Reducing the amount of disruptions to your sleep and making sure you are well-rested each night can lower your ‘sleep age’ – and extend your life up to 8.7 years, study finds.
Lowering your sleep age by reducing the amount of disruptions, improving quality of rest and getting an adequate amount each night can help ward of diseases like Parkinson’s and extend a person’s life by reducing their ‘sleep age’, a new study finds.
A joint research team from Stanford University and the Danish Center for Sleep Medicine found a clear correlation between the estimated sleep age of a person and their life-span.
They used polysomnography tests (PSGs), which gauge multiple biometrics to determine sleep-quality and diagnose potential sleep issues in people to figure a person’s sleep age. Elderly people generally suffer more disturbances, and a decrease in quality of sleep can be an early sign that a person will develop a cognitive impairment like Parkinson’s, Alzheimer’s or dementia in the future.
- Researchers found that a person’s ‘sleep age’ is primarily determined by the amount of disruptions to their sleep each night.
- Reducing disruptions – and lowering sleep age – can help a person extend their lifespan.
- Sleep fragmentation is often one of the earliest signs that a person will eventually suffer from Alzheimer’s, Parkinson’s or dementia.
- Experts recommend a person keep a consistent sleep schedule, avoid alcohol and caffeine and create a comfortable sleep environment to stop disturbances.
Researchers, who published their findings in npj Digital Medicine, gathered data from 13,332 PSGs for the study.
These tests gauged a person’s airflow, nasal pressure, blood oxygen saturation and other metrics while they slept each night.
A PSG can detect disruptions in sleep by seeing when these metrics reach abnormal levels. It can also tell what stage of sleep a person is in, whether it is light, deep or rapid eye movement sleep – often known as REM.
Many of these disruptions are undetectable to the person who is sleeping. A person could wake up for less than a minute before immediately going back to bed – and never even remember that it occurred.
This means that many people who believe they are getting a full night of undisrupted sleep may be suffering a problem they are unaware of.
They used a machine-learning system to interpret the data from the PSGs and generated a ‘sleep age’ for each of the participants.
Why study sleep age?
When you sleep, you’re disconnected from sensory inputs — you’re, ideally, not being bothered by the noisy external world or bright lights.
During sleep, it’s not just the brain that’s going through an automatic program, but heart rate and breathing also change, and variations in these can be early predictors of a health disturbance. We spend about a third of our lives sleeping, so it’s a substantial component of our general well-being.
It’s well known that, in pretty much any disorder, sleep is one of the first things that is disturbed. For example, about five or 10 years before other symptoms appear in Parkinson’s disease patients, a specific sleep disturbance occurs during which the patient violently acts out dreams, shouts or punches into a wall.
What was the most important finding from the study?
Our main finding was that sleep fragmentation — when people wake up multiple times throughout the night for less than a minute without remembering it — was the strongest predictor of mortality. Though we see a link in the data, how it contributes to mortality is unknown. This is different from a person realizing they were waking up, which happens during sleep disorders such as insomnia.
Determining why sleep fragmentation is so detrimental to health is something we plan to study in the future.
Can we measure our own sleep age? Can it be improved?
The code is available for physicians and researchers, but the average person would likely have trouble running it through a computer. Regardless, it’s not deterministic. There is enormous variation. Even if you have an older sleep age than your chronological age, it doesn’t mean that your mortality risk is going to be higher. You see people chain smoking and drinking alcohol at 90 years old and you wonder, “How is this person surviving so long?” There is always huge natural variation.
Going to bed and waking up at regular hours is a key to improving your sleep. This means not oversleeping but ensuring you’re fully rested. It’s a different amount for everyone and often the window varies slightly — for example, being a night owl versus an early bird.
Getting solid light exposure — preferably with outside light — during the day, keeping the sleep environment dark at night, exercising regularly but not too close to bedtime, not drinking alcohol and caffeine around bedtime, and avoiding heavy nighttime meals all contribute to healthy sleep. And, of course, make sure any sleep disorder is treated.
How did you calculate sleep age in this study?
We used a machine learning program to predict sleep age by feeding sleep study data and each person’s age into these programs. This tells us what an average sleep looks like at a particular age. The algorithm recognizes patterns in the data and uses that information to predict a sleep age. Once the algorithm has been built out, we can use it to assign additional sleep ages. For some people, their sleep age looks much older than their chronological age.
We can use the difference between their chronological age and their sleep age to predict mortality, based on the idea that older sleep age is an indicator of a health problem. And, indeed, we found that people with older sleep ages compared to their actual age are at an increased risk of mortality, based on the sleep of patients who later died. From other studies, we know that poor sleep is found in a variety of conditions such as sleep apnea, neurodegeneration, obesity and chronic pain. How poor sleep causes, exacerbates or results from these conditions is unknown.
What are the next steps with your research?
I hope to use sleep studies to better predict and treat disease before it manifests into death. This study included only 12,000 people. In the future, we will try to predict the future occurrence of heart attacks, strokes and Alzheimer’s disease that cause mortality.
We are working with scientists from Harvard University to collect 250,000 sleep studies. Much of the data in this larger set was collected 10 years ago, allowing us to make better mortality predictions.
Can you imagine if we could use sleep studies to predict a person’s heart attack risk and then use that information to start early interventions? That would be a big deal.