Estimating circadian phase in elementary school children: leveraging advances in physiologically informed models of circadian entrainment and wearable devices

Mar 11, 2022Sleep

Estimating Body Clock Timing in Elementary School Children Using Improved Models and Wearable Devices

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Circadian Biology on OpenScience ↗PubMed ↗DOI ↗

Abstract

A physiologically based mathematical model predicted circadian phase with a Lin's Concordance Correlation Coefficient of 0.79 in children.

Predictions of dim light melatonin onset (DLMO) using the Hannay model were more accurate than those based on sleep/wake parameters.
The mean absolute error for the Hannay model was 31 minutes, compared to 35-38 minutes for sleep/wake variables.
Sleep/wake behaviors were found to be weak proxies for DLMO phase in children.
Data collected from wearable devices may improve the accuracy of circadian phase predictions.
Further research is needed to adapt adult mathematical models for use in children.

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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 wake time).

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 lx). 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 min for the Hannay model compared to 35-38 min for the sleep/wake variables.

CONCLUSION: Our findings suggest that 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.

CLINICAL TRIAL: The i Heart Rhythm Project: Healthy Sleep and Behavioral Rhythms for Obesity Prevention https://clinicaltrials.gov/ct2/show/NCT04445740.

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Estimating circadian phase in elementary school children: leveraging advances in physiologically informed models of circadian entrainment and wearable devices

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