on 483,507 participants from the UK Biobank (UKB) with an average follow-up of 11.3 years, there was a non-linear relationship between AD incidence and sleep duration (P for non-linear < 0.001) by restricted cubic splines (RCS). Sleep duration was categorized into short sleep duration (< 6 h/night), normal sleep duration (6-9 h/night), and long sleep duration (> 9 h/night). No statistically significant interaction was identified between sleep duration and the AD-GRS (Alzheimer's disease genetic risk score, P for interaction = 0.45) using Cox proportional risk model. Compared with the participants who had a low AD-GRS and normal sleep duration, there was associated with a higher risk of AD in participants with a low AD-GRS and long sleep duration (HR = 3.4806; 95% CI 2.0011-6.054, p < 0.001), participants with an intermediate AD-GRS and long sleep duration (HR = 2.0485; 95% CI 1.3491-3.1105, p < 0.001), participants with a high AD-GRS and normal sleep duration (HR = 1.9272; 95% CI 1.5361-2.4176, p < 0.001), and participants with a high AD-GRS and long sleep duration (HR = 5.4548; 95% CI 3.1367-9.4863, p < 0.001).In addition, there was no causal association between AD and sleep duration using Two Sample Mendelian randomization (MR).

CONCLUSION

In the UKB population, though there was no causal association between AD and sleep duration analyzed using Two Sample MR, long sleep duration (> 9 h/night) was significantly associated with a higher risk of AD, regardless of high, intermediate or low AD-GRS. Prolonged sleep duration may be one of the clinical predictors of a higher risk of AD.

Associations of long-term exposure to ambient air pollution and road traffic noise with sleep health in UK Biobank

BACKGROUND

Evidence about associations of pollutants with sleep is limited, and most of studies focused on individual sleep behaviors, neglecting their interrelation. We aimed to assess the relationship between ambient air pollution and road traffic noise with overall sleep health.

METHODS

The study included 378,223 participants from the UK Biobank. Including five sleep behaviors (chronotype, sleep duration, insomnia, snoring, and daytime sleepiness) to construct overall sleep pattern. Ambient air pollution exposure was estimated using Land Use Regression model. Road traffic noise exposure was estimated using a simplified version of the Common Noise Assessment Methods model. Using multinomial and binary logistic regression models to identify the associations between pollutants with overall and individual sleep behaviors, respectively.

RESULTS

Participants were derived in three sleep patterns: healthy (n = 140,490), intermediate (n = 220,627), and poor (n = 17,106). After adjustment for potential confounders, compared with the lowest quartile of PM2.5, the highest quartile had higher odds of intermediate and poor compared to healthy sleep pattern [OR (95% CI) for poor: 1.28 (1.21-1.36); for intermediate: 1.11 (1.09-1.14)]. We observed similar relationships for PM10, PM2.5 absorbance, PMcoarse, NOx, and NO2. In unadjusted model, compared with low exposure of Lnight, high Lnight exposure had higher odds of intermediate and poor compared to healthy sleep pattern [OR (95% CI) for poor: 1.13 (1.06-1.20); for intermediate: 1.03 (1.00-1.06)]. However, such associations disappeared after further adjustment for potential confounders.

CONCLUSIONS

Long-term ambient air pollution is associated with overall sleep health. Road traffic noise itself is weakly associated with overall sleep health.