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The objective of this narrative review paper is to discuss about sleep duration needed across the lifespan. Sleep duration varies widely across the lifespan and shows an inverse relationship with age. Sleep duration recommendations issued by public health authorities are important for surveillance and help to inform the population of interventions, policies, and healthy sleep behaviors. However, the ideal amount of sleep required each night can vary between different individuals due to genetic factors and other reasons, and it is important to adapt our recommendations on a case-by-case basis. Sleep duration recommendations (public health approach) are well suited to provide guidance at the population-level standpoint, while advice at the individual level (eg, in clinic) should be individualized to the reality of each person. A generally valid assumption is that individuals obtain the right amount of sleep if they wake up feeling well rested and perform well during the day. Beyond sleep quantity, other important sleep characteristics should be considered such as sleep quality and sleep timing (bedtime and wake-up time). In conclusion, the important inter-individual variability in sleep needs across the life cycle implies that there is no “magic number” for the ideal duration of sleep. However, it is important to continue to promote sleep health for all. Sleep is not a waste of time and should receive the same level of attention as nutrition and exercise in the package for good health.
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Nature and Science of Sleep 2018:10 421–430
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REVIEW
open access to scientific and medical research
Open Access Full Text Article
http://dx.doi.org/10.2147/NSS.S163071
Sleeping hours: what is the ideal number and how
does age impact this?
Jean-Philippe Chaput1–4
Caroline Dutil1,3
Hugues Sampasa-Kanyinga1,4
1Healthy Active Living and Obesity
Research Group, Children’s Hospital
of Eastern Ontario Research Institute,
Ottawa, ON, Canada; 2Department
of Pediatrics, University of Ottawa,
Ottawa, ON, Canada; 3School of
Human Kinetics, University of Ottawa,
Ottawa, ON, Canada; 4School of
Epidemiology and Public Health,
University of Ottawa, Ottawa, ON,
Canada
Abstract: The objective of this narrative review paper is to discuss about sleep duration needed
across the lifespan. Sleep duration varies widely across the lifespan and shows an inverse
relationship with age. Sleep duration recommendations issued by public health authorities
are important for surveillance and help to inform the population of interventions, policies,
and healthy sleep behaviors. However, the ideal amount of sleep required each night can vary
between different individuals due to genetic factors and other reasons, and it is important to
adapt our recommendations on a case-by-case basis. Sleep duration recommendations (public
health approach) are well suited to provide guidance at the population-level standpoint, while
advice at the individual level (eg, in clinic) should be individualized to the reality of each person.
A generally valid assumption is that individuals obtain the right amount of sleep if they wake
up feeling well rested and perform well during the day. Beyond sleep quantity, other important
sleep characteristics should be considered such as sleep quality and sleep timing (bedtime and
wake-up time). In conclusion, the important inter-individual variability in sleep needs across the
life cycle implies that there is no “magic number” for the ideal duration of sleep. However, it
is important to continue to promote sleep health for all. Sleep is not a waste of time and should
receive the same level of attention as nutrition and exercise in the package for good health.
Keywords: sleep, recommendations, guidelines, population heath, public health, life cycle
Introduction
Sleep is increasingly recognized as a critical component of healthy development and
overall health.1–3 Healthy sleep comprises many dimensions, including adequate dura-
tion, good quality, appropriate timing, and the absence of sleep disorders.4,5 Not getting
enough sleep at night is generally associated with daytime sleepiness, daytime fatigue,
depressed mood, poor daytime functioning, and other health and safety problems.6–9
Chronic insufficient sleep has become a concern in many countries, given its associa-
tion with morbidity and mortality.10,11 For example, habitual short sleep duration has
been associated with adverse health outcomes including obesity,12 type 2 diabetes,13
hypertension,14 cardiovascular disease,15 depression,16 and all-cause mortality.17 Inter-
est in finding ways to improve sleep patterns of individuals at the population-level
standpoint is growing, and experts recommend that sleep should be considered more
seriously by public health bodies, ie, given as much attention and resources as nutri-
tion and physical activity.18–20
Guidelines on the recommended amount of sleep needed for optimal health exist;
they are a vital tool for surveillance, they help inform policies, they can provide a
starting point for intervention strategies, and they educate the general public about
Correspondence: Jean-Philippe Chaput
Healthy Active Living and Obesity
Research Group, Children’s Hospital
of Eastern Ontario Research Institute,
401 Smyth Road, Ottawa, ON K1H 8L1,
Canada
Tel +1 613 737 7600 (ext 3683)
Email jpchaput@cheo.on.ca
Journal name: Nature and Science of Sleep
Article Designation: Review
Year: 2018
Volume: 10
Running head verso: Chaput et al
Running head recto: Sleep duration across the lifespan
DOI: http://dx.doi.org/10.2147/NSS.S163071
This article was published in the following Dove Press journal:
Nature and Science of Sleep
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Chaput et al
healthy sleep behaviors. However, sleep needs may vary from
one person to another at any given age across the lifespan.
Additionally, some age groups and populations are more
likely to report insufficient sleep duration and may be at
greater risk for detrimental health outcomes.5,6,11 The objec-
tive of this narrative review article is to discuss whether or
not an ideal amount of sleep exists for optimal health and
how it is impacted by age.
Insufcient sleep across the lifespan
Insufficient sleep has become widespread over the last
decades, especially among adolescents.11,21 Both physi-
ological factors and exogenous exposures come into play in
explaining insufficient sleep in this age group. Sleep curtail-
ment is often attributed to extrinsic factors, such as artificial
light, caffeine use, lack of physical activity, no bedtime rules
in the household, and the increased availability of informa-
tion and communication technologies.22–25 In adolescence,
insufficient sleep has also been attributed to intrinsic factors
such as pubertal hormonal changes, which is associated with
a shift toward an evening chronotype26 that may also lead to
an asynchrony between the biological clock, characterized by
a phase delay, and the social clock.27 In adolescents, this bio-
logical phase delay combined with the social clock, for which
the main synchronizer is the fixed and early school start time,
contributes to the observed sleep deficits in this population.27
The conflict between intrinsic and extrinsic factors, biological
time and social time, has been indicated to be greater during
adolescence than at any other point in our lives.28
Despite some overlap between factors that could explain
insufficient sleep among adolescents and adults, such as
exposure to artificial light at night, lack of physical activity,
caffeine consumption, and poor sleep hygiene, other factors
that could specifically be related to insufficient sleep among
adults may include but not be limited to work demands,
social commitments, health and/or affective problems, and
family dynamics (eg, working mothers and children with
full agendas).10
In the elderly, sleep patterns and distribution undergoes
significant quantitative and qualitative changes. Older adults
tend to have a harder time falling asleep and more trouble
staying asleep. This period of life is often accompanied by
a circadian shift to a morning chronotype, as opposed to the
evening chronotype change during adolescence, that results
in early bedtime and risetime.29 Research suggests that the
need for sleep may not change with age, but it is the abil-
ity to get the needed sleep that decreases with age.10 This
decreased ability to sleep in older adults is often secondary to
their comorbidities and related medications (polypharmacy)
rather than normal aging processes per se.30–32 Furthermore,
the increased frequency of sleep-related disorders in the
elderly population contribute to much of the sleep deficien-
cies observed in this population.33–36 Inadequate sleep in
the elderly could also be related to other factors, such as
life changes (eg, retirement, physical inactivity, decreased
social interactions), age-related changes in metabolism, and
environmental changes (eg, placement in a nursing home).37
A systematic review and meta-analysis reported that
in the elderly population both short and long sleep are
independently associated with increased risk of cardiovas-
cular-related and cancer-related mortality.38 Additionally,
adjustments for health conditions in the studies examining
the association between sleep duration and mortality risks
did not attenuate the strength of the association between long
sleep and increased risk of mortality, which suggests that the
mechanisms in these associations may differ between long
sleep and short sleep duration.38 One possible explanation for
this association, between long sleep duration and increased
risk of non-communicable diseases related mortality, may be
related to the increased prevalence of sleep fragmentation in
this population.38,39 While older adults may report long sleep
duration, other sleep characteristics, namely sleep archi-
tecture and quality, are altered by sleep fragmentation. As
the relationship between long sleep duration and increased
risk of cardiovascular-related and cancer-related mortality
is unique to the elderly population, the causality should be
further investigated.
Normative sleep duration values across
the lifespan
Sleep–wake regulation and sleep states evolve very rapidly
during the first year of life.40 For example, newborns (0–3
months) do not have an established circadian rhythm and
therefore their sleep is distributed across the full 24-hour
day. 41 At 10–12 weeks, the circadian rhythm emerges and
sleep becomes more nocturnal between ages 4 and 12
months.42 Children continue to take daytime naps between 1
and 4 years of age, and night wakings are common.43 Daytime
naps typically stop by the age of 5 years and overnight sleep
duration gradually declines throughout childhood, in part
due to a shift to later bedtimes and unchanged wake times.43
Sleep patterns are explained by a complex interplay
between genetic, behavioral, environmental, and social fac-
tors. Examples of factors that can determine sleep duration
include daycare/school schedules, parenting practices, cul-
tural preferences, family routines, and individual differences
in genetic makeup. Despite inter-individual differences in
sleep duration, international normative data exist to show the
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Sleep duration across the lifespan
normal distribution of sleep duration for different age groups.
However, it is important to keep in mind that normative
reference values by no means indicate anything about what
the ideal or optimal sleep duration should be, ie, the amount
of sleep associated with health benefits. Nevertheless, they
tell us about what is normal (or not) in the population and
provide a valuable yardstick for practitioners and educators
when dealing with sleep-related issues.
A meta-analysis by Galland et al44 examined the scientific
literature with regards to normal sleep patterns in infants and
children aged 0–12 years. The review included 69,542 partici-
pants from 18 countries and subjective measures were used
to determine sleep duration (sleep diary or questionnaire).
They calculated mean reference values and ranges (±1.96
SD) for sleep duration of 12.7 h/day (9.0–13.3) for infants
(<2 years), 11.9 h/day (9.9–13.8) for toddlers/preschoolers
(ages 2–5 years), and 9.2 h/day (7.6–10.8) for children (6–12
years). Normative sleep duration data across age categories
are shown in Figure 1. A strong inverse relationship with age
was evident from these data, with the fastest rate of decline
observed over the first 6 months of life (10.5 min/month
decline in sleep duration). The review also highlighted that
Asians had significantly shorter sleep (1 hour less over the
0–12-year range) compared to Caucasians or other ethnic
groups. Overall, these reference values should be considered
as global norms because the authors combined different
countries and cultures.
Galland et al45 also reported in 2018 normative sleep dura-
tion values for children aged 3–18 years as measured with
actigraphy (objective assessment of sleep duration). Their
meta-analysis included 79 articles and involved children from
17 countries. As shown in Figure 2, pooled mean estimates
for overnight sleep duration declined from 9.68 hours (3–5
years age band) to 8.98 hours (6–8 years age band), 8.85 hours
(9–11 years age band), 8.05 hours (12–14 years age band),
and 7.4 hours (15–18 years age band). These normative sleep
duration values may aid in the interpretation of actigraphy
measures from nighttime recordings in the pediatric popula-
tion for any given age.
A meta-analysis of objectively assessed sleep from child-
hood to adulthood was also published by Ohayon et al46 in
2004 to determine normative sleep values across the lifespan.
A total of 65 studies representing 3,577 healthy individu-
als aged 5–102 years were included. Polysomnography or
actigraphy was used to assess sleep duration in the included
studies. They observed that total sleep time significantly
14.6
13.6
12.9 12.6 12.9 12.6
12
11.5
9.7 9.4 9.3 9.3 9.1 98.9
0–2 m
6
8
10
12
14
Sleep duration (hours/day)
16
18
20
1–2 y 2–3 y 4–5 y
Age
6 y7 y8 y9 y 10 y11 y 12 y3 m6 m9 m 12 m
Figure 1 Normal self-reported sleep durations in children aged 0–12 years.
Note: The mean reference values are from a meta-analysis of 34 studies from 18 countries.44
Abbreviations: m, months; y, years.
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Chaput et al
decreased with age in adults, while it was the case in children
and adolescents only in studies performed on school days.
This pattern suggests that, in children and adolescents, the
decrease in total sleep time is not related to maturation but
to other factors such as earlier school start times.
In summary, normative sleep duration values are helpful
in providing information on what constitutes the norm for
a given age and what is considered outside the norm. These
reference values are impacted by the method used to deter-
mine sleep duration (objective vs subjective assessment)
and provide norms at the population-level standpoint. Many
factors can determine sleep duration at the individual level.
Although international normative data provide information
about the normal distribution of sleep duration in the popula-
tion, they do not identify the duration associated with health
benefits. For example, having a sleep duration that fits with
the average of the population is by no means indicative of
either a good or a bad sleep amount. Optimal sleep duration,
or the amount of sleep associated with favorable outcomes,
is what is used for public health recommendations and is
discussed in the next section.
Recommended amount of sleep across
the lifespan
In 2015, the National Sleep Foundation in the US released
their updated sleep duration recommendations to make scien-
tifically sound and practical recommendations for daily sleep
duration across the lifespan.47 The same year, the American
Academy of Sleep Medicine and the Sleep Research Society
released a consensus recommendation for the amount of
sleep needed to promote optimal health in adults.48 The year
after, they released their recommended amount of sleep for
pediatric populations.49 Both sleep guidelines issued by the
US used a similar developmental approach to deliver their
sleep duration recommendations, which included a consensus
and a voting process with a multidisciplinary expert panel.
The sleep duration recommendations can be found in Table 1.
Many organizations around the world have their own sleep
duration recommendations, and the aim of this article is not
to review the different sleep duration guidelines. Overall, they
are all very similar, and often reference the recommendations
from the US. In Canada, robust and evidence-informed sleep
guidelines became available in 2016.50,51 The sleep recom-
mendations in Canada for children of all ages, also known
as the 24-hour guidelines, are integrated with physical
activity and sedentary behavior recommendations to cover
the entire 24-hour period (sleep/wake period). This allows
to put more emphasis on the overall “cocktail” of behaviors
for a healthier 24-hour day, rather than isolating individual
behaviors. This integrated approach to health, with a focus
on the interrelationships among sleep, sedentary behavior,
and physical activity, is an important advancement in public
9.68
8.98 8.85
8.05
7.4
3–5 6–8 9–11 12–14 15–18
6
7
8
9
10
Sleep duration (hours/night)
11
12
Age (Years)
Figure 2 Normal actigraphy-determined sleep duration values in children aged 3–18 years.
Note: The mean reference values are from a meta-analysis of 79 studies from 17 countries.45
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Sleep duration across the lifespan
health messaging. It emphasizes that all of these behaviors
matter equally, and balancing all three is required for favor-
able health outcomes.
The Canadian 24-hour guidelines were the impetus for
the development of similar guidelines in Australia,52 New
Zealand,53 and the initiation of similar global guidelines by
the World Health Organization. Similar integrated 24-hour
guidelines for adults and older adults are currently being
developed in Canada to cover the entire lifespan. The sleep
duration recommendations contained within the 24-hour
movement guidelines can be found in Table 1.
Although sleep duration recommendations are based on
the best available evidence and expert consensus, they are still
largely reliant on observational studies using self-reported
sleep duration. More longitudinal studies and sleep restric-
tion/extension experiments are needed to better quantify
the upper and lower limits of healthy sleep duration, and
the shape of the dose–response curve with a wide range of
health outcomes. Current sleep duration recommendations
also suggest that a generalized optimum exists for the entire
population; however, it is unlikely to be the case and this opti-
mum can vary depending on the health outcome examined.54
There is also inter-individual variability in sleep needs in that
sleeping shorter or longer than the recommended amount
may not necessarily result in adverse effects on health. For
example, genetic differences between individuals can explain
some of the variability in sleep needs. However, intention-
ally restricting sleep over a prolonged period of time (ie,
chronic sleep deprivation) is not a good idea and can impact
health and safety.47 Thus, although sleep recommendations
are a good tool for public health surveillance, they need to
be adapted on a case-by-case basis in clinic (not a one-size-
fits-all recommendation).
Sleep duration recommendations have ranges, or zones
of optimal sleep, suggesting that the relationship between
sleep duration and adverse health outcomes is U-shaped,
with both extremities, sleep durations that are too short or
too long, associated with negative effects on health.47–51
There is a large body of evidence providing biological
plausibility for short sleep as causally related to a wide
range of adverse health outcomes; however, the role of long
sleep is less clear. Aside from the elderly population, long
sleep is generally associated with other health problems
(eg, depression, chronic pain, low socioeconomic status)
that can confound the associations.55,56 Reverse causation
and residual confounding are thus better mechanisms to
explain the associations between long sleep and adverse
health outcomes.55,56 This may explain why the American
Academy of Sleep Medicine and the Sleep Research Soci-
ety recommends a threshold value for adults (7 hours per
night) rather than a range (eg, 7–9 hours per night) (Table
1). However, excessive long sleep duration may be infor-
mative as it can be indicative of poor sleep efficiency (ie,
spending a lot of time in bed but of low quality).
Table 1 Sleep duration recommendations in the US and Canada
National sleep foundation
(US)
AASM/SRS
(US)
24-hour movement guidelines
(Canada)
Age group Recommendation Age group Recommendation Age group Recommendation
Newborns
(0–3 months)
14–17 hours Newborns
(0–3 months)
Not included Newborns
(0–3 months)
14–17 hours
Infants
(4–11 months)
12–15 hours Infants
(4–11 months)
12–16 hours Infants
(4–11 months)
12–16 hours
Toddlers
(1–2 years)
11–14 hours Toddlers
(1–2 years)
11–14 hours Toddlers
(1–2 years)
11–14 hours
Preschoolers
(3–5 years)
10–13 hour Preschoolers
(3–5 years)
10–13 hours Preschoolers
(3–4 years)
10–13 hours
Children
(6–13 years)
9–11 hours Children
(6–12 years)
9–12 hours Children
(5–13 years)
9–11 hours
Teenagers
(14–17 years)
8–10 hours Teenagers
(13–17 years)
8–10 hours Teenagers
(14–17 years)
8–10 hours
Young adults
(18–25 years)
7–9 hours Adults
(18–60 years)
7 hours Adults
(18–64 years)
In development
Adults
(26–64 years)
7–9 hours Older adults
(65 years)
In development
Older adults
(65 years)
7–8 hours
Note: Papers describing the sleep duration recommendations can be found elsewhere.47–51
Abbreviations: AASM, American Academy of Sleep Medicine; SRS, Sleep Research Society.
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Chaput et al
Self-reported sleep duration is typically used in popula-
tion health surveillance studies, because it provides several
advantages (eg, inexpensive, not invasive, and logistically
easy to administer to a large sample of individuals). How-
ever, the concession is that sleep duration recommenda-
tions are then largely based on self-reported data. It is
well-known that self-reported sleep duration overestimates
actual sleep duration.57 Thus, it would be misleading to
use an objective measure of sleep duration to report the
prevalence of short sleepers in a given sample; this would
result in an overestimation of true short sleepers. The grow-
ing popularity of actigraphy and wearable technologies for
health behavior tracking in epidemiology is nevertheless
desirable for providing better sleep estimates and more pre-
cise associations with health outcomes.58,59 Sleep duration
recommendations are also likely to evolve over time, as
more objective measures of sleep are used in future studies.
For example, an individual self-reporting 7 hours of sleep
per night may actually get 6 hours if assessed objectively
with actigraphy, as it can better account for total sleep by
accurately measuring sleep onset and episodes of night
wakings.60 Thus, using reliable tools for tracking sleep
duration over time is important, and one must keep in mind
that the overall sleep duration pattern is more critical to
long-term health than one snapshot in time (ie, chronic
effect vs acute effect of insufficient sleep on health).
Consumers have also become increasingly interested in
using fitness trackers and smartphone applications to assess
their sleep. These devices provide information on sleep
duration and even sleep quality from in-built accelerometry
but the mechanisms and algorithms are propriotery.61–64 The
growing body of evidence on consumer sleep tracking devices
against polysomnography/actigraphy shows that they tend to
underestimate sleep disruptions and overestimate sleep dura-
tion and sleep efficiency in healthy individuals.61–64 Although
consumer sleep tracking devices are changing the landscape
of sleep health and have important advantages, more research
is needed to better determine their utility and reduce current
shortcomings.61–64
Population statistics in Canada indicate that 16% of
preschoolers sleep less than recommended, while 20% of
children and one-third of teenagers, adults, and older adults
report less-than-recommended sleep durations for optimal
health.65–67 These nationally representative surveys use sub-
jective data and are thus comparable to the sleep duration
guidelines. As shown in Figure 3, the average sleep duration
of Canadians by age group is situated at the lower border of
the sleep duration recommendations. On average, a large
10.6
9.43
8.07
7.12 7.24
Recommended sleep duration range Average sleep duration duration of Canadians
Newborns Infants Toddlers Preschoolers School-aged
children
Teenagers Aduts Older adults
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Sleep duration (hours/night)
Age group
Figure 3 Sleep duration estimates of Canadians (dashed line) compared with the sleep duration recommendation ranges (solid lines).
Notes: Sleep duration estimates for the Canadian population have been recently published.65–67 However, they are not available for newborns, infants, or toddlers. Canadians
sleeping less than recommended for optimal health is estimated at 16% for preschoolers, 20% for school-aged children, 30% for teenagers, 32% for adults, and 31% for
older adults.
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Sleep duration across the lifespan
proportion of Canadians meet the sleep duration recom-
mendations (eg, two-third of teenagers and adults); however,
a large number of individuals fail to meet the guidelines
(eg, one-third of teenagers and adults). If we dig deeper,
we realize that the teenage group has shown the greatest
rate of decline in sleep duration in past decades, especially
on school days.11 Knowing the age groups more likely to
experience insufficient sleep is critical to help inform the
development of interventions aimed at improving sleep (eg,
having school start times not earlier than 8:30 am for high-
school students).68–70
Ideal amount of sleep: fact or ction?
As discussed in this article, there is no magic number
for all in terms of the ideal sleep amount to obtain each
night. Sleep duration recommendations are meant for
public health guidance, but need to be individualized to
each patient in the clinic. Sleep needs are determined by
a complex set of factors, including our genetic makeup,
environmental and behavioral factors. For example, high-
performance athletes need more sleep to perform at high
level and recover from their intense physical training. Sleep
needs in children and adolescents can also be driven by
their maturation stage, independent of their chronological
age.46 This means that changes in sleep patterns may happen
earlier (at a younger age) for some or at an older age for
others. Objectively, our current evidence of sleep need is
based on circadian, homeostatic, and ultradian processes
of sleep regulation and sleep need.
The notion of “optimal sleep” is complex and
poorly understood.71 The definitions of optimal sleep
also vary in the literature. It is very often defined as the
amount recommended by public health authorities. It has
also been defined as the daily amount of sleep that allows
an individual to be fully awake (ie, not sleepy), and able
to sustain normal levels of performance during the day.72
Others have also defined it as the amount of sleep required
to feel refreshed in the morning.73 The notion of a new
definition to optimal sleep based on performance is of
growing interest in the literature. For example, sleep exten-
sion interventions have been shown to improve athletic
performance.74,75
However, as discussed in this article and by other sleep
experts,76 there is no magic number for optimal sleep, and
sleep is influenced by inter- and intra-individual factors.
Similarly, in a context of sleep deprivation, individual dif-
ferences in sleep homeostatic and circadian rhythm contri-
butions to neurobehavioral impairments have been elegantly
documented by Van Dongen.77–79
Optimal sleep should be conceptualized as the amount of
sleep needed to optimize outcomes (eg, performance, cogni-
tive function, mental health, physical health, quality of life,
etc). This implies that there might be many dose–response
curves that may differ in shape between outcomes.54 Typically,
the peaks of each health outcome should fall somewhere
within the recommended sleep duration range. However, the
exact amount of sleep to get each night for optimizing all
relevant health outcomes is not straightforward or ubiquitous
as the optimal amount for one outcome may not be the same
for another outcome (eg, 9 hours of sleep per night could be
the ideal for athletic performance, while 7 hours could be
the best for academic achievement). Also, determining the
causal effects of sleep need on health is not an easy task and
requires experiments (eg, interventional study designs with
improved vs reduced sleep, both acutely and chronically
applied, and then assessing outcomes on physiology, well-
being, health, and behavior).
Although the present article focused on sleep duration,
many other dimensions of sleep are important beyond get-
ting a sufficient amount each night. These include aspects
of sleep quality such as sleep efficiency (ie, proportion of
the time in bed actually asleep), sleep timing (ie, bedtime/
wake-up times), sleep architecture (ie, sleep stages), sleep
consistency (ie, day-to-day variability in sleep duration),
sleep consolidation (ie, organization of sleep across the
night), and sleep satisfaction. For example, the National Sleep
Foundation recently released evidence-informed sleep quality
recommendations for individuals across the lifespan.80 These
included sleep continuity variables such as sleep latency,
number of awakenings >5 minutes, wake after sleep onset,
and sleep efficiency. Along the same lines, monophasic sleep
(ie, sleeping once per day, typically at night) is considered the
norm in our society but other sleep patterns (eg, biphasic or
polyphasic) are also observed depending on the preference
of each person or culture. Napping is increasingly seen as a
public health tool and countermeasure for sleep deprivation
in terms of reducing accidents and cardiovascular events and
improving working performance.81
Conclusion
In summary, there is no magic number or ideal amount of
sleep to get each night that could apply broadly to all. The
optimal amount of sleep should be individualized, as it
depends on many factors. However, it is a fair assumption to
say that the optimal amount of sleep, for most people, should
be within the age-appropriate sleep duration recommended
ranges. Future studies should try to better inform contem-
porary sleep duration recommendations by examining dose–
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Chaput et al
response curves with a wide range of health outcomes. In the
meantime, promoting the importance of a good night’s sleep
should be a priority given its influence on other behaviors and
the well-known adverse consequences of insufficient sleep.82
Important sleep hygiene tips include removing screens from
the bedroom, exercising regularly during the day, and having
a consistent and relaxing bedtime routine.
Acknowledgment
Jean-Philippe Chaput is a Research Scientist funded by the
Children’s Hospital of Eastern Ontario Research Institute
(ON, Canada).
Disclosure
The authors report no conflicts of interest in this work.
References
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relationships between sleep duration and health indicators in school-
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... This information is missing in most of the studies and particular attention should be taken during participant screening, especially if involving undergraduate students [58], being more prone to manifest chronically limited sleep [119]. Even though the optimal number of sleep hours is strongly subjective and depends on the age [120], we suggest participants sleep 7 to 9 hours before the experiments. ...
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Mental health is influenced by the fast-paced nature of life. In this scenario, stressful events play an important role. Extensive research has been carried out to develop non-invasive devices for stress detection, which primarily use physiological data and, more recently, artificial intelligence algorithms. When developing either a new device or algorithm, tests in controlled environments are preferred, because of the supervision of possible confounding factors while running the experiments. However, because of the extremely subjective perception of stress, the characteristics of the investigated samples, and the conditions under which the experiment is conducted, the data may not be representative of a perceived stressful condition, leading to biases. Given the importance of reliable experimental protocols for stress induction, especially if cortisol level is not monitored, this work aims to present approaches for inducing and assessing acute mental stress in controlled conditions, analyzing the problem from engineering and psychological perspectives. All the phases of the experimental protocol are discussed, examining both the factors that could induce stress and the assessment tools, like questionnaires and physiological signals. The analysis of the latter will be focused on the exogenous factors that may compromise the measures, providing solutions for their mitigation. With this work, researchers with different backgrounds can improve the efficacy of their studies, limiting biases and misleading results.
... Furthermore, our sleep measure does not directly quantify health risks, as we did not exclusively focus on health-relevant thresholds of less than six hours or more than ten hours (Hirshkowitz et al., 2015). Still, individual sleep needs vary, and individual variability exists (Chaput et al., 2018). Therefore, we assume that every reduction in sleep has the potential to pose a health risk, as we focus on intraindividual change. ...
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Objective: This study examines the impact of work-family conflict on sleep duration by gender from a longitudinal perspective, differentiating between work-to-family (WTFC) and family-to-work conflict (FTWC) as well as time- vs. strain-based conflict. Background: In previous research, work-family conflict was found to be related to adverse health outcomes. Although sleep is crucial for overall health, relatively few studies have explored the relationship between sleep and work-family conflict, especially with regard to the direction and type of conflict and gender. In exploring these aspects, we apply the Conservation of Resources Theory and Stress Process Theory, in which the distinction between conflict direction and type, as well as gender, is essential. Method: Using the German Family Panel study “pairfam” and a sample of 3,719 respondents, we apply fixed effects regression models to estimate the effects of time- and strain-based WTFC and FTWC on sleep duration for men and women. Results: Our results show a negative impact of both WTFC and FTWC on sleep duration, which is consistent with previous findings. Overall, FTWC affects sleep duration more strongly than WTFC. Looking at the type of conflict, the results for WTFC and FTWC differ: for WTFC, the time-based conflict has a stronger effect on sleep duration; for FTWC, the strain-based conflict is more relevant. Gender differences emerge, with men reducing their sleep duration with increasing WTFC and FTWC, while women only with FTWC. For women, only strain-based FTWC decreases sleep duration; for men, mainly time-based WTFC does so. Conclusion: It seems that the interference of time-based work demands with family life reduces sleep duration primarily among men, whereas when family demands interfere with work it is the psychological strain of the resulting conflict that impacts sleep for women.
... The duration of sleep depends on the age of the person. The National Sleep Foundation advises that elderly people sleep fewer than 7-8 hours a night, while younger adults and adults between the ages of 18 and 25 and between the ages of 26 and 64 should sleep 7-9 hours [4]. Some studies carried out among university students showed that in general longer duration of sleep was related to better academic performance [3]. ...
... thus, it is imperative to ensure an adequate amount of sleep and to seek timely therapeutic intervention for any sleep disturbances in order to enhance sleep quality. With respect to sleep duration, although individual sleep requirements vary, for the enhancement of health, it is advised that adults secure 7 to 9 hours of sleep per night; older adults aim for 7 to 8 hours; children aged between 6 to 13 should obtain 9 to 11 hours, and adolescents aged 14 to 17 necessitate 8 to 10 hours of rest each night [11]. ...
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Diabetes represents one of the most susceptible chronic diseases, encompassing an array of diverse complications. The lack of awareness regarding the detrimental effects of diabetes on dental health is evident therefore this article is to educate people regarding such condition. Currently, there is moderate evidence suggesting a significant impact of diabetes on dental health, Furthermore, it exhibits a pronounced association with periodontitis. as well as a bilateral relationship between periodontal disease and diabetes with each condition potentially exacerbating the other. The present article addresses the existing deficiencies in this field by incorporating an analysis of the impact of diabetes on dental health and proposing effective strategies for its management. The implementation of this approach may effectively contribute to a reduction in the prevalence of diabetes and promote dental health. For individuals diagnosed with diabetes, it enables them to gain awareness regarding the detrimental impact of diabetes on their oral health and take appropriate measures to mitigate such effects.
... Sleep duration was self-reported by the question 'How many hours of sleep do you typically get at night on weekdays or workdays?' Responses were classified into two categories: optimal sleep (7-9 h per night) and nonoptimal sleep (< 7 or > 9 h per night), following established sleep duration guidelines [34][35][36]. ...
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Objective In this study, the associations between healthy lifestyles and obstructive sleep apnea (OSA) in middle-aged and elderly adults were investigated via data from the National Health and Nutrition Examination Survey (NHANES) for the periods of 2005–2008 and 2015–2018. Methods A total of 6,406 participants aged 40 years and older were included in the analysis. Healthy lifestyle behaviors were assessed through diet quality, physical activity, sleep duration, alcohol consumption, smoking status, and body mass index (BMI). A composite healthy lifestyle score (ranging from 0 to 6) was created and categorized into insufficient (0–2), intermediate (3–4), and optimal (5–6) health groups. Weighted logistic regression models were used to examine the association between these lifestyle scores and OSA, adjusting for some demographic, socioeconomic, and clinical covariates. Additionally, mediation analysis was conducted to evaluate the role of BMI as a mediator in the relationship between the composite healthy lifestyle score and OSA, determining the proportion of the total effect mediated by BMI. Results Participants were classified into insufficient (17.81%), intermediate (56.82%), and optimal (25.37%) lifestyle groups. Higher dietary quality (OR: 0.81, 95% CI: 0.66–0.99) and adequate weight (OR: 0.09, 95% CI: 0.07–0.11) were statistically associated with reduced OSA odds after adjustments, whereas the variables were not. Each one-point increase in the healthy lifestyle score was linked to a 33% reduction in OSA odds (OR: 0.67, 95% CI: 0.63–0.71). A significant linear trend was observed, with better adherence to healthy lifestyle correlating with lower odds of OSA (p for trend < 0.001). Compared with insufficient lifestyle, intermediate lifestyle was linked to a 27% reduction in OSA (OR: 0.73, 95% CI: 0.58–0.91), whereas optimal lifestyle was associated with a 74% reduction (OR: 0.26, 95% CI: 0.21–0.33). Mediation analysis revealed that BMI significantly mediated the relationship between healthy lifestyle score and OSA, accounting for approximately 59.2% of the total effect (P < 0.001). The direct effect of the healthy lifestyle score on OSA remained significant even when controlling for BMI (P < 0.001). Subgroup analyses confirmed consistent benefits across different demographic groups. Conclusions This study revealed that adherence to healthy lifestyles significantly reduces the odds of OSA, with optimal lifestyles leading to a marked decrease in the odds of OSA. Notably, BMI plays a critical mediating role in this relationship. These findings emphasize the importance of promoting healthy lifestyle interventions as a key strategy for the prevention and management of OSA.
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Background A healthy dietary habit may contribute to good sleep quality. The present study investigates the correlation between the quality and quantity of daily carbohydrate consumption and poor sleep patterns. Methods The exposures of interest included low-and high-quality carbohydrate consumption and total daily carbohydrate consumption. Subjects were classified into four different carbohydrate consumption patterns: Pattern 1 was characterized by high-quality carbohydrates below the median and low-quality carbohydrates above the median; Pattern 2 included both high-and low-quality carbohydrates below the median; Pattern 3 was defined as high-and low-quality carbohydrates above the median; Pattern 4 referred to high-quality carbohydrates above the median and low-quality carbohydrates below the median. The comprehensive sleep patterns included three different sleep behaviors: sleep duration, daytime sleepiness, and snoring, which were used to score sleep patterns. A score ranging from 0 to 1 was classified as having a healthy sleep pattern, while a score between 2 and 3 showed poor sleep patterns. Survey-weighted multivariable logistic regression analyses were adopted. Results In the multivariate analysis, individuals who consumed more high-quality carbohydrates were linked to a decreased likelihood of experiencing poor sleep patterns [odds ratio (OR) 0.71; 95% confidence interval (CI) 0.62–0.81], while increased consumption of low-quality carbohydrates (OR 1.39; 95%CI 1.20–1.61) and total daily carbohydrates (OR 1.31; 95%CI 1.10–1.57) was related to an elevated risk of poor sleep patterns. Participants who adhered to carbohydrate intake pattern 4 exhibited a 36% lower risk of poor sleep patterns than those who followed carbohydrate intake pattern 1 (OR 0.64; 95%CI 0.56–0.74). There was a positive correlation between elevated added sugar consumption and an increased probability of developing poor sleep patterns. In contrast, an elevated intake of whole grains, fruits, or non-starchy vegetables was related to a decreased likelihood of experiencing poor sleep patterns. Conclusion The increased consumption of low-quality carbohydrates may heighten the susceptibility to poor sleep patterns, whereas the increased consumption of high-quality carbohydrates may mitigate the risk of developing poor sleep patterns.
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Background: Athletes experience various situations and conditions that can interfere with their sleep, which is crucial for optimal psychological and physiological recovery as well as subsequent performance. Conventional sleep screening and intervention approaches may not be efficacious for athletes given their lifestyle, the demands of training and travel associated with interstate/international competition. Objectives: The present systematic review aimed to summarize and evaluate sleep intervention studies targeting subsequent performance and recovery in competitive athletes. Based on the findings, a secondary aim was to outline a possible sleep intervention for athletes, including recommendations for content, mode of delivery and evaluation. Methods: A systematic review was conducted based on the PRISMA guidelines in May 2016 with an update completed in September 2017. Ten studies met our inclusion criteria comprising a total of 218 participants in the age range of 18-24 years with athletes from various sports (e.g., swimming, soccer, basketball, tennis). A modified version of the quality assessment scale developed by Abernethy and Bleakley was used to evaluate the quality of the studies. Results: The included studies implemented several sleep interventions, including sleep extension and napping, sleep hygiene, and post-exercise recovery strategies. Evidence suggests that sleep extension had the most beneficial effects on subsequent performance. Consistent with previous research, these results suggest that sleep plays an important role in some, but not all, aspects of athletes' performance and recovery. Conclusion: Future researchers should aim to conduct sleep interventions among different athlete populations, compare results, and further establish guidelines and intervention tools for athletes to address their specific sleep demands and disturbances.
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Background: New Canadian 24-Hour Movement Guidelines for the Early Years have been released in 2017. According to the guidelines, within a 24-h period, preschoolers should accumulate at least 180 min of physical activity (of which at least 60 min is moderate-to-vigorous physical activity), engage in no more than 1 h of screen time, and obtain between 10 and 13 h of sleep. This study examined the proportions of preschool-aged (3 to 4 years) Canadian children who met these new guidelines and different recommendations within the guidelines, and the associations with adiposity indicators. Methods: Participants were 803 children (mean age: 3.5 years) from cycles 2-4 of the Canadian Health Measures Survey (CHMS), a nationally representative cross-sectional sample of Canadians. Physical activity was accelerometer-derived, and screen time and sleep duration were parent-reported. Participants were classified as meeting the overall 24-Hour Movement Guidelines if they met all three specific time recommendations for physical activity, screen time, and sleep. The adiposity indicators in this study were body mass index (BMI) z-scores and BMI status (World Health Organization Growth Standards). Results: A total of 12.7% of preschool-aged children met the overall 24-Hour Movement Guidelines, and 3.3% met none of the three recommendations. A high proportion of children met the sleep duration (83.9%) and physical activity (61.8%) recommendations, while 24.4% met the screen time recommendation. No associations were found between meeting individual or combined recommendations and adiposity. Conclusions: Very few preschool-aged children in Canada (~13%) met all three recommendations contained within the 24-Hour Movement Guidelines. None of the combinations of recommendations were associated with adiposity in this sample. Future work should focus on identifying innovative ways to reduce screen time in this population, and should examine the associations of guideline adherence with health indicators other than adiposity.
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Background: In 2017, the Australian Government funded the update of the National Physical Activity Recommendations for Children 0-5 years, with the intention that they be an integration of movement behaviours across the 24-h period. The benefit for Australia was that it could leverage research in Canada in the development of their 24-h guidelines for the early years. Concurrently, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) working group published a model to produce guidelines based on adoption, adaption and/or de novo development using the GRADE evidence-to-decision framework. Referred to as the GRADE-ADOLOPMENT approach, it allows guideline developers to follow a structured and transparent process in a more efficient manner, potentially avoiding the need to unnecessarily repeat costly tasks such as conducting systematic reviews. The purpose of this paper is to outline the process and outcomes for adapting the Canadian 24-Hour Movement Guidelines for the Early Years to develop the Australian 24-Hour Movement Guidelines for the Early Years guided by the GRADE-ADOLOPMENT framework. Methods: The development process was guided by the GRADE-ADOLOPMENT approach. A Leadership Group and Consensus Panel were formed and existing credible guidelines identified. The draft Canadian 24-h integrated movement guidelines for the early years best met the criteria established by the Panel. These were evaluated based on the evidence in the GRADE tables, summaries of findings tables and draft recommendations from the Canadian Draft Guidelines. Updates to each of the Canadian systematic reviews were conducted and the Consensus Panel reviewed the evidence for each behaviour separately and made a decision to adopt or adapt the Canadian recommendations for each behaviour or create de novo recommendations. An online survey was then conducted (n = 302) along with five focus groups (n = 30) and five key informant interviews (n = 5) to obtain feedback from stakeholders on the draft guidelines. Results: Based on the evidence from the Canadian systematic reviews and the updated systematic reviews in Australia, the Consensus Panel agreed to adopt the Canadian recommendations and, apart from some minor changes to the wording of good practice statements, keep the wording of the guidelines, preamble and title of the Canadian Guidelines. The Australian Guidelines provide evidence-informed recommendations for a healthy day (24-h), integrating physical activity, sedentary behaviour (including limits to screen time), and sleep for infants (<1 year), toddlers (1-2 years) and preschoolers (3-5 years). Conclusions: To our knowledge, this is only the second time the GRADE-ADOLOPMENT approach has been used. Following this approach, the judgments of the Australian Consensus Panel did not differ sufficiently to change the directions and strength of the recommendations and as such, the Canadian recommendations were adopted with very minor alterations. This allowed the Guidelines to be developed much faster and at lower cost. As such, we would recommend the GRADE-ADOLOPMENT approach, especially if a credible set of guidelines, with all supporting materials and developed using a transparent process, is available. Other countries may consider using this approach when developing and/or revising national movement guidelines.
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The concept of sleep health is gaining momentum globally. Rather than “medicalizing” sleep with a focus on sleep disorders and their treatment, there is growing interest in sleep health promotion for all and on the prevention of sleep problems. In Canada, sleep health is increasingly becoming part of a holistic vision of health and provides a metric for health promotion efforts. One of the outcomes of this evolving understanding of sleep health in Canada has been the release of the world's first integrated 24-hour movement guidelines for the pediatric population in 2016. These were the first systematic review-informed sleep guidelines in Canada, and provided important benchmarks for surveillance. They also integrated sleep health with other lifestyle behaviors by putting the emphasis on the full 24-hour period rather than nocturnal sleep duration. Among the possible solutions to counter the adverse effects of insufficient sleep, public health policies are crucial to help prioritizing sleep health in children. The future of pediatric sleep health in Canada is bright, and we need to align our efforts and continue to push for this important topic in the public health arena. It is expected that this action will result in the prioritization of sleep health by the public health community in Canada so that it becomes an equal counterpart to the attention and resources given to other lifestyle behaviors such as healthy nutrition and sufficient amounts of physical activity.
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Objective To examine the relationships between objectively measured sleep patterns (sleep duration, sleep efficiency and bedtime) and sugar-sweetened beverage (SSB) consumption (regular soft drinks, energy drinks, sports drinks and fruit juice) among children from all inhabited continents of the world. Design Multinational, cross-sectional study. Setting The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE). Subjects Children ( n 5873) 9–11 years of age. Results Sleep duration was 12 min per night shorter in children who reported consuming regular soft drinks ‘at least once a day’ compared with those who reported consuming ‘never’ or ‘less than once a week’. Children were more likely to sleep the recommended 9–11 h/night if they reported lower regular soft drink consumption or higher sports drinks consumption. Children who reported consuming energy drinks ‘once a week or more’ reported a 25-min earlier bedtime than those who reported never consuming energy drinks. Children who reported consuming sports drinks ‘2–4 d a week or more’ also reported a 25-min earlier bedtime compared with those who reported never consuming sports drinks. The associations between sleep efficiency and SSB consumption were not significant. Similar associations between sleep patterns and SSB consumption were observed across all twelve study sites. Conclusions Shorter sleep duration was associated with higher intake of regular soft drinks, while earlier bedtimes were associated with lower intake of regular soft drinks and higher intake of energy drinks and sports drinks in this international study of children. Future work is needed to establish causality and to investigate underlying mechanisms.
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Background Despite the widespread use of actigraphy in pediatric sleep studies, there are currently no age-related normative data. Objectives To systematically review the literature, calculate pooled mean estimates of actigraphy-derived pediatric nighttime sleep variables and to examine the magnitude of change with age. Methods A systematic search was performed across eight databases of studies that included at least one actigraphy sleep variable from healthy children aged 0–18 years. Data suitable for meta-analysis were confined to ages 3–18 years with seven actigraphy variables analyzed using random effects meta-analysis and meta-regression performed using age as a covariate. Results In total, 1334 articles did not meet inclusion criteria; 87 had data suitable for review and 79 were suitable for meta-analysis. Pooled mean estimates for overnight sleep duration declined from 9.68 hours (3–5 years age band) to 8.98, 8.85, 8.05, and 7.4 for age bands 6–8, 9–11, 12–14, and 15–18 years, respectively. For continuous data, the best-fit (R² = 0.74) equation for hours over the 0–18 years age range was 9.02 − 1.04 × [(age/10)^2 − 0.83]. There was a significant curvilinear association between both sleep onset and offset with age (p < .001). Sleep latency was stable at 19.4 min per night. There were significant differences among the older age groups between weekday and weekend/nonschool days (18 studies). Total sleep time in 15–18 years old was 56 min longer, and sleep onset and offset almost 1 and 2 hours later, respectively, on weekend or nonschool days. Conclusion These normative values have potential application to assist the interpretation of actigraphy measures from nighttime recordings across the pediatric age range, and aid future research.
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Aim: This study examined the association between social media and sleep duration among Canadian students aged 11-20. Methods: Data from 5242 students were obtained from the 2015 Ontario Student Drug Use and Health Survey, a province-wide, school-based survey that has been conducted every two years since 1977. We measured the respondents' sleep duration against the recommended ranges of 9-11 h per night at 11-13 years of age, 8-10 h at 14-17 and 7-9 h per night for those aged 18 years or more. Results: Overall, 36.4% of students met or exceeded the recommended sleep duration and 63.6% slept less than recommended, with 73.4% of students reporting that they used social media for at least one hour per day. After adjusting for various covariates, the use of social media was associated with greater odds of short sleep duration in a dose-response manner (p for linear trend <0.001). Odds ratios ranged from 1.82 for social media use of at least one hour per day to 2.98 for at least five hours per day. Conclusion: Greater use of social media was associated with shorter sleep duration in a dose-response fashion among Canadian students aged 11-20.
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This article provides recent estimates of the duration and quality of sleep of Canadian adults and of the percentage who adhere to sleep duration guidelines (7 to 9 hours per night at ages 18 to 64, and 7 to 8 hours per night at age 65 or older). The study is based on 10,976 respondents aged 18 to 79 from the 2007-to-2013 Canadian Health Measures Survey, a nationally representative, cross-sectional survey. Sleep duration and quality were self-reported. Mean sleep duration was 7.12 hours per night at ages 18 to 64 and 7.24 hours per night at ages 65 to 79. An estimated 65% of 18- to 64-year-olds and 54% of seniors slept the recommended number of hours per night. However, short sleep duration and poor sleep quality were relatively common. About a third slept fewer hours than recommended. At ages 18 to 64, an estimated 43% of men and 55% of women reported trouble going to sleep or staying asleep "sometimes/most of the time/all of the time" the corresponding percentages at ages 65 to 79 were 40% and 59%.
Article
Objective: To examine the relationship between sleep duration and consumption of sugar sweetened beverages (SSBs) and energy drinks (EDs) among adolescents. Methods: Data on 9,473 adolescents aged 11-20 years were obtained from the 2015 cycle of the Ontario Student Drug Use and Health Survey, a province-wide and cross-sectional school based survey of students in middle and high school. Respondents self-reported their sleep duration and consumption of SSBs and EDs. Those who did not meet the age-appropriate sleep duration recommendation were considered short sleepers. Results: Overall, 81.4% and 12.0% of respondents reported that they had at least one SSBs and EDs in the past week, respectively. Males were more likely than females to consume SSBs and EDs. High school students were more likely than those in middle school to report drinking EDs. After adjusting for multiple covariates, results from logistic regression analyses indicated that short sleep duration was associated with greater odds of SSB consumption in middle school students (odd ratio (OR) = 1.64, 95% confidence interval (CI) = 1.18-2.11), but not those in high school (OR = 1.06, 95% CI = 0.86-1.31). Short sleep duration was associated with greater odds of ED consumption in both middle (OR = 1.60, 95% CI = 1.10-2.34) and high school (OR = 1.78, 95% CI = 1.38-2.30) students. Conclusion: Short sleep duration was associated with consumption of EDs in middle and high school students and with SSBs in middle school students only. Future studies are needed to establish causality and to determine whether improving sleep patterns can reduce the consumption of SSBs and EDs among adolescents.