Waking to use technology at night, and associations with driving and work outcomes: A screenshot of Australian adults

The use of smartphones/electronic devices and their relationship with outcomes are understudied in adult populations. We determined daytime functional correlates of using technology during the night in a population sample of Australian adults. A cross-sectional, national online survey of sleep health was conducted in 2019 (n = 1984, 18-90 years). Nocturnal technology use was assessed with: “In the past seven days, how often did you wake or were woken to send or receive text messages, emails or other electronic communications?” Waking to use technology during all/most nights was reported by 4.9%, with 13.8% reporting two to three nights per week, and 12.7% reporting just one night per week. Technology users were more likely to be younger, employed, experience financial stress, and speak English as a second language. In adjusted analyses, compared to no use, technology use at least two to three nights per week was significantly associated with daytime problems (sleepiness, fatigue and impaired mood, motivation, and attention) and was more evident in participants not reporting/perceiving a sleep problem. Technology use was independently associated with at least one drowsy driving-related motor vehicle accidents/near miss per month (odds ratio [OR] = 6.4, 95% CI = 3.8 to 10.7) and with missing work (OR = 4.8, 95% CI: 3.2 to 7.2) and making errors at work (OR = 2.2, 95% CI = 1.5 to 3.3) at least 1 day in the past 3 months due to sleepiness/sleep problem. These associations were not significantly modified by age. Public health implications of waking to engage with electronic devices at night may be significant in terms of safety, productivity, and well-being. Limiting sleep-disrupting technology use will require innovative language-diverse strategies targeted broadly across age groups

Prevalence and associations of co-morbid insomnia and sleep apnoea in an Australian population-based sample

Introduction: Insomnia and obstructive sleep apnoea (OSA) are the two most prevalent sleep disorders, and frequently co-occur (COMISA) in sleep clinic samples. However, few studies have investigated the prevalence or associations of COMISA in the general population. Methods: We used population-based online survey data from 2044 Australian adults. The prevalence and associations of insomnia, OSA and COMISA were investigated according to symptom-level, and disorder-level definitions. Insomnia was defined according to chronic difficulties initiating and/or maintaining sleep (DIMS; symptom-level), and ICSD-3 chronic insomnia disorder (disorder-level). OSA was defined according to self-reported frequent obstructive events, snoring or doctor-diagnosed OSA (symptom-level), and doctor-diagnosed OSA (disorder-level). COMISA was defined if both conditions were met (for symptom-level, and disorder-level threshold). Associations with other conditions, and general health were investigated with Poisson regression analyses. Results: Chronic insomnia occurred more frequently among participants with doctor-diagnosed OSA (22.3%), compared to those without (14.3%, p = 0.010). Doctor-diagnosed OSA was more common among participants with chronic insomnia (10.2%) compared to those without (6.2%; p = 0.010). DIMS also occurred more frequently among participants with OSA symptoms (66.6%), compared to those without (47.2%; p < 0.001). Participants with symptom-level COMISA reported increased co-morbid conditions, and worse general health compared to participants with symptoms of insomnia-alone, OSA-alone, or neither insomnia/OSA. Conclusions: COMISA at symptom and disorder level were common and associated with increased medical and psychiatric co-morbidity, as well as poor general health. More investigation is required to understand bi-directional associations underpinning the high co-morbidity, and improve diagnostic and treatment approaches for COMISA to reduce associated morbidity

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

Who is ‘on-call’ in Australia? A new classification approach for on-call employment in future population-level studies

Background On-call research and guidance materials typically focus on ‘traditional’ on-call work (e.g., emergency services, healthcare). However, given the increasing prevalence of non-standard employment arrangements (e.g., gig work and casualisation), it is likely that a proportion of individuals who describe themselves as being on-call are not included in current on-call literature. This study therefore aimed to describe the current sociodemographic and work characteristics of Australian on-call workers. Methods A survey of 2044 adults assessed sociodemographic and work arrangements. Of this population, 1057 individuals were workforce participants, who were asked to provide information regarding any on-call work they performed over the last three months, occupation type, weekly work hours, and the presence or absence of non-standard work conditions. Results Of respondents who were working, 45.5% reported working at least one day on-call in the previous month. There was a high prevalence of on-call work in younger respondents (63.1% of participants aged 18–24 years), and those who worked multiple jobs and more weekly work hours. Additionally, high prevalence rates of on-call work were reported by machinery operators, drivers, community and personal service workers, sales workers, and high-level managers. Conclusions These data suggest that on-call work is more prevalent than previously recorded and is likely to refer to a broad set of employment arrangements. Current classification systems may therefore be inadequate for population-level research. A taxonomy for the classification of on-call work is proposed, incorporating traditional on-call work, gig economy work, relief, or unscheduled work, and out of hours work

Prevalence of probable shift work disorder in non-standard work schedules and associations with sleep, health and safety outcomes: A cross-sectional analysis

Purpose: We aimed to estimate the prevalence of probable shift work disorder (pSWD) in a representative sample of Australian workers and identify sleep, health and safety correlates. Patients and Methods: In 2019, data were collected from working respondents as part of a cross-sectional national sleep health survey conducted online (n=964 total; n=448 individuals on non-standard work schedules). We established the prevalence of pSWD according to International Classification of Sleep Disorders criteria (ICSD-R, ICSD-2 and ICSD-3). Poisson regression was used to determine crude and adjusted prevalence association (prevalence ratio, PR) of pSWD with sleep, health and safety outcomes. Results: Overall prevalence of pSWD in workers on non-standard work schedules was 10.5%, ranging from 9.6% in early morning workers to 12.7% in rotating shift workers. In adjusted models, workers who met the criteria for pSWD were 1.8 times more likely to report both depression/bipolar disorder, and anxiety/panic disorder, and 1.7 times more likely to report work errors due to a sleep problem. Conclusion: The prevalence of pSWD in employees engaged in non-standard work schedules is influenced by selection of factors used to quantify pSWD, including sleep/wake patterns. Higher likelihoods of mental health problems and workplace errors in those with pSWD highlight the importance of intervention and management of this under-recognised sleep disorder

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions