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

Author:

Moreno Jennette P1ORCID,Hannay Kevin M23,Walch Olivia34,Dadabhoy Hafza1,Christian Jessica1,Puyau Maurice1,El-Mubasher Abeer1,Bacha Fida1ORCID,Grant Sarah R1,Park Rebekah Julie1,Cheng Philip5ORCID

Affiliation:

1. Department of Pediatrics, USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine , Houston, TX , USA

2. Department of Mathematics, University of Michigan , Ann Arbor, MI , USA

3. Arcascope Inc. , Chantilly, VA , USA

4. Department of Neurology, University of Michigan , Ann Arbor, MI , USA

5. Thomas Roth Sleep Disorders and Research Center, Henry Ford Health System , Detroit, MI , USA

Abstract

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 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.

Funder

Eunice Kennedy Shriver National Institute of Child Health and Human Development

National Institutes of Health

USDA

ARS

National Heart, Lung, and Blood Institute

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Physiology (medical),Neurology (clinical)

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