Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children

Abstract

Study objectives Sleep plays an important role in cardiometabolic health. While the importance of considering sleep as a multidimensional construct is widely appreciated, studies have largely focused on individual sleep characteristics. The association between actigraphy-derived sleep profiles and cardiometabolic health in healthy adults and children has not been examined. Methods This study used actigraphy-measured sleep data collected between February 2015 and March 2016 in the Child Health CheckPoint study. Participants wore actigraphy monitors (GENEActiv Original, Cambs, UK) on their non-dominant wrist for seven days and sleep characteristics (period, efficiency, timing and variability) were derived from raw actigraphy data. Actigraphy-derived sleep profiles of 1,043 Australian children aged 11-12 years and 1337 adults were determined using K-means cluster analysis. The association between cluster membership and biomarkers of cardiometabolic health (blood pressure, body mass index, apolipoproteins, glycoprotein acetyls, composite metabolic syndrome severity score) were assessed using Generalised Estimating Equations, adjusting for geographic clustering, with sex, socioeconomic status, maturity stage (age for adults, pubertal status for children) and season of data collection as covariates. Results Four actigraphy-derived sleep profiles were identified in both children and adults: Short sleepers, Late to bed, Long sleepers, and Overall good sleepers. The Overall good sleeper pattern (characterised by adequate sleep period time, high efficiency, early bedtime and low day-to-day variability) was associated with better cardiometabolic health in the majority of comparisons (80%). Conclusion Actigraphy-derived sleep profiles are associated with cardiometabolic health in adults and children. The Overall good sleeper pattern is associated with more favourable cardiometabolic health.

Accelerometry‐assessed sleep clusters and cardiometabolic risk factors in adolescents

“…Several studies have identified sleep patterns by comprehensively considering multiple objectively assessed sleep characteristics, including cluster analysis [10,27], latent class analysis [28,29], and composite sleep scores considering self-reported sleep behaviors [30], but only a few studies have been conducted in children and adolescents. [36].…”

“…Cluster analysis provides the ability to consider multidimensional sleep characteristics from a holistic perspective [9]. To date, only one study has applied this approach to identify sleep patterns and explored their relationships with cardiometabolic health in children and adults using accelerometry-measured sleep data [10]. Four patterns were identified, and the "overall good sleepers" pattern was associated with more favorable body mass index (BMI) and metabolic syndrome severity score.…”

Effects of Montmorency Tart Cherry and Blueberry Juice on Cardiometabolic Outcomes in Healthy Individuals: Protocol for a 3-Arm Placebo Randomized Controlled Trial

“…Sleep quality is diminished in patients with cardiometabolic disease [ 54 ] and intake of dietary polyphenols [ 55 ], and supplementation of Montmorency tart cherry has been demonstrated to enhance sleep quality and symptoms of insomnolence [ 56 , 57 ]. Therefore, general sleep quality will be examined using the Pittsburgh sleep quality index [ 58 ], daytime sleepiness using the Epworth Sleepiness Scale [ 59 ] and symptoms of insomnolence via the Insomnia Severity Index [ 60 ].…”

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“…Certain adverse childhood experiences such as physical, sexual, and emotional abuse and neglect have a lasting impact on sleep quality in adulthood, highlighting the need to mitigate their impact to prevent negative health outcomes associated with poor sleep quality. [15]…”