Subjective sleep quality is poorly associated with actigraphy and heart rate measures in community-dwelling older men

There has been a proliferation in the use of commercially-available accelerometry- and heart rate-based wearable devices to monitor sleep. While the underlying technology is reasonable at detecting sleep quantity, the ability of these devices to predict subjective sleep quality is currently unknown. We tested whether the fundamental signals from such devices are useful in determining subjective sleep quality.

Older, community-dwelling men (76.5 ± 5.77 years) enrolled in the Osteoporotic Fractures in Men Study (MrOS) participated in an overnight sleep study during which sleep was monitored with actigraphy (wrist-worn accelerometry) and polysomnography (PSG), including electrocardiography (N = 1141). Subjective sleep quality was determined the next morning using 5-point Likert-type scales of sleep depth and restfulness. Lasso and random forest regression models analyzed the relationship between actigraph-determined sleep variables, the shape of the activity patterns during sleep (functional principal component analysis), average heart rate, heart rate variability (HRV), demographics, and self-reported depression, anxiety, habitual sleep, and daytime sleepiness measures.

Actigraphy data, in combination with heart rate, HRV, demographic, and psychological variables, do not predict well subjective sleep quality (R² = 0.025 to 0.162).

Findings are consistent with previous studies that objective sleep measures are not well correlated with subjective sleep quality. Developing validated biomarkers of subjective sleep quality could improve both existing and novel treatment modalities and advance sleep medicine towards precision healthcare standards.