Title

Estimating Circadian Phase in Elementary School Children: Leveraging Advances in Physiologically-Informed Models of Circadian Entrainment and Wearable Devices

Document Type

Article

Publication Date

3-11-2022

Publication Title

Sleep

Abstract

STUDY OBJECTIVES: Examine the ability of a physiologically based mathematical model of human circadian rhythms to predict circadian phase, as measured by salivary dim light melatonin onset (DLMO), in children compared to other proxy measurements of circadian phase (bedtime, sleep midpoint, and waketime).

METHODS: As part of an ongoing clinical trial, a sample of 29 elementary school children (mean age: 7.4 +/- .97 years) completed 7 days of wrist actigraphy before a lab visit to assess DLMO. Hourly salivary melatonin samples were collected under dim light conditions (< 5 lux). Data from actigraphy were used to generate predictions of circadian phase using both a physiologically based circadian limit cycle oscillator mathematical model (Hannay model), and published regression equations that utilize average sleep onset, midpoint, and offset to predict DLMO. Agreement of proxy predictions with measured DLMO were assessed and compared.

RESULTS: DLMO predictions using the Hannay model outperformed DLMO predictions based on children's sleep/wake parameters with a Lin's Concordance Correlation Coefficient (LinCCC) of 0.79 compared to 0.41 - 0.59 for sleep/wake parameters. The mean absolute error was 31 minutes for the Hannay model compared to 35 - 38 minutes for the sleep/wake variables.

CONCLUSION: Our findings suggest sleep-wake behaviors were weak proxies of DLMO phase in children, but mathematical models using data collected from wearable data can be used to improve the accuracy of those predictions. Additional research is needed to better adapt these adult models for use in children.

PubMed ID

35275213

ePublication

ePub ahead of print

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