Categories
Circadian Personal Sleeping Troubles

Measuring Sleep Regularity

What is sleep regularity and why is it important?

Sleep regularity is a gauge of how consistent a person’s sleep patterns are, based on the day-to-day variability in their sleep–wake times. In general, having poorer sleep regularity, or irregular sleep patterns, has been shown to lead to many adverse outcomes in metabolism, mental health, and cognitive performance. Low sleep regularity has even been linked to increased inflammation. In order to avoid these and other complications, you want to increase your sleep regularity by aiming to get into bed at the same time every night.

How can we score sleep regularity?

There are at least five different metrics that can be used to quantify sleep regularity, each capturing different aspects of it and useful in its own way. The five measures of sleep regularity that we’ll look at in this blog post are listed below:

Traditional/Overall Metrics:

  • Individual Standard Deviation (StDev)
  • Interdaily Stability (IS)
  • Social Jet Lag (SJL)

Newer Metrics:

  • Composite Phase Deviation (CPD)
  • Sleep Regularity Index (SRI)

Traditionally, the most common overall metrics that have been used to assess sleep regularity are quantified by measuring sleep deviations in sleep patterns from an individual’s average. Examples of overall metrics are StDev and IS, both of which compare sleep from each day to an average sleep–wake pattern, and SJL, a metric that compares two average sleep patterns (workdays and free days).

StDev: lower is more regular / StDev⬇ = Sleep regularity⬆

This score is just the standard deviation of your sleep metric of choice, like sleep onset, sleep offset, or sleep midpoint. The standard deviation captures the variation of a quantity from its mean. 

IS: higher is more regular / IS⬆ = Sleep regularity⬆

This metric uses sleep-wake data (can also use rest-activity data) over a period of days to measure the stability of a person’s sleep-wake rhythms. It does this by comparing the pattern of daily sleep activity to the average pattern across many days. 

SJL: lower is more regular / SJL⬇ = Sleep regularity⬆

Social jet lag is a metric that quantifies the mismatch in the average mid-sleep timing between workdays and free days. Negative SJL values represent earlier mid-sleep timing on weekends than weekdays while positive values indicate the opposite.

Two newer measures of sleep regularity are CPD and SRI. These two fall under the category of consecutive metrics, which means they measure variability in sleep–wake patterns between consecutive days. The circadian system makes adjustments daily, and consecutive metrics were developed in order to utilize day-to-day information and more accurately predict circadian disruptions associated with poor sleep regularity.

CPD: Lower is more regular /  CPD⬇ = Sleep regularity⬆

Composite phase deviation is a metric that was created with shift workers in mind. CPD quantifies circadian disruption where sleep is both irregular (rotating shifts) and mistimed (sleeping in daytime). This metric uses an individual’s chronotype to determine optimal timing of sleep. The chronotype then helps to quantify how “mistimed” they are. The regularity aspect is calculated using the difference between mid-sleep timing from one day to that of the prior day. In order for CPD to be derived it requires data that has one main sleep session per day or some other daily sleep variable, like sleep duration.

SRI: higher is more regular /  SRI⬆ = Sleep regularity⬆

The sleep regularity index is a measure based on binary sleep-wake time series. It measures the similarity of a person’s sleep-wake pattern from one day to the next. The scale for this metric ranges from 0 (random) – 100 (perfectly regular) and it represents the percentage probability that an individual will be in the same sleep/wake state at any two time points. It’s important to note that this metric does not account for total sleep time so a person that (hypothetically) sleeps 0% of the time will still be able to get an SRI value of 100.

So I’m regular, that means I’m healthy right?

Well, not quite. Depending on the kind of variability you have in your sleep patterns and the method used to record your sleep, different metrics may tell you very different stories regarding your sleep regularity. Context is very important when making a decision about which sleep regularity metric to use. 

Just think about what would happen if you increased the variability in your work week sleep timing, but maintained a consistent average. Your SJL score would stay the same, while your other metrics would likely shift to indicate greater variability. The ordering of days also matters. In Fischer et al. they shuffle days around to show how consecutive metrics can give you different stories on regularity than overall metrics do.  

In order to properly assess sleep regularity for yourself or your patients, it is necessary to understand the little things that go into calculating each of these sleep metrics. A variety of unknowns, such as the type of data being gathered or the length of the data set, can cause these metrics to disagree with each other. The good news is that you’ve got lots of options to choose from. 

This blog post is heavily based on “Measuring sleep regularity: Theoretical properties and practical usage of existing metrics” by Fischer et al. The authors didn’t have anything to do with the making of this post, but we want to thank them for writing an inspiring paper. 

This post was written by Arcascope’s intern, Ali Abdalla. Thanks, Ali!