Rethinking the sleep-health link

Sleep of Nurses: A Comprehensive Scoping Review

AIM

To map the extent, range and nature of studies that examine sleep of nurses and identify how sleep has been examined in relation to the different aspects of nurses' health and nursing work and practice.

DESIGN

A scoping review.

DATA SOURCES

A search of five electronic databases including MEDLINE, Embase, EMcare, PsycINFO (using the Ovid platform) and Scopus was undertaken in May 2023 to identify primary studies that examined nurses' sleep.

REVIEW METHODS

This review was undertaken in accordance with the Joanna Briggs Institute methodology for scoping reviews and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist.

RESULTS

This review included 1040 studies from a wide range of countries. Most studies were observational in design and examined nurses working in the acute care sector. Studies were mostly descriptive (32%) or discussed sleep as a workforce issue (21%) or lifestyle behaviour that is important for the health of nurses working clinically (27%). A range of different sleep parameters were examined, with sleep quality the focus of most studies, especially in relation to well-being.

CONCLUSION

There has been an exponential increase in the number of studies that examine nurses' sleep. Efforts to examine the sleep of nurses are beginning to align with contemporary understandings and methodological approaches to examining sleep. However, this field of research could benefit from better consistency in the definition and reporting of sleep, prioritising objective measures of sleep and improving understanding of the relative and combined importance of different dimensions of sleep.

IMPACT

This review provides a comprehensive overview of studies that examine nurses' sleep. Findings highlight areas of growing interest, areas in need of further research and methodological considerations to strengthen research in this field.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution. REGISTRATION DOI: https://doi.org/10.17605/OSF.IO/RZC4M.

Sleep Profiles Among Ethnically-Racially Minoritized Adolescents: Associations with Sociocultural Experiences and Developmental Outcomes

OBJECTIVE

This study used latent profile analyses to (1) identify heterogeneous patterns of sleep profiles; (2) examine how discrimination was related to sleep profiles; and (3) investigate how developmental outcomes varied across sleep profiles among ethnically-racially minoritized adolescents.

METHOD

Participants were 350 ethnically-racially minoritized adolescents (69% female; 22% Black-African American, 41% Asian American, and 37% Latinx; Mage = 14.27 years old, SD = 0.61) completed self-reported presurvey measures of everyday discrimination, ethnic-racial discrimination, and self-reported post-survey measures of depressive symptoms, somatic symptoms, self-esteem, and rumination. Objectively and subjectively measured sleep were assessed utilizing a short-term longitudinal (i.e., two-week) design, where adolescents wore a wrist actigraph and completed daily diaries for 14 consecutive days.

RESULTS

Drawing on multiple objectively and subjectively measured sleep indicators, three profiles were identified: Nighttime Sleeper (76.57%), Disrupted Sleeper (14.29%), and Daytime Sleeper (9.14%). Adolescents experiencing higher levels of ethnic-racial discrimination were more likely to be characterized in the Disrupted Sleeper, relative to the Nighttime Sleeper profile. Compared with Asian and Latinx Americans, Black adolescents were more likely to be in the Daytime Sleeper, relative to the Nighttime Sleeper profile. Those in the Disrupted Sleeper profile exhibited the worst developmental outcomes.

CONCLUSIONS

The findings inform clinical interventions focusing on sleep experiences, especially as they relate to protective processes for coping with discrimination. Clinical efforts (e.g., sleep education or therapy to develop routines for adaptive napping) may be beneficial to facilitating healthy sleep behaviors and mitigating sleep disturbances, which in turn, improve developmental well-being among ethnically-racially minoritized adolescents.

The association between childhood maltreatment and multidimensional sleep health in adolescents at high risk of emotional and behavioral problems

STUDY OBJECTIVES

Impaired sleep following trauma such as childhood maltreatment is both a prognostic factor for future mental illness and a feasible intervention point. Yet, associations between childhood maltreatment and objectively measured sleep components are rarely found. New approaches advance the use of multidimensional sleep health scores instead of individual sleep components. However, no such methodology has been used to study the consequences of maltreatment on sleep health in adolescent cohorts so far. We hypothesized that childhood maltreatment will be associated with poorer sleep health in adolescence.

METHODS

A cross-sectional sample of 494 adolescents at high risk of emotional and behavioral problems (mean age 17.9) completed the Childhood Trauma Questionnaire-Short Form to assess five forms of maltreatment (emotional and physical abuse/neglect and sexual abuse) assessed as continuous sum scores. During nine nights of actigraphy and sleep diary measurements, data on sleep regularity, satisfaction, alertness, timing, efficiency, and duration were collected, which were combined into a sleep health composite score ranging from 0 to 6. Linear regression models were adjusted for age, sex, household income, ethnic origin, educational level, urbanization of living environment, and parental psychopathological problems.

RESULTS

Associations were found between all forms of maltreatment and poorer sleep health (p < .031), except for sexual abuse (p = .224). Partial r effect sizes ranged from -0.12 (95% CI = -0.22 to -0.01) for emotional neglect to -0.18 (-0.28 to -0.08) for total maltreatment.

CONCLUSIONS

Maltreatment was associated with impairment in everyday sleep health, reflected in both subjective and objective measurements of sleep.

Association Between Maternal Sleep Health and Mental Health: Moderating Role of Family Function

OBJECTIVE

Pregnancy, as a complex physiological process, significantly alters maternal sleep patterns, which are closely associated with various maternal health outcomes. This study explored the association between maternal sleep health and anxiety/depression symptoms and whether this association differed by family function.

METHODS

A cross-sectional survey was conducted among pregnant women attending obstetrics departments at two hospitals in Nanjing, China. The Sleep Health Index, Family APGAR, and Patient Health Questionnaire-4 were administered to evaluate sleep health, family function, and anxiety and depression symptoms of pregnant women in late pregnancy, respectively. Multiple linear and logistic regressions were applied, with the moderation effect of the family function being assessed by adding interaction terms in the models.

RESULTS

A total of 199 pregnant women in late pregnancy completed the survey. The average age and gestational age were 30.95 years (SD = 3.38, Range: 19-42) and 36.39 weeks (SD = 2.52, Range: 28-40), respectively. The scores of sleep health, anxiety, depression, and family function were 84.37 ± 10.61, 0.00 (0.00, 2.00), 0.00 (0.00, 1.00), and 8.79 ± 1.82, respectively. Results showed that better sleep health was associated with lower scores of anxiety (β=-0.03, p < .001) and depression (β=-0.04, p < .001) symptoms and lower odds of anxiety (adjusted odds ratio, aOR = 0.92, p = .006) and depression (aOR = 0.93, p = .003) symptoms. Family function significantly moderated the relationship between sleep health and scores of anxiety (β = 0.01, p = .013) and depression (β = 0.01, p < .001) symptoms.

CONCLUSION

Good sleep health in late pregnancy is associated with reduced anxiety and depression symptoms, with a stronger association found in pregnant women with weaker family function.

Dimensionality and cross-language invariance of Pittsburgh Sleep Quality Index among Indian adolescents and adults

Sleep quality, key to physical and mental health, requires regular assessment in clinical and non-clinical settings. Despite widespread use, the dimensionality of the Pittsburgh Sleep Quality Index (PSQI) is debated, and its Hindi version's factor structure remains unexplored. Our study evaluates the PSQI's dimensionality among Indian adolescents and adults aiming to demonstrate cross-language (Hindi and English) invariance of its factor structure. The PSQI showed satisfactory item reliability, and a best-fitting two-factor model: "sleep efficiency" (comprising sleep duration and habitual sleep efficiency), and "perceived sleep quality" (comprising remaining five PSQI components). This model showed configural invariance across age groups, sexes, and languages. Metric invariance was noted across age groups, but a partial metric non-invariance was observed across languages and sexes as reflected by differences in factor loadings. The second-order factor structure model had an excellent fit indicating the usefulness of aggregate scores of the two factors as a single index of sleep quality. Our findings better support a two-factor structure of sleep quality (both for English and Hindi versions of PSQI) in India. However, further validation in diverse clinical and non-clinical samples is warranted.

The independent and combined associations of nocturnal sleep duration, sleep midpoint, and sleep onset latency with global cognitive function in older Chinese adults

This study aims to investigate the independent and combined associations of nocturnal sleep duration, sleep midpoint, and sleep onset latency with global cognitive function in older Chinese adults. Our cross-sectional study included 4601 community-dwelling cognitively unimpaired adults aged 60 years or older from the West China Health and Aging Cohort Study. Sleep characteristics were assessed using the Pittsburgh Sleep Quality Index, and global cognitive function was evaluated using the Mini-Mental State Examination (MMSE). Multivariable linear regression models were employed, adjusting for an extensive set of demographic, lifestyle, and comorbidity factors. Subgroup analyses were performed based on sex, age, and genetic risk profiles for cognitive performance. The mean age of participants was 69.0 ± 5.53 years, with 52.1% being female. The mean MMSE total score was 24.9 ± 3.20. Compared to the reference category for each sleep variable, sleep duration < 5 h/day or > 8 h/day, sleep midpoint earlier than 1:30 AM, and sleep latency > 60 min were each independently associated with significantly lower MMSE scores (β range - 0.36 to - 0.34; 95% confidence interval range - 0.60 to - 0.10). A combined analysis revealed that individuals with concurrent extreme sleep duration, early midpoint, and/or long latency had even lower MMSE scores, especially among those with genetically predicted poorer cognitive performance (β up to - 1.86). Multiple dimensions of sleep are independently and jointly associated with global cognitive function in older Chinese adults, highlighting the importance of a holistic approach to sleep in cognitive aging research and interventions.

Accelerometry-assessed sleep clusters and obesity in adolescents and young adults: a longitudinal analysis in GINIplus/LISA birth cohorts

BACKGROUND

Some studies have revealed various sleep patterns in adolescents and adults using multidimensional objective sleep parameters. However, it remains unknown whether these patterns are consistent from adolescence to young adulthood and how they relate to long-term obesity.

METHODS

Seven-day accelerometry was conducted in German Infant Study on the influence of Nutrition Intervention PLUS environmental and genetic influences on allergy development (GINIplus) and Influence of Lifestyle factors on the development of the Immune System and Allergies in East and West Germany (LISA) birth cohorts during the 15-year and 20-year follow-ups, respectively. Five sleep clusters were identified by k-means cluster analysis using 12 sleep characteristics at each follow-up. Adjusted linear and logistic regression models using generalized estimating equations were examined. Further, the interaction effects with time of follow-ups and polygenic risk scores (PRS) for body mass index (BMI) were tested.

RESULTS

Five sleep clusters were classified consistently in both adolescence (n = 1347, aged 14.3-16.4 years) and young adulthood (n = 1262, aged 19.5-22.4 years). Adolescents in the "good sleep", "delayed sleep phase", and "fragmented sleep" clusters displayed greater stability transitioning into young adulthood, while those in the "sleep irregularity and variability", and "prolonged sleep latency" clusters showed lower stability (n = 636). Compared to the "good sleep" cluster, the "prolonged sleep latency" cluster exhibited associations with higher BMI [β = 0.56, 95% confidence interval (CI) = (0.06, 1.05)] and increased odds of overweight/obesity [Odds ratio = 1.55, 95% CI = (1.02, 2.34)]. No significant PRS-sleep cluster interaction was found for BMI or overweight/obesity. Among males only, the "delayed sleep phase", "sleep irregularity and variability" and "fragmented sleep" clusters showed stronger associations with overweight/obesity as age increased.

CONCLUSION

Adolescents and young adults shared five consistent sleep patterns, with the "prolonged sleep latency" pattern linked to higher BMI and overweight/obesity.

Extent, range, and nature of studies examining sleep in nurses: a scoping review protocol

OBJECTIVE

This scoping review aims to comprehensively map the extent, range, and nature of studies that examine the various dimensions of nurses' sleep across all health care settings or countries.

INTRODUCTION

Over the past 2 decades, the importance of sleep for nurses has gained increasing attention from health care administrators, researchers, and policymakers. Despite growing research in the area, it remains unclear as to how research on sleep in nurses aligns with emerging concepts in sleep medicine more broadly, particularly in terms of how outcomes and predictors are associated with different dimensions of sleep.

INCLUSION CRITERIA

This review will consider sources of evidence reporting on nurses who hold professional accreditation, such as a registered nurse or equivalent, regardless of career stage or specialty. This review will include primary studies that examine nurses' sleep. All dimensions of sleep (eg, duration, timing, variability, quality, common disorders) reported objectively or subjectively will be considered for inclusion.

METHODS

This review will follow a modified version of the JBI methodology for scoping reviews and will be reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Databases to be searched include MEDLINE (Ovid), Emcare (Ovid), Embase (Ovid), PsycINFO (Ovid), and Scopus. A 3-step search strategy will be undertaken to identify primary studies published in English, with no date limit. Both double-screening and single-screening of titles and abstract records and of full-text reports will be used, with discussion to resolve any conflicts prior to single-screening. Data extraction will similarly involve duplicate extraction, followed by single extraction, with discrepancies resolved in a group meeting as needed. The data extracted will include specific details about the nursing population, sleep dimension, outcome measures, methodology, and key findings. Figurative, tabular, and accompanying narrative synthesis will be used to present the results in line with the review questions.

REVIEW REGISTRATION

Open Science Framework https://osf.io/rzc4m.

Sex differences in the association between short sleep duration and obesity: A systematic-review and meta-analysis

AIMS

Obesity is a leading contributor to global morbidity and mortality. Short sleep duration is significantly associated with the incidence of obesity, however, it remains unclear whether this relationship is influenced by sex. The purpose of this meta-analysis was to systematically evaluate the evidence of whether the association between short sleep duration and obesity differs between males and females.

DATA SYNTHESIS

The protocol was registered with PROSPERO (CRD42023374205). From inception through June 2023, Medline, Embase and Web of Science databases were searched for longitudinal cohort studies with minimum 12 months of observation. The quality of studies was assessed using the Newcastle-Ottawa Quality Assessment for Cohort Studies. Results were pooled using a random effects model. Results are expressed as ratio of odds ratios (ROR) with 95% confidence interval (CI). ROR directly estimates the relative strength of the association of interest (measured as odds ratio [OR] between females and males). Sensitivity analysis was performed and inconsistency between studies was assessed using I2 statistics. A total of 4582 articles were retrieved with the search strategy, of which 6 were included. The meta-analysis indicated that the association between short sleep duration and obesity incidence was statistically significant in both men [OR 1.26 (95% CI 1.13-1.40)] and women [OR 1.36 (95% CI 1.16-1.59)]. However, it did not differ significantly between sexes ROR (women/men) 1.04 (95%CI 0.79-1.36; I2 20.1%).

CONCLUSIONS

This meta-analysis indicates that women and men who subjectively report short sleep duration have similarly increased risks of incident obesity.

Sex Differences in the Associations Between Chronic Diseases and Insomnia Symptoms Among Older Adults in India

Background

Sleep problems are a critical issue in the aging population, affecting quality of life, cognitive efficiency, and contributing to adverse health outcomes. The coexistence of multiple diseases is common among older adults, particularly women. This study examines the associations between specific chronic diseases, multimorbidity, and insomnia symptoms among older Indian men and women, with a focus on the interaction of sex in these associations.

Methods

Data were drawn from 31,464 individuals aged 60 and older in the Longitudinal Ageing Study in India, Wave-1 (2017-18). Insomnia symptoms were assessed using four questions adapted from the Jenkins Sleep Scale (JSS-4), covering difficulty falling asleep, waking up, waking too early, and feeling unrested during the day. Multivariable logistic regression models, stratified by sex, were used to analyze the associations between chronic diseases and insomnia symptoms.

Results

Older women had a higher prevalence of insomnia symptoms than men (44.73% vs 37.15%). Hypertension was associated with higher odds of insomnia in both men (AOR: 1.20) and women (AOR: 1.36). Women with diabetes had lower odds of insomnia (AOR: 0.80), while this association was not significant in men. Neurological or psychiatric disorders, stroke, and bone and joint diseases were linked to higher odds of insomnia in both sexes. Chronic lung disease was associated with insomnia in men (AOR: 1.65), but not in women. Additionally, having three or more chronic diseases significantly increased the odds of insomnia in both men (AOR: 2.43) and women (AOR: 2.01).

Conclusion

Hypertension, bone and joint diseases, lung diseases, stroke, neurological or psychiatric disorders, and multimorbidity are linked to insomnia symptoms in older Indian adults. Disease-specific management and routine insomnia screening are crucial for promoting healthy aging in this vulnerable population.

Monitoring the sleep health of adults: a scoping review of routine national surveillance systems

Study Objectives

The aims of this review were to identify existing national surveillance systems monitoring one or more domains of sleep health in adults, and to describe the specific sleep health indicators used.

Methods

We systematically searched the gray and peer-reviewed literature for routinely conducted cross-sectional and longitudinal nationally representative health surveys that included the assessment of at least one domain of sleep health. The methodology involved: (1) targeted searches of the websites of national and international health agencies and statistics departments for 199 countries, (2) country-specific customized internet searches, and (3) country-specific electronic database searches of PubMed.

Results

A total of 19 762 records were identified from both the gray and peer-reviewed literature. Sleep health surveillance at the national level was conducted by 51 countries (25.6%) across 69 national health surveys. Sleep quality (96.1% of countries that surveilled sleep) was the most frequently assessed followed by sleep duration (27.5%), sleep medication use (25.5%), sleep disorders (17.6%), daytime alertness (15.7%), sleep satisfaction (15.7%), and sleep timing (7.8%). Additionally, 34.8% of the surveys utilized multiple sleep health indicators.

Conclusions

This study identified three significant gaps in the coverage of sleep health within national surveillance systems. Limited population sleep data in low- and middle-income countries, inconsistent use of sleep-related items in surveys and questionnaires, and substantial variability in the definitions of sleep health indicators. Advocacy for the inclusion of sleep health within national surveillance systems may be warranted given the important role sleep plays in public health.

Validity and reliability of self-reported methods for assessment of 24-h movement behaviours: a systematic review

BACKGROUND

Time spent in sleep, sedentary behaviour (SB), and physical activity are exhaustive and mutually exclusive parts of a 24-h day that need to be considered in a combination. The aim of this study was to identify validated self-reported tools for assessment of movement behaviours across the whole 24-h day, and to review their attributes and measurement properties.

METHODS

The databases PubMed, Scopus, and SPORTDiscus were searched until September 2023. Inclusion criteria were: (i) published in English language, (ii) per-reviewed paper, (iii) assessment of self-reported time spent in sleep, SB, and physical activity, (iv) evaluation of measurement properties of all estimates across the full 24-h day, and (v) inclusion of adolescents, adults, or older adults. The methodological quality of included studies was assessed using the Consensus-based Standards for the selection of health Measurement Instruments checklist.

RESULTS

Our search returned 2064 records. After studies selection, we included 16 articles that reported construct validity and/or test-retest reliability of 12 unique self-reported tools - eight questionnaires, three time-use recalls, and one time-use diary. Most tools enable assessment of time spent in sleep, and domain-specific SB and physical activity, and account that sum of behaviours should be 24 h. Validity (and reliability) correlation coefficients for sleep ranged between 0.22 and 0.69 (0.41 and 0.92), for SB between 0.06 and 0.57 (0.33 and 0.91), for light-intensity physical activity between 0.18 and 0.46 (0.55 and 0.94), and for moderate- to vigorous-intensity physical activity between 0.38 and 0.56 (0.59 and 0.94). The quality of included studies being mostly fair-to-good.

CONCLUSIONS

This review found that only a limited number of validated self-reported tools for assessment of 24-h movement behaviours are currently available. Validity and reliability of most tools are generally adequate to be used in epidemiological studies and population surveillance, while little is known about adequacy for individual level assessments and responsiveness to behavioural change. To further support research, policy, and practice, there is a need to develop new tools that resonate with the emerging 24-h movement paradigm and to evaluate measurement properties by using compositional data analysis.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42022330868.

Sleep, circadian activity patterns and postpartum depression: A systematic review and meta-analysis of actigraphy studies

Transition to motherhood is a period full of challenges and demands. In this review, we focused on the associations of sleep and circadian activity patterns during and after pregnancy with postpartum mental health factors. A systematic review and meta-analysis were conducted (PROSPERO reference 316,505). A search for articles was performed using PsycARTICLES, PsycINFO, PubMed, MEDLINE, Scopus, Cochrane, DARE, hand search, and citation tracking. The search was meant to identify peer-reviewed, experimental and observational studies reporting on women over 18 years old that assessed sleep and circadian activity patterns during pregnancy or postpartum using actigraphy, and investigated postpartum mental health factors. Nineteen relevant publications were selected. Postpartum total sleep at night was the indicator that was most closely related to the psychological functioning of women after childbirth. The results of the systematic review indicated that postpartum total sleep at night was related to postpartum fatigue, and the results of the meta-analysis suggested that total sleep at night was most strongly linked with postpartum depression. More studies are needed to estimate the associations of sleep-wake rhythm during pregnancy and in the postpartum period with postpartum mental health factors.

The effects of a web-based 24-hour movement behavior lifestyle education program on mental health and psychological well-being in parents of children with autism spectrum disorder: A randomized controlled trial

BACKGROUND AND PURPOSE

Compared with parents of neurotypical children or children diagnosed with other disabilities, parents of children with autism spectrum disorder (ASD) often experience poorer mental health, greater stress, and more depression and anxiety symptoms. This study aimed to assess the effects of a web-based 24-h movement behavior lifestyle education program on mental health and psychological well-being in parents of children with ASD.

METHODS

This study employed a randomized controlled trial utilizing the Health Action Process Approach (HAPA) as a theoretical framework. A total of 318 parents of children with ASD were enrolled and randomly assigned to the experimental or control group. The experimental group received an 8-week web-based 24-h movement behavior lifestyle education program, while the control group followed their usual routine. Two instruments, the Depression Anxiety and Stress Scale (DASS-21) and the Satisfaction With Life Scale (SWLS), were used to measure mental health and psychological well-being, respectively. The data were collected at two time points-at the beginning and the end of the intervention.

RESULTS

Compared with the baseline and control groups, the experimental group demonstrated significant improvements in all outcome measures (p < 0.01). There were significant differences in the DASS-21 and SWLS scores between the two groups before and after the intervention (p ≤ 0.01).

CONCLUSION

This study represents the first randomized controlled trial involving a web-based 24-h movement behavior lifestyle education program specifically designed to address the mental health and psychological well-being of parents of children with ASD. The findings confirm the potential impact of 24-h movement behavior lifestyle education as a functional and effective strategy for parents of children with ASD.

[Is socioeconomic residential segregation associated with sleep problems? Insights from ELSA-Brasil]

Several factors influence sleep, which is essential for health. While the role of neighborhood socioeconomic context on sleep health has been studied in recent years, results are inconsistent. The study aimed to investigate the association between socioeconomic residential segregation and sleep problems, using data from the second evaluation (2012-2014) of 9,918 public servants participating in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Socioeconomic residential segregation was assessed using the Getis-Ord Local Gi* statistic. Sleep duration and deprivation, complaints of insomnia, and daytime sleepiness were obtained through interviews. Binomial and multinomial logistic regression models were used to estimate the odds ratio (OR). Regarding sleep, 49% had short duration and 3% long duration, 23% reported complaints of insomnia, 45% sleep deprivation, 42% daytime sleepiness, and 48% reported ≥ 2 sleep problems. In the model adjusted for demographic and socioeconomic variables, there was an association between high socioeconomic residential segregation and short sleep duration (OR = 1.22; 95%CI: 1.07; 1.40), sleep deprivation (OR = 1.20; 95%CI: 1.05; 1.37), daytime sleepiness (OR = 1.17; 95%CI: 1.03; 1.34) and ≥ 2 associated sleep problems (OR = 1.24; 95%CI: 1.08; 1.41). Individuals living in neighborhoods with high socioeconomic residential segregation are more likely to have short sleep duration, sleep deprivation, daytime sleepiness, and ≥ 2 associated sleep problems. This information reinforces that public policy measures to reduce socioeconomic inequalities can improve the population's sleep health.

Time use and dimensions of healthy sleep: A cross-sectional study of Australian children and adults

BACKGROUND

Sleep is increasingly recognized as a multidimensional construct that occurs within the 24-hour day. Despite advances in our understanding, studies continue to consider the relationship between sleep, sedentary time and physical activity separately, and not as part of the 24-hour day.

AIMS

To determine the association between the 24-hour activity composition and dimensions of healthy sleep.

METHODS

This study examined data on 1168 children (mean age 12years; 49% female) and 1360 adults (mean age 44years; 87% female) collected as part of the Child Health CheckPoint study. Participants were asked to wear a GENEActiv monitor (Activinsights, Cambs, UK) on their nondominant wrist for eight consecutive days to measure 24-hour time-use. Compositional data analysis was used to examine the association between time use (actigraphy-derived sleep duration, sedentary time, light physical activity and moderate-vigorous physical activity) and dimensions of healthy sleep. Healthy sleep was conceptualized in terms of continuity/efficiency, timing, alertness/sleepiness, satisfaction/quality, and regularity. Time allocations were also examined.

RESULTS

The 24-hour activity composition was significantly associated with all objectively measured and self-report dimensions of healthy sleep in both children and adults. Allocating more time to sleep was associated with earlier sleep onsets, later sleep offsets, less efficient and more consistent sleep patterns for both children and adults.

CONCLUSION

This study highlights the integral relationship between daily activities and dimensions of sleep. Considering sleep within the 24-hour day activity composition framework may help inform lifestyle decisions to improve sleep health.

A dual fusion recognition model for sleep posture based on air mattress pressure detection

In order to solve the difficult portability problem of traditional non-invasive sleeping posture recognition algorithms arising from the production cost and computational cost, this paper proposes a sleeping posture recognition model focusing on human body structural feature extraction and integration of feature space and algorithms based on a specific air-spring mattress structure, called SPR-DE (SPR-DE is the Sleep Posture Recognition-Data Ensemble acronym form). The model combines SMR (SMR stands for Principle of Spearman Maximal Relevance) with horizontal and vertical division based on the barometric pressure signals in the human body's backbone region to reconstruct the raw pressure data into strongly correlated non-image features of the sleep postures in different parts and directions and construct the feature set. Finally, the recognit-ion of the two sleep postures is accomplished using the AdaBoost-SVM integrated classifier. SPR-DE is compared with the base and integrated classifiers to verify its performance. The experimental results show that the amount of significant features helps the algorithm to classify different sleeping patterns more accurately, and the f1 score of the SPR-DE model determined by the comparison experiments is 0.998, and the accuracy can reach 99.9%. Compared with other models, the accuracy is improved by 2.9% ~ 7.7%, and the f1-score is improved by 0.029 ~ 0.076. Therefore, it is concluded that the SMR feature extraction strategy in the SPR-DE model and the AdaBoost-SVM can achieve high accuracy and strong robustness in the task of sleep posture recognition in a small area, low-density air-pressure mattress, taking into account the comfort of the mattress structural design and the sleep posture recognition, integrated with the mattress adaptive adjustment system.

Preferences and Avoidance of Sleeping Positions Among Patients With Chronic Low Back Pain: A Cross-Sectional Study

Background Chronic low back pain (CLBP) is a common issue among the working-age population. Sleeping position may affect CLBP, with the prone position commonly suggested to be avoided. This study aims to examine the relationship between preferred and avoided sleeping positions and to explore the frequency of increased pain in various sleeping positions among patients with nonspecific CLBP and pain and disability levels. Methods This cross-sectional study included all adult patients referred for specialist consultation for CLBP at the outpatient clinic of the Central Hospital of Central Finland's spine department. Pain intensity was measured using a visual analog scale (VAS), and disability was assessed with the Oswestry Disability Index (ODI). Patients completed a questionnaire detailing the main sleeping positions and positions avoided due to low back pain (LBP). Results The study enrolled 375 consecutive patients, with a mean age of 51 ± 17 years; 64% (n=240) were female. The mean VAS score was 63 ± 24, and the mean Oswestry Index was 38 ± 18%. The majority of patients (87%, n=327) reported sleeping in a side-lying position, followed by supine (47%, n=176) and prone (22%, n=82) positions. A negative correlation was found between age and the preference for sleeping in the prone position. No significant gender differences in sleep positions were observed (p=0.69). Sleep was disturbed in 77% of patients (n=289) due to LBP, and 87% (n=327) reported difficulties due to LBP when getting up. Overall, 92% of participants (n=345) experienced difficulties sleeping or getting up in the morning due to LBP. Many patients avoided certain positions due to pain: 42% (n=157) avoided the prone position, 35% (n=131) the back, 15% (n=56) the left side, and 13% (n=49) the right side. Although the prone position was most commonly linked with pain, especially among women, our findings suggest that any sleeping position could potentially exacerbate pain in individuals with CLBP. Conclusions This study highlights the variability in how sleeping positions affect pain in patients with nonspecific CLBP. While the prone position is most frequently associated with increased pain, individual preferences and responses vary significantly, and often sidelying and supine positions provoke pain. The diversity in sleeping positions that exacerbate pain highlights the need for tailored advice in the management of patients with CLBP.

Association between adherence to the mediterranean diet, physical activity, and sleep apnea-hypopnea syndrome (SAHS) in a middle-aged population with cardiovascular risk: Insights from the ILERVAS cohort

INTRODUCTION

Sleep Apnea-Hypopnea Syndrome (SAHS) is a common sleep disorder influenced by factors like age, gender, and obesity. The Mediterranean Diet (MedDiet) and physical activity have shown health benefits in lung diseases, but their effects on SAHS remain underexplored.

METHODS

In a cross-sectional analysis of 678 middle-aged individuals with low-to-moderate cardiovascular risk from the ILERVAS cohort, we assessed adherence to the MedDiet and physical activity levels using validated tools. Sleep parameters, SAHS severity, and excessive daytime sleepiness were evaluated through non-attended cardiorespiratory polygraphy and the Epworth Sleepiness Scale. Multinomial logistic regression models were employed to assess the relationship between MedDiet adherence, physical activity, and SAHS severity.

RESULTS

The prevalence of severe, moderate, and mild SAHS was 15.5%, 23.2% and 36.1%, respectively. We found no significant associations between adherence to the MedDiet, physical activity levels, and the presence or severity of SAHS. However, we noted a significant interaction between MedDiet and physical activity with minimum SpO2 values (p = 0.049). Notably, consuming more than one serving of red meat per day was independently associated with a higher risk of moderate SAHS [OR = 2.65 (1.29-5.44), p = 0.008].

CONCLUSION

Individually, MedDiet adherence and physical activity did not show independent correlations with SAHS. However, when considered together, a minimal but significant effect on minimum SpO2 was observed. Additionally, red meat consumption was associated with a moderate risk of SAHS. Further research is necessary to comprehend the intricate connections between lifestyle factors and sleep-breathing disorders, with a focus on personalized approaches for high-risk populations.

The impact of 5-hydroxytryptophan supplementation on sleep quality and gut microbiota composition in older adults: A randomized controlled trial

BACKGROUND & AIMS

Sleep quality is a pivotal part of health and there is growing evidence on the association between gut microbiota composition and sleep quality. 5-Hydroxytryptophan (5-HTP) is known as a precursor of the sleep regulating neurotransmitter and hormone. However, efficacy of 5-HTP supplementation for improving sleep quality in older adults is unclear. Hence, the aim of this study is to assess the impact of 5-HTP supplementation on sleep quality and gut microbiota composition in older adults.

METHODS

This is a single-blinded, 12-week parallel randomized controlled trial. Thirty older adults (66 ± 3 years) in Singapore were randomly assigned to either consume or not consume 100 mg 5-HTP daily. Every 4 weeks, sleep quality was assessed via both subjective (Pittsburg Sleep Quality Index) and objective (actigraphy watch) measures. A global sleep score (GSS) was obtained from the PSQI, where a GSS>5 defines as poor sleeper while a GSS≤5 defines as good sleeper. Blood serotonin level, urine melatonin concentration, gut microbiota composition and stool short chain fatty acids (SCFA) content were assessed at week 0 and 12. This study was registered in clinicaltrials.gov as NCT04078724 (https://clinicaltrials.gov/ct2/show/NCT04078724).

RESULTS

5-HTP supplementation showed an overall favorable effect on certain sleep quality components and an increase in serum serotonin concentration. In particular, at week 12, not good sleepers but poor sleepers with 5-HTP supplementation were able to significantly improve subjective GSS (ΔSL5-HTP: -2.80 ± 1.10 min, p-value = 0.005). In addition, they showed an increase in microbiota diversity (Simpson5-HTP vs. SimpsonControl: 0.037 ± 0.032 a.u. vs. -0.007 ± 0.022 a.u.; pinteraction: 0.013) and relative abundance of SCFA producing bacteria in the gut.

CONCLUSIONS

5-HTP supplementation can improve certain sleep quality components in older adults and this benefit was more prominently observed in poor sleepers. 5-HTP was also able to improve the gut microbiota composition in poor sleepers.

Vertebral Subluxation and Systems Biology: An Integrative Review Exploring the Salutogenic Influence of Chiropractic Care on the Neuroendocrine-Immune System

In this paper we synthesize an expansive body of literature examining the multifaceted influence of chiropractic care on processes within and modulators of the neuroendocrine-immune (NEI) system, for the purpose of generating an inductive hypothesis regarding the potential impacts of chiropractic care on integrated physiology. Taking a broad, interdisciplinary, and integrative view of two decades of research-documented outcomes of chiropractic care, inclusive of reports ranging from systematic and meta-analysis and randomized and observational trials to case and cohort studies, this review encapsulates a rigorous analysis of research and suggests the appropriateness of a more integrative perspective on the impact of chiropractic care on systemic physiology. A novel perspective on the salutogenic, health-promoting effects of chiropractic adjustment is presented, focused on the improvement of physical indicators of well-being and adaptability such as blood pressure, heart rate variability, and sleep, potential benefits that may be facilitated through multiple neurologically mediated pathways. Our findings support the biological plausibility of complex benefits from chiropractic intervention that is not limited to simple neuromusculoskeletal outcomes and open new avenues for future research, specifically the exploration and mapping of the precise neural pathways and networks influenced by chiropractic adjustment.

Sleep health predicted glucose metabolism among pregnant women: A prospective cohort study

AIMS

To examine whether sleep health in the first trimester could predict glucose metabolism in the second trimester.

METHODS

Pregnant women (N = 127) during the first trimester were recruited (August 2022 to March 2023). Overall sleep health was assessed by the Sleep Health Index. Various dimensions of sleep health were measured using a 7-day sleep diary and questionnaires. The outcomes, including diagnosis of gestational diabetes mellitus (GDM) and HbA1c, were obtained from the medical records in the second trimester. Poisson regression analysis and multiple linear regression were used for data analysis.

RESULTS

The average age of the participants was 32.6 years. The incidence of GDM was 28.3 % and the mean HbA1c was 5.2 % (33 mmol/mol). Sleep duration regularity (RR = 1.808; 95 %CI 1.023, 3.196) was associated with GDM after controlling for confounders. SHI total score (β = -0.278; 95 %CI -0.022, -0.005) and sleep duration regularity (β = 0.243; 95 %CI 0.057, 0.372) were associated with HbA1c.

CONCLUSIONS

Worse sleep health, particularly lower sleep regularity, predicted worse glucose metabolism among pregnant women. Healthcare professional may consider adding sleep-related assessment to prenatal care. Maintaining regular sleep should be encouraged. Studies examining the impact of sleep intervention on glucose metabolism among pregnant women are warranted.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

Accelerometry-assessed sleep clusters and cardiometabolic risk factors in adolescents

OBJECTIVE

This study aimed to identify sleep clusters based on objective multidimensional sleep characteristics and test their associations with adolescent cardiometabolic health.

METHODS

The authors included 1090 participants aged 14.3 to 16.4 years (mean = 15.2 years) who wore 7-day accelerometers during the 15-year follow-up of the German Infant Study on the influence of Nutrition Intervention PLUS environmental and genetic influences on allergy development (GINIplus) and the Influence of Lifestyle factors on the development of the Immune System and Allergies in East and West Germany (LISA) birth cohorts. K-means cluster analysis was performed across 12 sleep characteristics reflecting sleep quantity, quality, schedule, variability, and regularity. Cardiometabolic risk factors included fat mass index (FMI), blood pressure, triglycerides, high-density lipoprotein cholesterol, high-sensitivity C-reactive protein, and insulin resistance (n = 505). Linear and logistic regression models were examined.

RESULTS

Five sleep clusters were identified: good sleep (n = 337); delayed sleep phase (n = 244); sleep irregularity and variability (n = 108); fragmented sleep (n = 313); and prolonged sleep latency (n = 88). The "prolonged sleep latency" cluster was associated with increased sex-scaled FMI (β = 0.39, 95% CI: 0.15-0.62) compared with the "good sleep" cluster. The "sleep irregularity and variability" cluster was associated with increased odds of high triglycerides only in male individuals (odds ratio: 9.50, 95% CI: 3.22-28.07), but this finding was not confirmed in linear models.

CONCLUSIONS

The prolonged sleep latency cluster was associated with higher FMI in adolescents, whereas the sleep irregularity and variability cluster was specifically linked to elevated triglycerides (≥1.7 mmol/L) in male individuals.

Sleep, Nutrition, and Injury Risk in Adolescent Athletes: A Narrative Review

This narrative review explores the impact of sleep and nutrition on injury risk in adolescent athletes. Sleep is viewed as essential to the recuperation process and is distinguished as an active participant in recovery through its involvement in growth, repair, regeneration, and immunity. Furthermore, the literature has shown that the sleep of athletes impacts elements of athletic performance including both physical and cognitive performance, recovery, injury risk, and mental well-being. For sleep to have a restorative effect on the body, it must meet an individual's sleep needs whilst also lasting for an adequate duration and being of adequate quality, which is age-dependent. The literature has suggested that athletes have increased sleep needs compared to those of the general population and thus the standard recommendations may not be sufficient for athletic populations. Therefore, a more individualised approach accounting for overall sleep health may be more appropriate for addressing sleep needs in individuals including athletes. The literature has demonstrated that adolescent athletes achieve, on average, ~6.3 h of sleep, demonstrating a discrepancy between sleep recommendations (8-10 h) and actual sleep achieved. Sleep-wake cycles undergo development during adolescence whereby adaptation occurs in sleep regulation during this phase. These adaptations increase sleep pressure tolerance and are driven by the maturation of physiological, psychological, and cognitive functioning along with delays in circadian rhythmicity, thus creating an environment for inadequate sleep during adolescence. As such, the adolescent period is a phase of rapid growth and maturation that presents multiple challenges to both sleep and nutrition; consequently, this places a significant burden on an adolescent athletes' ability to recover, thus increasing the likelihood of injury. Therefore, this article aims to provide a comprehensive review of the available literature on the importance of sleep and nutrition interactions in injury risk in adolescent athletes. Furthermore, it provides foundations for informing further investigations exploring the relation of sleep and nutrition interactions to recovery during adolescence.

The sleep justice study - a prospective cohort study assessing sleep as a cardiometabolic risk factor after incarceration: a protocol paper

BACKGROUND

An estimated 11 million individuals are released from U.S. jails and prisons each year. Individuals with a history of incarceration have higher rates of cardiovascular disease (CVD) events and mortality compared to the general population, especially in the weeks following release from carceral facilities. Healthy sleep, associated with cardiovascular health, is an underexplored factor in the epidemiology of CVD in this population. Incarcerated people may have unique individual, environmental, and institutional policy-level reasons for being sleep deficient. The social and physical environment within carceral facilities and post-release housing may synergistically affect sleep, creating disparities in sleep and cardiovascular health. Since carceral facilities disproportionately house poor and minoritized groups, population-specific risk factors that impact sleep may also contribute to inequities in cardiovascular outcomes.

METHODS

This study is ancillary to an ongoing prospective cohort recruiting 500 individuals with known cardiovascular risk factors within three months of release from incarceration, the Justice-Involved Individuals Cardiovascular Disease Epidemiology (JUSTICE) study. The Sleep Justice study will measure sleep health among participants at baseline and six months using three validated surveys: the Pittsburgh Sleep Quality Index (PSQI), the STOP-Bang, and the Brief Index of Sleep Control. In a subsample of 100 individuals, we will assess sleep over the course of one week using wrist actigraphy, a validated objective measure of sleep that collects data on rest-activity patterns, sleep, and ambient light levels. Using this data, we will estimate and compare sleep health and its association with CVD risk factor control in individuals recently released from carceral facilities.

DISCUSSION

The incarceration of millions of poor and minoritized groups presents an urgent need to understand how incarceration affects CVD epidemiology. This study will improve our understanding of sleep health among people released from carceral facilities and its potential relationship to CVD risk factor control. Using subjective and objective measures of sleep will allow us to identify unique targets to improve sleep health and mitigate cardiovascular risk in an otherwise understudied population.

The associations between physical activity, sedentary behaviour, and sleep with mortality and incident cardiovascular disease, cancer, diabetes and mental health in adults: a systematic review and meta-analysis of prospective cohort studies

BACKGROUND

Physical activity, sedentary behaviour and sleep are interrelated and may have a synergistic impact on health. This systematic review and meta-analysis of prospective cohort studies aimed to evaluate the combined influence of different combinations of these behaviours on mortality risk and incidence of cardiovascular disease (CVD), cancer, diabetes, and mental health.

METHODS

Four online databases were used to identify studies from database inception to May 2023. Prospective cohort studies that examined how different combinations of physical activity, sedentary and sleep behaviours were associated with mortality and incident cardiovascular disease, cancer, diabetes and mental health in adults were included. Random effects meta-analyses using the Der Simonian and Laird method were conducted.

RESULTS

Assessment of 4583 records resulted in twelve studies being included. Studies were qualitatively summarised and a sub-group of studies (n = 5) were meta-analysed. The most frequent combination of behaviours was duration of leisure time physical activity and sleep (n = 9), with all-cause mortality (n = 16), CVD mortality (n = 9) and cancer mortality (n = 7) the most frequently examined outcomes. Meta-analysis revealed that relative to High physical activity & Mid sleep, High physical activity and Short sleep was not associated with risk of all-cause mortality (RR = 1.05, 95% CI = 0.97, 1.14), however Low physical activity and Short Sleep (RR = 1.42, 95% CI = 1.24, 1.63), Low physical activity and Mid Sleep (RR = 1.30, 95% CI = 1.12, 1.52), High physical activity and Long Sleep (RR = 1.16, 95% CI = 1.01, 1.32), and Low physical activity and Long Sleep were associated with risk of all-cause mortality (RR = 1.63, 95% CI = 1.21, 2.20).

CONCLUSIONS

High levels of physical activity may offset all-cause mortality risks associated with short sleep duration. Low levels of physical activity combined with short sleep duration and any level of physical activity in combination with long sleep duration appear to increase mortality risk. Currently there is limited evidence regarding how dimensions of physical activity, sedentary and sleep behaviours other than duration (e.g., quality, timing, type) are associated with future health status.

Branched-chain amino acids and sleep: a population-derived study of Australian children aged 11-12 years and their parents

Micronutrients, particularly amino acids, are thought to play an important role in sleep regulation and maintenance. While tryptophan is a known predictor of sleep, less is known about branched-chain amino acids (BCAAs), which compete with tryptophan for transport across the blood-brain barrier. The aim of this study was to determine the association between BCAAs and actigraphy-derived sleep duration, timing and efficiency, and self-reported trouble sleeping. This study examined data on children and adults collected as part of the Child Health CheckPoint study. Linear mixed models, adjusted for geographic clustering, were used to determine the association between BCAAs and sleep characteristics. Complete-case analysis was conducted for 741 children aged 11-12 years old (51% females) and 941parents (87% mothers). While BCAAs were significantly associated with children's sleep duration, timing and self-reported trouble sleeping, no associations were observed in adults, in fully adjusted models. In children, higher levels of BCAAs are associated with shorter sleep duration, delayed sleep timing, and more frequent reports of trouble sleeping.

The association between 24-hour activity, sedentary and sleep compositions and mental health in Australian adults: a cross-sectional study

BACKGROUND

Physical activity, sedentary behaviour, and sleep are key components to health and well-being. Compositional data analysis of activity data overcomes the limitations of traditional statistical approaches and comprehensively assesses the association of all activities throughout a 24-hour day. Few studies have used compositional analysis to explore associations between movement behaviours and mental health. This study examined the association between 24-hour activity compositions and mental health in middle-aged Australian adults.

METHODS

This study used cross-sectional data from participants (n = 322; mean age 40.4 years; 58.1% female; 47.8% university degree; 84.8% partnered) in the longitudinal Annual Rhythms in Adults' lifestyle and health study (Adelaide, Australia). Activity composition (sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity) was derived using 24-hour Fitbit accelerometry from the first month of participation (December). Mental health outcomes (depression, anxiety, and stress) were obtained from the Depression Anxiety Stress Scale 21-item short-form (DASS-21). The associations between activity composition (conveyed as isometric log ratios) and DASS-21 scores were examined using compositional multi-level linear regression models with a random intercept for clustering of individuals within families. Using the compositional time reallocation model, expected differences in mental health were examined for hypothetical time reallocations between individual activities.

RESULTS

Favourable associations were observed when time (15 min) was reallocated to light physical activity from sleep (depression: -0.31 [95% CI=-0.57: -0.06]; anxiety: -0.20 [95% CI=-0.37: -0.03] and from sedentary behaviour (depression: -0.29 [95% CI=-0.46: -0.13]; anxiety: -0.14 [95% CI=-0.25: -0.03]; stress: -0.16 [95% CI=-0.31: -0.01]). Detrimental associations were observed when time was reallocated away from light physical activity to sleep (depression: 0.32 [95% CI = 0.07: 0.58]; anxiety: 0.20 [95% CI = 0.03: 0.37]) and to sedentary behaviour (depression: 0.30 [95% CI = 0.13: 0.48); anxiety: 0.15 [95% CI = 0.03: 0.26]; stress: 0.17 [95% CI = 0.01: 0.32]). There were no associations when time was allocated to or from moderate-to-vigorous physical activity.

CONCLUSION

The way adults spend their time across a 24-hour day is associated with their mental health. Spending more time in light physical activity appears favourable if this time is taken from sleep and sedentary behaviour. These findings provide support for "move more, sit less" public health messages.

TRIAL REGISTRATION

This study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123) on the 16/10/2019.

Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students

Video games are a popular form of entertainment. However, there is mixed evidence for the association between video game usage and poor sleep quality, short sleep duration, or delayed sleep timing. The current study examined associations between daily sleep behaviours and video game usage via a Bayesian and frequentist statistical approach. Caffeine and alcohol consumption were also assessed as moderators, as these behaviours may co-occur with video game usage and poor sleep. 1032 (72% female) undergraduate students were recruited between 2006-2007. Participants completed questionnaires examining video game and substance use, as well as sleep diaries for 1 week. Frequentist analyses revealed that video game usage was related to increased variability in the total sleep time, and a later average sleep midpoint, but not sleep efficiency. Alcohol use moderated the relationships between video game usage and both average and variability in total sleep time. Caffeine use was related to shorter average total sleep time and more variability in sleep efficiency. Alcohol consumption was related to more variability in the total sleep time and sleep midpoint, and a later average sleep midpoint. Bayesian models suggested strong evidence that video game playing was associated with later average sleep midpoint. Like the frequentist approach, alcohol consumption moderated the relationship between video game usage and both average and variability in total sleep time, but the evidence was weak. The effect sizes for both approaches tended to be small. Using a rigorous statistical approach and a large sample, this study provides robust evidence that video game usage may not be strongly associated with poor sleep among undergraduate students.

AI-Driven sleep staging from actigraphy and heart rate

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold standard for sleep assessment and the clinical diagnosis of sleep disorders is polysomnography (PSG). However, PSG requires an overnight clinic visit and trained technicians to score the obtained multimodality data. Wrist-worn consumer devices, such as smartwatches, are a promising alternative to PSG because of their small form factor, continuous monitoring capability, and popularity. Unlike PSG, however, wearables-derived data are noisier and far less information-rich because of the fewer number of modalities and less accurate measurements due to their small form factor. Given these challenges, most consumer devices perform two-stage (i.e., sleep-wake) classification, which is inadequate for deep insights into a person's sleep health. The challenging multi-class (three, four, or five-class) staging of sleep using data from wrist-worn wearables remains unresolved. The difference in the data quality between consumer-grade wearables and lab-grade clinical equipment is the motivation behind this study. In this paper, we present an artificial intelligence (AI) technique termed sequence-to-sequence LSTM for automated mobile sleep staging (SLAMSS), which can perform three-class (wake, NREM, REM) and four-class (wake, light, deep, REM) sleep classification from activity (i.e., wrist-accelerometry-derived locomotion) and two coarse heart rate measures-both of which can be reliably obtained from a consumer-grade wrist-wearable device. Our method relies on raw time-series datasets and obviates the need for manual feature selection. We validated our model using actigraphy and coarse heart rate data from two independent study populations: the Multi-Ethnic Study of Atherosclerosis (MESA; N = 808) cohort and the Osteoporotic Fractures in Men (MrOS; N = 817) cohort. SLAMSS achieves an overall accuracy of 79%, weighted F1 score of 0.80, 77% sensitivity, and 89% specificity for three-class sleep staging and an overall accuracy of 70-72%, weighted F1 score of 0.72-0.73, 64-66% sensitivity, and 89-90% specificity for four-class sleep staging in the MESA cohort. It yielded an overall accuracy of 77%, weighted F1 score of 0.77, 74% sensitivity, and 88% specificity for three-class sleep staging and an overall accuracy of 68-69%, weighted F1 score of 0.68-0.69, 60-63% sensitivity, and 88-89% specificity for four-class sleep staging in the MrOS cohort. These results were achieved with feature-poor inputs with a low temporal resolution. In addition, we extended our three-class staging model to an unrelated Apple Watch dataset. Importantly, SLAMSS predicts the duration of each sleep stage with high accuracy. This is especially significant for four-class sleep staging, where deep sleep is severely underrepresented. We show that, by appropriately choosing the loss function to address the inherent class imbalance, our method can accurately estimate deep sleep time (SLAMSS/MESA: 0.61±0.69 hours, PSG/MESA ground truth: 0.60±0.60 hours; SLAMSS/MrOS: 0.53±0.66 hours, PSG/MrOS ground truth: 0.55±0.57 hours;). Deep sleep quality and quantity are vital metrics and early indicators for a number of diseases. Our method, which enables accurate deep sleep estimation from wearables-derived data, is therefore promising for a variety of clinical applications requiring long-term deep sleep monitoring.

Factors associated with use of wearable technology to support activity, well-being, or a healthy lifestyle in the adult population and among older adults

The use of wearable technology, which is often acquired to support well-being and a healthy lifestyle, has become popular in Western countries. At the same time, healthcare is gradually taking the first steps to introduce wearable technology into patient care, even though on a large scale the evidence of its' effectiveness is still lacking. The objective of this study was to identify the factors associated with use of wearable technology to support activity, well-being, or a healthy lifestyle in the Finnish adult population (20-99) and among older adults (65-99). The study utilized a cross-sectional population survey of Finnish adults aged 20 and older (n = 6,034) to analyse non-causal relationships between wearable technology use and the users' characteristics. Logistic regression models of wearable technology use were constructed using statistically significant sociodemographic, well-being, health, benefit, and lifestyle variables. Both in the general adult population and among older adults, wearable technology use was associated with getting aerobic physical activity weekly according to national guidelines and with marital status. In the general adult population, wearable technology use was also associated with not sleeping enough and agreeing with the statement that social welfare and healthcare e-services help in taking an active role in looking after one's own health and well-being. Younger age was associated with wearable technology use in the general adult population but for older adults age was not a statistically significant factor. Among older adults, non-use of wearable technology went hand in hand with needing guidance in e-service use, using a proxy, or not using e-services at all. The results support exploration of the effects of wearable technology use on maintaining an active lifestyle among adults of all ages.

Psychometric evaluation of the Chinese version of Sleep Health Index in pregnant women

OBJECTIVE

The aim of this study was to investigate the psychometric properties of the Chinese version of the Sleep Health Index (SHI-C) among pregnant women.

DESIGN

Cross-sectional design.

SETTING

Outpatient clinic of three hospitals in China.

PARTICIPANTS

Pregnant women (N = 264) aged between 18 and 45 years were recruited via convenience sampling.

METHODS

The Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS) and Insomnia Severity Index (ISI) were used to measure sleep quality, daytime sleepiness, and insomnia, respectively. The Fatigue Assessment Scale (FAS) and the Edinburgh Postnatal Depression Scale (EPDS) were used to measure fatigue and depression, respectively. Structural validity was assessed via confirmatory factor analysis (CFA). Concurrent and convergent validity were assessed using bivariate correlation analyses. Known-group validity was assessed by comparing the SHI-C score between different groups. Cronbach's α was calculated for reliability.

FINDINGS

The average sample age was 30.6 years old and their average score of SHI-C was 86.4 (SD 8.2). Based on PSQI, ISI, and ESS, 43.6%, 32.2%, and 26.9% had poor sleep quality, insomnia, and excessive daytime sleepiness, respectively. The SHI-C total and sleep quality sub-index scores had moderate to strong correlations with both PSQI (r=-0.542, p<0.01; r=-0.648, p<0.01) and ISI (r=-0.692, p<0.01; r=-0.752, p<0.01). The SHI-C total and sleep quality sub-index scores were significantly associated with ESS, FAS, and EPDS (r=-0.171 to -0.276; p<0.01). The SHI-C total score was higher in the second trimester and among those who were working, never drank coffee, or took a nap every day. The Cronbach's α of the SHI-C total and the sleep quality sub-index were 0.723 and 0.806, respectively. The Cronbach's α of sleep duration and disordered sleep sub-indices were 0.594 and 0.545, respectively.

KEY CONCLUSIONS

Overall, the SHI-C has good validity and acceptable reliability among the pregnant population in China. It can be a useful tool for the assessment of sleep health. More research is warranted to refine the sleep duration and disordered sleep sub-indices.

IMPLICATIONS FOR PRACTICE

The use of SHI-C would facilitate the assessment of sleep health among pregnant women, which could contribute to the promotion of perinatal care.

The past, present, and future of sleep quality assessment and monitoring

Sleep quality is considered to be an individual's self-satisfaction with all aspects of the sleep experience. Good sleep not only improves a person's physical, mental and daily functional health, but also improves the quality-of-life level to some extent. In contrast, chronic sleep deprivation can increase the risk of diseases such as cardiovascular diseases, metabolic dysfunction and cognitive and emotional dysfunction, and can even lead to increased mortality. The scientific evaluation and monitoring of sleep quality is an important prerequisite for safeguarding and promoting the physiological health of the body. Therefore, we have compiled and reviewed the existing methods and emerging technologies commonly used for subjective and objective evaluation and monitoring of sleep quality, and found that subjective sleep evaluation is suitable for clinical screening and large-scale studies, while objective evaluation results are more intuitive and scientific, and in the comprehensive evaluation of sleep, if we want to get more scientific monitoring results, we should combine subjective and objective monitoring and dynamic monitoring.

The association between sleep quality and telomere length: A systematic literature review

Several sleep parameters present an elevated risk for processes that contribute to cellular aging. Short sleep duration, sleep apnoea, and insomnia are significantly associated with shorter telomeres, a biological marker of cellular aging. However, there has been no review or analysis of studies that have examined the association between the psychological construct of sleep quality and telomere length. The present study aimed to provide a systematic review of the association between sleep quality and telomere length. A systematic review of English articles was conducted using MEDLINE/PubMed, PsycINFO, Google Scholar, and Web of Science electronic databases, with the final search conducted on 3rd September 2021. Search terms included sleep quality, poor sleep, insomnia, sleep difficulties, sleep issue*, non-restorative sleep, telomere*, cellular aging, and immune cell telomere length. Study eligibility criteria included human participants aged 18 years or older and a reproducible methodology. Study appraisal and synthesis were completed using a systematic search in line with a PICOS approach (P = Patient, problem, or population; I = Intervention, prognostic factor, exposure; C = Comparison, control, or comparator; O = Outcomes; S = Study designs). Twenty-two studies met review inclusion criteria. Qualitative synthesis of the literature indicated insufficient evidence overall to support a significant association between sleep quality and telomere length. Limitations across studies were addressed, such as the assessment of examined constructs. Findings highlight important targets for future research, including the standardised operationalisation of the sleep quality construct and experimental study designs. Research in this area has clinical significance by identifying possible mechanisms that increase the risk for age-related disease and mortality. PROSPERO Registration No.: CRD 42021233139.

Multidimensional Sleep and Cardiometabolic Risk Factors for Type 2 Diabetes: Examining Self-Report and Objective Dimensions of Sleep

Purpose:

The purpose of the study was to determine the association between objective and self-report measures of sleep and cardiometabolic risk factors for type 2 diabetes.

Methods:

This study examines data on Australian adults, collected as part of the Child Health CheckPoint study. Sleep was examined in terms of actigraphy-derived sleep duration, timing, efficiency and variability; and self-report trouble sleeping. Cardiometabolic risk factors for type 2 diabetes were examined in terms of body mass index and biomarkers of inflammation and dyslipidemia. Generalized estimating equations, adjusted for geographic clustering, were used to determine the association between measures of sleep and cardiometabolic risk factors.

Results:

Complete case analysis was conducted for 1017 parents (87% mothers). Both objective and self-report measures of sleep were significantly but weakly associated with cardiometabolic risk factors.

Conclusion:

Both objective and self-report measures of sleep are significantly associated with cardiometabolic risk factors for type 2 diabetes. Self-report troubled sleep is associated with poorer cardiometabolic health, independent of actigraphy-derived sleep parameters.

Sleep and Circadian Disturbance in Cardiovascular Risk

PURPOSE OF REVIEW

We discuss the relationship between sleep and circadian factors with cardiovascular disease (CVD) risk, including physiologic, behavioral, and psychological mechanisms along this pathway.

RECENT FINDINGS

The relationship between short and long sleep duration, as well as insomnia, with CVD risk is well-established. Recent work has highlighted how other sleep factors, such as sleep regularity (i.e., consistency of sleep timing), multidimensional sleep health, and circadian factors like chronotype and social jetlag, relate to CVD risk. Sleep-focused interventions (e.g., cognitive behavioral therapy for insomnia and sleep extension) may be effective to reduce CVD risk and disease burden. Sleep is increasingly recognized as an integral component of cardiovascular health. This was underscored by the recent inclusion of sleep duration as a health behavior in the American Heart Association's Life's Essential 8 for defining optimal cardiovascular health.

Prevalence of short and long sleep duration: Ravansar NonCommunicable Disease (RaNCD) cohort study

Background

Prevalence of short and long sleep duration varies in different countries and changes over time. There are limited studies on Iranians’ sleep duration, and we aimed to evaluate the prevalence of short and long sleep duration and associated factors among people living in Kermanshah, Iran.

Methods

This population-based cross-sectional study was conducted between November 2014 and February 2017. Data was collected from 10,025 adults aged 35 to 65 years using census sampling, and we evaluated the short and long sleep duration (≤ 6 and ≥ 9 h, respectively) and its relation with the socio-demographic factors and health-related status of the participants.

Results

Mean age of participants was 48.1 years (standard deviation = 8.2), and 47.4% of participants were male. Of our participants, 11.6% had short, and 21.9% had long sleep duration. Age ≥ 50 years, female gender, being single, mobile use for longer than 8 h per day, working in night shifts, moderate and good levels of physical activity, BMI ≥ 30, past smoking, and alcohol use were associated with short sleep duration (P < 0.05). Female gender and living in rural areas were associated with long sleep duration (P < 0.05).

Conclusion

In the Ravansar population, short and long sleep duration are prevalent, with long sleep duration having higher prevalence. People at risk, such as night shift workers, as well as modifiable factors, such as mobile phone use, can be targeted with interventions to improve sleep hygiene.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14061-4.

Spanish version of Jenkins Sleep Scale in physicians and nurses: psychometric properties from a Peruvian nationally representative sample

OBJECTIVE

To evaluate the psychometric properties of the Spanish version of Jenkins Sleep Scale with 4 items (JSS-4) of the Peruvian health system's (PHS) nurses and physicians.

METHODS

We carried out a psychometric study based on secondary analysis in a sample from a nationally representative survey that used acomplex sampling design. The participants were physicians and nurses aged 18-65 years, working in PHS private and public facilities, who have fulfilled all JSS-4 items. We performed a confirmatory factor analysis. Reliability was evaluated via two estimates - classic alpha (α) and categorical omega (ω) coefficients. Also, we tested the invariance across groups of variables. The convergent validity was evaluated based on the relation between JSS-4 and PHQ-2 using Pearson's correlation coefficient and effect size (Cohen's d). Also, we designed normative values based on percentiles.

RESULTS

We included 2100 physicians and 2826 nurses in the analysis. We observed that the unidimensional model has adequate goodness-of-fit indices and values of α and ω coefficients. No measurement invariance was found between the groups of professionals and age groups; however, invariance was achieved between sex, monthly income, work-related illness, and chronic illness groups. Regarding the relation with other variables, the JSS-4 has a small correlation with PHQ-2. Also, profession and age-specific normative values were proposed.

CONCLUSION

JSS-4 Spanish version has adequate psychometric properties in PHS nurses and physicians.

Age Trends in Actigraphy and Self-Report Sleep Across the Life Span: Findings From the Pittsburgh Lifespan Sleep Databank

OBJECTIVE

Sleep changes over the human life span, and it does so across multiple dimensions. We used individual-level cross-sectional data to characterize age trends and sex differences in actigraphy and self-report sleep dimensions across the healthy human life span.

METHODS

The Pittsburgh Lifespan Sleep Databank consists of harmonized participant-level data from sleep-related studies conducted at the University of Pittsburgh (2003-2019). We included data from 1065 (n = 577 female; 21 studies) Pittsburgh Lifespan Sleep Databank participants aged 10 to 87 years without a major psychiatric, sleep, or medical condition. All participants completed wrist actigraphy and the self-rated Pittsburgh Sleep Quality Index. Main outcomes included actigraphy and self-report sleep duration, efficiency, and onset/offset timing, and actigraphy variability in midsleep timing.

RESULTS

We used generalized additive models to examine potentially nonlinear relationships between age and sleep characteristics and to examine sex differences. Actigraphy and self-report sleep onset time shifted later between ages 10 and 18 years (23:03-24:10 [actigraphy]; 21:58-23:53 [self-report]) and then earlier during the 20s (00:08-23:40 [actigraphy]; 23:50-23:34 [self-report]). Actigraphy and self-report wake-up time also shifted earlier during the mid-20s through late 30s (07:48-06:52 [actigraphy]; 07:40-06:41 [self-report]). Self-report, but not actigraphy, sleep duration declined between ages 10 and 20 years (09:09-07:35). Self-report sleep efficiency decreased over the entire life span (96.12-93.28), as did actigraphy variability (01:54-01:31).

CONCLUSIONS

Awareness of age trends in multiple sleep dimensions in healthy individuals-and explicating the timing and nature of sex differences in age-related change-can suggest periods of sleep-related risk or resilience and guide intervention efforts.

Cross-sectional and prospective associations of sleep duration and bedtimes with adiposity and obesity risk in 15 810 youth from 11 international cohorts

OBJECTIVES

To investigate associations of bedtimes and sleep durations with adiposity levels in children and adolescents.

METHODS

Individual data were pooled for 12 247 children (5819 with follow-up adiposity at 2.3 ± 1.4 years post-baseline) and 3563 adolescents from 11 international studies. Associations between questionnaire-based sleep durations, bedtimes and four groups of combined bedtimes and sleep lengths (later-shorter [reference]/earlier-shorter/later-longer/earlier-longer) with measured adiposity (body mass index [BMI] and waist circumference z-scores) and weight status, were investigated.

RESULTS

In children, longer sleep durations were consistently associated with lower adiposity markers, and earlier bedtimes were related to lower BMI z-score. Compared to sleeping <10 h, longer baseline sleep duration favourably predicted Δwaist z-score in girls (≥10 and <11 h (β-coefficient (95% confidence interval [CI])): -0.06 (-0.12 to -0.01)) and boys (≥11 h: -0.10 [-0.18 to -0.01]). Combined groups that were defined by longer sleep (later-longer and earlier-longer sleep patterns) were associated with lower adiposity, and later-longer sleep favourably predicted Δwaist z-score in girls (-0.09 [-0.15 to -0.02]). In adolescents, longer sleep durations and earlier bedtimes were associated with lower BMI z-score in the whole sample, and also with lower waist z-score in boys. Combined groups that were characterized by earlier bedtimes were associated with the same outcomes. For example, earlier-shorter (-0.22 (-0.43 to -0.01) and earlier-longer (-0.16 (-0.25 to -0.06) sleep were both associated with lower BMI z-score.

CONCLUSIONS

If the associations are causal, longer sleep duration and earlier bedtimes should be targeted for obesity prevention, emphasizing longer sleep for children and earlier bedtimes for adolescents.

Association Between Dietary Protein Intake and Sleep Quality in Middle-Aged and Older Adults in Singapore

Poor sleep has been associated with the increased risk of developing detrimental health conditions. Diet and certain nutrients, such as dietary protein (PRO) may improve sleep. This cross-sectional study aimed to investigate the relationship between PRO intake, their amino acid components, and sources with sleep quality in middle-aged and older adults residing in Singapore. A dataset of 104 healthy subjects between the age of 50 and 75 years old were used. Collected data included 3-day food record and sleep quality [sleep duration, global sleep score (GSS), sleep latency (SL), and sleep efficiency (SE)]. The collected 3-day food records were extracted for PRO, tryptophan (Trp), and large neutral amino acid (LNAA) intake. PRO intake was further categorized into plant and animal PRO. A multivariate multiple linear regression (MLR) was performed to assess the association between PRO intake and sleep quality. Dietary Trp:LNAA ratio was positively associated with sleep duration (β_total: 108.234 h; p: 0.005) after multiple covariates adjustment. Similarly, plant Trp (β_plant: 2.653 h/g; p: 0.020) and plant Trp:LNAA (β_plant: 54.006 h; p: 0.008) was positively associated with sleep duration. No significant associations were observed for both SL and SE. Sleep duration in middle-aged and older Singaporean adults was positively associated with dietary Trp and Trp:LNAA, especially when obtained from plant sources.

Evaluation of a Single-Channel EEG-Based Sleep Staging Algorithm

Sleep staging is the basis of sleep assessment and plays a crucial role in the early diagnosis and intervention of sleep disorders. Manual sleep staging by a specialist is time-consuming and is influenced by subjective factors. Moreover, some automatic sleep staging algorithms are complex and inaccurate. The paper proposes a single-channel EEG-based sleep staging method that provides reliable technical support for diagnosing sleep problems. In this study, 59 features were extracted from three aspects: time domain, frequency domain, and nonlinear indexes based on single-channel EEG data. Support vector machine, neural network, decision tree, and random forest classifier were used to classify sleep stages automatically. The results reveal that the random forest classifier has the best sleep staging performance among the four algorithms. The recognition rate of the Wake phase was the highest, at 92.13%, and that of the N1 phase was the lowest, at 73.46%, with an average accuracy of 83.61%. The embedded method was adopted for feature filtering. The results of sleep staging of the 11-dimensional features after filtering show that the random forest model achieved 83.51% staging accuracy under the condition of reduced feature dimensions, and the coincidence rate with the use of all features for sleep staging was 94.85%. Our study confirms the robustness of the random forest model in sleep staging, which also represents a high classification accuracy with appropriate classifier algorithms, even using single-channel EEG data. This study provides a new direction for the portability of clinical EEG monitoring.

Improving Practices of Mental Health Professionals in Recommending More Physical Activity and Less Sedentary Behaviour to Their Clients: An Intervention Trial

We investigated the effects of increasing physical activity (PA) and reducing sedentary behaviour (SB) of mental health professionals on their attitudes towards and practices in recommending more PA and less SB to their clients. A 4-week pre-post intervention trial was conducted involving 17 mental health professionals. The participants who increased their own physical activity during the intervention increased the frequency of recommending more PA (p = 0.009) and less SB (p = 0.005) to their clients. A relatively simple, low-cost intervention, consisting of group behaviour change counselling, goal setting and positive feedback, may improve the practices of mental health professionals.Supplemental data for this article is available online at https://doi.org/10.1080/01612840.2021.1972189 .

Dietary tryptophan and the risk of obesity and type 2 diabetes: Total effect and mediation effect of sleep duration

OBJECTIVE

The aims of this study were to examine the effects of tryptophan consumption on obesity and type 2 diabetes (T2D) risk and whether sleep duration mediates these effects.

METHODS

Overall, data of 7,908 participants were obtained from the China Health and Nutrition Survey (1997-2011). A total of 6,373 and 4,398 participants who reported sleep duration and had blood samples, respectively, were incorporated into subgroup analyses. Multivariate Cox regression models were used to assess the associations between tertiles of tryptophan intake with obesity and T2D. General linear regression models were used to evaluate the effect of tryptophan on sleep time and plasma biomarkers.

RESULTS

Dietary tryptophan was significantly associated with decreased risk of obesity and T2D risk (hazard ratio _{tertile 3 to tertile 1} : 0.602 [95% CI: 0.500-0.724]; 0.693 [95% CI: 0.565-0.850]). Sleep duration was significantly higher, and hemoglobin A1c, total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B-100 (APO-B) were lower in the high tertile of tryptophan compared with the low tertile (p < 0.05). In addition, mediation effects on the associations of tryptophan intake with obesity and T2D risk were observed for sleep duration (estimated mediation percentage: 31.902% and 37.391%).

CONCLUSIONS

Dietary tryptophan showed advantageous effects on obesity and T2D risk. Furthermore, sleep duration potentially mediated for these effects.

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

RATIONALE

Sleep health is best described by the co-occurrence of various dimensions (e.g., regularity, daytime alertness, satisfaction, efficiency, duration) but is rarely measured this way. Information is needed regarding common within-person patterns of sleep characteristics among adults and their relative healthiness.

OBJECTIVE

To deepen understanding of healthy and unhealthy sleep, the present study aimed to uncover multidimensional sleep profiles in adults and their associations with a variety of psychological and physical well-being outcomes.

METHODS

Survey data from 4622 adults who participated in the Midlife in the United States (MIDUS) project was used to identify latent sleep profiles across five core sleep dimensions. Adjusting for individual sleep dimensions and sociodemographic covariates, General Linear Models were used to test the associations of sleep profile membership with hedonic and eudemonic well-being and chronic physical conditions.

RESULTS

Four latent sleep profiles were revealed, good sleepers, sufficient but irregular sleepers, nappers, and short, dissatisfied, and inefficient sleepers. The profiles differentially related to well-being outcomes above and beyond individual sleep dimensions and sociodemographic covariates. Good sleepers generally reported the best outcomes, and short, dissatisfied, and inefficient sleepers generally reported the worst outcomes.

CONCLUSION

Four common sleep profiles describe adults' holistic sleep experiences and predict a variety of well-being outcomes beyond other known predictors. In adulthood, healthy sleep may involve sufficient sleep across all dimensions whereas unhealthy sleep may involve insufficient sleep across three key dimensions: duration, satisfaction, and efficiency.

Associations between brain structure and sleep patterns across adolescent development

STUDY OBJECTIVES

Structural brain maturation and sleep are complex processes that exhibit significant changes over adolescence and are linked to many physical and mental health outcomes. We investigated whether sleep-gray matter relationships are developmentally invariant (i.e. stable across age) or developmentally specific (i.e. only present during discrete time windows) from late childhood through young adulthood.

METHODS

We constructed the Neuroimaging and Pediatric Sleep Databank from eight research studies conducted at the University of Pittsburgh (2009-2020). Participants completed a T1-weighted structural MRI scan (sMRI) and 5-7 days of wrist actigraphy to assess naturalistic sleep. The final analytic sample consisted of 225 participants without current psychiatric diagnoses (9-25 years). We extracted cortical thickness and subcortical volumes from sMRI. Sleep patterns (duration, timing, continuity, regularity) were estimated from wrist actigraphy. Using regularized regression, we examined cross-sectional associations between sMRI measures and sleep patterns, as well as the effects of age, sex, and their interaction with sMRI measures on sleep.

RESULTS

Shorter sleep duration, later sleep timing, and poorer sleep continuity were associated with thinner cortex and altered subcortical volumes in diverse brain regions across adolescence. In a discrete subset of regions (e.g. posterior cingulate), thinner cortex was associated with these sleep patterns from late childhood through early-to-mid adolescence but not in late adolescence and young adulthood.

CONCLUSIONS

In childhood and adolescence, developmentally invariant and developmentally specific associations exist between sleep patterns and gray matter structure, across brain regions linked to sensory, cognitive, and emotional processes. Sleep intervention during specific developmental periods could potentially promote healthier neurodevelopmental outcomes.

Multidimensional sleep health is associated with mental well-being in Australian adults

The few studies assessing the relationship between mental health and a multidimensional measure of sleep have been conducted in samples of almost exclusively women. In the present study, we therefore assessed associations of multidimensional sleep health with mental well-being in Australian adults. A cross-sectional, national online survey of sleep health was conducted in 2019 in 2,044 community dwelling adults aged 18-90 years. Composite scores of self-reported healthy sleep were based on Ru-SATED (R-SATED) dimensions of satisfaction, alertness, timing, efficiency and duration scored 0 (never/rarely), 1 (sometimes) or 2 (usually/always), and regularity (social jet lag) was scored 0 (≥1 hr) or 1 (<1 hr). Mental well-being was identified by a report of no problem on the EuroQol (European quality of life) five dimension five level scale (EQ-5D-5L) anxiety/depression scale, as well as absence of six chronic depressive symptoms. Ordinal logistic regression analyses determined associations of mental well-being with sleep dimensions, and total R-SATED (range 0-11) and SATED scores (0-10), adjusted for sociodemographic and health factors. In males and females, healthy categories of SATED dimensions (but not regularity) were associated with mental well-being. A 1 unit increase in the total SATED score (mean [SD] 6.6 [2.1]) was associated with less problems on the EQ-5D-5L (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.08-1.14) and fewer chronic depressive symptoms (OR 1.20, 95% CI 1.17-1.23). These estimates did not differ when the total R-SATED score was considered. Sleep health promotion focussing solely on traditional messaging around healthy sleep duration may limit mental health gains. Rather, a more holistic approach to public health messaging to improve sleep health literacy may be beneficial for mental well-being.