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. 2021 Nov 9;2(4):658-666.
doi: 10.1093/ehjdh/ztab088. eCollection 2021 Dec.

Accelerometer-derived sleep onset timing and cardiovascular disease incidence: a UK Biobank cohort study

Affiliations

Accelerometer-derived sleep onset timing and cardiovascular disease incidence: a UK Biobank cohort study

Shahram Nikbakhtian et al. Eur Heart J Digit Health. .

Abstract

Aims: Growing evidence suggests that poor sleep health is associated with cardiovascular risk. However, research in this area often relies upon recollection dependent questionnaires or diaries. Accelerometers provide an alternative tool for measuring sleep parameters objectively. This study examines the association between wrist-worn accelerometer-derived sleep onset timing and cardiovascular disease (CVD).

Methods and results: We derived sleep onset and waking up time from accelerometer data collected from 103 712 UK Biobank participants over a period of 7 days. From this, we examined the association between sleep onset timing and CVD incidence using a series of Cox proportional hazards models. A total of 3172 cases of CVD were reported during a mean follow-up period of 5.7 (±0.49) years. An age- and sex-controlled base analysis found that sleep onset time of 10:00 p.m.-10:59 p.m. was associated with the lowest CVD incidence. An additional model, controlling for sleep duration, sleep irregularity, and established CVD risk factors, did not attenuate this association, producing hazard ratios of 1.24 (95% confidence interval, 1.10-1.39; P < 0.005), 1.12 (1.01-1.25; P = 0.04), and 1.25 (1.02-1.52; P = 0.03) for sleep onset <10:00 p.m., 11:00 p.m.-11:59 p.m., and ≥12:00 a.m., respectively, compared to 10:00 p.m.-10:59 p.m. Importantly, sensitivity analyses revealed this association with increased CVD risk was stronger in females, with only sleep onset <10:00 p.m. significant for males.

Conclusions: Our findings suggest the possibility of a relationship between sleep onset timing and risk of developing CVD, particularly for women. We also demonstrate the potential utility of collecting information about sleep parameters via accelerometry-capable wearable devices, which may serve as novel cardiovascular risk indicators.

Keywords: Cardiovascular health; Circadian rhythm; Digital health; Sleep; UK Biobank.

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Figures

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Graphical abstract
Figure 1
Figure 1
Flow of participants through the study.
Figure 2
Figure 2
Kaplan–Meier curves for cardiovascular disease incidence against time to occurrence, split by sleep onset time.
Figure 3
Figure 3
Histogram showing the relationship between sleep onset time and cardiovascular disease incidence rate for: (A) the overall sample, (B) males, and (C) females. The black line indicates the mean cardiovascular disease incidence rate per 30-min increments. Blue and green lines indicate 95% confidence intervals.

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