In the last few articles in this series, you’ve learned why sleep matters, you understand what happens during those precious hours of unconsciousness, how your sleep-wake cycle is regulated, and roughly how much sleep you actually need. Now comes the practical bit: what do you actually do with all that knowledge?
This is where sleep hygiene enters the picture, and where many people either get overwhelmed by endless optimisation tactics or are dismissive of advice that seems too simple to matter. Neither response serves you particularly well, because the truth sits somewhere in between these extremes. Sleep hygiene isn’t about biohacking your way to superhuman performance or obsessing over the perfect sleep environment, but it’s also not something you can dismiss as common sense that doesn’t require any real attention or effort.
Think of sleep hygiene as you would personal hygiene. Brushing your teeth isn’t a hack, and it’s certainly not exciting. You don’t post about it on social media, and you’d be hard-pressed to find anyone who feels passionate about their dental routine. But it’s a non-negotiable foundation that prevents problems and supports long-term health, which is precisely why you do it twice daily without much thought. The same principle applies here. Sleep hygiene is the collection of behavioural and environmental practices that encourage good sleep, and whilst these aren’t magic bullets or quick fixes, they’re the reliable, unsexy fundamentals that compound over time.
This is also the level you have direct control over, which matters more than you might initially think. Yes, there are medical and psychological interventions for sleep disorders that require professional help, but even sleep specialists will typically start with basic sleep hygiene as a first-line intervention. Before you consider medication or complex treatments, you need to know whether you’ve actually given your body the conditions it needs to sleep well. That’s what this series is about: establishing the highest-yield habits that form the bedrock of good sleep, so you can determine what’s genuinely working against you versus what’s simply a matter of not having the basics in place.
Could you potentially do millions of things to improve your sleep? Absolutely. Should you try to implement them all? Absolutely not, because you’d drive yourself mad in the process and likely make your sleep worse through sheer anxiety about whether you’re doing everything perfectly. What actually matters is understanding the principles through which these habits work, so you can make intelligent choices about which ones apply to your life, your biology, and your circumstances. We’re after the 80/20 here: the foundational practices that deliver the overwhelming majority of results without requiring you to turn sleep optimisation into a second job.
Table of Contents
Why Tracking Comes First
When you’re trying to improve your sleep, the temptation is to jump straight into solutions. You’ll buy blackout curtains, start taking magnesium, download a meditation app, and set your bedroom to exactly 18 degrees. But the problem with this approach is that you’re firing solutions at a target you haven’t properly identified. You’re guessing at what needs fixing without actually knowing what’s broken, which means you might spend considerable time, money, and energy on interventions that don’t address your actual issues.
This is why tracking your sleep is essential, and why it’s the logical first step in this series rather than something we get to later. Tracking isn’t glamorous, and it won’t feel like you’re actively improving anything in the moment. But it gives you something invaluable: evidence. Not vague impressions or hopeful assumptions, but actual evidence of what you need to work on, what’s already working well, and what changes are making a genuine difference versus which ones are just placebos you’ve convinced yourself are helping.
Consider what happens without tracking, because most people have lived this reality. You sleep poorly one night and immediately attribute it to that glass of wine you had with dinner, so you cut out alcohol entirely. But you haven’t accounted for the fact that you also had a particularly stressful day, ate dinner two hours later than usual, and scrolled your phone in bed for forty minutes before attempting sleep. Which factor actually disrupted your rest? You’ve no idea, so you’re left with superstition rather than understanding, making changes based on correlation you’ve imagined rather than patterns you’ve actually observed.
Or perhaps you feel exhausted by Thursday every week, but you haven’t connected it to the pattern of getting six hours of sleep Monday through Wednesday, then trying to “catch up” with ten hours on Friday and Saturday. Without tracking, you might assume you’re just tired because work is demanding or you’re getting older, missing the obvious solution sitting right in front of you: you simply need to protect more sleep time during the week. It’s not complicated, but it’s invisible without data.
Tracking transforms these vague impressions into concrete patterns that you can actually work with. It moves you from “I don’t sleep well” to “I take forty-five minutes to fall asleep on nights when I exercise after 7pm” or “I wake up three times per night when I eat dinner after 9pm” or “I feel significantly more rested on mornings following nights when I kept my bedroom window open, even though my sleep duration was the same.” This is actionable intelligence you can actually use to make informed decisions rather than just trying random interventions and hoping something sticks.
But tracking does something else, something perhaps more important; it makes you an active agent in your own sleep rather than a passive victim of it. When you’re not tracking, poor sleep just happens to you. It feels like something inflicted by circumstance, genetics, stress, bad luck, or whatever other forces beyond your control that you simply have to endure. But when you track your sleep, you’re gathering evidence about how your choices affect your outcomes. You’re investigating the relationship between what you do during your waking hours and how you rest during your sleeping ones. You’re taking responsibility for understanding yourself better, which is the first step toward changing anything.
This matters because sleep isn’t separate from the rest of your life, much as we might sometimes wish it were. The quality of your sleep determines the quality of your waking hours, which in turn determines your capacity to engage with what matters to you (i.e. to show up for the people you care about, to do work that means something, to have the energy and clarity needed to live according to your values rather than just survive from one day to the next). Sleep is foundational to human flourishing, which means that tracking is how you discover what actually supports or undermines that foundation for you specifically, not just for people in general or for the average person in a study.
What Actually Matters: The Metrics Worth Tracking
Not all sleep data is created equal, which is important to understand before you start tracking anything. If you’re going to invest time and energy in this practice, you need to know what’s actually worth paying attention to versus what’s just noise that will clutter your understanding without adding value. The goal isn’t to collect as much data as possible, because more data doesn’t necessarily mean better insights. What you’re after is the minimum viable information that allows you to identify patterns and make informed changes.
Bedtime and wake time are your anchoring points, and these are non-negotiable to track because they reveal your consistency, which is perhaps the single most important factor in good sleep. Your body thrives on regularity in a way that’s hard to overstate. When you go to bed at 10pm on Monday, midnight on Tuesday, 9pm on Wednesday, and 2am on Thursday, you’re essentially giving yourself jet lag without leaving your time zone. Your circadian rhythm doesn’t know what to expect, your sleep pressure doesn’t build predictably, and your body never quite settles into a rhythm. Tracking bedtime and wake time makes this pattern visible, and visibility is always the first step toward change.
Sleep latency (the time it takes you to fall asleep once you’re in bed) tells you whether you’re going to bed at the right time, which isn’t as straightforward as it might seem. If you’re consistently lying awake for forty-five minutes before sleep finally arrives, you’re probably going to bed before your body is actually ready, which means you’re just lying there getting frustrated and building negative associations with your bed. If you fall asleep within five minutes of your head hitting the pillow, you might be so sleep-deprived that you’re essentially crashing rather than sleeping in a healthy way. Somewhere between ten and twenty minutes is typically optimal, suggesting you’re tired enough to sleep but not desperately exhausted.
Night wakings matter, both in terms of how many times you wake and how long you’re awake when it happens. Everyone wakes briefly during the night as part of normal sleep architecture, but you just don’t usually remember these micro-awakenings because you fall back asleep within seconds. But if you’re waking fully three or four times and struggling to get back to sleep for twenty minutes or more, that’s worth investigating. These patterns can point to environmental issues like temperature, noise, or light; physiological factors like sleep apnoea or needing to urinate; psychological factors like anxiety or rumination; or lifestyle habits like alcohol consumption, late meals, or too much caffeine earlier in the day.
Total sleep time is straightforward enough: how many hours you actually slept, which is different from how long you were in bed. This difference between time asleep and time in bed gives you your sleep efficiency, which is the percentage that indicates how much of your time in bed was actually spent sleeping rather than lying there awake. If you’re in bed for eight hours but only sleeping six, your sleep efficiency is 75%, which suggests something’s preventing you from either falling asleep or staying asleep. Healthy sleep efficiency is generally above 85%, though this can vary somewhat between individuals. Poor sleep efficiency suggests either difficulty falling asleep, difficulty staying asleep, or going to bed before you’re actually tired; all of which are problems worth addressing but require different solutions.
Beyond these objective metrics, don’t underestimate the value of subjective assessment, because ultimately, what you care about isn’t achieving perfect numbers but feeling good enough to live well. How rested did you feel upon waking? Rate it on a simple scale of 1-10, nothing complicated. How was your energy throughout the day? Did you feel clear-headed and capable, or foggy and depleted by mid-afternoon? These subjective ratings often matter more than the objective data, because they reflect what actually affects your life. You’re not trying to win a sleep competition (don’t get caught up in the numbers!). You’re trying to feel rested enough to engage fully with your days.
Then there are the contextual factors that help you identify correlations, and these are where tracking becomes genuinely useful for experimentation. When did you exercise, and what type? How much caffeine did you consume, and when was your last cup? Did you drink alcohol, and if so, how much and how close to bedtime? What time did you eat dinner? What were you doing in the hour before bed? Were you watching television, reading, scrolling your phone, or having intense conversations? How stressed were you feeling? These aren’t sleep metrics per se, but they’re the variables you’re testing to see what actually affects your sleep and what doesn’t matter as much as you thought it might.
You don’t need to track all of this with scientific precision, because you’re not publishing a research paper. The goal is pattern recognition, not rigorous data collection that would satisfy peer review. You’re looking for trends over time, not obsessing over individual nights. You’re gathering enough information to experiment intelligently and make informed decisions, not enough to drive yourself mad with data points and correlations.
How to Track: Tools and Methods
The simplest method requires nothing but a notebook and a pen, which is both reassuring and slightly disappointing if you were hoping for a more high-tech solution. Each morning, you write down when you went to bed, when you woke up, roughly how long it took to fall asleep, how many times you remember waking during the night, and how rested you feel on that 1-10 scale. In the evening, you note anything potentially relevant: whether you exercised, how much caffeine you had and when, any alcohol, your general stress levels, and what you did in the hour before bed. This takes perhaps two minutes total per day, costs nothing, and gives you perfectly adequate information to work with.
You can make this slightly more systematic with a basic sleep diary template or a spreadsheet if you prefer that format. The advantage here is that patterns become easier to spot when you can see a week or month at a glance rather than flipping through journal pages. You can calculate averages, notice trends across time, and identify correlations more readily. It’s still a minimal time investment and costs nothing beyond whatever you’re already using for digital organisation.
Then there are wearable devices: fitness trackers, smartwatches, and sleep-specific rings that promise to measure your sleep with impressive precision. These devices track movement, heart rate, heart rate variability, and sometimes blood oxygen levels to estimate when you’re asleep, when you’re awake, and what sleep stage you’re in at any given moment. They’ll give you graphs and scores and detailed breakdowns of your sleep architecture that look remarkably scientific and authoritative.
However, what you need to understand about these devices, is that they’re estimating, not measuring. True sleep measurement requires polysomnography in a sleep lab, with electrodes attached to your scalp monitoring brain activity, sensors near your eyes tracking eye movements, and bands around your chest measuring breathing and muscle tone. That’s what actually tells you with certainty when you’re asleep and what stage you’re in. Wearables are making educated guesses based on indirect indicators (primarily movement and heart rate patterns), which means they’re approximations rather than precise measurements.
They’re reasonably good at estimating total sleep time and distinguishing sleep from wake, because those show fairly clear patterns in movement and heart rate. They’re considerably less accurate at identifying specific sleep stages, particularly when it comes to distinguishing light sleep from REM sleep, which can look similar from a movement and heart rate perspective. Validation studies comparing wearables to polysomnography show significant variability in accuracy across different devices and different individuals, with some people’s data being quite reliable and others’ being rather questionable.
Does this mean wearables are useless? Not at all, but it does mean you should understand what you’re actually getting for your money. You’re not getting clinical-grade sleep data that would satisfy a sleep specialist. You’re getting a reasonable approximation that’s consistent enough to identify trends in your sleep patterns over time, which is actually what matters for your purposes. If your device consistently shows more deep sleep on nights when you exercise in the morning versus evenings, that’s useful information even if the absolute numbers are slightly off. What you care about is relative comparison within your own data, not absolute accuracy that would hold up in a research setting.
The practical benefits of wearables are convenience and comprehensiveness, which shouldn’t be dismissed just because the technology isn’t perfect. You don’t have to remember to log anything when you wake up groggy and would rather just get on with your morning. You don’t have to estimate sleep latency or try to recall how many times you woke during the night. You just wear the device, sync it in the morning, and the data is there. For many people, this consistency alone makes wearables worth the investment, because manual tracking requires discipline that tends to fade after a few weeks when the initial enthusiasm wears off. Automated tracking continues indefinitely without requiring willpower or creating another task you can fail at.
The cost-benefit calculation depends entirely on your circumstances and what you value. A basic fitness tracker that includes sleep tracking might cost €50-100, whilst a dedicated sleep ring might be €200-300 or more. If that expenditure would cause financial stress or require careful consideration within your budget, stick with manual tracking. It works perfectly well and costs nothing. If you can comfortably afford it and you value the convenience and additional data, it might be worthwhile. But don’t convince yourself that you need an expensive device to improve your sleep, because you absolutely don’t. The fundamentals of sleep hygiene work regardless of how you track them or whether you track them at all.
When Tracking Becomes the Problem
However, we do have to also realise that tracking your sleep can be a problem. There’s a phenomenon that sleep researchers have identified called orthosomnia, which is an unhealthy obsession with achieving perfect sleep data that actually undermines the very sleep you’re trying to optimise. People lie in bed anxious about whether they’ll get enough deep sleep tonight, which creates arousal that prevents them from falling asleep easily. They wake up and immediately check their sleep score before they’ve even noticed how they actually feel, and that number determines their mood for the entire morning. They feel genuinely distressed if their device says they slept poorly, even if they subjectively feel fine and energised. They start making increasingly extreme changes to their sleep environment and routine to eke out another percentage point of sleep efficiency or another five minutes of REM sleep, sacrificing enjoyment and flexibility for marginal gains that may not even be real.
This is tracking gone comprehensively wrong, and it’s worth discussing explicitly because it’s surprisingly common among people who get invested in optimising their health. The point of tracking your sleep is to gather useful information that helps you feel better and function better in your daily life. If the tracking itself is making you anxious, if you’re more focused on the numbers than on how you actually feel, if you’re letting a device tell you whether you’re rested despite your own experience suggesting otherwise, then you’ve lost the plot. The tail is wagging the dog.
Sleep tracking devices are proxies, nothing more. They’re approximations of things we actually care about: feeling rested, having energy throughout the day, thinking clearly, being emotionally stable, and having the capacity to engage fully with our lives and the people in them. The map is not the territory. The sleep score is not the sleep. If you feel energised and capable despite your device telling you that you slept poorly and only got 23% deep sleep when you should have gotten 30%, trust your experience over the data. You are the ultimate arbiter of whether you slept well, not an algorithm that’s making educated guesses based on your heart rate and movement patterns.
This is particularly important because these devices aren’t perfect, as we’ve already discussed, and they can be wrong in ways that create unnecessary anxiety. Perhaps your device underestimates your sleep because you were reading in bed for twenty minutes before turning off the light, and it counted that time as restless sleep rather than wake. Perhaps it misjudges restful wakefulness (lying peacefully in bed after waking but before getting up) as poor-quality sleep. Perhaps its algorithm simply doesn’t calibrate well to your particular physiology, or perhaps you have a movement pattern during certain sleep stages that confuses the sensors. You don’t need to achieve perfect sleep scores to live well, and you certainly don’t need to let imperfect measurements create anxiety where none is warranted.
Ultimately, you want to track consistently enough to identify obvious patterns and correlations, but loosely enough to avoid obsession and maintain perspective. You’re after big-picture trends over weeks and months, not nightly perfection. You want to know whether your average sleep duration is adequate, whether your bedtime consistency needs work, or whether certain habits consistently correlate with better or worse sleep. You don’t need to know your exact percentage of REM sleep or achieve a “perfect” sleep efficiency score or optimise every variable down to the minute.
If you find yourself getting excessively caught up in the data (for example, if you’re checking your sleep score multiple times a day, if you’re making life decisions based on marginal differences in your numbers, or if you’re feeling anxious or guilty about your sleep metrics) take a break from tracking. Spend a few weeks just focusing on the basic sleep hygiene habits we’ll cover in this series without measuring anything at all. Notice how you feel without the numbers looming over you. Often, people discover they actually sleep better when they’re not anxious about their sleep data, which is a rather telling indication that the tracking was supposed to serve you, not the other way around.
Making Sense of What You’re Seeing
Once you’ve tracked your sleep for a week or two, you’ll have enough data to start identifying patterns, and this is where tracking becomes actually useful rather than just an exercise in data collection. You’re moving from scattered impressions to reliable insights about what helps and what hinders your sleep, which means you can finally make informed decisions rather than just trying things at random.
Look for trends, not individual nights, because trends matter more than people typically realise. One night of poor sleep means absolutely nothing in the grand scheme of things. Everyone has bad nights. Your sleep is disrupted by noise, stress, eating something that didn’t agree with you, staying up late for an event that mattered to you, etc. These things happen, and they’re not problems to solve. But if you’re consistently struggling to fall asleep on Wednesdays, or you wake up unrefreshed every Monday despite adequate sleep duration, or your sleep quality tanks every weekend even though you’re getting more hours in bed, those patterns warrant further investigation. What’s different about those nights or days? What variables are correlating with poor sleep that you might not have noticed without the data?
You’re looking for correlations that need further exploring, while understanding that correlation isn’t necessarily causation, and you’ll need to test these relationships through experimentation. Perhaps you notice that you sleep significantly better on nights when you’ve exercised at some point during the day, regardless of when. That’s worth leaning into. This exercise may not cause better sleep for everyone, but it apparently does for you. So, use that information to your advantage. Perhaps you see that your sleep quality drops noticeably on nights when you drink alcohol, even if it’s just a glass or two with dinner. That’s useful information you can factor into your decisions about whether a drink is worth the trade-off. Perhaps you discover that leaving your bedroom window open correlates with feeling more rested in the morning, even though your total sleep time is the same. Maybe temperature or air quality or the subtle sounds from outside matter more for you than you realised.
Sometimes the patterns reveal problems you can immediately address without any complex interventions. You might notice you’re getting six hours of sleep on weekdays because you’re staying up until midnight, but need to wake at 6am, then sleeping ten hours on Friday and Saturday nights in an attempt to catch up on your sleep debt, then eight hours on Sunday as you transition back toward the week. You feel exhausted by Thursday every single week, irritable with your family, and struggling to concentrate at work. The solution is obvious once you see the pattern: you need to protect more sleep time during the week. This isn’t a mystery requiring expensive supplements or medical intervention. It’s a scheduling problem with a straightforward solution, even if implementing that solution requires making hard choices about what you’re currently doing with your evening hours.
Other times, tracking reveals that the thing you thought was the culprit isn’t actually correlated with poor sleep at all, which can be just as valuable as finding what does matter. Perhaps you’ve been avoiding caffeine after noon for months, assuming it’s ruining your sleep based on something you read online, but your data shows no meaningful relationship between afternoon coffee and sleep quality or latency. That’s liberating information. You can have that 2pm coffee without guilt and without lying awake at night wondering if you’ve sabotaged yourself. Save your energy and willpower for changes that actually matter for your particular biology and circumstances.
You want to use your tracking data to experiment intelligently, which means changing one variable at a time and observing what happens. Try one change, maintain it for at least a week to let your body adjust and to see the pattern rather than the noise, and see what happens to your sleep. If you simultaneously stop drinking coffee after 2pm, start exercising in the morning instead of evening, change your dinner timing, and begin a new bedtime routine, you’ll never know which intervention actually helped. Ultimately, you’re not trying to follow a generic protocol you found in an article or heard from a friend. You need to discover what works for your biology, your psychology, your life circumstances, your preferences and constraints.
However, there are some red flags that suggest you should seek professional help rather than just adjusting your sleep hygiene. For example, if you’re consistently taking more than thirty minutes to fall asleep despite implementing good sleep hygiene practices, that’s worth discussing with a doctor. If you’re waking up gasping or choking, or if you have very loud snoring with witnessed pauses in breathing, those are signs of potential sleep apnoea that requires medical evaluation. If you’re experiencing overwhelming daytime sleepiness despite getting what should be an adequate sleep duration, something’s interfering with your sleep quality in ways that warrant investigation. If you’re dealing with severe insomnia lasting more than a few weeks, that’s not something to troubleshoot on your own with better tracking and sleep hygiene. These aren’t problems you can solve with the interventions we’ll discuss in this series, they’re conditions that need professional assessment and treatment.
But for most people, most of the time, tracking simply reveals that small, consistent habits matter more than you realised and that your sleep responds to fairly straightforward adjustments when you actually make them. Your body responds to regularity in bedtimes and wake times. It responds to respecting its need for wind-down time before sleep rather than going straight from high stimulation to bed. It responds to creating an environment that’s conducive to rest rather than one that’s subtly preventing good sleep. It responds to managing the variables within your control: when you exercise, when you consume stimulants, how you spend your evening hours, and whether you’ve created conditions that signal safety and relaxation rather than alertness and engagement.
Tracking Your Sleep: Foundational Sleep Hygiene
It would be easy to see sleep tracking as mere data collection, a preliminary step before the “real work” of improving your sleep begins with actual interventions and changes. But tracking is itself an act of taking responsibility for understanding yourself, which matters more than the specific numbers you’re recording. By tracking, you’re refusing to be a passive recipient of good or bad sleep, someone to whom sleep simply happens based on factors beyond your control or understanding. You’re investigating how your choices affect your capacity to rest, recover, and show up for your life, which is fundamentally an exercise in agency.
This matters because sleep is foundational to everything else you care about, even if you don’t always think about it in these terms. When you sleep well, you think more clearly and make better decisions. You regulate your emotions more effectively and respond to stress with more resilience. You have the energy to be genuinely present with the people who matter to you rather than just going through the motions whilst feeling depleted. You can engage with your work, your relationships, and your pursuits with the vitality and capacity they deserve rather than operating at half-mast. When you sleep poorly (especially when you sleep poorly chronically rather than just for a night or two), everything becomes harder. You’re operating at diminished capacity, which means you’re less able to live according to your values, less able to be who you want to be, and less able to do what matters to you.
Tracking your sleep is tracking a foundational core that is required for human flourishing. You’re gathering evidence about what supports or undermines your ability to live well, and whilst that might sound grandiose for something as simple as writing down when you went to bed, it’s genuinely what’s at stake. The goals here isn’t about achieving perfect sleep scores or optimising every metric for its own sake. It’s about building self-knowledge and taking agency over something that profoundly affects your quality of life and your capacity to engage with what matters.
You’re not trying to control sleep through force of will, because that’s not how sleep works. You can’t decide to sleep well any more than you can decide to digest your food faster or lower your blood pressure through conscious effort. Sleep is something that happens to you when you’ve created the right conditions for it, when you’ve removed the obstacles and provided the support your biology needs. But you can control those conditions, at least to a significant extent. You can experiment with different approaches and observe what actually works for you. You can make informed choices based on evidence rather than hopeful guesses or assumptions. You can stop surrendering to the belief that poor sleep is just your lot in life, something you have to endure because of your genetics or your age or your life circumstances.
This is the first step in reclaiming that agency: knowing where you actually stand, what’s actually happening with your sleep rather than what you assume is happening, and what variables seem to matter most for your particular situation. Once you have that foundation of understanding, you can build on it with the other sleep hygiene habits we’ll explore in this series (habits around light exposure, temperature, caffeine, alcohol, exercise timing, evening routines, and all the other factors that influence sleep). But without this foundation, you’re building on sand, hoping that generic advice will happen to apply to your specific situation without any way of knowing whether it’s actually helping.
The information you gather from tracking doesn’t just tell you what to fix, though that’s certainly valuable. It also tells you what’s already working well, which matters just as much because it helps you avoid wasting time and energy on areas that don’t need your attention. Perhaps you’re already excellent at maintaining consistent bedtimes within a fifteen-minute window, which means you don’t need to focus energy there. Perhaps your sleep environment is already optimised in ways that matter, so you can stop worrying about whether you need blackout curtains, weighted blankets or white noise machines. Tracking reveals where your leverage points actually are, so you can invest your limited time and energy wisely rather than trying to improve everything at once.
So start simple, because simple is usually sustainable and sustainable is what actually works. Pick your tracking method (pen and paper, spreadsheet, or wearable device, whatever actually fits your life and preferences) and commit to gathering data for at least two weeks. Write down the basics: when you went to bed, when you woke up, how you felt. Note the variables you suspect might matter: exercise, caffeine, alcohol, stress, evening activities, anything that seems potentially relevant to your sleep. Look for patterns, not perfection. Be curious about what you discover, not judgmental about what the data reveals or harsh with yourself about nights that didn’t go well.
You’re not trying to win at sleep tracking or achieve some perfect score that proves you’ve mastered this domain of your life. You’re trying to understand yourself better so you can make choices that support the life you want to live, the person you want to be, the capacity you need to engage fully with what matters. That’s what this entire series is about: not optimising metrics for their own sake, but building the foundation of physical and mental capacity that allows you to flourish rather than just function. Sleep is how you restore that capacity each night, giving your body and brain the recovery they need to meet another day. Tracking is how you learn to protect and improve that restoration process. Everything else we’ll discuss in this series builds from here.
As with everything, there is always more to learn, and we haven’t even begun to scratch the surface with all this stuff. However, if you are interested in staying up to date with all our content, we recommend subscribing to our newsletter and bookmarking our free content page. We do have a lot of content on sleep in our sleep hub.
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Finally, if you want to learn how to coach nutrition, then consider our Nutrition Coach Certification course. We do also have an exercise program design course, if you are a coach who wants to learn more about effective program design and how to coach it. We do have other courses available too, notably as a sleep course. If you don’t understand something, or you just need clarification, you can always reach out to us on Instagram or via email.
References and Further Reading
Vyazovskiy, V. (2015). Sleep, recovery, and metaregulation: explaining the benefits of sleep. Nature and Science of Sleep, 171. http://doi.org/10.2147/nss.s54036
Sharma, S., & Kavuru, M. (2010). Sleep and Metabolism: An Overview. International Journal of Endocrinology, 2010, 1–12. http://doi.org/10.1155/2010/270832
Yoo, S.-S., Gujar, N., Hu, P., Jolesz, F. A., & Walker, M. P. (2007). The human emotional brain without sleep — a prefrontal amygdala disconnect. Current Biology, 17(20). http://doi.org/10.1016/j.cub.2007.08.007
Copinschi G. Metabolic and endocrine effects of sleep deprivation. Essent Psychopharmacol. 2005;6(6):341-7. PMID: 16459757. https://pubmed.ncbi.nlm.nih.gov/16459757/
Spiegel, K., Leproult, R., L’Hermite-Balériaux, M., Copinschi, G., Penev, P. D., & Cauter, E. V. (2004). Leptin Levels Are Dependent on Sleep Duration: Relationships with Sympathovagal Balance, Carbohydrate Regulation, Cortisol, and Thyrotropin. The Journal of Clinical Endocrinology & Metabolism, 89(11), 5762–5771. http://doi.org/10.1210/jc.2004-1003
Nedeltcheva, A. V., Kilkus, J. M., Imperial, J., Kasza, K., Schoeller, D. A., & Penev, P. D. (2008). Sleep curtailment is accompanied by increased intake of calories from snacks. The American Journal of Clinical Nutrition, 89(1), 126–133. http://doi.org/10.3945/ajcn.2008.26574
Mullington, J. M., Chan, J. L., Dongen, H. P. A. V., Szuba, M. P., Samaras, J., Price, N. J., … Mantzoros, C. S. (2003). Sleep Loss Reduces Diurnal Rhythm Amplitude of Leptin in Healthy Men. Journal of Neuroendocrinology, 15(9), 851–854. http://doi.org/10.1046/j.1365-2826.2003.01069.x
Leproult, R., & Cauter, E. V. (2009). Role of Sleep and Sleep Loss in Hormonal Release and Metabolism. Pediatric Neuroendocrinology Endocrine Development, 11–21. http://doi.org/10.1159/000262524
Spaeth, A. M., Dinges, D. F., & Goel, N. (2013). Effects of Experimental Sleep Restriction on Weight Gain, Caloric Intake, and Meal Timing in Healthy Adults. Sleep, 36(7), 981–990. http://doi.org/10.5665/sleep.2792
Calvin, A. D., Carter, R. E., Adachi, T., Macedo, P. G., Albuquerque, F. N., Walt, C. V. D., … Somers, V. K. (2013). Effects of Experimental Sleep Restriction on Caloric Intake and Activity Energy Expenditure. Chest, 144(1), 79–86. http://doi.org/10.1378/chest.12-2829
Markwald, R. R., Melanson, E. L., Smith, M. R., Higgins, J., Perreault, L., Eckel, R. H., & Wright, K. P. (2013). Impact of insufficient sleep on total daily energy expenditure, food intake, and weight gain. Proceedings of the National Academy of Sciences, 110(14), 5695–5700. http://doi.org/10.1073/pnas.1216951110
Cauter, E. V., Spiegel, K., Tasali, E., & Leproult, R. (2008). Metabolic consequences of sleep and sleep loss. Sleep Medicine, 9. http://doi.org/10.1016/s1389-9457(08)70013-3
Spiegel, K., Leproult, R., & Cauter, E. V. (1999). Impact of sleep debt on metabolic and endocrine function. The Lancet, 354(9188), 1435–1439. http://doi.org/10.1016/s0140-6736(99)01376-8
Ness, K. M., Strayer, S. M., Nahmod, N. G., Schade, M. M., Chang, A.-M., Shearer, G. C., & Buxton, O. M. (2019). Four nights of sleep restriction suppress the postprandial lipemic response and decrease satiety. Journal of Lipid Research, 60(11), 1935–1945. http://doi.org/10.1194/jlr.p094375
Hirotsu, C., Tufik, S., & Andersen, M. L. (2015). Interactions between sleep, stress, and metabolism: From physiological to pathological conditions. Sleep Science, 8(3), 143–152. http://doi.org/10.1016/j.slsci.2015.09.002
Morselli, L., Leproult, R., Balbo, M., & Spiegel, K. (2010). Role of sleep duration in the regulation of glucose metabolism and appetite. Best Practice & Research Clinical Endocrinology & Metabolism, 24(5), 687–702. http://doi.org/10.1016/j.beem.2010.07.005
Lamon, S., Morabito, A., Arentson-Lantz, E., Knowles, O., Vincent, G. E., Condo, D., … Aisbett, B. (2020). The effect of acute sleep deprivation on skeletal muscle protein synthesis and the hormonal environment. http://doi.org/10.1101/2020.03.09.984666
Lipton, J. O., & Sahin, M. (2014). The Neurology of mTOR. Neuron, 84(2), 275–291. http://doi.org/10.1016/j.neuron.2014.09.034
Tudor, J. C., Davis, E. J., Peixoto, L., Wimmer, M. E., Tilborg, E. V., Park, A. J., … Abel, T. (2016). Sleep deprivation impairs memory by attenuating mTORC1-dependent protein synthesis. Science Signaling, 9(425). http://doi.org/10.1126/scisignal.aad4949
Dattilo, M., Antunes, H., Medeiros, A., Neto, M. M., Souza, H., Tufik, S., & Mello, M. D. (2011). Sleep and muscle recovery: Endocrinological and molecular basis for a new and promising hypothesis. Medical Hypotheses, 77(2), 220–222. http://doi.org/10.1016/j.mehy.2011.04.017
Thornton, S. N., & Trabalon, M. (2014). Chronic dehydration is associated with obstructive sleep apnoea syndrome. Clinical Science, 128(3), 225–225. http://doi.org/10.1042/cs20140496
Rosinger, A. Y., Chang, A.-M., Buxton, O. M., Li, J., Wu, S., & Gao, X. (2018). Short sleep duration is associated with inadequate hydration: cross-cultural evidence from US and Chinese adults. Sleep, 42(2). http://doi.org/10.1093/sleep/zsy210
Watson, A. M. (2017). Sleep and Athletic Performance. Current Sports Medicine Reports, 16(6), 413–418. http://doi.org/10.1249/jsr.0000000000000418
Bonnar, D., Bartel, K., Kakoschke, N., & Lang, C. (2018). Sleep Interventions Designed to Improve Athletic Performance and Recovery: A Systematic Review of Current Approaches. Sports Medicine, 48(3), 683–703. http://doi.org/10.1007/s40279-017-0832-x
Saidi, O., Davenne, D., Lehorgne, C., & Duché, P. (2020). Effects of timing of moderate exercise in the evening on sleep and subsequent dietary intake in lean, young, healthy adults: randomized crossover study. European Journal of Applied Physiology, 120(7), 1551–1562. http://doi.org/10.1007/s00421-020-04386-6
Abedelmalek, S., Chtourou, H., Aloui, A., Aouichaoui, C., Souissi, N., & Tabka, Z. (2012). Effect of time of day and partial sleep deprivation on plasma concentrations of IL-6 during a short-term maximal performance. European Journal of Applied Physiology, 113(1), 241–248. http://doi.org/10.1007/s00421-012-2432-7
Azboy, O., & Kaygisiz, Z. (2009). Effects of sleep deprivation on cardiorespiratory functions of the runners and volleyball players during rest and exercise. Acta Physiologica Hungarica, 96(1), 29–36. http://doi.org/10.1556/aphysiol.96.2009.1.3
Bird, S. P. (2013). Sleep, Recovery, and Athletic Performance. Strength and Conditioning Journal, 35(5), 43–47. http://doi.org/10.1519/ssc.0b013e3182a62e2f
Blumert, P. A., Crum, A. J., Ernsting, M., Volek, J. S., Hollander, D. B., Haff, E. E., & Haff, G. G. (2007). The Acute Effects of Twenty-Four Hours of Sleep Loss on the Performance of National-Caliber Male Collegiate Weightlifters. The Journal of Strength and Conditioning Research, 21(4), 1146. http://doi.org/10.1519/r-21606.1
Chase, J. D., Roberson, P. A., Saunders, M. J., Hargens, T. A., Womack, C. J., & Luden, N. D. (2017). One night of sleep restriction following heavy exercise impairs 3-km cycling time-trial performance in the morning. Applied Physiology, Nutrition, and Metabolism, 42(9), 909–915. http://doi.org/10.1139/apnm-2016-0698
Edwards, B. J., & Waterhouse, J. (2009). Effects of One Night of Partial Sleep Deprivation upon Diurnal Rhythms of Accuracy and Consistency in Throwing Darts. Chronobiology International, 26(4), 756–768. http://doi.org/10.1080/07420520902929037
Fullagar, H. H. K., Skorski, S., Duffield, R., Hammes, D., Coutts, A. J., & Meyer, T. (2014). Sleep and Athletic Performance: The Effects of Sleep Loss on Exercise Performance, and Physiological and Cognitive Responses to Exercise. Sports Medicine, 45(2), 161–186. http://doi.org/10.1007/s40279-014-0260-0
Gupta, L., Morgan, K., & Gilchrist, S. (2016). Does Elite Sport Degrade Sleep Quality? A Systematic Review. Sports Medicine, 47(7), 1317–1333. http://doi.org/10.1007/s40279-016-0650-6
Hausswirth, C., Louis, J., Aubry, A., Bonnet, G., Duffield, R., & Meur, Y. L. (2014). Evidence of Disturbed Sleep and Increased Illness in Overreached Endurance Athletes. Medicine & Science in Sports & Exercise, 46(5), 1036–1045. http://doi.org/10.1249/mss.0000000000000177
Mah, C. D., Mah, K. E., Kezirian, E. J., & Dement, W. C. (2011). The Effects of Sleep Extension on the Athletic Performance of Collegiate Basketball Players. Sleep, 34(7), 943–950. http://doi.org/10.5665/sleep.1132
Milewski, M. D., Skaggs, D. L., Bishop, G. A., Pace, J. L., Ibrahim, D. A., Wren, T. A., & Barzdukas, A. (2014). Chronic Lack of Sleep is Associated With Increased Sports Injuries in Adolescent Athletes. Journal of Pediatric Orthopaedics, 34(2), 129–133. http://doi.org/10.1097/bpo.0000000000000151
Mougin, F., Bourdin, H., Simon-Rigaud, M., Didier, J., Toubin, G., & Kantelip, J. (1996). Effects of a Selective Sleep Deprivation on Subsequent Anaerobic Performance. International Journal of Sports Medicine, 17(02), 115–119. http://doi.org/10.1055/s-2007-972818
Oliver, S. J., Costa, R. J. S., Laing, S. J., Bilzon, J. L. J., & Walsh, N. P. (2009). One night of sleep deprivation decreases treadmill endurance performance. European Journal of Applied Physiology, 107(2), 155–161. http://doi.org/10.1007/s00421-009-1103-9
Pallesen, S., Gundersen, H. S., Kristoffersen, M., Bjorvatn, B., Thun, E., & Harris, A. (2017). The Effects of Sleep Deprivation on Soccer Skills. Perceptual and Motor Skills, 124(4), 812–829. http://doi.org/10.1177/0031512517707412
Reilly, T., & Piercy, M. (1994). The effect of partial sleep deprivation on weight-lifting performance. Ergonomics, 37(1), 107–115. http://doi.org/10.1080/00140139408963628
Rossa, K. R., Smith, S. S., Allan, A. C., & Sullivan, K. A. (2014). The Effects of Sleep Restriction on Executive Inhibitory Control and Affect in Young Adults. Journal of Adolescent Health, 55(2), 287–292. http://doi.org/10.1016/j.jadohealth.2013.12.034
Sargent, C., & Roach, G. D. (2016). Sleep duration is reduced in elite athletes following night-time competition. Chronobiology International, 33(6), 667–670. http://doi.org/10.3109/07420528.2016.1167715
Skein, M., Duffield, R., Edge, J., Short, M. J., & Mündel, T. (2011). Intermittent-Sprint Performance and Muscle Glycogen after 30 h of Sleep Deprivation. Medicine & Science in Sports & Exercise, 43(7), 1301–1311. http://doi.org/10.1249/mss.0b013e31820abc5a
Souissi, N., Sesboüé, B., Gauthier, A., Larue, J., & Davenne, D. (2003). Effects of one nights sleep deprivation on anaerobic performance the following day. European Journal of Applied Physiology, 89(3), 359–366. http://doi.org/10.1007/s00421-003-0793-7
Caia, J., Kelly, V. G., & Halson, S. L. (2017). The role of sleep in maximising performance in elite athletes. Sport, Recovery, and Performance, 151–167. http://doi.org/10.4324/9781315268149-11
Alley, J. R., Mazzochi, J. W., Smith, C. J., Morris, D. M., & Collier, S. R. (2015). Effects of Resistance Exercise Timing on Sleep Architecture and Nocturnal Blood Pressure. Journal of Strength and Conditioning Research, 29(5), 1378–1385. http://doi.org/10.1519/jsc.0000000000000750
Kovacevic, A., Mavros, Y., Heisz, J. J., & Singh, M. A. F. (2018). The effect of resistance exercise on sleep: A systematic review of randomized controlled trials. Sleep Medicine Reviews, 39, 52–68. http://doi.org/10.1016/j.smrv.2017.07.002
Herrick, J. E., Puri, S., & Richards, K. C. (2017). Resistance training does not alter same-day sleep architecture in institutionalized older adults. Journal of Sleep Research, 27(4). http://doi.org/10.1111/jsr.12590
Edinger, J. D., Morey, M. C., Sullivan, R. J., Higginbotham, M. B., Marsh, G. R., Dailey, D. S., & McCall, W. V. (1993). Aerobic fitness, acute exercise and sleep in older men. Sleep, 16(4), 351-359. https://doi.org/10.1093/sleep/16.4.351
King, A. C. (1997). Moderate-intensity exercise and self-rated quality of sleep in older adults. A randomized controlled trial. JAMA: The Journal of the American Medical Association, 277(1), 32–37. http://doi.org/10.1001/jama.277.1.32
Passos, G. S., Poyares, D., Santana, M. G., Garbuio, S. A., Tufik, S., & Mello, M. T. (2010). Effect of Acute Physical Exercise on Patients with Chronic Primary Insomnia. Journal of Clinical Sleep Medicine, 06(03), 270–275. http://doi.org/10.5664/jcsm.27825
Reid, K. J., Baron, K. G., Lu, B., Naylor, E., Wolfe, L., & Zee, P. C. (2010). Aerobic exercise improves self-reported sleep and quality of life in older adults with insomnia. Sleep Medicine, 11(9), 934–940. http://doi.org/10.1016/j.sleep.2010.04.014
Viana, V. A. R., Esteves, A. M., Boscolo, R. A., Grassmann, V., Santana, M. G., Tufik, S., & Mello, M. T. D. (2011). The effects of a session of resistance training on sleep patterns in the elderly. European Journal of Applied Physiology, 112(7), 2403–2408. http://doi.org/10.1007/s00421-011-2219-2
Herring, M., Kline, C., & Oconnor, P. (2015). Effects of Exercise Training On Self-reported Sleep Among Young Women with Generalized Anxiety Disorder (GAD). European Psychiatry, 30, 465. http://doi.org/10.1016/s0924-9338(15)31893-9
Kredlow, M. A., Capozzoli, M. C., Hearon, B. A., Calkins, A. W., & Otto, M. W. (2015). The effects of physical activity on sleep: a meta-analytic review. Journal of Behavioral Medicine, 38(3), 427–449. http://doi.org/10.1007/s10865-015-9617-6
Yang, P.-Y., Ho, K.-H., Chen, H.-C., & Chien, M.-Y. (2012). Exercise training improves sleep quality in middle-aged and older adults with sleep problems: a systematic review. Journal of Physiotherapy, 58(3), 157–163. http://doi.org/10.1016/s1836-9553(12)70106-6
Kline, C. E., Sui, X., Hall, M. H., Youngstedt, S. D., Blair, S. N., Earnest, C. P., & Church, T. S. (2012). Dose–response effects of exercise training on the subjective sleep quality of postmenopausal women: exploratory analyses of a randomised controlled trial. BMJ Open, 2(4). http://doi.org/10.1136/bmjopen-2012-001044
Fairbrother, K., Cartner, B. W., Triplett, N., Morris, D. M., & Collier, S. R. (2011). The Effects of Aerobic Exercise Timing on Sleep Architecture. Medicine & Science in Sports & Exercise, 43(Suppl 1), 879. http://doi.org/10.1249/01.mss.0000402452.16375.20
Youngstedt, S. D., & Kline, C. E. (2006). Epidemiology of exercise and sleep. Sleep and Biological Rhythms, 4(3), 215–221. http://doi.org/10.1111/j.1479-8425.2006.00235.x
Stenholm, S., Head, J., Kivimäki, M., Hanson, L. L. M., Pentti, J., Rod, N. H., … Vahtera, J. (2018). Sleep Duration and Sleep Disturbances as Predictors of Healthy and Chronic Disease–Free Life Expectancy Between Ages 50 and 75: A Pooled Analysis of Three Cohorts. The Journals of Gerontology: Series A, 74(2), 204–210. http://doi.org/10.1093/gerona/gly01
Xiao, Q., Keadle, S. K., Hollenbeck, A. R., & Matthews, C. E. (2014). Sleep Duration and Total and Cause-Specific Mortality in a Large US Cohort: Interrelationships With Physical Activity, Sedentary Behavior, and Body Mass Index. American Journal of Epidemiology, 180(10), 997–1006. http://doi.org/10.1093/aje/kwu222
Reynolds, A. C., Dorrian, J., Liu, P. Y., Dongen, H. P. A. V., Wittert, G. A., Harmer, L. J., & Banks, S. (2012). Impact of Five Nights of Sleep Restriction on Glucose Metabolism, Leptin and Testosterone in Young Adult Men. PLoS ONE, 7(7). http://doi.org/10.1371/journal.pone.0041218
Åkerstedt, T., Palmblad, J., Torre, B. D. L., Marana, R., & Gillberg, M. (1980). Adrenocortical and Gonadal Steroids During Sleep Deprivation. Sleep, 3(1), 23–30. http://doi.org/10.1093/sleep/3.1.23
Cortés-Gallegos, V., Castañeda, G., Alonso, R., Sojo, I., Carranco, A., Cervantes, C., & Parra, A. (1983). Sleep Deprivation Reduces Circulating Androgens in Healthy Men. Archives of Andrology, 10(1), 33–37. http://doi.org/10.3109/01485018308990167
González-Santos, M. R., Gajá-Rodíguez, O. V., Alonso-Uriarte, R., Sojo-Aranda, I., & Cortés-Gallegos, V. (1989). Sleep Deprivation and Adaptive Hormonal Responses of Healthy Men. Archives of Andrology, 22(3), 203–207. http://doi.org/10.3109/01485018908986773
Penev, P. D. (2007). Association Between Sleep and Morning Testosterone Levels In Older Men. Sleep, 30(4), 427–432. http://doi.org/10.1093/sleep/30.4.427
Kloss, J. D., Perlis, M. L., Zamzow, J. A., Culnan, E. J., & Gracia, C. R. (2015). Sleep, sleep disturbance, and fertility in women. Sleep Medicine Reviews, 22, 78–87. http://doi.org/10.1016/j.smrv.2014.10.005
Mahoney, M. M. (2010). Shift Work, Jet Lag, and Female Reproduction. International Journal of Endocrinology, 2010, 1–9. http://doi.org/10.1155/2010/813764
Labyak, S., Lava, S., Turek, F., & Zee, P. (2002). Effects Of Shiftwork On Sleep And Menstrual Function In Nurses. Health Care for Women International, 23(6-7), 703–714. http://doi.org/10.1080/07399330290107449
Pal, L., Bevilacqua, K., Zeitlian, G., Shu, J., & Santoro, N. (2008). Implications of diminished ovarian reserve (DOR) extend well beyond reproductive concerns. Menopause, 15(6), 1086–1094. http://doi.org/10.1097/gme.0b013e3181728467
Axelsson, G., Rylander, R., & Molin, I. (1989). Outcome of pregnancy in relation to irregular and inconvenient work schedules. Occupational and Environmental Medicine, 46(6), 393–398. http://doi.org/10.1136/oem.46.6.393
Bisanti, L., Olsen, J., Basso, O., Thonneau, P., & Karmaus, W. (1996). Shift Work and Subfecundity: A European Multicenter Study. Journal of Occupational & Environmental Medicine, 38(4), 352–358. http://doi.org/10.1097/00043764-199604000-00012
Rossmanith, W. G. (1998). The impact of sleep on gonadotropin secretion. Gynecological Endocrinology, 12(6), 381–389. http://doi.org/10.3109/09513599809012840
Fernando, S., & Rombauts, L. (2014). Melatonin: shedding light on infertility? – a review of the recent literature. Journal of Ovarian Research, 7(1). http://doi.org/10.1186/s13048-014-0098-y
Rocha, C., Rato, L., Martins, A., Alves, M., & Oliveira, P. (2015). Melatonin and Male Reproductive Health: Relevance of Darkness and Antioxidant Properties. Current Molecular Medicine, 15(4), 299–311. http://doi.org/10.2174/1566524015666150505155530
Song, C., Peng, W., Yin, S., Zhao, J., Fu, B., Zhang, J., … Zhang, Y. (2016). Melatonin improves age-induced fertility decline and attenuates ovarian mitochondrial oxidative stress in mice. Scientific Reports, 6(1). http://doi.org/10.1038/srep35165
Espino, J., Macedo, M., Lozano, G., Ortiz, Á., Rodríguez, C., Rodríguez, A. B., & Bejarano, I. (2019). Impact of Melatonin Supplementation in Women with Unexplained Infertility Undergoing Fertility Treatment. Antioxidants, 8(9), 338. http://doi.org/10.3390/antiox8090338
Tamura, H., Takasaki, A., Taketani, T., Tanabe, M., Kizuka, F., Lee, L., … Sugino, N. (2012). The role of melatonin as an antioxidant in the follicle. Journal of Ovarian Research, 5(1), 5. http://doi.org/10.1186/1757-2215-5-5
Saaresranta, T., & Polo, O. (2003). Sleep-disordered breathing and hormones. European Respiratory Journal, 22(1), 161–172. http://doi.org/10.1183/09031936.03.00062403
Cappuccio, F. P., Cooper, D., Delia, L., Strazzullo, P., & Miller, M. A. (2011). Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies. European Heart Journal, 32(12), 1484–1492. http://doi.org/10.1093/eurheartj/ehr007
Jansen, E. C., Dunietz, G. L., Tsimpanouli, M.-E., Guyer, H. M., Shannon, C., Hershner, S. D., … Baylin, A. (2018). Sleep, Diet, and Cardiometabolic Health Investigations: a Systematic Review of Analytic Strategies. Current Nutrition Reports, 7(4), 235–258. http://doi.org/10.1007/s13668-018-0240-3
Knutson, K. L., Cauter, E. V., Rathouz, P. J., Yan, L. L., Hulley, S. B., Liu, K., & Lauderdale, D. S. (2009). Association Between Sleep and Blood Pressure in Midlife. Archives of Internal Medicine, 169(11), 1055. http://doi.org/10.1001/archinternmed.2009.119
Besedovsky, L., Lange, T., & Born, J. (2011). Sleep and immune function. Pflügers Archiv – European Journal of Physiology, 463(1), 121–137. http://doi.org/10.1007/s00424-011-1044-0
Besedovsky, L., Lange, T., & Haack, M. (2019). The Sleep-Immune Crosstalk in Health and Disease. Physiological Reviews, 99(3), 1325–1380. http://doi.org/10.1152/physrev.00010.2018
Orr, W. C., Fass, R., Sundaram, S. S., & Scheimann, A. O. (2020). The effect of sleep on gastrointestinal functioning in common digestive diseases. The Lancet Gastroenterology & Hepatology, 5(6), 616–624. http://doi.org/10.1016/s2468-1253(19)30412-1
Tang, Y., Preuss, F., Turek, F. W., Jakate, S., & Keshavarzian, A. (2009). Sleep deprivation worsens inflammation and delays recovery in a mouse model of colitis. Sleep Medicine, 10(6), 597–603. http://doi.org/10.1016/j.sleep.2008.12.009
Chen, Y., Tan, F., Wei, L., Li, X., Lyu, Z., Feng, X., … Li, N. (2018). Sleep duration and the risk of cancer: a systematic review and meta-analysis including dose–response relationship. BMC Cancer, 18(1). http://doi.org/10.1186/s12885-018-5025-y
Almendros, I., Martinez-Garcia, M. A., Farré, R., & Gozal, D. (2020). Obesity, sleep apnea, and cancer. International Journal of Obesity, 44(8), 1653–1667. http://doi.org/10.1038/s41366-020-0549-z
Erren, T. C., Falaturi, P., Morfeld, P., Knauth, P., Reiter, R. J., & Piekarski, C. (2010). Shift Work and Cancer. Deutsches Aerzteblatt Online. http://doi.org/10.3238/arztebl.2010.0657
Bernert, R. A., Kim, J. S., Iwata, N. G., & Perlis, M. L. (2015). Sleep Disturbances as an Evidence-Based Suicide Risk Factor. Current Psychiatry Reports, 17(3). http://doi.org/10.1007/s11920-015-0554-4
Kim, J.-H., Park, E.-C., Cho, W.-H., Park, J.-Y., Choi, W.-J., & Chang, H.-S. (2013). Association between Total Sleep Duration and Suicidal Ideation among the Korean General Adult Population. Sleep, 36(10), 1563–1572. http://doi.org/10.5665/sleep.3058
Mccall, W. V., & Black, C. G. (2013). The Link Between Suicide and Insomnia: Theoretical Mechanisms. Current Psychiatry Reports, 15(9). http://doi.org/10.1007/s11920-013-0389-9
Li, S. X., Lam, S. P., Zhang, J., Yu, M. W. M., Chan, J. W. Y., Chan, C. S. Y., … Wing, Y.-K. (2016). Sleep Disturbances and Suicide Risk in an 8-Year Longitudinal Study of Schizophrenia-Spectrum Disorders. Sleep, 39(6), 1275–1282. http://doi.org/10.5665/sleep.5852
Littlewood, D. L., Gooding, P., Kyle, S. D., Pratt, D., & Peters, S. (2016). Understanding the role of sleep in suicide risk: qualitative interview study. BMJ Open, 6(8). http://doi.org/10.1136/bmjopen-2016-012113
Lin, H.-T., Lai, C.-H., Perng, H.-J., Chung, C.-H., Wang, C.-C., Chen, W.-L., & Chien, W.-C. (2018). Insomnia as an independent predictor of suicide attempts: a nationwide population-based retrospective cohort study. BMC Psychiatry, 18(1). http://doi.org/10.1186/s12888-018-1702-2
Freeman, D., Sheaves, B., Waite, F., Harvey, A. G., & Harrison, P. J. (2020). Sleep disturbance and psychiatric disorders. The Lancet Psychiatry, 7(7), 628–637. http://doi.org/10.1016/s2215-0366(20)30136-x
Benca, R. M. (1992). Sleep and Psychiatric Disorders. Archives of General Psychiatry, 49(8), 651. http://doi.org/10.1001/archpsyc.1992.01820080059010
Breslau, N., Roth, T., Rosenthal, L., & Andreski, P. (1996). Sleep disturbance and psychiatric disorders: A longitudinal epidemiological study of young Adults. Biological Psychiatry, 39(6), 411–418. http://doi.org/10.1016/0006-3223(95)00188-3
Baglioni, C., Nanovska, S., Regen, W., Spiegelhalder, K., Feige, B., Nissen, C., … Riemann, D. (2016). Sleep and mental disorders: A meta-analysis of polysomnographic research. Psychological Bulletin, 142(9), 969–990. http://doi.org/10.1037/bul0000053
Goldstein, A. N., & Walker, M. P. (2014). The Role of Sleep in Emotional Brain Function. Annual Review of Clinical Psychology, 10(1), 679–708. http://doi.org/10.1146/annurev-clinpsy-032813-153716
Postuma, R. B., Iranzo, A., Hu, M., Högl, B., Boeve, B. F., Manni, R., … Pelletier, A. (2019). Risk and predictors of dementia and parkinsonism in idiopathic REM sleep behaviour disorder: a multicentre study. Brain, 142(3), 744–759. http://doi.org/10.1093/brain/awz030
Wintler, T., Schoch, H., Frank, M. G., & Peixoto, L. (2020). Sleep, brain development, and autism spectrum disorders: Insights from animal models. Journal of Neuroscience Research, 98(6), 1137–1149. http://doi.org/10.1002/jnr.24619
Shokri-Kojori, E., Wang, G.-J., Wiers, C. E., Demiral, S. B., Guo, M., Kim, S. W., … Volkow, N. D. (2018). β-Amyloid accumulation in the human brain after one night of sleep deprivation. Proceedings of the National Academy of Sciences, 115(17), 4483–4488. http://doi.org/10.1073/pnas.1721694115
Mantovani, S., Smith, S. S., Gordon, R., & Osullivan, J. D. (2018). An overview of sleep and circadian dysfunction in Parkinsons disease. Journal of Sleep Research, 27(3). http://doi.org/10.1111/jsr.12673
Malhotra, R. K. (2018). Neurodegenerative Disorders and Sleep. Sleep Medicine Clinics, 13(1), 63–70. http://doi.org/10.1016/j.jsmc.2017.09.006
Huang, L.-B., Tsai, M.-C., Chen, C.-Y., & Hsu, S.-C. (2013). The Effectiveness of Light/Dark Exposure to Treat Insomnia in Female Nurses Undertaking Shift Work during the Evening/Night Shift. Journal of Clinical Sleep Medicine, 09(07), 641–646. http://doi.org/10.5664/jcsm.2824
Zhang, Y., & Papantoniou, K. (2019). Night shift work and its carcinogenicity. The Lancet Oncology, 20(10). http://doi.org/10.1016/s1470-2045(19)30578-9
Perry-Jenkins, M., Goldberg, A. E., Pierce, C. P., & Sayer, A. G. (2007). Shift Work, Role Overload, and the Transition to Parenthood. Journal of Marriage and Family, 69(1), 123–138. http://doi.org/10.1111/j.1741-3737.2006.00349.x
Rodziewicz TL, Hipskind JE. Medical Error Prevention. 2020 May 5. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020 Jan–. PMID: 29763131. https://pubmed.ncbi.nlm.nih.gov/29763131/
Tanaka, K., Takahashi, M., Hiro, H., Kakinuma, M., Tanaka, M., Kamata, N., & Miyaoka, H. (2010). Differences in Medical Error Risk among Nurses Working Two- and Three-shift Systems at Teaching Hospitals: A Six-month Prospective Study. Industrial Health, 48(3), 357–364. http://doi.org/10.2486/indhealth.48.357
Admi H, Tzischinsky O, Epstein R, Herer P, Lavie P. Shift work in nursing: is it really a risk factor for nurses’ health and patients’ safety?. Nurs Econ. 2008;26(4):250-257. https://pubmed.ncbi.nlm.nih.gov/18777974/
Clendon, J., & Gibbons, V. (2015). 12h shifts and rates of error among nurses: A systematic review. International Journal of Nursing Studies, 52(7), 1231–1242. http://doi.org/10.1016/j.ijnurstu.2015.03.011
Hammadah, M., Kindya, B. R., Allard‐Ratick, M. P., Jazbeh, S., Eapen, D., Tang, W. W., & Sperling, L. (2017). Navigating air travel and cardiovascular concerns: Is the sky the limit?, Clinical Cardiology, 40 (9), 660–666. http://doi.org/10.1002/clc.22741
Lieber, B. A., Han, J., Appelboom, G., Taylor, B. E., Han, B., Agarwal, N., & Connolly, E. S. (2016). Association of Steroid Use with Deep Venous Thrombosis and Pulmonary Embolism in Neurosurgical Patients: A National Database Analysis. World Neurosurgery, 89, 126–132. http://doi.org/10.1016/j.wneu.2016.01.033
El-Menyar, A., Asim, M., & Al-Thani, H. (2017). Obesity Paradox in Patients With Deep Venous Thrombosis. Clinical and Applied Thrombosis/Hemostasis, 24(6), 986–992. http://doi.org/10.1177/1076029617727858
Klovaite, J., Benn, M., & Nordestgaard, B. G. (2014). Obesity as a causal risk factor for deep venous thrombosis: a Mendelian randomization study. Journal of Internal Medicine, 277(5), 573–584. http://doi.org/10.1111/joim.12299
Davies, H. O., Popplewell, M., Singhal, R., Smith, N., & Bradbury, A. W. (2016). Obesity and lower limb venous disease – The epidemic of phlebesity. Phlebology: The Journal of Venous Disease, 32(4), 227–233. http://doi.org/10.1177/0268355516649333
Liljeqvist, S., Helldén, A., Bergman, U., & Söderberg, M. (2008). Pulmonary embolism associated with the use of anabolic steroids. European Journal of Internal Medicine, 19(3), 214–215. http://doi.org/10.1016/j.ejim.2007.03.016
Linton MF, Yancey PG, Davies SS, Jerome WG (Jay), Linton EF, Vickers KC. The Role of Lipids and Lipoproteins in Atherosclerosis. In: De Groot LJ, Chrousos G, Dungan K, et al., eds. Endotext. South Dartmouth (MA): MDText.com, Inc.; 2000. http://www.ncbi.nlm.nih.gov/books/NBK343489/.
Rescheduling of meals may ease the effects of jet lag. (2017). Nursing Standard, 31(48), 16–16. http://doi.org/10.7748/ns.31.48.16.s17
Ruscitto, C., & Ogden, J. (2016). The impact of an implementation intention to improve mealtimes and reduce jet lag in long-haul cabin crew. Psychology & Health, 32(1), 61–77. http://doi.org/10.1080/08870446.2016.1240174
Reid, K. J., & Abbott, S. M. (2015). Jet Lag and Shift Work Disorder. Sleep Medicine Clinics, 10(4), 523–535. http://doi.org/10.1016/j.jsmc.2015.08.006
Srinivasan, V., Spence, D. W., Pandi-Perumal, S. R., Trakht, I., & Cardinali, D. P. (2008). Jet lag: Therapeutic use of melatonin and possible application of melatonin analogs. Travel Medicine and Infectious Disease, 6(1-2), 17–28. http://doi.org/10.1016/j.tmaid.2007.12.002
Edwards, B. J., Atkinson, G., Waterhouse, J., Reilly, T., Godfrey, R., & Budgett, R. (2000). Use of melatonin in recovery from jet-lag following an eastward flight across 10 time-zones. Ergonomics, 43(10), 1501–1513. http://doi.org/10.1080/001401300750003934
Zee, P. C., & Goldstein, C. A. (2010). Treatment of Shift Work Disorder and Jet Lag. Current Treatment Options in Neurology, 12(5), 396–411. http://doi.org/10.1007/s11940-010-0090-9
https://www.nhlbi.nih.gov/health-topics/circadian-rhythm-disorders
Borodkin, K., & Dagan, Y. (2013). Diagnostic Algorithm for Circadian Rhythm Sleep Disorders. Encyclopedia of Sleep, 66–73. http://doi.org/10.1016/b978-0-12-378610-4.00284-9
Lockley, S. (2013). Special Considerations and Future Directions in Circadian Rhythm Sleep Disorders Diagnosis. Encyclopedia of Sleep, 138–149. http://doi.org/10.1016/b978-0-12-378610-4.00299-0
Crowley, S., & Youngstedt, S. (2013). Pathophysiology, Associations, and Consequences of Circadian Rhythm Sleep Disorder. Encyclopedia of Sleep, 16–21. http://doi.org/10.1016/b978-0-12-378610-4.00266-7
Franken, P., & Dijk, D.-J. (2009). Circadian clock genes and sleep homeostasis. European Journal of Neuroscience, 29(9), 1820–1829. http://doi.org/10.1111/j.1460-9568.2009.06723.x
Burgess, H. J., & Emens, J. S. (2016). Circadian-Based Therapies for Circadian Rhythm Sleep-Wake Disorders. Current Sleep Medicine Reports, 2(3), 158–165. http://doi.org/10.1007/s40675-016-0052-1
Jones, C. R., Huang, A. L., Ptáček, L. J., & Fu, Y.-H. (2013). Genetic basis of human circadian rhythm disorders. Experimental Neurology, 243, 28–33. http://doi.org/10.1016/j.expneurol.2012.07.012
Toh KL. Basic science review on circadian rhythm biology and circadian sleep disorders. Ann Acad Med Singap. 2008;37(8):662-668. https://pubmed.ncbi.nlm.nih.gov/18797559/
Farhud D, Aryan Z. Circadian Rhythm, Lifestyle and Health: A Narrative Review. Iran J Public Health. 2018;47(8):1068-1076. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123576/
Dodson, E. R., & Zee, P. C. (2010). Therapeutics for Circadian Rhythm Sleep Disorders. Sleep Medicine Clinics, 5(4), 701–715. http://doi.org/10.1016/j.jsmc.2010.08.001
Zhu, L., & Zee, P. C. (2012). Circadian Rhythm Sleep Disorders. Neurologic Clinics, 30(4), 1167–1191. http://doi.org/10.1016/j.ncl.2012.08.011
Kim MJ, Lee JH, Duffy JF. Circadian Rhythm Sleep Disorders. J Clin Outcomes Manag. 2013;20(11):513-528. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212693/
Zhong, G., Naismith, S. L., Rogers, N. L., & Lewis, S. J. G. (2011). Sleep-wake disturbances in common neurodegenerative diseases: A closer look at selected aspects of the neural circuitry. Journal of the Neurological Sciences, 307(1-2), 9–14. http://doi.org/10.1016/j.jns.2011.04.020
Dijk, D.-J., Boulos, Z., Eastman, C. I., Lewy, A. J., Campbell, S. S., & Terman, M. (1995). Light Treatment for Sleep Disorders: Consensus Report. Journal of Biological Rhythms, 10(2), 113–125. http://doi.org/10.1177/074873049501000204
Barion, A., & Zee, P. C. (2007). A clinical approach to circadian rhythm sleep disorders. Sleep Medicine, 8(6), 566–577. http://doi.org/10.1016/j.sleep.2006.11.017
Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol. 1976;4(2):97-110. https://pubmed.ncbi.nlm.nih.gov/1027738/
Adan, A., & Almirall, H. (1991). Horne & Östberg morningness-eveningness questionnaire: A reduced scale. Personality and Individual Differences, 12(3), 241–253. http://doi.org/10.1016/0191-8869(91)90110-w
Urbán, R., Magyaródi, T., & Rigó, A. (2011). Morningness-Eveningness, Chronotypes and Health-Impairing Behaviors in Adolescents. Chronobiology International, 28(3), 238–247. http://doi.org/10.3109/07420528.2010.549599
https://www.thewep.org/documentations/mctq
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193–213. http://doi.org/10.1016/0165-1781(89)90047-4
Bastien, C. (2001). Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Medicine, 2(4), 297–307. http://doi.org/10.1016/s1389-9457(00)00065-4
Yang, M., Morin, C. M., Schaefer, K., & Wallenstein, G. V. (2009). Interpreting score differences in the Insomnia Severity Index: using health-related outcomes to define the minimally important difference. Current Medical Research and Opinion, 25(10), 2487–2494. http://doi.org/10.1185/03007990903167415
Morin, C. M., Belleville, G., Bélanger, L., & Ivers, H. (2011). The Insomnia Severity Index: Psychometric Indicators to Detect Insomnia Cases and Evaluate Treatment Response. Sleep, 34(5), 601–608. http://doi.org/10.1093/sleep/34.5.601
Castriotta RJ, Wilde MC, Lai JM, Atanasov S, Masel BE, Kuna ST. Prevalence and consequences of sleep disorders in traumatic brain injury. J Clin Sleep Med. 2007;3(4):349-356. https://pubmed.ncbi.nlm.nih.gov/17694722/
Chokroverty S. Overview of sleep & sleep disorders. Indian J Med Res. 2010;131:126-140. https://pubmed.ncbi.nlm.nih.gov/20308738/
Pavlova, M. K., & Latreille, V. (2019). Sleep Disorders. The American Journal of Medicine, 132(3), 292–299. http://doi.org/10.1016/j.amjmed.2018.09.021
Olejniczak, P. W., & Fisch, B. J. (2003). Sleep disorders. Medical Clinics of North America, 87(4), 803–833. http://doi.org/10.1016/s0025-7125(03)00006-3
https://www.nhlbi.nih.gov/health-topics/sleep-apnea
https://clevemed.com/what-is-sleep-apnea/patient-sleep-apnea-screener/
Spicuzza, L., Caruso, D., & Maria, G. D. (2015). Obstructive sleep apnoea syndrome and its management. Therapeutic Advances in Chronic Disease, 6(5), 273–285. http://doi.org/10.1177/2040622315590318
Bixler, E. O., Vgontzas, A. N., Lin, H.-M., Liao, D., Calhoun, S., Fedok, F., … Graff, G. (2008). Blood Pressure Associated With Sleep-Disordered Breathing in a Population Sample of Children. Hypertension, 52(5), 841–846. http://doi.org/10.1161/hypertensionaha.108.116756
Campos, A. I., García-Marín, L. M., Byrne, E. M., Martin, N. G., Cuéllar-Partida, G., & Rentería, M. E. (2020). Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank. Nature Communications, 11(1). http://doi.org/10.1038/s41467-020-14625-1
Morgenthaler, T. I., Kagramanov, V., Hanak, V., & Decker, P. A. (2006). Complex Sleep Apnea Syndrome: Is It a Unique Clinical Syndrome? Sleep, 29(9), 1203–1209. http://doi.org/10.1093/sleep/29.9.1203
El-Ad, B., & Lavie, P. (2005). Effect of sleep apnea on cognition and mood. International Review of Psychiatry, 17(4), 277–282. http://doi.org/10.1080/09540260500104508
Morgenstern, M., Wang, J., Beatty, N., Batemarco, T., Sica, A. L., & Greenberg, H. (2014). Obstructive Sleep Apnea. Endocrinology and Metabolism Clinics of North America, 43(1), 187–204. http://doi.org/10.1016/j.ecl.2013.09.002
Sleep–Related Breathing Disorders in Adults: Recommendations for Syndrome Definition and Measurement Techniques in Clinical Research. (1999). Sleep, 22(5), 667–689. http://doi.org/10.1093/sleep/22.5.667
Ruehland, W. R., Rochford, P. D., O’Donoghue, F. J., Pierce, R. J., Singh, P., & Thornton, A. T. (2009). The New AASM Criteria for Scoring Hypopneas: Impact on the Apnea Hypopnea Index. Sleep, 32(2), 150–157. http://doi.org/10.1093/sleep/32.2.150
Selim, B. J., Koo, B. B., Qin, L., Jeon, S., Won, C., Redeker, N. S., … Yaggi, H. K. (2016). The Association between Nocturnal Cardiac Arrhythmias and Sleep-Disordered Breathing: The DREAM Study. Journal of Clinical Sleep Medicine, 12(06), 829–837. http://doi.org/10.5664/jcsm.5880
Ahmed, M. H. (2010). Obstructive sleep apnea syndrome and fatty liver: Association or causal link? World Journal of Gastroenterology, 16(34), 4243. http://doi.org/10.3748/wjg.v16.i34.4243
Singh, H., Pollock, R., Uhanova, J., Kryger, M., Hawkins, K., & Minuk, G. Y. (2005). Symptoms of Obstructive Sleep Apnea in Patients with Nonalcoholic Fatty Liver Disease. Digestive Diseases and Sciences, 50(12), 2338–2343. http://doi.org/10.1007/s10620-005-3058-y
Lawati, N. M. A., Patel, S. R., & Ayas, N. T. (2009). Epidemiology, Risk Factors, and Consequences of Obstructive Sleep Apnea and Short Sleep Duration. Progress in Cardiovascular Diseases, 51(4), 285–293. http://doi.org/10.1016/j.pcad.2008.08.001
Young, T. (2004). Risk Factors for Obstructive Sleep Apnea in Adults. Jama, 291(16), 2013. http://doi.org/10.1001/jama.291.16.2013
Yaggi, H. K., Concato, J., Kernan, W. N., Lichtman, J. H., Brass, L. M., & Mohsenin, V. (2005). Obstructive Sleep Apnea as a Risk Factor for Stroke and Death. New England Journal of Medicine, 353(19), 2034–2041. http://doi.org/10.1056/nejmoa043104
Redline, S., Budhiraja, R., Kapur, V., Marcus, C. L., Mateika, J. H., Mehra, R., … Quan, A. S. F. (2007). The Scoring of Respiratory Events in Sleep: Reliability and Validity. Journal of Clinical Sleep Medicine, 03(02), 169–200. http://doi.org/10.5664/jcsm.26818
Basheer B, Hegde KS, Bhat SS, Umar D, Baroudi K. Influence of mouth breathing on the dentofacial growth of children: a cephalometric study. J Int Oral Health. 2014;6(6):50-55. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4295456/
Ruhle, K. H., & Nilius, G. (2008). Mouth Breathing in Obstructive Sleep Apnea prior to and during Nasal Continuous Positive Airway Pressure. Respiration, 76(1), 40–45. http://doi.org/10.1159/000111806
Izu, S. C., Itamoto, C. H., Pradella-Hallinan, M., Pizarro, G. U., Tufik, S., Pignatari, S., & Fujita, R. R. (2010). Obstructive sleep apnea syndrome (OSAS) in mouth breathing children. Brazilian Journal of Otorhinolaryngology, 76(5), 552–556. http://doi.org/10.1590/s1808-86942010000500003
Lee, S. H., Choi, J. H., Shin, C., Lee, H. M., Kwon, S. Y., & Lee, S. H. (2007). How Does Open-Mouth Breathing Influence Upper Airway Anatomy? The Laryngoscope, 117(6), 1102–1106. http://doi.org/10.1097/mlg.0b013e318042aef7
Tuomilehto, H. P. I., Seppä, J. M., Partinen, M. M., Peltonen, M., Gylling, H., Tuomilehto, J. O. I., … Uusitupa, M. (2009). Lifestyle Intervention with Weight Reduction. American Journal of Respiratory and Critical Care Medicine, 179(4), 320–327. http://doi.org/10.1164/rccm.200805-669oc
https://www.cdc.gov/nchs/fastats/obesity-overweight.htm
Neill, A. M., Angus, S. M., Sajkov, D., & Mcevoy, R. D. (1997). Effects of sleep posture on upper airway stability in patients with obstructive sleep apnea. American Journal of Respiratory and Critical Care Medicine, 155(1), 199–204. http://doi.org/10.1164/ajrccm.155.1.9001312
Loord, H., & Hultcrantz, E. (2007). Positioner–a method for preventing sleep apnea. Acta Oto-Laryngologica, 127(8), 861–868. http://doi.org/10.1080/00016480601089390
Szollosi, I., Roebuck, T., Thompson, B., & Naughton, M. T. (2006). Lateral Sleeping Position Reduces Severity of Central Sleep Apnea / Cheyne-Stokes Respiration. Sleep, 29(8), 1045–1051. http://doi.org/10.1093/sleep/29.8.1045
Silverberg DS, Iaina A, Oksenberg A. Treating obstructive sleep apnea improves essential hypertension and quality of life. Am Fam Physician. 2002;65(2):229-236. https://pubmed.ncbi.nlm.nih.gov/11820487/
Aurora, R. N., Chowdhuri, S., Ramar, K., Bista, S. R., Casey, K. R., Lamm, C. I., … Tracy, S. L. (2012). The Treatment of Central Sleep Apnea Syndromes in Adults: Practice Parameters with an Evidence-Based Literature Review and Meta-Analyses. Sleep, 35(1), 17–40. http://doi.org/10.5665/sleep.1580
Hsu, A. A. L., & Lo, C. (2003). Continuous positive airway pressure therapy in sleep apnoea. Respirology, 8(4), 447–454. http://doi.org/10.1046/j.1440-1843.2003.00494.x
Patel, S. R., White, D. P., Malhotra, A., Stanchina, M. L., & Ayas, N. T. (2003). Continuous Positive Airway Pressure Therapy for Treating gess in a Diverse Population With Obstructive Sleep Apnea. Archives of Internal Medicine, 163(5), 565. http://doi.org/10.1001/archinte.163.5.565
Sundaram, S., Lim, J., & Lasserson, T. J. (2005). Surgery for obstructive sleep apnoea in adults. Cochrane Database of Systematic Reviews. http://doi.org/10.1002/14651858.cd001004.pub2
Chen, H., & Lowe, A. A. (2012). Updates in oral appliance therapy for snoring and obstructive sleep apnea. Sleep and Breathing, 17(2), 473–486. http://doi.org/10.1007/s11325-012-0712-4
Gaisl, T., Haile, S. R., Thiel, S., Osswald, M., & Kohler, M. (2019). Efficacy of pharmacotherapy for OSA in adults: A systematic review and network meta-analysis. Sleep Medicine Reviews, 46, 74–86. http://doi.org/10.1016/j.smrv.2019.04.009
Ohayon, M., Wickwire, E. M., Hirshkowitz, M., Albert, S. M., Avidan, A., Daly, F. J., … Vitiello, M. V. (2017). National Sleep Foundations sleep quality recommendations: first report. Sleep Health, 3(1), 6–19. http://doi.org/10.1016/j.sleh.2016.11.006
Youngstedt, S. D., Goff, E. E., Reynolds, A. M., Kripke, D. F., Irwin, M. R., Bootzin, R. R., … Jean-Louis, G. (2016). Has adult sleep duration declined over the last 50 years? Sleep Medicine Reviews, 28, 69–85. http://doi.org/10.1016/j.smrv.2015.08.004
Chaput, J.-P., Mcneil, J., Després, J.-P., Bouchard, C., & Tremblay, A. (2013). Seven to Eight Hours of Sleep a Night Is Associated with a Lower Prevalence of the Metabolic Syndrome and Reduced Overall Cardiometabolic Risk in Adults. PLoS ONE, 8(9). http://doi.org/10.1371/journal.pone.0072832
Wild, C. J., Nichols, E. S., Battista, M. E., Stojanoski, B., & Owen, A. M. (2018). Dissociable effects of self-reported daily sleep duration on high-level cognitive abilities. Sleep, 41(12). http://doi.org/10.1093/sleep/zsy182
Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C., Bruni, O., Doncarlos, L., … Hillard, P. J. A. (2015). National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health, 1(1), 40–43. http://doi.org/10.1016/j.sleh.2014.12.010
Cappuccio, F. P., Delia, L., Strazzullo, P., & Miller, M. A. (2010). Sleep Duration and All-Cause Mortality: A Systematic Review and Meta-Analysis of Prospective Studies. Sleep, 33(5), 585–592. http://doi.org/10.1093/sleep/33.5.585
Gottlieb, D. J., Punjabi, N. M., Newman, A. B., Resnick, H. E., Redline, S., Baldwin, C. M., & Nieto, F. J. (2005). Association of Sleep Time With Diabetes Mellitus and Impaired Glucose Tolerance. Archives of Internal Medicine, 165(8), 863. http://doi.org/10.1001/archinte.165.8.863
Short, M. A., Agostini, A., Lushington, K., & Dorrian, J. (2015). A systematic review of the sleep, sleepiness, and performance implications of limited wake shift work schedules. Scandinavian Journal of Work, Environment & Health, 41(5), 425–440. http://doi.org/10.5271/sjweh.3509
Cappuccio, F. P., Taggart, F. M., Kandala, N.-B., Currie, A., Peile, E., Stranges, S., & Miller, M. A. (2008). Meta-Analysis of Short Sleep Duration and Obesity in Children and Adults. Sleep, 31(5), 619–626. http://doi.org/10.1093/sleep/31.5.619
Mong, J. A., & Cusmano, D. M. (2016). Sex differences in sleep: impact of biological sex and sex steroids. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1688), 20150110. http://doi.org/10.1098/rstb.2015.0110
Krishnan, V., & Collop, N. A. (2006). Gender differences in sleep disorders. Current Opinion in Pulmonary Medicine, 12(6), 383–389. http://doi.org/10.1097/01.mcp.0000245705.69440.6a
Mehta, N., Shafi, F., & Bhat, A. (2015). Unique Aspects of Sleep in Women. Missouri medicine, 112(6), 430–434. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6168103/
Moline, M. L., Broch, L., & Zak, R. (2004). Sleep in women across the life cycle from adulthood through menopause. Medical Clinics of North America, 88(3), 705–736. http://doi.org/10.1016/j.mcna.2004.01.009
He, Y., Jones, C. R., Fujiki, N., Xu, Y., Guo, B., Holder, J. L., … Fu, Y.-H. (2009). The Transcriptional Repressor DEC2 Regulates Sleep Length in Mammals. Science, 325(5942), 866–870. http://doi.org/10.1126/science.1174443
Theorell-Haglöw, J., Berglund, L., Berne, C., & Lindberg, E. (2014). Both habitual short sleepers and long sleepers are at greater risk of obesity: a population-based 10-year follow-up in women. Sleep Medicine, 15(10), 1204–1211. http://doi.org/10.1016/j.sleep.2014.02.014
Mezick, E. J., Wing, R. R., & Mccaffery, J. M. (2014). Associations of self-reported and actigraphy-assessed sleep characteristics with body mass index and waist circumference in adults: moderation by gender. Sleep Medicine, 15(1), 64–70. http://doi.org/10.1016/j.sleep.2013.08.784
Kim, S. J. (2011). Relationship Between Weekend Catch-up Sleep and Poor Performance on Attention Tasks in Korean Adolescents. Archives of Pediatrics & Adolescent Medicine, 165(9), 806. http://doi.org/10.1001/archpediatrics.2011.128
Kim, C.-W., Choi, M.-K., Im, H.-J., Kim, O.-H., Lee, H.-J., Song, J., … Park, K.-H. (2012). Weekend catch-up sleep is associated with decreased risk of being overweight among fifth-grade students with short sleep duration. Journal of Sleep Research, 21(5), 546–551. http://doi.org/10.1111/j.1365-2869.2012.01013.x
Sun, W., Ling, J., Zhu, X., Lee, T. M.-C., & Li, S. X. (2019). Associations of weekday-to-weekend sleep differences with academic performance and health-related outcomes in school-age children and youths. Sleep Medicine Reviews, 46, 27–53. http://doi.org/10.1016/j.smrv.2019.04.003
Kang, S.-G., Lee, Y. J., Kim, S. J., Lim, W., Lee, H.-J., Park, Y.-M., … Hong, J. P. (2014). Weekend catch-up sleep is independently associated with suicide attempts and self-injury in Korean adolescents. Comprehensive Psychiatry, 55(2), 319–325. http://doi.org/10.1016/j.comppsych.2013.08.023
Zhao, M., Tuo, H., Wang, S., & Zhao, L. (2020). The Effects of Dietary Nutrition on Sleep and Sleep Disorders. Mediators of Inflammation, 2020, 1–7. http://doi.org/10.1155/2020/3142874
Doherty, Madigan, Warrington, & Ellis. (2019). Sleep and Nutrition Interactions: Implications for Athletes. Nutrients, 11(4), 822. http://doi.org/10.3390/nu11040822
Sutanto CN, Wang MX, Tan D, Kim JE. Association of Sleep Quality and Macronutrient Distribution: A Systematic Review and Meta-Regression. Nutrients. 2020 Jan 2;12(1):126. doi: 10.3390/nu12010126. PMID: 31906452; PMCID: PMC7019667. https://pubmed.ncbi.nlm.nih.gov/31906452/
Peuhkuri, K., Sihvola, N., & Korpela, R. (2012). Diet promotes sleep duration and quality. Nutrition Research, 32(5), 309–319. http://doi.org/10.1016/j.nutres.2012.03.009
Afaghi, A., Oconnor, H., & Chow, C. M. (2007). High-glycemic-index carbohydrate meals shorten sleep onset. The American Journal of Clinical Nutrition, 85(2), 426–430. http://doi.org/10.1093/ajcn/85.2.426
Golem, D. L., Martin-Biggers, J. T., Koenings, M. M., Davis, K. F., & Byrd-Bredbenner, C. (2014). An Integrative Review of Sleep for Nutrition Professionals. Advances in Nutrition, 5(6), 742–759. http://doi.org/10.3945/an.114.006809
Grandner, M. A., Jackson, N., Gerstner, J. R., & Knutson, K. L. (2013). Sleep symptoms associated with intake of specific dietary nutrients. Journal of Sleep Research, 23(1), 22–34. http://doi.org/10.1111/jsr.12084
Porter, J., & Horne, J. (1981). Bed-time food supplements and sleep: Effects of different carbohydrate levels. Electroencephalography and Clinical Neurophysiology, 51(4), 426–433. http://doi.org/10.1016/0013-4694(81)90106-1
Halson, S. L. (2014). Sleep in Elite Athletes and Nutritional Interventions to Enhance Sleep. Sports Medicine, 44(S1), 13–23. http://doi.org/10.1007/s40279-014-0147-0
Rondanelli, M., Opizzi, A., Monteferrario, F., Antoniello, N., Manni, R., & Klersy, C. (2011). The Effect of Melatonin, Magnesium, and Zinc on Primary Insomnia in Long-Term Care Facility Residents in Italy: A Double-Blind, Placebo-Controlled Clinical Trial. Journal of the American Geriatrics Society, 59(1), 82–90. http://doi.org/10.1111/j.1532-5415.2010.03232.x
Tahara, Y., & Shibata, S. (2014). Chrono-biology, Chrono-pharmacology, and Chrono-nutrition. Journal of Pharmacological Sciences, 124(3), 320–335. http://doi.org/10.1254/jphs.13r06cr
Landolt, H.-P., Werth, E., Borbély, A. A., & Dijk, D.-J. (1995). Caffeine intake (200 mg) in the morning affects human sleep and EEG power spectra at night. Brain Research, 675(1-2), 67–74. http://doi.org/10.1016/0006-8993(95)00040-w
Gottesmann, C. (2002). GABA mechanisms and sleep. Neuroscience, 111(2), 231–239. http://doi.org/10.1016/s0306-4522(02)00034-9
Campbell, S. S., Dawson, D., & Anderson, M. W. (1993). Alleviation of Sleep Maintenance Insomnia with Timed Exposure to Bright Light. Journal of the American Geriatrics Society, 41(8), 829–836. http://doi.org/10.1111/j.1532-5415.1993.tb06179.x
Zhao, J., Tian, Y., Nie, J., Xu, J., & Liu, D. (2012). Red Light and the Sleep Quality and Endurance Performance of Chinese Female Basketball Players. Journal of Athletic Training, 47(6), 673–678. http://doi.org/10.4085/1062-6050-47.6.08
Smolensky, M. H., Sackett-Lundeen, L. L., & Portaluppi, F. (2015). Nocturnal light pollution and underexposure to daytime sunlight: Complementary mechanisms of circadian disruption and related diseases. Chronobiology International, 32(8), 1029–1048. http://doi.org/10.3109/07420528.2015.1072002
Düzgün, G., & Akyol, A. D. (2017). Effect of Natural Sunlight on Sleep Problems and Sleep Quality of the Elderly Staying in the Nursing Home. Holistic Nursing Practice, 31(5), 295–302. http://doi.org/10.1097/hnp.0000000000000206
Valham, F., Sahlin, C., Stenlund, H., & Franklin, K. A. (2012). Ambient Temperature and Obstructive Sleep Apnea: Effects on Sleep, Sleep Apnea, and Morning Alertness. Sleep, 35(4), 513–517. http://doi.org/10.5665/sleep.1736
Okamoto-Mizuno, K., Tsuzuki, K., & Mizuno, K. (2004). Effects of mild heat exposure on sleep stages and body temperature in older men. International Journal of Biometeorology, 49(1). http://doi.org/10.1007/s00484-004-0209-3
St-Onge, M.-P., & Shechter, A. (2014). Sleep disturbances, body fat distribution, food intake and/or energy expenditure: pathophysiological aspects. Hormone Molecular Biology and Clinical Investigation, 17(1). http://doi.org/10.1515/hmbci-2013-0066
Chaput, J.-P., Després, J.-P., Bouchard, C., & Tremblay, A. (2008). The Association Between Sleep Duration and Weight Gain in Adults: A 6-Year Prospective Study from the Quebec Family Study. Sleep, 31(4), 517–523. http://doi.org/10.1093/sleep/31.4.517
Dekker, S. A., Noordam, R., Biermasz, N. R., Roos, A., Lamb, H. J., Rosendaal, F. R., … Mutsert, R. (2018). Habitual Sleep Measures are Associated with Overall Body Fat, and not Specifically with Visceral Fat, in Men and Women. Obesity, 26(10), 1651–1658. http://doi.org/10.1002/oby.22289
Tunnicliffe, J. M., Erdman, K. A., Reimer, R. A., Lun, V., & Shearer, J. (2008). Consumption of dietary caffeine and coffee in physically active populations: physiological interactions. Applied Physiology, Nutrition, and Metabolism, 33(6), 1301–1310. http://doi.org/10.1139/h08-124
Mahoney, C. R., Giles, G. E., Marriott, B. P., Judelson, D. A., Glickman, E. L., Geiselman, P. J., & Lieberman, H. R. (2019). Intake of caffeine from all sources and reasons for use by college students. Clinical Nutrition, 38(2), 668–675. http://doi.org/10.1016/j.clnu.2018.04.004
Binks, H., Vincent, G. E., Gupta, C., Irwin, C., & Khalesi, S. (2020). Effects of Diet on Sleep: A Narrative Review. Nutrients, 12(4), 936. http://doi.org/10.3390/nu12040936
Rao, T. P., Ozeki, M., & Juneja, L. R. (2015). In Search of a Safe Natural Sleep Aid. Journal of the American College of Nutrition, 34(5), 436–447. http://doi.org/10.1080/07315724.2014.926153
Abbasi B, Kimiagar M, Sadeghniiat K, Shirazi MM, Hedayati M, Rashidkhani B. The effect of magnesium supplementation on primary insomnia in elderly: A double-blind placebo-controlled clinical trial. J Res Med Sci. 2012 Dec;17(12):1161-9. https://pubmed.ncbi.nlm.nih.gov/23853635/
Aspy, D. J., Madden, N. A., & Delfabbro, P. (2018). Effects of Vitamin B6 (Pyridoxine) and a B Complex Preparation on Dreaming and Sleep. Perceptual and Motor Skills, 003151251877032. http://doi.org/10.1177/0031512518770326
Parazzini F. Resveratrol, tryptophanum, glycine and vitamin E: a nutraceutical approach to sleep disturbance and irritability in peri- and post-menopause. Minerva Ginecol. 2015;67(1):1-5. https://pubmed.ncbi.nlm.nih.gov/25660429/
Siegel JM. The neurotransmitters of sleep. J Clin Psychiatry. 2004;65 Suppl 16:4-7. https://pubmed.ncbi.nlm.nih.gov/15575797/
Djeridane, Y., Touitou, Y. Chronic diazepam administration differentially affects melatonin synthesis in rat pineal and Harderian glands. Psychopharmacology154, 403–407 (2001). https://doi.org/10.1007/s002130000631
Betti L, Palego L, Demontis GC, Miraglia F, Giannaccini G. Hydroxyindole-O-methyltransferase (HIOMT) activity in the retina of melatonin-proficient mice. Heliyon. 2019;5(9):e02417. Published 2019 Sep 14. doi:10.1016/j.heliyon.2019.e02417
Haduch, A., Bromek, E., Wójcikowski, J., Gołembiowska, K., Daniel, W.. Melatonin Supports Serotonin Formation by Brain CYP2D. Drug Metabolism and DispositionMarch 1, 2016, 44 (3) 445-452; DOI: https://doi.org/10.1124/dmd.115.067413
Morton, D. J. (1987). Mechanism of Inhibition of Bovine Pineal Gland Hydroxyindole-O-Methyltransferase (EC 2.1.1.4) by Divalent Cations. Journal of Pineal Research, 4(3), 295–303. http://doi.org/10.1111/j.1600-079x.1987.tb00867.x
Markova-Car, E. P., Jurišić, D., Ilić, N., & Pavelić, S. K. (2014). Running for time: circadian rhythms and melanoma. Tumor Biology, 35(9), 8359–8368. http://doi.org/10.1007/s13277-014-1904-2
Slominski AT, Zmijewski MA, Skobowiat C, Zbytek B, Slominski RM, Steketee JD. Sensing the environment: regulation of local and global homeostasis by the skin’s neuroendocrine system. Adv Anat Embryol Cell Biol. 2012;212:v-115. doi:10.1007/978-3-642-19683-6_1 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3422784/
Chalupsky, K., Kračun, D., Kanchev, I., Bertram, K., & Görlach, A. (2015). Folic Acid Promotes Recycling of Tetrahydrobiopterin and Protects Against Hypoxia-Induced Pulmonary Hypertension by Recoupling Endothelial Nitric Oxide Synthase. Antioxidants & Redox Signaling, 23(14), 1076–1091. http://doi.org/10.1089/ars.2015.6329
Dianzani, I., Sanctis, L. D., Smooker, P. M., Gough, T. J., Alliaudi, C., Brusco, A., … Cotton, R. G. H. (1998). Dihydropteridine reductase deficiency: Physical structure of the QDPR gene, identification of two new mutations and genotype–phenotype correlations. Human Mutation, 12(4), 267–273. http://doi.org/10.1002/(sici)1098-1004(1998)12:4<267::aid-humu8>3.0.co;2-c
Nichol, C. A., Lee, C. L., Edelstein, M. P., Chao, J. Y., & Duch, D. S. (1983). Biosynthesis of tetrahydrobiopterin by de novo and salvage pathways in adrenal medulla extracts, mammalian cell cultures, and rat brain in vivo. Proceedings of the National Academy of Sciences, 80(6), 1546–1550. http://doi.org/10.1073/pnas.80.6.1546
Titus, F., Dávalos, A., Alom, J., & Codina, A. (1986). 5-Hydroxytryptophan versus Methysergide in the Prophylaxis of Migraine. European Neurology, 25(5), 327–329. http://doi.org/10.1159/000116030
Birdsall TC. 5-Hydroxytryptophan: a clinically-effective serotonin precursor. Altern Med Rev. 1998;3(4):271-280. https://pubmed.ncbi.nlm.nih.gov/9727088/
Volpi-Abadie J, Kaye AM, Kaye AD. Serotonin syndrome. Ochsner J. 2013;13(4):533-540. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3865832/
Valadas, J. S., Esposito, G., Vandekerkhove, D., Miskiewicz, K., Deaulmerie, L., Raitano, S., … Verstreken, P. (2018). ER Lipid Defects in Neuropeptidergic Neurons Impair Sleep Patterns in Parkinson’s Disease. Neuron, 98(6). http://doi.org/10.1016/j.neuron.2018.05.022
Chung SY, Moriyama T, Uezu E, et al. Administration of phosphatidylcholine increases brain acetylcholine concentration and improves memory in mice with dementia. J Nutr. 1995;125(6):1484-1489. doi:10.1093/jn/125.6.1484 https://pubmed.ncbi.nlm.nih.gov/7782901/
Montgomery, P., Burton, J. R., Sewell, R. P., Spreckelsen, T. F., & Richardson, A. J. (2014). Fatty acids and sleep in UK children: subjective and pilot objective sleep results from the DOLAB study – a randomized controlled trial. Journal of Sleep Research, 23(4), 364–388. http://doi.org/10.1111/jsr.12135
Alzoubi, K. H., Mayyas, F., & Zamzam, H. I. A. (2019). Omega-3 fatty acids protects against chronic sleep-deprivation induced memory impairment. Life Sciences, 227, 1–7. http://doi.org/10.1016/j.lfs.2019.04.028
Nasehi, M., Mosavi-Nezhad, S.-M., Khakpai, F., & Zarrindast, M.-R. (2018). The role of omega-3 on modulation of cognitive deficiency induced by REM sleep deprivation in rats. Behavioural Brain Research, 351, 152–160. http://doi.org/10.1016/j.bbr.2018.06.002
Jahangard, L., Sadeghi, A., Ahmadpanah, M., Holsboer-Trachsler, E., Bahmani, D. S., Haghighi, M., & Brand, S. (2018). Influence of adjuvant omega-3-polyunsaturated fatty acids on depression, sleep, and emotion regulation among outpatients with major depressive disorders – Results from a double-blind, randomized and placebo-controlled clinical trial. Journal of Psychiatric Research, 107, 48–56. http://doi.org/10.1016/j.jpsychires.2018.09.016
Scorza, F. A., Cavalheiro, E. A., Scorza, C. A., Galduróz, J. C. F., Tufik, S., & Andersen, M. L. (2013). Sleep Apnea and Inflammation – Getting a Good Night’s Sleep with Omega-3 Supplementation. Frontiers in Neurology, 4. http://doi.org/10.3389/fneur.2013.00193
Hansen, A. L., Dahl, L., Olson, G., Thornton, D., Graff, I. E., Frøyland, L., … Pallesen, S. (2014). Fish Consumption, Sleep, Daily Functioning, and Heart Rate Variability. Journal of Clinical Sleep Medicine, 10(05), 567–575. http://doi.org/10.5664/jcsm.3714
Xie, L., Kang, H., Xu, Q., Chen, M. J., Liao, Y., Thiyagarajan, M., … Nedergaard, M. (2013). Sleep Drives Metabolite Clearance from the Adult Brain. Science, 342(6156), 373–377. http://doi.org/10.1126/science.1241224
Varshavsky, A. (2012). Augmented generation of protein fragments during wakefulness as the molecular cause of sleep: a hypothesis. Protein Science, 21(11), 1634–1661. http://doi.org/10.1002/pro.2148
Mackiewicz, M., Shockley, K. R., Romer, M. A., Galante, R. J., Zimmerman, J. E., Naidoo, N., … Pack, A. I. (2007). Macromolecule biosynthesis: a key function of sleep. Physiological Genomics, 31(3), 441–457. http://doi.org/10.1152/physiolgenomics.00275.2006
Scharf, M. T., Naidoo, N., Zimmerman, J. E., & Pack, A. I. (2008). The energy hypothesis of sleep revisited. Progress in Neurobiology, 86(3), 264–280. http://doi.org/10.1016/j.pneurobio.2008.08.003
Horne, J. (2009). REM sleep, energy balance and ‘optimal foraging.’ Neuroscience & Biobehavioral Reviews, 33(3), 466–474. http://doi.org/10.1016/j.neubiorev.2008.12.002
Berger, R. J., & Phillips, N. H. (1995). Energy conservation and sleep. Behavioural Brain Research, 69(1-2), 65–73. http://doi.org/10.1016/0166-4328(95)00002-b
Benington, J. H., & Heller, H. C. (1995). Restoration of brain energy metabolism as the function of sleep. Progress in Neurobiology, 45(4), 347–360. http://doi.org/10.1016/0301-0082(94)00057-o
Abel, T., Havekes, R., Saletin, J. M., & Walker, M. P. (2013). Sleep, Plasticity and Memory from Molecules to Whole-Brain Networks. Current Biology, 23(17). http://doi.org/10.1016/j.cub.2013.07.025
Rasch, B., & Born, J. (2013). About Sleeps Role in Memory. Physiological Reviews, 93(2), 681–766. http://doi.org/10.1152/physrev.00032.2012
Cirelli, C., & Tononi, G. (2008). Is Sleep Essential? PLoS Biology, 6(8). http://doi.org/10.1371/journal.pbio.0060216
Siegel, J. M. (2005). Clues to the functions of mammalian sleep. Nature, 437(7063), 1264–1271. http://doi.org/10.1038/nature04285
Campbell, S. S., & Tobler, I. (1984). Animal sleep: A review of sleep duration across phylogeny. Neuroscience & Biobehavioral Reviews, 8(3), 269–300. http://doi.org/10.1016/0149-7634(84)90054-x
Tobler, I. (1995). Is sleep fundamentally different between mammalian species? Behavioural Brain Research, 69(1-2), 35–41. http://doi.org/10.1016/0166-4328(95)00025-o
Tononi, G., & Cirelli, C. (2006). Sleep function and synaptic homeostasis. Sleep Medicine Reviews, 10(1), 49–62. http://doi.org/10.1016/j.smrv.2005.05.002
Dongen, H. P. A. V., Vitellaro, K. M., & Dinges, D. F. (2005). Individual Differences in Adult Human Sleep and Wakefulness: Leitmotif for a Research Agenda. Sleep, 28(4), 479–498. http://doi.org/10.1093/sleep/28.4.479
Vyazovskiy, V. V., & Delogu, A. (2014). NREM and REM Sleep. The Neuroscientist, 20(3), 203–219. http://doi.org/10.1177/1073858413518152
Mignot, E. (2008). Why We Sleep: The Temporal Organization of Recovery. PLoS Biology, 6(4). http://doi.org/10.1371/journal.pbio.0060106
Siegel, J. M. (2009). Sleep viewed as a state of adaptive inactivity. Nature Reviews Neuroscience, 10(10), 747–753. http://doi.org/10.1038/nrn2697
Horne, J. (2000). REM sleep — by default? Neuroscience & Biobehavioral Reviews, 24(8), 777–797. http://doi.org/10.1016/s0149-7634(00)00037-3
Baran, B., Pace-Schott, E. F., Ericson, C., & Spencer, R. M. C. (2012). Processing of Emotional Reactivity and Emotional Memory over Sleep. Journal of Neuroscience, 32(3), 1035–1042. http://doi.org/10.1523/jneurosci.2532-11.2012
Tononi, G., & Cirelli, C. (2014). Sleep and the Price of Plasticity: From Synaptic and Cellular Homeostasis to Memory Consolidation and Integration. Neuron, 81(1), 12–34. http://doi.org/10.1016/j.neuron.2013.12.025
Li, J., Vitiello, M. V., & Gooneratne, N. S. (2018). Sleep in Normal Aging. Sleep Medicine Clinics, 13(1), 1–11. http://doi.org/10.1016/j.jsmc.2017.09.001
Murillo-Rodriguez, E., Arias-Carrion, O., Zavala-Garcia, A., Sarro-Ramirez, A., & Huitron-Resendiz, S. (2012). Basic Sleep Mechanisms: An Integrative Review. Central Nervous System Agents in Medicinal Chemistry, 12(1), 38–54. http://doi.org/10.2174/187152412800229107
Weber, F. D. (2018). Sleep: Eye-Opener Highlights Sleep’s Organization. Current Biology, 28(5). http://doi.org/10.1016/j.cub.2018.01.054
Yetton, B. D., Mcdevitt, E. A., Cellini, N., Shelton, C., & Mednick, S. C. (2018). Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks. Plos One, 13(4). http://doi.org/10.1371/journal.pone.0194604
Colrain, I. M., Nicholas, C. L., & Baker, F. C. (2014). Alcohol and the sleeping brain. Handbook of Clinical Neurology Alcohol and the Nervous System, 415–431. http://doi.org/10.1016/b978-0-444-62619-6.00024-0
Zisapel, N. (2018). New perspectives on the role of melatonin in human sleep, circadian rhythms and their regulation. British Journal of Pharmacology, 175(16), 3190–3199. http://doi.org/10.1111/bph.14116
Tosini, G., Baba, K., Hwang, C. K., & Iuvone, P. M. (2012). Melatonin: An underappreciated player in retinal physiology and pathophysiology. Experimental Eye Research, 103, 82–89. http://doi.org/10.1016/j.exer.2012.08.009
Blasiak, J., Reiter, R. J., & Kaarniranta, K. (2016). Melatonin in Retinal Physiology and Pathology: The Case of Age-Related Macular Degeneration. Oxidative Medicine and Cellular Longevity, 2016, 1–12. http://doi.org/10.1155/2016/6819736
Bellingham, J., Chaurasia, S. S., Melyan, Z., Liu, C., Cameron, M. A., Tarttelin, E. E., … Lucas, R. J. (2006). Evolution of Melanopsin Photoreceptors: Discovery and Characterization of a New Melanopsin in Nonmammalian Vertebrates. PLoS Biology, 4(8). http://doi.org/10.1371/journal.pbio.0040254
Zaidi, F. H., Hull, J. T., Peirson, S. N., Wulff, K., Aeschbach, D., Gooley, J. J., … Lockley, S. W. (2007). Short-Wavelength Light Sensitivity of Circadian, Pupillary, and Visual Awareness in Humans Lacking an Outer Retina. Current Biology, 17(24), 2122–2128. http://doi.org/10.1016/j.cub.2007.11.034
Legates, T. A., Altimus, C. M., Wang, H., Lee, H.-K., Yang, S., Zhao, H., … Hattar, S. (2012). Aberrant light directly impairs mood and learning through melanopsin-expressing neurons. Nature, 491(7425), 594–598. http://doi.org/10.1038/nature11673
Sikka, G., Hussmann, G. P., Pandey, D., Cao, S., Hori, D., Park, J. T., … Berkowitz, D. E. (2014). Melanopsin mediates light-dependent relaxation in blood vessels. Proceedings of the National Academy of Sciences, 111(50), 17977–17982. http://doi.org/10.1073/pnas.1420258111
Buhr, E. D., Yoo, S.-H., & Takahashi, J. S. (2010). Temperature as a Universal Resetting Cue for Mammalian Circadian Oscillators. Science, 330(6002), 379–385. http://doi.org/10.1126/science.1195262
Robbins, R., Grandner, M. A., Buxton, O. M., Hale, L., Buysse, D. J., Knutson, K. L., … Jean-Louis, G. (2019). Sleep myths: an expert-led study to identify false beliefs about sleep that impinge upon population sleep health practices. Sleep Health, 5(4), 409–417. http://doi.org/10.1016/j.sleh.2019.02.002
Damiola, F. (2000). Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes & Development, 14(23), 2950–2961. http://doi.org/10.1101/gad.183500
Abel, T., Havekes, R., Saletin, J. M., & Walker, M. P. (2013). Sleep, Plasticity and Memory from Molecules to Whole-Brain Networks. Current Biology, 23(17). http://doi.org/10.1016/j.cub.2013.07.025
Muzet, A., Ehrhart, J., Candas, V., Libert, J. P., & Vogt, J. J. (1983). Rem Sleep and Ambient Temperature in Man. International Journal of Neuroscience, 18(1-2), 117–125. http://doi.org/10.3109/00207458308985885
Saini, C., Morf, J., Stratmann, M., Gos, P., & Schibler, U. (2012). Simulated body temperature rhythms reveal the phase-shifting behavior and plasticity of mammalian circadian oscillators. Genes & Development, 26(6), 567–580. http://doi.org/10.1101/gad.183251.111
Franco P, Szliwowski H, Dramaix M, Kahn A. Influence of ambient temperature on sleep characteristics and autonomic nervous control in healthy infants. Sleep. 2000 May 1;23(3):401-7. https://pubmed.ncbi.nlm.nih.gov/10811384/
Libert JP, Candas V, Muzet A, Ehrhart J. Thermoregulatory adjustments to thermal transients during slow wave sleep and REM sleep in man. J Physiol (Paris). 1982;78(3):251-7 https://pubmed.ncbi.nlm.nih.gov/7166740/
Palca, J. W., Walker, J. M., & Berger, R. J. (1986). Thermoregulation, metabolism, and stages of sleep in cold-exposed men. Journal of Applied Physiology, 61(3), 940–947. http://doi.org/10.1152/jappl.1986.61.3.940
Lack. (2009). Chronotype differences in circadian rhythms of temperature, melatonin, and sleepiness as measured in a modified constant routine protocol. Nature and Science of Sleep, 1. http://doi.org/10.2147/nss.s6234
Samson, D. R., Crittenden, A. N., Mabulla, I. A., Mabulla, A. Z. P., & Nunn, C. L. (2017). Chronotype variation drives night-time sentinel-like behaviour in hunter–gatherers. Proceedings of the Royal Society B: Biological Sciences, 284(1858), 20170967. http://doi.org/10.1098/rspb.2017.0967
Walker, R. J., Kribs, Z. D., Christopher, A. N., Shewach, O. R., & Wieth, M. B. (2014). Age, the Big Five, and time-of-day preference: A mediational model. Personality and Individual Differences, 56, 170–174. http://doi.org/10.1016/j.paid.2013.09.003
Bjorness, T., & Greene, R. (2009). Adenosine and Sleep. Current Neuropharmacology, 7(3), 238–245. http://doi.org/10.2174/157015909789152182
Dworak, M., Diel, P., Voss, S., Hollmann, W., & Strüder, H. (2007). Intense exercise increases adenosine concentrations in rat brain: Implications for a homeostatic sleep drive. Neuroscience, 150(4), 789–795. http://doi.org/10.1016/j.neuroscience.2007.09.062
Rainnie, D., Grunze, H., Mccarley, R., & Greene, R. (1994). Adenosine inhibition of mesopontine cholinergic neurons: implications for EEG arousal. Science, 263(5147), 689–692. http://doi.org/10.1126/science.8303279
Daly, J. W., Shi, D., Nikodijevic, O., & Jacobson, K. A. (1994). The role of adenosine receptors in the central action of caffeine. Pharmacopsychoecologia, 7(2), 201–213. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4373791/
