Wearable metric

Sleep efficiency

SE

The fraction of time in bed actually spent asleep — the single most actionable wearable sleep metric.

Moderate relevance1 cited sourceNo fastingFree with device.sleep

What it measures

Total sleep time divided by total time in bed, expressed as a percentage. Captures both sleep latency (time to fall asleep) and wake-after-sleep-onset. Validated against polysomnography in modern wearables (Oura, Whoop, Apple Watch) with reasonable but imperfect accuracy.

Reference context

2 guideline sources

Younger adults typically achieve 88–92% efficiency. Efficiency declines slightly with age — 80–85% in healthy older adults is normal. Wearable measurements tend to overestimate sleep efficiency compared with polysomnography by 5–10%.

Population context — consult guideline targets below

Mechanism

Why moving this marker matters

Low sleep efficiency reflects fragmented or insufficient sleep, both of which independently associate with impaired glucose tolerance, cardiovascular risk, mood disturbance, and cognitive performance.

Guideline targets

What major guidelines recommend

AASM (healthy adults)

Strong

≥85%

AASM (insomnia threshold)

Strong

<85% consistently with subjective complaint warrants evaluation

How to measure

The test, where to get it, when to repeat

Method

Computed automatically by sleep-tracking wearables overnight. Manual estimate possible with a sleep diary.

Where

Free with any sleep-tracking wearable.

Typical cost

Free with device.

Fasting

Not required

When to test

  • AASM 2015

    Track over weekly rolling averages; identify patterns rather than fixating on single nights.

How to track

Devices and apps that measure this

These consumer wearables and connected devices report this metric. Healicus is not connected to your device — your data lives in the maker's app and never reaches us.

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Context

Reading the numbers

Younger adults typically achieve 88–92% efficiency. Efficiency declines slightly with age — 80–85% in healthy older adults is normal. Wearable measurements tend to overestimate sleep efficiency compared with polysomnography by 5–10%.

Caveats

Wearable algorithms are most accurate for total sleep time and least accurate for sleep stages. Use efficiency and total sleep time as the actionable metrics; treat stage breakdowns with skepticism.

See also

Related markers

Take to your physician

Worth discussing

  • If sleep efficiency is consistently <80% with daytime symptoms, whether sleep apnea workup is warranted.
  • Whether CBT-i would be appropriate if efficiency is low due to insomnia rather than sleep apnea.
  • How to interpret stage breakdowns from your wearable in context of overall sleep quality.

Sources

Cited literature

Edited by Carl Pöhl, MD · Healicus editorial

Last reviewed May 2026

Educational reference. Population-level information for the longevity-curious reader. Healicus does not compute scores, interpret your specific values, or produce personalised recommendations from your clinical data. Discuss your own results and any decisions with your physician.

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