Healthy lifestyle is associated with reduced cardiovascular disease, depression and mortality in people at elevated risk of sleep apnea.

We assessed: (1) the independent and joint association of obstructive sleep apnea risk and healthy lifestyle with common consequences (excessive daytime sleepiness, depression, cardiovascular disease and stroke) of obstructive sleep apnea; and (2) the effect of healthy lifestyle on survival in people with increased obstructive sleep apnea risk. Data from 13,694 adults (median age 46 years; 50% men) were used for cross-sectional and survival analyses (mortality over 15 years). A healthy lifestyle score with values from 0 (most unhealthy) to 5 (most healthy) was determined based on diet, alcohol intake, physical activity, smoking and body mass index. In the cross-sectional analysis, obstructive sleep apnea risk was positively associated with all chronic conditions and excessive daytime sleepiness in a dose-response manner (p for trend < 0.001). The healthy lifestyle was inversely associated with all chronic conditions (p for trend < 0.001) but not with excessive daytime sleepiness (p for trend = 0.379). Higher healthy lifestyle score was also associated with reduced odds of depression and cardiovascular disease. We found an inverse relationship between healthy lifestyle score with depression (p for trend < 0.001), cardiovascular disease (p for trend = 0.003) and stroke (p for trend = 0.025) among those who had high obstructive sleep apnea risk. In the survival analysis, we found an inverse association between healthy lifestyle and all-cause mortality for all categories of obstructive sleep apnea risk (moderate/high- and high-risk groups [p for trend < 0.001]). This study emphasises the crucial role of a healthy lifestyle in mitigating the effects of obstructive sleep apnea risk in individuals with an elevated obstructive sleep apnea risk.

The Good Sleeper Scale-15 items: a questionnaire for the standardised assessment of good sleepers.

Research with 'good sleepers' is ubiquitous, yet there are no standardised criteria to identify a 'good sleeper'. The present study aimed to create and validate a questionnaire for identifying good sleepers for use in research studies known as the Good Sleeper Scale-15 items (GSS-15). Data were derived from a population-based survey of Australian adults (n = 2,044). A total of 23 items were chosen for possible inclusion. An exploratory factor analysis (EFA) was conducted on ~10% of the survey dataset (n = 191) for factor identification and item reduction. A confirmatory factor analysis (CFA) was conducted on the remaining data (n = 1,853) to test model fit. Receiver operating characteristic curves and correlations were conducted to derive cut-off scores and test associations with sleep, daytime functioning, health, and quality-of-life. The EFA identified six factors: 'Sleep Difficulties', 'Timing', 'Duration', 'Regularity', 'Adequacy', and 'Perceived Sleep Problem'. The CFA showed that model fit was high and comparable to other sleep instruments, χ2 (63) = 378.22, p < 0.001, root mean square error of approximation = 0.05, with acceptable internal consistency (α = 0.76). Strong correlations were consistently found between GSS-15 global scores and outcomes, including 'a good night's sleep' (r = 0.7), 'feeling un-refreshed' (r = -0.59), and 'experienced sleepiness' (r = -0.51), p < 0.001. Cut-off scores were derived to categorise individuals likely to be a good sleeper (GSS-15 score ≥40) and those very likely to be a good sleeper (GSS-15 score ≥45). The GSS-15 is a freely available, robust questionnaire that will assist in identifying good sleepers for the purpose of sleep research. Future work will test relationships with other sleep measures in community and clinical samples.

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.

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.

The Development and Validation of the Health Belief Model for Shift Workers (HBM-SW) Scale.

OBJECTIVE: Shift work is associated with circadian misalignment, sleep loss, and suboptimal health behaviors, which may contribute to longer term negative health outcomes. To inform future interventions for shift workers, the present study aimed to develop and evaluate the Health Belief Model for Shift Workers (HBM-SW) scale. METHODS: The HBM-SW development involved a seven-step process, including a literature review, expert panel analysis, cognitive interviews with shift workers, and a trial with a pilot sample of shift workers (n = 153). Utilizing exploratory factor analysis for factor identification and item reduction, the developed scale loaded on seven factors in line with the theoretical framework of the Health Belief Model: Perceived Threat, Perceived Severity, Perceived Benefits, Perceived Barriers, Cues to Action, Self-efficacy, and Health Motivation. Validation of the scale was conducted utilizing Pittsburgh Sleep Quality Index, International Physical Activity Questionnaire, and Food Frequency Questionnaire. RESULTS: The pilot sample had an average age of 34.0 (18.0) years, was majority female (54.2%), with an average of 8.0 (11.0) years shift work experience. The HBM-SW showed good - excellent (α = 0.74-0.93) internal consistency and moderate - good (ICC = 0.64-0.89) test re-test reliability. Using health behavior outcome measures, the HBM-SW scale showed meaningful correlations with sleep quality, sleep duration, diet quality and leisure time physical activity, and acceptable validity and reliability. Further testing should be conducted in a larger sample to facilitate confirmatory factor analysis. CONCLUSIONS: The developed Health Belief Model for Shift Workers scale is likely beneficial for use in future studies of interventions for shift workers.

"I need to be alert at night to provide care": Factors associated with problematic sleep among young Australian caregivers.

OBJECTIVES: There is increased recognition that young people (<25 years) may occupy a carer role for family or others with health conditions or disability. This is often in addition to study and social activities. This means competing demands on time, and insufficient sleep. Our aim was to determine the contribution of caring duties to problematic sleep in young carers. METHODS: A survey of Australian carers was conducted, including questions on demographics, characteristics of the carer and care recipient, and sleep quality and quantity. Participants were eligible if they reported sleep time <7 hr or dissatisfaction with their sleep, and were aged 15-24 years. RESULTS: A total of 110 participants (71.8%_female = 79, 15-17 years = 62, 18-24 years = 48) were included in analysis; 55.5% (n= 61) reporting dissatisfaction with their sleep and 62.7% (n= 69) reporting typically less than 7 hr sleep per night. Sleep duration was significantly shorter for those who reported 1-2 or ≥3 awakenings to provide care, compared with no awakenings (p_< .05). Sleep quality, as described by scores on the Pittsburgh Sleep Quality Index (PSQI) was also significantly worse for those who were frequently awoken by their care recipient (p < .05). Worrying about the care recipient, being woken by the care recipient, and listening out for the care recipient were the most frequently identified factors impacting on sleep. CONCLUSION: Young carers experience reduced sleep duration and poor sleep quality. Strategies to alleviate the burden of care work on young carer's sleep would benefit the health and safety of this group.

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.

The effect of a short burst of exercise during the night on subsequent sleep.

When on-call workers wake during the night to perform work duties, they may experience reduced alertness and impaired performance as a result of sleep inertia. After performing their duties, on-call workers may have the opportunity to return to sleep. Thus, it is important that sleep inertia countermeasures do not affect subsequent sleep. Exercise may be a suitable countermeasure; however, the impact on subsequent sleep is untested. Healthy participants (n = 15) completed three conditions in a counterbalanced order: sedentary, low-intensity exercise or high-intensity exercise, performed for 2 min upon awakening. Sleep was recorded 2 hr later using polysomnography, the Karolinska Sleepiness Scale was administered to measure subjective sleepiness, and core body temperature was measured continuously. Results indicate there was no effect of condition on most sleep variables; however, three variables had small differences, with longer total sleep time (p = .006), higher sleep efficiency (p = .006) and shorter N3 latency (p < .001) in the low-intensity exercise condition. There was no difference in subjective sleepiness (p = .124) or core body temperature (p = .216) 90 min after the exercise intervention. These results indicate that using a short burst of exercise to counteract sleep inertia when woken during the night may be a suitable countermeasure for on-call workers who not only need to be alert upon waking but also need quality sleep when returning to bed. Future research could include participants of other ages and health statuses to investigate whether the results are generalizable.

Sleep Duration Moderates the Relationship Between Perceived Work-Life Interference and Depressive Symptoms in Australian Men and Women from the North West Adelaide Health Study.

BACKGROUND: Mental health disorders are prevalent and costly to workplaces and individuals in Australia. Work-life interference is thought to contribute negatively. The interplay between work-life interference, depressive symptoms and sleep has not been explored to date in population data. The aims of this study were to establish whether sleep duration moderates the relationship between work-life interference and depressive symptoms, and whether this is expressed differentially in male and female respondents. METHODS: Data were drawn from the North West Adelaide Health Study (NWAHS) longitudinal, representative population-based cohort study. Working members of the cohort were invited to participate in a telephone survey about their work conditions, with an 86.7% response rate achieved. Data from 823 respondents were analysed after employing purposeful selection of covariates, using multivariable regression analysis. RESULTS: Sleep duration was found to moderate the relationship between work-life interference and depressive symptoms (F7,815 = 26.60, p < 0.001), and accounted for 19% of the variance observed in depressive symptoms. The strongest effect of work-life interference on depressive symptoms was observed in habitual short sleepers, with the effect weakening as sleep duration increased. The relationship was observed in male and female respondents, but was stronger in females. CONCLUSIONS: Supporting and educating workers about the benefits of sleep for managing the relationship between work-life interference and depressive symptoms may offer a novel strategy for improving worker well-being, particularly when negative facets of work-life interference are not easily remedied or 'reduced'. There is a need for education and support strategies around sleep in Australian workplaces.

What Factors Influence the Sleep of On-call Workers?

Objective: On-call work is becoming increasingly common in response to service demands. This study had two aims; 1) describe the demographic profile of on-call workers in Australia, and 2) establish the impacts of on-call work on workers' sleep. Methods: A cross-sectional study was conducted using an online questionnaire completed by Australian on-call workers (n = 228) from various professions. The questionnaire included items on i) demographic and work characteristics, ii) rumination about on-call factors, iii) sleep quantity and quality. Analyses were conducted using mixed effects ordinal regression and multivariable logistic regression. Results: Workers slept <7 hours per night when on-call (80%), and reported sleep was impacted on-call even when no-calls were received (56%). On-call workers rated interruptions to family/leisure time (70%), missing a call (69%), preplanning in case of a call (69%), and not able to make plans (67%) as the main factors they ruminated about. Female on-call workers were more likely to think about the likelihood of being called, report frequent thoughts about what they would need to do if called, and think about interruptions to family/leisure time as a result of a call. Younger workers were more likely to think about the likelihood of being called compared to older adults, however middle-aged workers were less likely to plan for a call compared to younger workers. Conclusions: This study is the first to describe Australia's on-call population, including factors that specifically impact sleep. Future studies should implement tailored education and support strategies to address the unique challenges facing on-call workers.

Barriers and Enablers to Modifying Sleep Behavior in Adolescents and Young Adults: A Qualitative Investigation.

OBJECTIVE: Many young adults obtain less than the recommended sleep duration for healthy and safe functioning. Behavior change interventions have had only moderate success in increasing sleep duration for this cohort. This may be because the way young adults think about sleep, including their willingness and ability to change sleep behavior, is unknown. The purpose of the present study was to determine what changes, if any, young adults are willing to make to their sleep behavior, and to identify factors that may enable or prevent these changes. PARTICIPANTS: Fifty-seven young adults (16-25 years; 57% female) took part in focus groups addressing (a) willingness to change, (b) desired outcomes of change, and (c) barriers to change in regards to sleep behavior. METHODS: An inductive approach to data analysis was employed, involving data immersion, coding, categorization, and theme generation. RESULTS: Participants were willing to change sleep behavior, and had previously employed strategies including advancing bedtime and minimizing phone use, with limited success. Desired changes were improved waking function, advanced sleep onset, optimized sleep periods, and improved sleep habits. Barriers to making these changes included time demands, technology use, difficulty switching off, and unpredictable habits. Young adults want to improve sleep behavior and waking function; this is an important first step in modifying behavior. Notably, participants wanted more efficient and better quality sleep, rather than increasing sleep duration. CONCLUSION: The reported barriers to sleep, particularly using technology for social purposes, will require innovative and specialized strategies if they are to be overcome.

Working (longer than) 9 to 5: are there cardiometabolic health risks for young Australian workers who report longer than 38-h working weeks?

PURPOSE: The average Australian working week in middle-aged and older workers exceeds government recommendations. Long working weeks are associated with poor health outcomes; however, the relationship between long working weeks and health in young Australian workers is unknown. METHODS: Data were drawn from the 22-year follow-up of the Western Australian Pregnancy Cohort (Raine) Study in Perth, Western Australia. Information was available from 873 young adults about working hours per week, shift work and sleep duration. Blood samples provided measures of cardiometabolic risk (CMR) factors. RESULTS: Almost one-third (32.8%) of young workers reported > 38 h working weeks. This was commonly reported in mining and construction industries for males; health and social assistance, mining and retail trade industries for females. CMR factors including increased waist circumference, higher fasting plasma glucose and reduced HDL cholesterol were associated with > 38 h working weeks. These relationships were not moderated by gender or by BMI for glucose and HDL cholesterol. Total sleep time was significantly lower in both male and female workers reporting > 38 h working weeks, but did not mediate the relationships seen with CMR factors. CONCLUSIONS: These findings point to early associations between > 38 h working weeks and CMR risk, and highlight the potential benefit of making young employees aware of the health associations with working arrangements to reduce the longer-term relationships seen with working hours and poor cardiometabolic health in population studies.

Sleep Schedule Regularity Is Associated with Sleep Duration in Older Australian Adults: Implications for Improving the Sleep Health and Wellbeing of Our Aging Population.

OBJECTIVES: The National Sleep Foundation (NSF) recommends 7 to 9 hours of sleep per night for adults ≥ 65 years of age. Sleep duration below 7h per night has been associated with negative health consequences, so enabling older adults to obtain at least 7 hours per night is important for health and wellbeing. However, little is known about behavioral factors that support sleep duration (≥ 7h/24h) in this group. Our aim was to determine factors associated with sleep duration in older adults, and evaluate the utility of sleep schedule regularity in particular, given the relationship between lifestyle regularity (of which sleep is an important component) and health in this population. METHODS: A sample of 311 Australian adults (≥ 65 years old; 156 male, 155 female) completed a telephone survey assessing sleep history over the prior 24 hours, sleep schedule regularity, demographic and health factors as part of a larger study of the Australian population. RESULTS: Sleep schedules with variability in bed and rise times of > 60 minutes were associated with increased odds of reporting sleep duration below 7 hours per night (< 7h/24h; OR = 2.38, CI = 1.26-4.48, p = .007). No other behaviors were associated with meeting sleep duration recommendations. CONCLUSIONS: Sleep schedule regularity may be associated with sleep duration (≥ 7h/24h) in older adults. CLINICAL IMPLICATIONS: Empowering older adults to maintain sleep schedule regularity may be a practical and efficacious strategy to support sleep durations that are in line with recommendations (≥ 7h/24h).

Diagnosis and management of sleep disorders in shift workers, with patient informed solutions to improve health services research and practice.

BACKGROUND: The combination of shift work and an unmanaged sleep disorder carries health and safety risks. Yet, diagnosis rates for sleep disorders are low in shift workers. The aim of this study was to understand the experience of sleep disorder diagnosis and treatment in shift workers, and consider patient informed solutions to improve access to health services. METHODS: Semi-structured interviews were conducted with 16 Australian shift workers with a diagnosed sleep disorder. Patient journey mapping and reflexive thematic analysis were used to understand diagnosis and management experiences. RESULTS: There were highly variable experiences with diagnosis and management, often taking >5 years to seek help from a health care provider (HCP) after noticing symptoms of a sleep disorder. Three themes were constructed, including 'the cause of the problem', 'prioritising work', and '(dis)satisfaction and (dis)connection'. Extent of patient and HCP awareness of sleep disorders, and a prevailing attitude of shift work being 'the problem' impacted diagnosis, as did organisational needs (including rostering, which had both positive and negative influences on help seeking). Relationships with HCPs were important, and living on non-standard time was both a barrier and an enabler to sleep disorder care. Participants identified the need for education and awareness, prompts and easy access to screening and referral pathways, and tailored models of care. CONCLUSION: Education and awareness initiatives for shift workers, their employers and HCPs, together with development of a model of care for shift workers with sleep disorders may address some of the unique barriers to diagnosis and management.

Reconsidering screening thresholds in health assessments for obstructive sleep apnea using operational and safety incident data.

The rail industry in Australia screens workers for probable obstructive sleep apnea (OSA) due to known safety risks. However, existing criteria to trigger screening only identify a small proportion of workers with OSA. The current study sought to examine the relationship between OSA risk and rail incidents in real-world data from Australian train drivers, and conducted a proof of concept analysis to determine whether more conservative screening criteria are justified. Health assessment (2016-2018) and subsequent rail incident data (2016-2020) were collected from two passenger rail service providers. Predictors included OSA status (confirmed no OSA with a sleep study, controlled OSA, unknown OSA [no recorded sleep assessment data] and confirmed OSA with no indication of treatment); OSA risk according to the current Standard, and OSA risk according to more conservative clinical markers (BMI threshold and cardiometabolic burden). Coded rail safety incidents involving the train driver were included. Data were analysed using zero-inflated negative binomial models to account for over-dispersion with high 0 counts, and rail safety incidents are reported using Incidence Risk Ratios (IRRs). A total of 751 train drivers, typically middle-aged, overweight to obese and mostly men, were included in analyses. There were 43 (5.7%) drivers with confirmed OSA, 62 (8.2%) with controlled OSA, 13 (1.7%) with confirmed no OSA and 633 (84.4%) drivers with unknown OSA. Of the 633 train drivers with unknown OSA status, 21 (3.3%) met 'at risk' criteria for OSA according to the Standard, and incidents were 61% greater (IRR: 1.61, 95% Confidence Interval (CI) 1.02-2.56) in the years following their health assessment compared to drivers who did not meet 'at risk' criteria. A more conservative OSA risk status using lower BMI threshold and cardiometabolic burden identified an additional 30 'at risk' train drivers who had 46% greater incidents compared to drivers who did not meet risk criteria (IRR (95% CI) 1.46 (1.00-2.13)). Our more conservative OSA risk criteria identified more workers, with greater prospective incidents. These findings suggest that existing validated tools could be considered in future iterations of the Standard in order to more sensitively screen for OSA.

Assessment and management of sleep disorders in shift workers: Challenges and considerations for general practice.

BACKGROUND: Shift work is characterised by displaced sleep opportunities and associated sleep disturbance. Shift workers often report sleepiness and other wake time symptoms associated with poor sleep. However, clinical sleep disorders are also prevalent in shift workers. Although prevalence rates are similar or higher in shift workers compared with the general population, help seeking in shift workers with sleep disorders is low. OBJECTIVE: This article aims to provide general practitioners with a contemporary overview of the prevalence rates for sleep disorders in shift workers, to clarify the existing evidence relating to mental and physical health consequences of sleep disorders in shift workers and to highlight the need to consider undiagnosed sleep disorders before attributing sleep-related symptoms solely to work schedules. DISCUSSION: Symptoms of sleep loss associated with shift work overlap with symptoms experienced by individuals living with sleep disorders. Although >40% of middle-aged Australians live with a sleep disorder that requires investigation and management, symptoms in shift workers are often attributed to the work schedule and, as a result, might not be investigated for appropriate diagnosis and treatment. We argue that screening for sleep disorders in shift workers with sleep complaints should be a priority.

Sex differences in response to cognitive behavioural therapy for insomnia: A chart review of 455 patients with chronic insomnia.

BACKGROUND: Insomnia is more prevalent in females, however studies examining sex differences in response to insomnia treatment are scarce. This study assessed sex-specific differences in cognitive behavioural therapy for insomnia (CBT-I)-related changes in insomnia symptoms in a large clinical cohort. METHODS: A chart review was conducted of a clinical cohort (females n = 305, males n = 150) referred to a sleep clinic. Participants had a registered psychologist confirm diagnosis of chronic insomnia according to DSM-IV/V criteria and a Level 1 or 2 sleep study. Daily sleep diaries and questionnaires including the Insomnia Severity Index (ISI), Flinders Fatigue Scale (FFS), the Daytime Feelings and Functioning Scale (DFFS), and the Depression, Anxiety and Stress Scale-21 items (DASS), were administered at baseline, post-treatment, and three-month follow-up. Linear mixed models determined interactions between sex and timepoint on symptoms. RESULTS: Mean (SD) age was 51.7 yrs (15.7, range = 18-90 yrs), and mean BMI was 26.3 kg/m2 (4.9), neither of which differed by sex. At pre-treatment, females demonstrated higher objective total sleep time (min) [343.5 (97.6) vs 323.8 min (92.1), p = 0.044], ISI [19.7 (4.2) vs 18.6 (4.4), p = 0.033], and FFS scores [19.2 (6.0) vs 16.9 (7.2), p = 0.003]. Compared to males, females experienced a greater reduction in FFS and DFFS scores and DASS depressive symptoms (p for interaction: 0.017, 0.043, 0.016 respectively) from baseline to follow-up. The greater reduction in depressive symptoms did not persist after controlling for age, BMI, and sleep apnea severity. Subjective total sleep time similarly increased across treatment for both males [baseline: 335.7 (15.1), post: 357.9 (15.5)] and females [baseline: 318.3 (10.4), post: 354.4 (10.7)], p for interaction: 0.22. CONCLUSION: Females and males experience similar, substantial benefits from CBT-I after accounting for comorbidities, suggesting the same treatment can resolve insomnia in both sexes.

Sleep disorder risk, perceived control over sleep, and mental health symptoms in paramedicine students.

Paramedics commonly experience both poor sleep and mental health symptoms. Clarifying whether sleep or mental health symptoms are a challenge prior to commencement of employment is important, as early prevention and intervention initiatives during training could support these workers. Paramedicine students (n=53) were included, with sleep disorder screening (obstructive sleep apnea, insomnia and restless legs syndrome), and mental health outcomes (depressive symptoms: Patient Health Questionnaire-9, and anxiety symptoms: General Anxiety Disorder-7). Data were analysed using robust regression models, adjusted for age, sex, and shift work status. Meeting criteria for a sleep disorder (n=21) was associated with higher scores for anxiety (8.2 [95% CI: 5.9-10.5] v 4.6, [3.4-5.8]) and depressive symptoms (11.1 [8.6-13.6] v 4.4 [3.1-5.7)] compared to those who did not meet the criteria for a sleep disorder (n=32). Depressive symptoms were lower in those with perceived control over sleep (5.2 [3.2-7.2] v 9.8 [7.7-11.8]). There was no interaction between sleep disorder risk and perceived control over sleep on mental health symptoms. Investigation and management of factors contributing to low perceived control over sleep, together with early screening and management of sleep disorders, are likely to be important priorities to support paramedic student wellbeing prior to commencing shift work.

Are we getting enough sleep? Frequent irregular sleep found in an analysis of over 11 million nights of objective in-home sleep data.

OBJECTIVES: Evidence-based guidelines recommend that adults should sleep 7-9 h/night for optimal health and function. This study used noninvasive, multinight, objective sleep monitoring to determine average sleep duration and sleep duration variability in a large global community sample, and how often participants met the recommended sleep duration range. METHODS: Data were analyzed from registered users of the Withings under-mattress Sleep Analyzer (predominantly located in Europe and North America) who had ≥28 nights of sleep recordings, averaging ≥4 per week. Sleep durations (the average and standard deviation) were assessed across a ∼9-month period. Associations between age groups, sex, and sleep duration were assessed using linear and logistic regressions, and proportions of participants within (7-9 hours) or outside (<7 hours or >9 hours) the recommended sleep duration range were calculated. RESULTS: The sample consisted of 67,254 adults (52,523 males, 14,731 females; aged mean ± SD 50 ± 12 years). About 30% of adults demonstrated an average sleep duration outside the recommended 7-9 h/night. Even in participants with an average sleep duration within 7-9 hours, about 40% of nights were outside this range. Only 15% of participants slept between 7 and 9 hours for at least 5 nights per week. Female participants had significantly longer sleep durations than male participants, and middle-aged participants had shorter sleep durations than younger or older participants. CONCLUSIONS: These findings indicate that a considerable proportion of adults are not regularly sleeping the recommended 7-9 h/night. Even among those who do, irregular sleep is prevalent. These novel data raise several important questions regarding sleep requirements and the need for improved sleep health policy and advocacy.