Human Sleep Falls Into at Least 16 Distinct Types, Large Data Study Finds

A systematic review of sleep data from more than 100,000 people in the United Kingdom has revealed 16 different ways to sleep. One day, the clusters will allow experts to diagnose insomnia in individuals.

The data from smart wristbands used by the United Kingdom Biobank was used to determine wakefulness and sleep patterns.

The real-world sleepscape that was the result of the long-term study showed quite the diversity of sleep cycle patterns.

There are five broad categories in the clusters. Those who fall in the first category experience insomnia with long sleep duration and wake up in the middle of the night.

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The clusters are divided into two groups, the b's and the 2's. The cluster of people who show irregular sleep schedules is probably an indication of shift work.

2b is defined by the authors as fragmented sleep with short sleep duration.

3a is a group of people who experience insomnia with normal sleep duration, and 4a is a group of people who suffer from insomnia with short sleep duration.

There are clusters of sleep types. Katori et al., PNAS, 2022.

The clusters 3b and 4b are further divided into eight subcategories of fragmented sleep.

3b-1 is a large group of people who sleep deeply but can't fall asleep easily once they wake up.

Another large cluster is 4b-1. 4b-2 houses all the morning people and 4b6 houses all the night people.

The authors define 4b-4 and 4b-5 as preinsomnia. Both clusters show normal wake-up durations in the middle of the night, but those in the former cluster wake and fall asleep frequently, which suggests they struggle to maintain sleep. Less fragmented sleep is shown in Cluster 4b-5.

Depending on whether someone is working or on holiday, 4b-3 has a shorter sleep-wake cycle that gets out of sync. This is also known as social jet lag.

There were eight clusters in the outlier dataset. Katori et al., PNAS, 2022.

The current research shows that the clusters are complex and diverse. They could prove clinically meaningful with future research.

Past studies suggest that insomnia marked by short sleep duration is linked to impaired cognitive function, while insomnia marked by normal sleep duration is linked to an anxious-ruminative profile.

Data recorded from people moving their arms during sleep could help identify those with insomnia and reveal those most at risk of developing mental or physical health issues.

We need more research to get to that stage. While other forms of brain and muscle measurement during sleep are too short-term to identify the nuances of social jet lag or morning/evening types, the clusters identified in this research still need to be verified further.

The authors hope that one day the clustering method will be linked with other personal information to help us better understand the status of an individual.

The study was published in a journal.