Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality.

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion, 1448 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 34.7 min (95% limits of agreement (LoA): -37.8-107.2 min) for total sleep duration, 2.6 min for REM duration (95% LoA: -68.4-73.4 min) and 32.1 min (95% LoA: -54.4-118.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with 100,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66,214 UK Biobank participants, 1642 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration of 6-7.9 h, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.58; 95% confidence intervals (CIs): 1.19-2.11) or high sleep efficiency (HRs: 1.45; 95% CIs: 1.16-1.81). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Prevalence of excessive daytime sleepiness and its association with daily life factors in Japanese first-year university students.

As lifestyles have shifted to favor nighttime activities, daytime sleepiness and sleep-related problems have become increasingly common in Japan. Excessive daytime sleepiness (EDS) is an adverse consequence of sleep loss and an important public health concern. EDS may cause academic difficulties, behavioral abnormalities, and psychological dysfunction; therefore, it is a particularly important issue among university students. We conducted a cross-sectional study to investigate the prevalence of EDS and its associated lifestyle factors among Japanese university students. A questionnaire was completed by 1470 first-year university students, aged 19.0 (± 1.0) years. Using the questionnaire, we collected information on (1) demographic variables, (2) lifestyle variables, and (3) sleep habits and daytime sleepiness. Daytime sleepiness was measured using the Japanese version of the Epworth Sleepiness Scale, a frequently used subjective scale for assessing sleepiness. The overall prevalence of EDS was 57% (53% in men and 61% in women). Multivariate logistic regression analysis revealed that the following factors were associated with EDS: female sex, exercise habits, long commuting times, later wake-up times, and shorter sleep duration. Given that more than 50% of first-year university students reported having EDS, interventions should be considered to decrease its risk, including educational programs that provide strategies to extend sleep duration and delay wake-up time. Such strategies may also be valuable for students with other potential risk factors, such as exercise habits or long commute times, that are associated with EDS.

The interrelationships between sleep regularity, obstructive sleep apnea, and hypertension in a middle-aged community population.

STUDY OBJECTIVES: Little is known about the interrelationships between sleep regularity, obstructive sleep apnea (OSA) and important health markers. This study examined whether irregular sleep is associated with OSA and hypertension, and if this modifies the known association between OSA and hypertension. METHODS: Six hundred and two adults (age mean(SD) = 56.96(5.51) years, female = 60%) from the Raine Study who were not evening or night shift workers were assessed for OSA (in-laboratory polysomnography; apnea-hypopnea index ≥ 15 events/hour), hypertension (doctor diagnosed, or systolic blood pressure ≥140 mmHg and/or diastolic ≥90 mmHg) and sleep (wrist actigraphy for ≥5 days). A sleep regularity index (SRI) was determined from actigraphy. Participants were categorized by tertiles as severely irregular, mildly irregular, or regular sleepers. Logistic regression models examined the interrelationships between SRI, OSA and hypertension. Covariates included age, sex, body mass index, actigraphy sleep duration, insomnia, depression, activity, alcohol, smoking, and antihypertensive medication. RESULTS: Compared to regular sleepers, participants with mildly irregular (OR 1.97, 95% confidence intervals [CI] 1.20 to 3.27) and severely irregular (OR 2.06, 95% CI: 1.25 to 3.42) sleep had greater odds of OSA. Compared to those with no OSA and regular sleep, OSA and severely irregular sleep combined had the highest odds of hypertension (OR 2.34 95% CI: 1.07 to 5.12; p for interaction = 0.02) while those with OSA and regular/mildly irregular sleep were not at increased risk (p for interaction = 0.20). CONCLUSIONS: Sleep irregularity may be an important modifiable target for hypertension among those with OSA.

Relationship between TV Watching during Childhood and Adolescence, and Artery Function in Adulthood.

PURPOSE: Artery dysfunction is an early, integral stage in atherogenesis that predicts future cardiovascular events. Sedentary behavior, such as TV watching, is highly prevalent and associated with increased risk of developing cardiovascular diseases. This study investigated whether patterns of TV watching throughout childhood and adolescence were associated with artery function in adulthood. METHODS: TV watching data were collected when participants of the Raine Study were aged 5, 8, 10, 14, 17, and 20 yr. Previous latent class analysis indicated three trajectory groups of TV watching: low TV (<14 h·wk -1 ), high TV (>14 h·wk -1 ), and increasing TV (change from low TV to high TV). At age 28 yr, participants were invited to undergo tests of brachial and femoral artery function by flow-mediated dilation (FMD). General linear models examined differences in artery function between TV trajectory groups for men and women. RESULTS: Five hundred sixty participants (n = 261 women, n = 299 men) were included in the study. In women, the low TV group had significantly greater femoral artery FMD (10.8 ± 1.6%) than both High TV (9.0 ± 1.3%, P = 0.005) and Increasing TV groups (8.5 ± 1.3%, P < 0.001); these results were maintained following mediation analysis, including contemporaneous risk factors. There were no significant differences in femoral artery FMD between TV trajectory groups in men ( P = 0.955). CONCLUSIONS: This study suggests that TV watching behaviors during childhood and adolescence may have legacy impacts on artery function at age 28 yr, particularly in women. This may increase the risk of atherosclerotic vascular pathologies in later life.

Health behaviour profiles in young Australian adults in relation to physical and mental health: The Raine Study.

ISSUES ADDRESSED: We aimed to identify latent health behaviour profiles of young adults and examine their associations with physical and mental health outcomes. We also characterised the profiles by socio-demographic characteristics. METHODS: Data were collected between 2012 and 2014. Participants (N = 476) were young adults (M age [SD] = 22.1 [.57] years) from Generation 2 of the Raine Study longitudinal cohort. Health behaviours were measured via ActiGraph GT3X waist monitors (physical activity, sedentary behaviour) and questionnaires (diet quality, alcohol, smoking and sleep). Physical and mental health were measured using clinical health assessments, blood biomarkers, and questionnaires. Latent Profile Analysis using Mplus (8.2) was employed to identify profiles. RESULTS: Four latent profiles were identified: 'heavy drinkers with moderately unhealthy eating habits' (high takeaway foods; n = 135), 'unhealthy food abstainers' (low takeaway foods; n = 138), 'moderately sedentary alcohol abstainers' (n = 139) and 'physically active drinkers with unhealthy eating habits' (high takeaway foods and sugary drinks; n = 64). 'Physically active drinkers with unhealthy eating habits' had the poorest (physical and mental) health outcomes, yet the lowest insulin resistance. 'Unhealthy food abstainers' had the most favourable health outcomes (adiposity, health perceptions, blood pressure). Sex differed among the profiles. CONCLUSIONS: The profiles identified among young adults are different to profiles with general adult populations. A novel finding was that 'physically active drinkers with unhealthy eating habits' had low insulin resistance. The findings also suggest that future interventions may need to be sex specific. SO WHAT: Our findings suggest that health behaviour interventions for young adults should be targeted to distinct profile characteristics.

Predicting obstructive sleep apnoea and perioperative respiratory adverse events in children: role of upper airway collapsibility measurements.

BACKGROUND: Obstructive sleep apnoea (OSA) and perioperative respiratory adverse events are significant risks for anaesthesia in children undergoing adenotonsillectomy. Upper airway collapse is a crucial feature of OSA that contributes to respiratory adverse events. A measure of upper airway collapsibility to identify undiagnosed OSA can help guide perioperative management. We investigated the utility of pharyngeal closing pressure (PCLOSE) for predicting OSA and respiratory adverse events. METHODS: Children scheduled for elective adenotonsillectomy underwent in-laboratory polysomnography 2-12 weeks before surgery. PCLOSE measurements were obtained while the child was anaesthetised and breathing spontaneously just before surgery. Logistic regression was used to assess the predictive performance of PCLOSE for detecting OSA and perioperative respiratory adverse events after adjusting for potential covariates. RESULTS: In 52 children (age, mean [standard deviation] 5.7 [1.8] yr; 20 [38%] females), airway collapse during PCLOSE was observed in 42 (81%). Of these, 19 of 42 (45%) patients did not have OSA, 15 (36%) had mild OSA, and eight (19%) had moderate-to-severe OSA. All 10 children with no evidence of airway collapse during the PCLOSE measurements did not have OSA. PCLOSE predicted moderate-to-severe OSA (odds ratio [OR] 1.71; 95% confidence interval [CI]: 1.2-2.8; P=0.011). All children with moderate-to-severe OSA could be identified at a PCLOSE threshold of -4.0 cm H2O (100% sensitivity), and most with no or mild OSA were ruled out (64.7% specificity; receiver operating characteristic/area under the curve=0.857). However, there was no significant association between respiratory adverse events and PCLOSE (OR 1.0; 95% CI: 0.8-1.1; P=0.641). CONCLUSIONS: Measurement of PCLOSE after induction of anaesthesia can reliably identify moderate or severe OSA but not perioperative respiratory adverse events in children before adenotonsillectomy. CLINICAL TRIAL REGISTRATION: ANZCTR ACTRN 12617001503314.

The need to promote sleep health in public health agendas across the globe.

Healthy sleep is essential for physical and mental health, and social wellbeing; however, across the globe, and particularly in developing countries, national public health agendas rarely consider sleep health. Sleep should be promoted as an essential pillar of health, equivalent to nutrition and physical activity. To improve sleep health across the globe, a focus on education and awareness, research, and targeted public health policies are needed. We recommend developing sleep health educational programmes and awareness campaigns; increasing, standardising, and centralising data on sleep quantity and quality in every country across the globe; and developing and implementing sleep health policies across sectors of society. Efforts are needed to ensure equity and inclusivity for all people, particularly those who are most socially and economically vulnerable, and historically excluded.

Early life predictors of obstructive sleep apnoea in young adults: Insights from a longitudinal community cohort (Raine study).

OBJECTIVE: Early-life obstructive sleep apnoea (OSA) predictors are unavailable for young adults. This study identifies early-life factors predisposing young adults to OSA. METHODS: This retrospective study included 923 young adults and their mothers from the Western Australian Pregnancy Raine Study Cohort. OSA at 22 years was determined from in-laboratory polysomnography. Logistic regression was used to identify maternal and neonatal factors associated with OSA in young adulthood. RESULTS: OSA was observed in 20.8% (192) participants. Maternal predictors of OSA included gestational diabetes mellitus (odds ratio (OR) 9.54, 95% confidence interval (CI) 1.7, 58.5, P = 0.011), preterm delivery (OR 3.18, 95%CI 1.1,10.5, P = 0.043), preeclampsia (OR 2.95, 95%CI 1.1,8.0, P = 0.034), premature rupture of membranes (OR 2.46, 95%CI 1.2, 5.2, P = 0.015), age ≥35 years (OR 2.28, 95%CI 1.2,4.4, P = 0.011), overweight and obesity (pregnancy BMI≥25 kg/m2) (OR 2.00, 95%CI 1.2,3.2, P = 0.004), pregnancy-induced hypertension (OR 1.89, 95%CI 1.1,3.2, P = 0.019), and Chinese ethnicity (OR 2.36,95%CI 1.01,5.5, P = 0.047). Neonatal predictors included male child (OR 2.10, 95%CI 1.5,3.0, P < 0.0001), presence of meconium-stained liquor during delivery (OR 1.60, 95%CI 1.0,2.5, P = 0.044) and admission to special care nursery (OR 1.51 95%CI 1.0,2.2, P = 0.040). Higher birth lengths reduced OSA odds by 7% for each centimetre (OR 0.93, 95%CI 0.87, 0.99, P = 0.033). CONCLUSIONS: A range of maternal and neonatal factors predict OSA in young adults, including those related to poor maternal metabolic health, high-risk pregnancy and stressful perinatal events. This information could assist in the early identification and management of at-risk individuals and indicates that better maternal health may reduce the likelihood of young adults developing OSA.

Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community.

Comparisons of actigraphy findings between studies are challenging given differences between brand-specific algorithms. This issue may be minimized by using open-source algorithms. However, the accuracy of actigraphy-derived sleep parameters processed in open-source software needs to be assessed against polysomnography (PSG). Middle-aged adults from the Raine Study (n = 835; F 58%; Age 56.7 ± 5.6 years) completed one night of in-laboratory PSG and concurrent actigraphy (GT3X+ ActiGraph). Actigraphic measures of total sleep time (TST) were analyzed and processed using the open-source R-package GENEActiv and GENEA data in R (GGIR) with and without a sleep diary and additionally processed using proprietary software, ActiLife, for comparison. Bias and agreement (intraclass correlation coefficient) between actigraphy and PSG were examined. Common PSG and sleep health variables associated with the discrepancy between actigraphy, and PSG TST were examined using linear regression. Actigraphy, assessed in GGIR, with and without a sleep diary overestimated PSG TST by (mean ± SD) 31.0 ± 50.0 and 26.4 ± 69.0 minutes, respectively. This overestimation was greater (46.8 ± 50.4 minutes) when actigraphy was analyzed in ActiLife. Agreement between actigraphy and PSG TST was poor (ICC = 0.27-0.44) across all three methods of actigraphy analysis. Longer sleep onset latency and longer wakefulness after sleep onset were associated with overestimation of PSG TST. Open-source processing of actigraphy in a middle-aged community population, agreed poorly with PSG and, on average, overestimated TST. TST overestimation increased with increasing wakefulness overnight. Processing of actigraphy without a diary in GGIR was comparable to when a sleep diary was used and comparable to actigraphy processed with proprietary algorithms in ActiLife.

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality.

Background: Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. Methods: We developed and validated a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry data from three countries (Australia, the UK, and the USA). The model was validated within-cohort using subject-wise five-fold cross-validation for sleep-wake classification and in a three-class setting for sleep stage classification wake, rapid-eye-movement sleep (REM), non-rapid-eye-movement sleep (NREM) and by external validation. We assessed the face validity of our model for population inference by applying the model to the UK Biobank with 100,000 participants, each of whom wore a wristband for up to seven days. The derived sleep parameters were used in a Cox regression model to study the association of sleep duration and sleep efficiency with all-cause mortality. Findings: After exclusion, 1,448 participant nights of data were used to train the sleep classifier. The difference between polysomnography and the model classifications on the external validation was 34.7 minutes (95% limits of agreement (LoA): -37.8 to 107.2 minutes) for total sleep duration, 2.6 minutes for REM duration (95% LoA: -68.4 to 73.4 minutes) and 32.1 minutes (95% LoA: -54.4 to 118.5 minutes) for NREM duration. The derived sleep architecture estimate in the UK Biobank sample showed good face validity. Among 66,214 UK Biobank participants, 1,642 mortality events were observed. Short sleepers (<6 hours) had a higher risk of mortality compared to participants with normal sleep duration (6 to 7.9 hours), regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.69; 95% confidence intervals (CIs): 1.28 to 2.24 ) or high sleep efficiency (HRs: 1.42; 95% CIs: 1.14 to 1.77). Interpretation: Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Sleep health of young adults in Western Australia and associations with physical and mental health: A population-level cross-sectional study.

OBJECTIVES: This article aims to report on the sleep health characteristics of a population-level sample of young Australian adults and examine associations with measures of physical and mental health. METHODS: A cross-sectional study using data from the Raine Study. Data from participants (n = 1234) born into the study (Generation 2) at the 22-year follow-up were used, including data from a self-report questionnaire and polysomnography. RESULTS: The highest prevalence of suboptimal sleep health was seen on measures of sleep duration (30%), onset latency (18%), satisfaction (25%) and regularity (60%). Dissatisfaction with sleep (physical health: ß =0.08; mental health: ß =0.34) and impaired daytime alertness (physical health: ß =0.09; mental health: ß =0.08) were significantly associated with poorer physical and mental health and inadequate polysomnography-measured sleep duration was associated poorer mental health (ß =0.07) (all ps<0.05). CONCLUSIONS: Satisfaction with sleep and daytime alertness, both of which are assessed via self-report, are essential aspects of sleep health for young adults. IMPLICATIONS FOR PUBLIC HEALTH: Findings could inform public health interventions, including screening guidelines, to improve the sleep health and, in turn, the physical and mental health of young adults in Australia.

Insomnia and workplace productivity loss among young working adults: a prospective observational study of clinical sleep disorders in a community cohort.

OBJECTIVE: To examine associations between three clinically significant sleep disorders (chronic insomnia, obstructive sleep apnoea, restless legs syndrome) and workplace productivity losses among young Australian adults. DESIGN, SETTING: Prospective, observational study; 22-year follow-up of participants in the longitudinal birth cohort Raine Study (Perth, Western Australia). PARTICIPANTS: Currently employed 22-year-old Raine Study participants who underwent in-laboratory sleep disorder screening for moderate to severe obstructive sleep apnoea (apnoea-hypopnea index of more than fifteen events/hour or obstructive sleep apnoea syndrome) and were assessed for insomnia and restless legs syndrome using validated measures. MAIN OUTCOME MEASURES: Total workplace productivity loss over twelve months, assessed with the World Health Organization Health and Work Performance Questionnaire. RESULTS: Of 1235 contactable 22-year-old Raine Study cohort members, 554 people (44.9%; 294 women [53%]) underwent overnight polysomnography, completed the baseline sleep questionnaire, and completed at least three quarterly workplace productivity assessments. One or more clinically significant sleep disorders were identified in 120 participants (21.7%); 90 participants had insomnia (17%), thirty clinically significant obstructive sleep apnoea (5.4%), and two restless legs syndrome (0.4%). Seventeen people (14% of those with sleep disorders) had previously been diagnosed with a sleep disturbance by a health professional, including fourteen with insomnia. Median total workplace productivity loss was greater for participants with sleep disorders (164 hours/year; interquartile range [IQR], 0-411 hours/year) than for those without sleep disorders (30 hours/year; IQR, 0-202 hours/year); total workplace productivity loss was 40% greater for participants with sleep disorders (adjusted incidence rate ratio, 1.40; bias-corrected and accelerated 95% confidence interval, 1.10-1.76). The estimated population total productivity loss (weighted for disorder prevalence) was 28 644 hours per 1000 young workers per year, primarily attributable to insomnia (28 730 hours/1000 workers/year). CONCLUSION: Insomnia is a risk factor for workplace productivity loss in young workers. Tailored interventions are needed to identify and manage sleep disorders, particularly as most of the sleep disorders detected in the Raine Study had not previously been diagnosed.

OSA-Onset: An algorithm for predicting the age of OSA onset.

STUDY OBJECTIVES: There is currently no way to estimate the period of time a person has had obstructive sleep apnoea (OSA). Such information would allow identification of people who have had an extended exposure period and are therefore at greater risk of other medical disorders; and enable consideration of disease chronicity in the study of OSA pathogenesis/treatment. METHOD: The 'age of OSA Onset' algorithm was developed in the Wisconsin Sleep Cohort (WSC), in participants who had ≥2 sleep studies and not using continuous positive airway pressure (n = 696). The algorithm was tested in a participant subset from the WSC (n = 154) and the Sleep Heart Health Study (SHHS; n = 705), those with an initial sleep study showing no significant OSA (apnea-hypopnea index (AHI) < 15 events/hr) and later sleep study showing moderate to severe OSA (AHI≥15 events/hr). RESULTS: Regression analyses were performed to identify variables that predicted change in AHI over time (BMI, sex, and AHI; beta weights and intercept used in the algorithm). In the WSC and SHHS subsamples, the observed years with OSA was 3.6 ± 2.6 and 2.7 ± 0.6 years, the algorithm estimated years with OSA was 10.6 ± 8.2 and 9.0 ± 6.2 years. CONCLUSIONS: The OSA-Onset algorithm estimated years of exposure to OSA with an accuracy of between 6.6 and 7.8 years (mean absolute error). Future studies are needed to determine whether the years of exposure derived from the OSA-Onset algorithm is related to worse prognosis, poorer cognitive outcomes, and/or poorer response to treatment.

Childhood sleep health and epigenetic age acceleration in late adolescence: Cross-sectional and longitudinal analyses.

AIM: Investigate if childhood measures of sleep health are associated with epigenetic age acceleration in late adolescence. METHODS: Parent-reported sleep trajectories from age 5 to 17, self-reported sleep problems at age 17, and six measures of epigenetic age acceleration at age 17 were studied in 1192 young Australians from the Raine Study Gen2. RESULTS: There was no evidence for a relationship between the parent-reported sleep trajectories and epigenetic age acceleration (p ≥ 0.17). There was a positive cross-sectional relationship between self-reported sleep problem score and intrinsic epigenetic age acceleration at age 17 (b = 0.14, p = 0.04), which was attenuated after controlling for depressive symptom score at the same age (b = 0.08, p = 0.34). Follow-up analyses suggested this finding may represent greater overtiredness and intrinsic epigenetic age acceleration in adolescents with higher depressive symptoms. CONCLUSION: There was no evidence for a relationship between self- or parent-reported sleep health and epigenetic age acceleration in late adolescence after adjusting for depressive symptoms. Mental health should be considered as a potential confounding variable in future research on sleep and epigenetic age acceleration, particularly if subjective measures of sleep are used.

Relationship between TV watching during childhood and adolescence and fitness in adulthood in the Raine Study cohort.

To investigate: (1) whether TV watching habits throughout childhood and adolescence, a proxy of sedentary behaviour, impacted cardiorespiratory fitness (CRF) in adulthood, and (2) whether any potential impact of TV watching in childhood and adolescence on CRF in adulthood was changed by adult physical activity (PA) levels. A longitudinal study with questionnaire data available regarding TV watching collected at ages 5, 8, 10, 14, 17 and 20 yrs, allowed trajectories of TV watching to be developed. At age 28 yrs, participants completed a V̇O2peak test and the International Physical Activity Questionnaire. General linear models tested for differences in CRF (time to exhaustion TTE and V̇O2peak mL·kg-1·min-1) between TV watching trajectories. The secondary analysis tested the potential effect current PA levels has on the relationship between TV trajectory and fitness. In total, 449 participants [male n = 255 (56.8%), 28.3 ± 0.5 yrs; female n = 194 (43.2%), 28.2 ± 0.4 yrs] were included in the study. Three distinct trajectories of TV watching were identified: High TV, Increasing TV and Low TV. CRF was lowest in the High TV watching trajectory and increased progressively from High to Increasing TV and Increasing to Low TV (all P < .05). Within each of the TV trajectories, those engaging in high levels of current PA had greater CRF than those engaging in low and moderate PA. TV watching in childhood and adolescence negatively impacts upon adult fitness at the age of 28 years. However, this negative impact of historical TV watching on CRF can largely be attenuated by engaging in higher levels of PA in adulthood.

Is cognitive behavioral therapy for insomnia (CBTi) efficacious for treating insomnia symptoms in shift workers? A systematic review and meta-analysis.

Shift workers commonly report insomnia symptoms. Cognitive behavioral therapy for insomnia (CBTi) is the first line treatment for insomnia, however efficacy in shift workers is not well understood. This systematic review and meta-analysis evaluates existing trials of CBTi in shift working populations. A systematic literature search was conducted across seven electronic databases (n = 2120). Fifty-two full-text articles were reviewed and of these, nine studies (across ten publications with a total of 363 participants) were deemed suitable for inclusion. Heterogeneity was considerable between studies, with variability in study design, style and delivery of intervention, and follow-up times. Small sample sizes were common and attrition was high. Some studies modified aspects of CBTi for use in shift workers, while others were limited to psycho-education as part of larger intervention studies. Mean differences (MD) pre and post CBTi were modest for both the insomnia severity index (ISI; MD: -3.08, 95% CI: -4.39, -1.76) and the Pittsburgh sleep quality index (PSQI; MD: -2.38, 95% CI: -3.55, -1.21). Neither difference was of a magnitude considered to reflect a clinically significant improvement. Tailored approaches to CBTi are needed for shift workers to improve efficacy, ideally including co-production with workers to ensure interventions meet this population's needs.

Cross-sectional interrelationships between chronotype, obstructive sleep apnea and blood pressure in a middle-aged community cohort.

Chronotype is linked to adverse health measures and may have important associations with obstructive sleep apnea and blood pressure, but data are limited. This study aimed to determine the separate and combined associations of chronotype with obstructive sleep apnea and blood pressure in a middle-aged community population. Adults (n = 811) from the Raine Study (female = 59.2%; age mean [range] = 56.6 [42.1-76.6] years) were assessed for chronotype (Morningness-Eveningness Questionnaire), blood pressure and hypertension (doctor diagnosed or systolic blood pressure ≥ 140 mmHg and/or diastolic ≥ 90 mmHg), and obstructive sleep apnea at different in-laboratory apnea-hypopnea index thresholds (5, 10, 15 events per hr). Linear and logistic regression models examined relationships between chronotype and the presence and severity of obstructive sleep apnea, blood pressure, hypertension, and blood pressure stratified by obstructive sleep apnea severity at above-mentioned apnea-hypopnea index thresholds. Covariates included age, sex, body mass index, alcohol consumption, smoking, physical activity, sleep duration, anti-hypertensive medication, insomnia, and depressive symptoms. Most participants were categorised as morning (40%) or intermediate (43%), with 17% meeting criteria for evening chronotypes. Participants with apnea-hypopnea index ≥ 15 events per hr and morning chronotype had higher systolic (9.9 mmHg, p < 0.001) and a trend for higher diastolic blood pressure (3.4 mmHg, p = 0.07) compared with those with an evening chronotype, and higher systolic blood pressure compared with those with an intermediate chronotype (4.8 mmHg, p = 0.03). Across chronotype categories, no differences in systolic or diastolic blood pressure or odds of hypertension were found at apnea-hypopnea index thresholds of ≥ 5 or ≥ 10 events per hr. Among participants with apnea-hypopnea index ≥ 15 events per hr, systolic blood pressure is higher in those with a morning chronotype than evening and intermediate chronotypes. Assessment for morning chronotype may improve risk stratification for hypertension in patients with obstructive sleep apnea.