Sleep and the sleep-wake rhythm are essential for children's health and well-being, yet reference values are lacking. This study therefore aimed to assess actigraphic estimates of sleep and the 24h sleep-wake rhythm, as well as 6-sulfatoxymelatonin (aMT6s) levels in healthy children of different age groups. Additionally, relationships between the outcomes and sex, highest parental educational level (as an indication of socioeconomic status (SES)), and body-mass-index (BMI) were explored. In this cross-sectional study, healthy Dutch children (2-18 years) wore an actigraph (GT3x) for 7 consecutive days, collected first-morning void urine and completed a sleep log and sociodemographic questionnaire. Actigraphically estimated sleep variables were sleep onset latency (SOL), sleep efficiency (SE), total sleep time (TST), and wake after sleep onset (WASO). Nonparametric sleep-wake rhythm variables were intradaily variability (IV); interdaily stability (IS); the activity counts and timing of the least active 5-h period (L5counts and midpoint) and of the most active 10-h period (M10 counts and midpoint); and the relative amplitude (RA), i.e. the ratio of the difference and the sum of M10 and L5 counts. Finally, creatinine-corrected aMT6s levels were obtained by isotope dilution mass spectrometry. Effects of age group (preschool 2-5 years/schoolaged 6-12 years/teenager 13-18 years), sex, highest parental educational level and BMI (Z-scores) were explored. Ninety-four children participated, equally divided across age groups (53% boys). Teenagers slept less, but more efficiently, than younger children, while their 24 h sleep-wake rhythm was the least stable and most fragmented (likely due to fragmentation of daytime activity). Additionally, aMT6s levels significantly declined over the age groups. Children from highly educated parents had lower sleep efficiency, but a more stable sleep-wake rhythm. Finally, sex or increase in BMI was not associated with any of the outcomes in this study. In conclusion, this study provides reference values of healthy children across different age groups and different sociodemographic factors. In the future, this information may help to better interpret outcomes in clinical populations.
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