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“Sleep age” could predict health and lifespan

A research team led by Stanford University has developed a new metric called “sleep age” which they hope could help clinicians predict emerging health issues and even mortality. Sleep age is a projected age which correlates to an individual health based on their chronological age and quality of sleep.

According to the experts, people with older sleep ages compared to their actual age are at an increased risk of mortality, and often suffer from various diseases, including sleep apnea, neurodegeneration, obesity, and chronic pain. However, how poor sleep causes, exacerbates, or results from such health conditions remains unclear.

By analyzing the sleeping patterns of over 12,000 individuals and feeding the data into a machine learning algorithm, the scientists manage to develop a system that could reliably assign one’s sleep age and identify the variations in sleep more closely related to illness and mortality. They discovered that sleep fragmentation – waking up multiple times throughout the night for less than a minute without remembering it – was the strongest predictor of mortality. However, how this contributes to mortality is not yet clear.

Moreover, the researchers stressed that a person’s sleep age is not necessarily 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,” explained study senior author Emmanuel Mignot, an expert in Sleep Medicine at Stanford.

According to Professor Mignot, going to bed and waking up at regular hours is key to improving sleep. In addition, “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.”

In further research, the scientists aim to extend their cohort and refine their algorithms in order to use this newly developed metric to predict more accurately the future occurrence of illnesses such as heart disease, strokes, or Alzheimer’s. “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,” Professor Mignot concluded.

The study is published in the journal npj Digital Medicine.

By Andrei Ionescu, Staff Writer  

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