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Poor sleep imparts a significant personal and societal burden. Therefore, it is important to have accurate estimates of its causes, prevalence and costs to inform health policy. A recent evaluation of the sleep habits of Australians demonstrates that frequent (daily or near daily) sleep difficulties (initiating and maintaining sleep, and experiencing inadequate sleep), daytime fatigue, sleepiness and irritability are highly prevalent (20%-35%). These difficulties are generally more prevalent among females, with the exception of snoring and related difficulties. While about half of these problems are likely to be attributable to specific sleep disorders, the balance appears attributable to poor sleep habits or choices to limit sleep opportunity. Study of the economic impact of sleep disorders demonstrates financial costs to Australia of $5.1 billion per year. This comprises $270 million for health care costs for the conditions themselves, $540 million for care of associated medical conditions attributable to sleep disorders, and about $4.3 billion largely attributable to associated productivity losses and non-medical costs resulting from sleep loss-related accidents. Loss of life quality added a substantial further non-financial cost. While large, these costs were for sleep disorders alone. Additional costs relating to inadequate sleep from poor sleep habits in people without sleep disorders were not considered. Based on the high prevalence of such problems and the known impacts of sleep loss in all its forms on health, productivity and safety, it is likely that these poor sleep habits would add substantially to the costs from sleep disorders alone.
Sleep disorders
S7MJA 199 (8) · 21 October 2013
The Medical Journal of Australia ISSN: 0025-
729X 21 October 2013 199 8 7-10
©The Medical Journal of Australia 2013
leep is a basic and necessary biological process that
demands to be satisfied as much as our need for
food and drink. Inadequate sleep can occur if insuf-
ficient time is allowed for it or if a disorder is present that
disturbs sleep quality. It is only recently that we have
begun to understand the scale of the health and social
consequences of insufficient sleep and sleep disorders.
Sleep loss from these problems is associated with distur-
bances in cognitive and psychomotor function including
mood, thinking, concentration, memory, learning, vigi-
lance and reaction times.1,2 These disturbances have
adverse effects on wellbeing, productivity and safety.
Insufficient sleep is a direct contributor to injury and death
from motor vehicle and workplace accidents.3 Further,
relationships have been demonstrated between shortened
sleep and a range of health problems including hyperten-
sion,4 type 2 diabetes,5 obesity,6 cardiovascular disease7,8
and total mortality risk.9 Specific sleep disorders such as
insomnia,10 obstructive sleep apnoea (OSA)11 and restless
leg syndrome12 have also been associated with increased
morbidity and mortality. These sleep-related problems
incur financial costs relating to health and other expendi-
tures and non-financial costs relating to loss of quality of
life. This article considers the prevalence and economic
impacts of sleep problems in Australia.
Prevalence of sleep problems
There have been very few studies of the prevalence of
disturbed sleep in Australia. A small survey (n=216) of
sleeping difficulties, daytime sleepiness and hypnotic
medication use was conducted in Adelaide more than 20
years ago.13 A larger survey (n= 535) was conducted in
Newcastle, New South Wales, in 1996 but was limited to a
question about insomnia and hypnotic medications.14
Another small survey (n= 267) in rural Victoria among
Australian day workers was heavily weighted to men.15
More recently, a large NSW mail survey (n= 3300) reported
that 18.4% of participants slept less than 6.5 hours a night
and 11.7% complained of chronic sleepiness.16 A recent
study of the insomnia burden suggested a prevalence of
5.6%, with increased use of health care.17
To further characterise sleep quality in a large represent-
ative sample of Australians, in 2010, the Sleep Health
Foundation ( commis-
sioned a national survey of sleeping difficulties and nega-
tive daytime consequences of poor sleep. It was modelled
on the Sleep in America surveys conducted by the National
Sleep Foundation, in part to allow international compari-
sons. A national polling organisation (Roy Morgan
Research) was commissioned to perform the work. It
conducted a national landline telephone survey of adoles-
cents and adults (14 to > 70 years of age) across successive
weekend evenings. The survey contained 14 questions
about sleep: five about sleeping difficulty, two about snor-
ing and OSA, one about restless legs, one about sleeping
medication, three about daytime impairments usually
associated with sleep disturbance, and two about noctur-
nal sleep duration (weekdays and weekends) (Box 1).
There were 1512 respondents from all states and ter-
ritories, both urban and rural, with sampling proportionate
to the populations of those areas, sex and age.
Box 1 shows the proportions of respondents reporting
current sleep difficulties and daytime impairments at least
a few times per week (indicative of significant problem), as
well as average self-reported sleep duration for the popu-
lation overall, for males and females, and for each age
group. The results illustrate that a considerable proportion
of Australians report frequent sleeping difficulties. Overall,
20% of respondents had frequent difficulty falling asleep,
which was more prevalent among females and younger
age groups. Frequent waking during the night was
reported by 35% overall, again more commonly among
females but increasing with age. Thirty-five per cent
reported waking unrefreshed and 24% reported inade-
quate sleep. Daytime sleepiness, fatigue/exhaustion and
irritability were common issues (19%–24%).
Symptoms were examined to determine likely pre-
valence of insomnia by selecting those with specific self-
Public health implications of sleep loss:
the community burden
David R Hillman
Sleep Physician1
Leon C Lack
Professor of Psychology2
1 Department of Pulmonary
Physiology and Sleep
Medicine, Sir Charles
Gairdner Hospital,
Perth , WA.
2 School of Psychology,
Flinders University,
Adelaide, S A.
MJA 2013; 199: S7–S10
doi: 10.5694/mja13.10620
Poor sleep imparts a significant personal and societal
burden. Therefore, it is important to have accurate
estimates of its causes, prevalence and c osts to inform
health policy.
A recen t evaluation of the sleep habits of Australi ans
demonstrates that freque nt (daily or near daily) sleep
difficulties (initiating and maintaining sleep, and
experiencing inadequate sleep), daytime fatigue,
sleepiness and irritability are highly prevalent (20%–
35%). These difficulties are gene rally more prevalent
among females, with the exception of snoring and
related difficulties. While about half of these problems
are likely to be attributable to specific sleep disorders, the
balance appears attributable to poor sleep habits or
choices to limit sleep opportunity.
Study of the economic impact of sleep disorders
demonstrates financial costs to Australia of $5.1 billion
per year. This comprises $270 million for health care
costs f or the con ditions them selves, $5 40 millio n for care
of associated medical conditions attribu table to sleep
disorders, and about $4.3 billion largely attributable to
associated productivity losses and non- medical costs
resulting from sleep loss-related accidents. Loss of life
quality added a subs tantial further non-financial cost.
While large, these costs were for sleep disorders alone.
Additional costs rel ating to inadequate sleep from poor
sleep habits in people without sleep disorders were not
considered. Ba sed on the high prevalence of such
problems and the known impacts of sleep loss in all its
forms on health, producti vity and safety, it i s likely th at
these poor sleep habits would add substantially to the
costs from sleep disorders alone.
Online first 17/10/13
MJA 199 (8 ) · 21 October 2013S8
reported sleep difficulties plus daytime impairment18 to
derive a score that very closely simulates the Insomnia
Severity Index, a highly reliable and valid tool to identify
clinical insomnia.19 This suggested an overall presence of
severe insomnia (Insomnia Severity Index, > 14) of 6.9%,
8.7% in women and 5% in men (Box 1).
Prevalence of sleep apnoea was derived by determining
the proportion of respondents who snored loudly at least a
few times a week and had observed breathing pauses
during sleep at least a few times a month. An overall
prevalence of 4.9% was noted, but in this case, prevalence
was higher among males (6.4%) than females (3.6%).
While these prevalences of specific sleep disorders were
derived from combinations of questionnaire responses,
they are similar to the prevalences determined from other
population-based studies.10,20 These findings suggest that
specific sleep disorders may account for about half of the
complaints of daytime sleepiness and fatigue and exhaus-
tion noted in our survey. While other health problems can
disturb sleep, particularly in older patients, much of the
balance may be due to insufficient sleep duration by choice
or through circumstances that result in sleep being given a
lower priority than work, social or family activities. Sleep
duration estimates are significantly below the putative
average adolescent sleep requirement of 9 hours a night
and adult sleep requirement of 7.5–8 hours a night for both
men and women, particularly among those between the
ages of 35 and 65 years.21 Insufficient sleep at least a few
times a week was reported by 23.7% of the sample, more
frequently by females, and more commonly in the younger
to middle-aged groups. Perhaps relevant to this, a study of
young adults has shown that those with shorter habitual
sleep patterns carried the highest sleep debt, suggesting
self-selected sleep restriction.22
The general point that emerges from these data is that
inadequate sleep (duration or quality) and its daytime
consequences are widely prevalent in Australians, either
because of a specific sleep-related disorder or from volun-
tarily shortened sleep through choice or circumstance.
Although there are limitations with telephone surveys (eg,
low response rates to landline phone calls), the results are
very comparable with those observed in similar surveys
conducted elsewhere, such as the 2008 Centers for Disease
Control and Prevention study, which reported that 28% of
United States adults had insufficient sleep or rest (< 7 h/
night) on most nights over a 30-day survey period.23
Economic impact
Poor sleep and its consequences result in significant costs
to the community. Although there have been no detailed
economic evaluations of the costs associated with insuffi-
cient sleep in otherwise healthy individuals, analyses have
been undertaken for those with sleep disorders.24,25 OSA
provides an example of a widely prevalent sleep disorder
with significant comorbidities, including impaired daytime
alertness, increased accident risk, hypertension, vascular
1 Proportions of survey respondents experiencing sleep difficulties, sleep disorder symptoms and daytime impairments a few times a week or more
(often), overall and by sex and age group
Sex Age group
Difficulty experienced often Overall Male Female 14–17 years 18–24 years 25–34 years 35–49 years 50–64 years 65 years
Weighted proportion of total 100% 49.4% 50.6% 6.4% 11.7% 17.4% 26.0% 21.9% 16.5%
Sleeping difficulty
Difficulty falling asleep 19.6% 16.9% 22.4%* 33.6 %32.2%17.6% 20.0% 14.6% 13.5%
Waking a lot during night 34.9% 3 0.4% 39.3%21.2% 28.1% 32.6% 42.6%31.8% 39.5%
Waki ng up too e arly 25.3% 22.9% 27.7%* 19.5% 23.4% 20.3% 29.1%* 25.5% 27.9%*
Waki ng feelin g unre fre shed 34.7% 31.8% 37.6%* 38.1%44.0%42.0%39.8% 28.5% 19.3%
Did not get adequate sleep 23.7% 17.9% 29.4%24.9%29.3 %25.3%24.5%21.4% 19.3%
Snoring, obstructed breathing
Frequent or loud snoring21.2% 26.4%12.1% 8.4% 8.6% 21.7%23.5%20.0%20.0%
Pauses in breathing in sleep6.6% 6.2% 5.1% 2.9% 4.4% 3.8% 4.6% 7. 8%* 8.4%*
Restless legs 9.4% 8.6% 10.3% 4.0% 5.3% 11.2%7.2% 10.7 %14.5%
Prescribed sleep medication use 3.6% 4.0% 3.1% 3.5% 2.5% 1.8% 2.4% 5.8%5.4%
Daytime symptoms
Daytime sleepiness 19.0% 15.7% 22.3% * 24.6%26.2%21.1%22.4%13.6% 11.4%
Fatigue or exhaustion 23.5% 20.0% 27.0%22.8% 27.7%27.7%29.1%18.8% 14.2%
Irritable or moody 18.8% 18.2% 19.3% 18.8% 19.2% 27.9%22.9%12.9% 9.8%
Sleep duration
Weeknights (Sunday–Thursday), h 7.16 7.1 5 7.1 7 8.247.49 * 7.1 8 6.86 7.01 7. 14 *
Weekend n igh ts (Friday, Sa turday ), h 7.37 7. 3 7 7. 37 8.457.3 7 7.5 4 7.19 7.29 7. 14
Overall, h 7.2 2 7. 2 1 7. 23 8.307.4 6* 7.2 8 6.95 7.09 7.1 4 *
Sleep disorder estimates
Severe clin ical ins omni a§6.9% 5.0% 8.7%* 2 .0% 11.3 %* 4.2% 10.1%* 6.9% 3.8%
Sleep apnoea‡,¶ 4.9% 6.3%* 3.6% 0 2.2% 2.1% 4.7% 7.7%* 7.0%*
* P<0.05. †P<0.001. ‡ Adjusted for the 10%–11% who “can't say”. § Estimated Insomnia Severity Index > 14, derived from data for sleeping diculty and daytime symptoms.
¶ Estimates derived from data for frequent breathing pauses and loud snoring.
Sleep disorders
S9MJA 199 (8) · 21 October 2013
disease and depression.20 The associated costs include the
direct care-related health costs of the sleep disorder itself
and the costs of medical conditions occurring as a result of
them. In addition, there are substantial indirect financial
and non-financial costs. Other financial costs include the
non-health costs of work-related injuries, motor vehicle
accidents and productivity losses — all common conse-
quences of insufficient sleep. Non-financial costs derive
from loss of quality of life and premature death.24
In 2011, the Sleep Health Foundation commissioned
Deloitte Access Economics, a national economics consul-
tancy with a strong health economics background, to
undertake an analysis of the direct and indirect costs
associated with sleep disorders for the 2010 calendar
year.25 The methods used were similar to those that they
had used in a previous evaluation.24 Such an analysis
requires robust data relating to the prevalence of the sleep
disorder under consideration, the prevalences and costs
associated with conditions with which it has a causal
relationship, and the risk ratios describing the strength of
these relationships. Using these data, the proportion of
each condition attributable to the sleep disorder (the
attributable fraction) can be derived. Specifying the preva-
lences and odds ratios used to calculate attributable frac-
tions imparts transparency to the assumptions involved in
calculating them. The fraction can then be used to derive
the share of the costs associated with that condition that is
attributable to the particular sleep disorder under consid-
eration. Using these methods, Deloitte Access Economics
examined costs associated with the three most common
sleep disorders — OSA, primary insomnia and restless legs
syndrome — as the robust data required for analysis were
available.25 It estimated total health care costs of $818
million per year for these conditions, comprising $274
million for the costs of caring for the disorders themselves
and $544 million for conditions associated with them. Of
these costs, $657 million per year related to OSA: $248
million for OSA itself and $409 million for the health costs
of conditions attributable to OSA. These conditions
include hypertension, vascular disease, depression, and
motor vehicle and workplace accidents. The analysis sug-
gested that 10.1% of depression, 5.3% of stroke, 4.5% of
workplace injuries and 4.3% of motor vehicle accidents are
attributable to a sleep disorder.
The indirect financial and non-financial costs associated
with sleep disorders are much greater than the direct costs.
The indirect financial costs were estimated to be $4.3
billion in 2010. These included $3.1 billion in lost produc-
tivity and $650 million in informal care and other indirect
costs resulting from motor vehicle and workplace acci-
dents. Of these indirect costs, OSA accounted for 61%
($2.6 billion), primary insomnia for 36% ($1.5 billion) and
restless leg syndrome for 3% ($115 million).
The report also estimated the effect of sleep disorders on
loss of quality of life in terms of disability-adjusted life-
years. These costs were calculated using the proportion of
total national health costs attributable to sleep disorders to
proxy the proportionality of the total national disease
burden attributable to these problems. A dollar cost was
calculated from the product of these years lost (190 000)
and the value of a statistical life-year ($165 000). This
added a further non-financial cost of $31.4 billion to the
total economic cost of sleep disorders (Box 2). The non-
financial nature of this cost gave it less tangibility than
financial costs, but the calculation does draw attention to
the substantial burden associated with the loss of quality of
life resulting from sleep disorders.
As large as they are, these costs are likely to significantly
underestimate the total cost to the community of sleep-
related problems. Deloitte Access Economics evaluated
costs associated with common sleep disorders. The costs of
accidents and illnesses associated with sleep loss resulting
from poor sleep habits from personal choice and/or from
conflicting priorities such as work, social or family activities
were not considered as they are difficult to estimate.
Further, the analysis used conservative estimates of the
prevalence of sleep disorders. For example, the base preva-
lence of OSA used was 4.7%, which is below the propor-
tion of moderate OSA observed in many contemporary
studies, a proportion which is likely to increase further as
the population ages and becomes more obese.20 The
prevalence of insomnia used in the analysis was also low at
3%, a figure based on primary insomnia estimates.26 Sec-
ondary insomnias resulting from other causes were not
considered. Our own estimate including all insomnia from
a representative Australian sample (Box 1) was closer to
7%. Potential comorbidities of sleep disorders, even if
reasonable evidence for an association existed (such as
metabolic disorders in the case of OSA), were also
excluded from consideration. Finally, the analysis did not
cost some aspects of the known comorbidities of sleep
disorders, such as the impact of presenteeism (being
present at work but operating suboptimally) on productiv-
ity and safety. The reason for this omission was the
difficulty in reliably quantifying its effects.
Poor or inadequate sleep is very common among Austral-
ian adolescents and adults, affecting over 20% on a daily or
near-daily basis. Epidemiological studies suggest about
2 Summary of the annual costs of sleep disorders and
associated conditions, 201021
Varia bl e AUD (mil lion)
Direct health care co st
Sleep disorders 274
Associated conditions* 544
Indirect fina ncial cost
Productivity 3132
Informal care for accident victims 129
Other cost of mot or vehicle a ccidents 465
Other cost of workplace acc idents 53
Deadweight loss to taxation system 472
Tot al fi na nc ia l co st 5069
Non-financial cost
Loss of disab ility-adj usted life-years 31 350
Total economic co st 36 419
* Hypert ension, v ascular dis ease, depr ession, motor vehi cle injur ies and
workplace injuries.
MJA 199 (8 ) · 21 October 2013S10
half of this problem can be attributable to common sleep
disorders such as OSA and insomnia, as together they
affect about 10% of the community. The balance appears
likely to be the result of inadequate sleep arising from
other health problems or issues such as poor sleep habits
or sleep loss because of competing demands on time from
work, social or family activities. Economic estimates dem-
onstrate that sleep disorders are associated with large
financial and non-financial costs. Given that the greatest
financial costs appear to be non-medical costs related to
loss of productivity and accident risk, it is likely that
inclusion of the effects of sleep restriction from poor sleep
habits or choice could add considerably to these already
substantial amounts.
Competing interests: No r elevant disclosu res.
Provena nce: Commissioned by supplement editors; externally peer reviewed.
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... This manifests in billions of USD annually in lost productivity, cost of accidents, and other downstream health sequelae [3]. There is profound evidence that sleep disorders are associated with a range of physical health problems, such as diabetes, cardiovascular disease, obesity, and hypertension, that lead to increased mortality and morbidity rates [2,[4][5][6]. Individuals with untreated sleep disorders are also at higher risk of deteriorating cognitive functioning that may impact occupational performance and social participation, thus compromising the quality of life and individuals' socioeconomic status [7][8][9]. ...
... Furthermore, the study has addressed the lack of long-term studies in naturalistic settings [7,12,13,16] by evaluating digital solutions. By providing more accessible and cost-effective methods of sleep assessment, digital health solutions have the potential to mitigate the socioeconomic burden of sleep disorders on healthcare systems and improve overall public health outcomes [2][3][4][5]. ...
... By providing more accessible and cost-effective methods of sleep assessment, digital health solutions have the potential to mitigate the socioeconomic burden of sleep disorders on healthcare systems and improve overall public health outcomes [2][3][4][5]. Thus, the findings from this study provide valuable insights into compliance and sleep duration patterns among participants using a morning and evening sleep diary app. ...
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Unlabelled: Sleep diaries are the gold standard for subjective assessment of sleep variables in clinical practice. Digitization of sleep diaries is needed, as paper versions are prone to human error, memory bias, and difficulties monitoring compliance. Methods: 45 healthy eligible participants (Mage = 50.3 years, range 23-74, 56% female) were asked to use a sleep diary mobile app for 90 consecutive days. Univariate and bivariate analysis was used for group comparison and linear regression for analyzing reporting trends and compliance over time. Results: Overall compliance was high in the first two study months but tended to decrease over time (p < 0.001). Morning and evening diary entries were highly correlated (r = 0.932, p < 0.001) and participants significantly answered on average 4.1 days (95% CI [1.7, 6.6]) more often in the morning (M = 60.2, sd = 22.1) than evening ((M = 56.1, sd = 22.2), p < 0.001). Conclusion: Using a daily diary assessment in a longitudinal sleep study with a sleep diary delivered through a mobile application was feasible, and compliance in this study was satisfactory.
... Insufficient sleep is estimated to effect between 20 and 35% of adults at any given time [1,2]. Aside from the associated short-term repercussions on daytime functioning like fatigue and decreased cognitive performance [3,4], consistent sleep deficiency is also related to other adverse health outcomes such as psychological disorders, cardiovascular disease, and obesity [5,6]. ...
... For example, estimates of the impact of insufficient sleep on the economies of developed countries range from 1.35% to nearly 3% of annual Gross Domestic Product. In the United States, this equates to $411 billion per year, and includes the costs of increased mortality risk, but also indirect costs such as workplace and motor vehicle accidents due to sleep deficiency, and the loss of productivity in the workplace [1,7]. Importantly, the sleep problems that contribute to these estimates are experienced by a roughly even combination of non-clinical populations and populations with specific sleep disorders [1], which highlights the need to also examine the mechanisms that drive poor sleep in non-clinical populations. ...
... In the United States, this equates to $411 billion per year, and includes the costs of increased mortality risk, but also indirect costs such as workplace and motor vehicle accidents due to sleep deficiency, and the loss of productivity in the workplace [1,7]. Importantly, the sleep problems that contribute to these estimates are experienced by a roughly even combination of non-clinical populations and populations with specific sleep disorders [1], which highlights the need to also examine the mechanisms that drive poor sleep in non-clinical populations. ...
Full-text available
Background: Sleep hygiene behaviours are a suggested set of behaviours people can engage in to improve sleep. However, there are numerous issues relating to the measurement of sleep hygiene, primarily, the lack of consensus as to which behaviours impact sleep and should therefore be included in scales. Method: Cross-sectional correlational methods were used to assess the association between sleep quality, a highly inclusive range of sleep hygiene behaviours, and individual perceptions of those behaviours in a non-clinical sample of 300 participants. Results: Of the 35 sleep hygiene behaviours assessed, 18 were independently associated with sleep quality. Post-hoc factor analysis revealed that behaviours clustered together across four factors. A 'routine' factor included behaviours such as going to bed and waking up at the same time each night, and were important predictors of sleep quality, as were behaviours belonging to the 'perseverative cognition' and 'negative emotionality' factor. Other behaviours related to physiological processes like exposure to sunlight during the day and going to bed hungry were also significantly associated with sleep. Negative perceptions moderated the relationship between daytime exposure to sunlight and sleep. Conclusions: Although certain behaviours were significantly related to sleep, almost half were not, supporting the need to examine the association between sleep and behaviours used for sleep hygiene recommendations more critically. Reframing sleep hygiene recommendations into a condensed set of shared underlying mechanisms may be of benefit for the development of sleep hygiene scales and interventions in non-clinical populations.
... Insufficient sleep is a pervasive issue that impacts substantial proportions of the general population, with estimates that typically range from 20 to 35% of the population at any given time (Grandner, 2019;Hillman & Lack, 2013;Liu et al., 2013). Those who experience insufficient sleep include people with sleep disorders, but also those without clinical diagnoses who experience issues like difficulty falling asleep, getting fewer than seven hours of sleep a night, and waking frequently during the night (Hillman & Lack, 2013). ...
... Insufficient sleep is a pervasive issue that impacts substantial proportions of the general population, with estimates that typically range from 20 to 35% of the population at any given time (Grandner, 2019;Hillman & Lack, 2013;Liu et al., 2013). Those who experience insufficient sleep include people with sleep disorders, but also those without clinical diagnoses who experience issues like difficulty falling asleep, getting fewer than seven hours of sleep a night, and waking frequently during the night (Hillman & Lack, 2013). Whether at or below clinical levels, insufficient sleep can contribute to a range of issues with physical improving sleep outcomes in general populations (Groenewold et al., 2019;Mairs & Mullan, 2015), others have shown efficacy in only certain types of sleep outcomes (e.g., sleep duration but not sleep efficiency; Anderson et al., 2022). ...
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Sleep hygiene behaviours are recommendations given to both clinical and non-clinical populations with a focus on modifying behaviours to maximise sleep outcomes. However, methodological issues present in sleep hygiene research make it difficult to conclusively determine the impact of each behaviour. This study aimed to address these issues by adopting a two-week, repeated measures design which incorporated objective sleep measures and used linear mixed effect modelling to assess the daily association of a wide range of sleep hygiene behaviours on sleep in a non-clinical, university sample. Between-persons effects revealed that bedtime and frequency of daytime napping, alcohol use, and social media use were negatively related to sleep duration while waketime and frequency of too much water consumption were positively related to sleep duration. Within-person effects revealed that later than usual bedtime, earlier than usual waketime, no sunlight exposure, poor ventilation, having an unpleasant conversation before bed were negatively associated with sleep duration whereas using alcohol to deliberately help full asleep was positively related to sleep duration. In contrast, disproportionately more behaviours were not significantly related to either sleep outcome, only some of which could be explained by individual differences, which suggests that more research is needed to determine the conditions under which these behaviours affect sleep, if at all.
... Sleep research has expanded since the 1960s, enhancing our knowledge of many aspects of the subject, including the links between sleep and various individual and public health outcomes [1][2][3]. Insufficient sleep is associated with increased mortality and morbidity, affecting various dimensions of health, such as cardiovascular, metabolic, immunologic, and mental health [4,5]. Inadequate sleep often results in tiredness or sleepiness and is associated with occupational and commuting accidents [6][7][8]. ...
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Background A growing body of research has clarified that sleep is influenced not only by biological factors but also by social factors. While studies have shown that social norms can affect sleep behavior and sleeping arrangements, including when, where, how, and with whom people sleep, researchers still know relatively little about how social norms affect sleep health, especially among adults. The current study explores the association between social norms and sleep health in the Israeli context. Methods Data were drawn from semi-structured, in-depth interviews with 66 Israelis—including women and men, Arabs and Jews, and religious and non-religious persons—conducted between February 2020 and February 2022. This article focuses on responses to a set of questions about the comments people make or hear from others about their sleep. Exploring how people comment on the sleep of others highlights prevalent social norms around sleep. Results Findings indicate that how sleep is “done” is policed by family and community members who react to norm violations by commenting on what is perceived as “inappropriate” sleep behavior. Comments were made in jest or earnest in response to breaches of social norms regarding sleep timing, duration, continuity, and alertness/sleepiness, indicating that social norms and expectations shape each of these sleep health dimensions. Conclusions This article expands the scholarly understanding of the social determinants of sleep health. The study concludes that since individuals may opt to conform to current social norms, which are enforced by members of the family and community, interventions aimed at promoting sleep health should target not only individuals but also the family and community.
... Sleep patterns and need are influenced by complex interactions between age, stage of maturity, genetics, behavior, and environmental and social factors [1,2]. Sleep deprivation (SD) in the contemporary world is caused by inadequate day-to-day work schedules, 24/7 lifestyles, psychosocial stress and frequent usage of electronic gadgets in bed, all of which have a negative impact on our body and mental health and put a heavy financial burden on our economy [3,4]. Because sleep plays a vital role in immunity, metabolism, cognition, and neuronal regeneration (all of them are necessary for normal brain function), SD can have negative effects on brain function. ...
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Sleep deprivation (SD) has reached epidemic proportions worldwide and negatively affects people of all ages. Cognitive impairment induced by SD involves neuroinflammation and mitochondrial dysfunction, but the underlying mechanisms are largely unknown. Urolithin A (UA) is a natural compound that can reduce neuroinflammation and improve mitochondrial health, but its therapeutic effects in a SD model have not yet been studied. Young (3-months old) and aged (12-months old) mice were sleep deprived for 24 h, and UA (2.5 mg/kg or 10 mg/kg) was injected intraperitoneally for 7 consecutive days before the SD period. Immunofluorescent staining, western blotting, and RT-PCR were employed to evaluate levels of proteins involved in neuroinflammation and mitochondrial function. Transmission electron microscope and Golgi-Cox staining were used to evaluate mitochondrial and neuronal morphology, respectively. Finally, contextual fear conditioning and the Morris water maze test were conducted to assess hippocampal learning and memory. In the hippocampus of young (3 months-old) and aged (12 months-old) mice subjected to 24 h SD, pretreatment with UA prevented the activation of microglia and astrocytes, NF-κB-NLRP3 signaling and IL-1β, IL6, TNF-α cytokine production, thus ameliorating neuroinflammation. Furthermore, UA also attenuated SD-induced mitochondrial dysfunction, normalized autophagy and mitophagy and protected hippocampal neuronal morphology. Finally, UA prevented SD-induced hippocampal memory impairment. Cumulatively, the results show that UA imparts cognitive protection by reducing neuroinflammation and enhancing mitochondrial function in SD mice. This suggests that UA shows promise as a therapeutic for the treatment of SD-induced neurological disorders.
... In Thailand, the prevalence of PSQ among adolescents was reportedly 32 to 48%. 7, 8 Insufficient sleep not only impacts at a personal level, but also can cause major impact on a larger scale through a high burden of non-communicable diseases, 12 many events such as motor vehicle crashes, 13 workplace accidents, increased mortality and reduced quality of life. 14 Media use such as watching TV and using electronic devices are activities that cause PSQ among children and adolescents. Especially among school age group, having a TV in the bedroom can disturb sleep resulting in decreased sleep duration and insufficient sleep. ...
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Background : Poor sleep quality (PSQ) is an increasing health problem among adolescents. Mobile phones and portable media devices have become a part of children’s lives and may affect their sleep duration and quality. This study aimed to explore the prevalence of PSQ and identify the association between media use and PSQ among adolescents studying in high school grades 10-12. Methods: This cross-sectional study was conducted in central Thailand. A multi-stage sampling technique was used to enroll 777 adolescents from eight schools from August to October 2016. The research instruments comprised factors of demographics and consumption behaviors and the Pittsburgh Sleep Quality Index questionnaire. Multivariable logistic regression was used to calculate adjusted odds ratios (OR adj ) and 95% confidence intervals (CI). Results: Prevalence of PSQ was 56.24%. The study subjects were mostly 16-17 years old (67.82%) and female (70.39%). Multivariable logistic regression, after controlling for possible confounders, revealed an increased odds of PSQ among those who used a social media device (OR=1.34, 95%CI=0.97-1.87), and showed a higher proportion of social media use in the PSQ group. Conclusion: A surveillance system to detect media use and PSQ should be conducted accompanied by knowledge sharing on media use among parents, teachers and adolescents. To determine causal relationships, further longitudinal studies will be required to test the association between media users and PSQ. This study may also provide some implications for health promotion on sleep quality of senior high school students.
Objective Girls with Turner syndrome (TS) often have features that have been associated with obstructive sleep‐disordered breathing (oSDB). However, little is known about oSDB in TS. Herein, we aimed to characterize oSDB in young patients with TS and identify associated risk factors. Study Design Retrospective cross‐sectional study. Setting Tertiary care pediatric hospital. Methods We reviewed medical records for patients diagnosed with TS seen at our institution between October 1, 2007 and December 31, 2019 with the first outpatient visit before age 6 years. The prevalence of oSDB was compared to the general pediatric population with 1‐sample binomial proportion tests. Clinical characteristics were compared between those diagnosed with oSDB and those without oSDB, and risk factors for oSDB were identified. Results Of 151 patients with TS, 73 (48%) were diagnosed with oSDB which is 4‐fold higher than the general pediatric population (12%, P < 0.0001). In the multivariable model, adenoid, tonsillar, and inferior turbinate hypertrophy, birthweight, failure to thrive, and older age at the last clinic visit were all associated with increased odds for oSDB. Conclusion Young children with TS have a high prevalence of oSDB and thus should be screened for oSDB. Polysomnography should be performed in those with associated risk factors and symptoms oSDB. Treatment of oSDB is imperative as individuals with TS are already at increased risk of behavioral problems, neurocognitive deficits, and growth impairment that may be worsened with oSDB.
This longitudinal study examines the association between bedroom nighttime temperature and sleep quality in a sample of community dwelling older adults. Using wearable sleep monitors and environmental sensors, we assessed sleep duration, efficiency, and restlessness over an extended period within participants' homes while controlling for potential confounders and covariates. Our findings demonstrated that sleep was most efficient and restful when nighttime ambient temperature ranged between 20 and 25 °C, with a clinically relevant 5-10 % drop in sleep efficiency when the temperature increased from 25 °C to 30 °C. The associations were primarily nonlinear, and substantial between-subject variations were observed. These results highlight the potential to enhance sleep quality in older adults by optimizing home thermal environments and emphasize the importance of personalized temperature adjustments based on individual needs and circumstances. Additionally, our study underscores the potential impact of climate change on sleep quality in older adults, particularly those with lower socioeconomic status, and supports increasing their adaptive capacity in the face of a changing climate.
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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: β =0.08; mental health: β =0.34) and impaired daytime alertness (physical health: β =0.09; mental health: β =0.08) were significantly associated with poorer physical and mental health and inadequate polysomnography-measured sleep duration was associated poorer mental health (β =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.
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Previous studies have shown that both short and long sleep durations are related to increased likelihood of diabetes and hypertension. However, the relation between sleep duration and cardiovascular disease (CVD) is not clear. We examined the hypothesis that compared with sleep duration of 7 hours, shorter and longer sleep durations are independently related to CVD. We conducted a cross-sectional study of 30,397 National Health Interview Survey 2005 participants > or = 18 years of age (57.1% women). Sleep duration was categorized as < or = 5 hours, 6 hours, 7 hours, 8 hours, and > or = 9 hours. The main outcome of interest was the presence of any CVD (n = 2146), including myocardial infarction, angina, and stroke. We found both short and long sleep durations to be independently associated with CVD, independent of age, sex, race-ethnicity, smoking, alcohol intake, body mass index, physical activity, diabetes mellitus, hypertension, and depression. Compared with a sleep duration of 7 h (referent), the multivariate odds ratio (95% confidence interval) of CVD was 2.20 (1.78, 2.71), 1.33 (1.13, 1.57), 1.23 (1.06, 1.41), and 1.57 (1.31, 1.89) for sleep duration < or = 5 h, 6 h, 8 h, and > or = 9 h. This association persisted in subgroup analyses by gender, race-ethnicity, and body mass index categories. Also, similar associations were observed when we examined myocardial infarction and stroke separately. Compared with sleep duration of 7 h, there was a positive association between both shorter and longer sleep durations and CVD in a representative sample of US adults. These results suggest that sleep duration may be an important marker of CVD.
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To examine the joint effect of insomnia and objective short sleep duration on hypertension risk. Representative cross-sectional study. Sleep laboratory. 1,741 men and women randomly selected from central Pennsylvania. None. Insomnia was defined by a complaint of insomnia with a duration > or = 1 year, while poor sleep was defined as a complaint of difficulty falling asleep, staying asleep, or early final awakening. Polysomnographic sleep duration was classified into 3 categories: > or = 6 h sleep (top 50% of the sample); 5-6 h (approximately the third quartile of the sample); and < or = 5 h (approximately the bottom quartile of the sample). Hypertension was defined based either on blood pressure measures or treatment. We controlled for age, race, sex, body mass index, diabetes, smoking, alcohol use, depression, sleep disordered breathing (SDB), and sampling weight. Compared to the normal sleeping and > 6 h sleep duration group, the highest risk of hypertension was in insomnia with < 5 h sleep duration group (OR [95% CI] 5.1 [2.2, 11.8]), and the second highest in insomnia who slept 5-6 hours (OR 3.5 [1.6, 7.9] P < 0.01). The risk for hypertension was significantly higher, but of lesser magnitude, in poor sleepers with short sleep duration. Insomnia with short sleep duration is associated with increased risk of hypertension, to a degree comparable to that of other common sleep disorders, e.g., SDB. Objective sleep duration may predict the severity of chronic insomnia a prevalent condition whose medical impact has been apparently underestimated.
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Sleep duration is associated with cardiovascular disease and diabetes risk factors, depression, automobile and workplace accidents, and prospective mortality. Little is known, however, about sleep patterns in the US population. The 2004-2007 National Health Interview Survey-Sample Adult Files provide nationally representative data for 110,441 noninstitutionalized US adults aged 18 years or older, and multinomial logistic regression examines whether variables in 5 domains-demographic, family structure, socioeconomic, health behavior, and health status-are associated with long or short sleep duration. Being older, non-Hispanic black, or a current or former smoker; having low levels of education, income, or few income sources; consuming few or numerous drinks in a week; or reporting cardiovascular disease, diabetes, depression, underweight, or activity limitations is associated with increased odds of both long and short sleep duration. Other variables are associated with shorter (e.g., living with young children, being unmarried, working long hours, more frequent binge drinking) or longer (e.g., being younger, Mexican American, pregnant, or having low levels of physical activity) sleep hours. The authors identify numerous risk factors for long and short sleep; many of those variables are potential confounders of the relation between sleep hours and other health outcomes.
To determine whether a cumulative sleep debt (in a range commonly experienced) would result in cumulative changes in measures of waking neurobehavioral alertness, 16 healthy young adults had their sleep restricted to an average 4.98 hrs per night for 7 consecutive nights. Ss slept in the laboratory, and sleep and waking were monitored. Three times each day, Ss were assessed for subjective sleepiness and mood and were evaluated on a brief performance battery that included psychomotor vigilance (PVT), probed memory (PRM), and serial-addition testing. Once each day they completed a series of visual analog scales (VASs) and reported sleepiness and somatic and cognitive/emotional problems. Sleep restriction resulted in statistically robust cumulative effects on waking functions. Subjective sleepiness ratings, subscale scores for fatigue, confusion, tension, and total mood disturbance from the mood and VAS ratings of mental exhaustion and stress were elevated across days of restricted sleep. PVT performance parameters were also significantly increased by restriction. Significant time-of-day effects were evident in subjective sleepiness and PVT data. Findings suggest that cumulative nocturnal sleep debt had a dynamic and escalating analog in cumulative daytime sleepiness and that asymptotic or steady-state sleepiness was not achieved in response to sleep restriction. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Objective: To determine the extent to which insomnia poses an independent burden on individual function and healthcare use in Australia. Methods: Cross-sectional data from 8,841 respondents and representative of the Australian population aged 16 to 85 in the 2007 National Mental Health and Wellbeing Survey were analysed. Insomnia was defined as ‘sleeping only in short bursts and being awake most of the night’ during the past week. This measure was validated against common epidemiological indicators of insomnia. Associations between insomnia, disability and healthcare consumption were explored using multivariate logistic regression. Results: Insomnia was reported by 5.6% of adults and was associated with older age, female gender, pain and psychological distress. Controlling for these and other a priori confounders, insomnia was associated with greater odds of (Adjusted Odds Ratio; 95% CI): disability days (1.62; 1.20–2.18), difficulties in daily activities (1.60; 1.10–2.31), life dissatisfaction (2.34; 1.11–4.93), use of sleep medication (1.78; 1.12–2.82) and a higher number of visits to general practitioners (1.57; 1.06–2.33). Insomnia was not significantly associated with the use of medications for mental health (1.17; 0.82–1.67), hospital admissions (1.31; 0.82–1.67), the use of complementary and alternative medicine (1.10; 0.73–1.67) or unmet need for healthcare (1.22; 0.84–1.77). Conclusions: One in twenty adult Australians experience a level of insomnia that is independently associated with impairments in functioning and increased use of healthcare. Implications: Increasing public and clinician awareness of the impact of insomnia, and promotion of available insomnia treatments may be warranted.
Obstructive sleep apnea (OSA) is gaining recognition as a cardiovascular and cerebrovascular risk factor. Sleep apnea is now implicated in the etiopathogenesis of stroke, coronary artery disease, hypertension, and congestive heart failure. OSA exerts its negative cardiovascular consequences through its unique pattern of intermittent hypoxia and arousals. The putative mechanisms involved in the pathogenesis of cardiovascular disease in OSA include fibrinolytic imbalance, endothelial dysfunction, oxidative stress, and inflammation. This study discusses the known cellular and molecular processes that promote atherogenesis and vascular dysfunction in patients with OSA, and their implications for cardiovascular disease and prevention in that patient population. Neurologists should familiarize themselves with the symptoms and signs of OSA and the pathophysiology of the association between untreated OSA and cardiovascular disease, including stroke. OSA should be ruled out in patients with cardiovascular disease and be regarded as an important modifiable risk factor. Knowledge of this association is of prime public health importance and can result in primary and secondary prevention of cardiovascular events. This study will also help neurologists in providing patient education and treatment.
To investigate the association between short sleep duration and elevated body mass index (BMI) and obesity in a large sample of Japanese adults over a short period. Prospective design with baseline in 2006 and 1-year follow-up. Workplaces of an electric power company in Japan. 35,247 company employees (31,477 men, 3,770 women) distributed throughout Japan. Measured weight and height and self-reported sleep duration were obtained at annual health checkup in 2006 and 2007. Weight change was defined as the difference in body mass index (BMI) between the baseline and 1 year later. Relative to the reference category (sleep duration 7-8 h), short sleep duration (< 5 and 5-6 h) and long sleep duration > or = 9 h were associated with an increased risk of weight gain among men after adjustment for covariates. Of the non-obese (BMI < 25) men at baseline, 5.8% became obese (BMI > or = 25) 1 year later. Higher incidence of obesity was observed among the groups with shorter sleep duration. Adjusted odds ratios for the development of obesity were 1.91 (95% CI 1.36, 2.67) and 1.50 (95% CI 1.24, 1.80) in men who slept < 5 and 5-6 h, respectively. No significant association between sleep duration and weight gain or obesity was found for women. Short sleep duration was associated with weight gain and the development of obesity over 1 year in men, but not in women.
This review of the scientific literature examines the widely observed relationship between sleep duration and mortality. As early as 1964, data have shown that 7-h sleepers experience the lowest risks for all-cause mortality, whereas those at the shortest and longest sleep durations have significantly higher mortality risks. Numerous follow-up studies from around the world (e.g., Japan, Israel, Sweden, Finland, the United Kingdom) show similar relationships. We discuss possible mechanisms, including cardiovascular disease, obesity, physiologic stress, immunity, and socioeconomic status. We put forth a social-ecological framework to explore five possible pathways for the relationship between sleep duration and mortality, and we conclude with a four-point agenda for future research.