A study analyzing data from 5 million nights of sleep in about 33,000 people found that your sleep tracker might reveal more than how well you sleep. It could also indicate chronic conditions like diabetes and sleep apnea and illnesses such as COVID-19.
Researchers identified five main types of sleep patterns, called sleep phenotypes, with 13 subtypes. They discovered that how often a person switches between these patterns could provide much more insight into their health than just their average sleep type.
Researchers used data from the Oura Ring, a smart ring that monitors sleep, skin temperature, and other metrics, to study individuals over several months. They tracked whether these individuals had chronic conditions like diabetes or sleep apnea or illnesses such as COVID-19 and the flu.
The study revealed that people often shift between different sleep patterns over time, which correlates with changes in their health conditions. This shifting pattern resembles a person’s journey through a detailed sleep landscape created by the researchers.
Benjamin Smarr, a senior author of the study from the University of California San Diego, explained, “We found that small changes in sleep quality helped us spot health risks. These changes wouldn’t be noticeable on an average night or in a questionnaire, highlighting how wearables can detect risks that might otherwise go unnoticed.”
The researchers emphasized that tracking changes in sleep over a long period across a large population could reveal valuable insights for public health. These insights might include early signs of chronic illness or susceptibility to infections through shifts in sleep patterns.
Researchers identified five distinct types of sleep patterns based on their data analysis from 5 million nights of sleep among approximately 33,000 people. Here’s a summary of each sleep phenotype:
- Phenotype 1: This resembles “normal” sleep, where individuals consistently get about eight hours of uninterrupted sleep for at least six consecutive nights, as recommended by health guidelines. It was the most common type observed.
- Phenotype 2: Individuals in this group sleep continuously for about half the night, but they sleep in short bouts of less than three hours on the other half.
- Phenotype 3: People in this category mostly sleep continuously, except for one night per week when they experience interrupted sleep. This night typically includes one longer period of sleep (around five hours) and one shorter period (less than three hours).
- Phenotype 4: Similar to Phenotype 3, individuals here mostly sleep without interruption but occasionally experience nights where more prolonged sleep bouts are separated by waking up in the middle of the night.
- Phenotype 5: This is characterized by very short periods of sleep each night, indicating highly disrupted sleep. It was the least common phenotype observed in the study.
These sleep phenotypes help researchers understand different sleep patterns across populations, shedding light on how sleep quality and continuity vary among individuals.
To study changes in sleep patterns over time, Viswanath created a model where each night’s sleep phenotype was like an island in a spatial map. These islands represented weeks of similar sleep patterns. By tracking individuals’ movements between these islands, researchers identified how their sleep patterns evolved.
Interestingly, for individuals with chronic conditions like diabetes or sleep apnea, what mattered most wasn’t their average sleep pattern. Instead, it was how often they switched between different islands in this sleep landscape. Even occasional switches provided valuable health insights.
The data revealed that most people experience some nights of disrupted sleep occasionally.
Researchers found that the specific ways disruptions occur can tell us a lot. Even if they’re rare, their frequency matters, too. It’s not just about how well you sleep each night but also about your sleep patterns over time.
People didn’t tend to stay permanently in patterns of disrupted sleep, but the frequency of visits to these patterns was a key indicator of their well-being.
“If you think of a landscape of sleep types, it’s less about where you usually sleep and more about how often you move between different areas,” added Viswanath, the paper’s lead author.
In their paper published on June 20, the research team improved upon previous studies by refining techniques used in the most significant prior investigation of sleep. The earlier study, drawing data from around 103,000 nights in the UK Biobank, focused on sleep timing and awakenings but needed more longitudinal data and connections to health outcomes.
Unlike earlier research that primarily examined superficial sleep characteristics like total sleep time, this new study innovates by quantifying how people’s sleep patterns change over time. It shows for the first time that tracking these changes can provide deeper insights into sleep health and potentially identify risks for various health conditions.
Journal reference:
- Viswanath, V.K., Hartogenesis, W., Dilchert, S. et al. Five million nights: temporal dynamics in human sleep phenotypes. npj Digital Medicine. DOI: 10.1038/s41746-024-01125-5.