Literature DB >> 35275213

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

Jennette P Moreno1, Kevin M Hannay2,3, Olivia Walch3,4, Hafza Dadabhoy1, Jessica Christian1, Maurice Puyau1, Abeer El-Mubasher1, Fida Bacha1, Sarah R Grant1, Rebekah Julie Park1, Philip Cheng5.   

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.
© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  actigraphy; children; circadian rhythm; mathematical model; wearable data

Mesh:

Substances:

Year:  2022        PMID: 35275213      PMCID: PMC9189953          DOI: 10.1093/sleep/zsac061

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   6.313


  47 in total

1.  Influence of light at night on melatonin suppression in children.

Authors:  Shigekazu Higuchi; Yuki Nagafuchi; Sang-il Lee; Tetsuo Harada
Journal:  J Clin Endocrinol Metab       Date:  2014-05-19       Impact factor: 5.958

2.  Finding DLMO: estimating dim light melatonin onset from sleep markers derived from questionnaires, diaries and actigraphy.

Authors:  Andrew M Reiter; Charli Sargent; Gregory D Roach
Journal:  Chronobiol Int       Date:  2020-09-07       Impact factor: 2.877

3.  Activity-based sleep-wake identification: an empirical test of methodological issues.

Authors:  A Sadeh; K M Sharkey; M A Carskadon
Journal:  Sleep       Date:  1994-04       Impact factor: 5.849

Review 4.  Delayed sleep phase syndrome and bipolar disorder: Pathogenesis and available common biomarkers.

Authors:  Farid Talih; Nour Y Gebara; Farah S Andary; Stefania Mondello; Firas Kobeissy; Raffaele Ferri
Journal:  Sleep Med Rev       Date:  2018-02-13       Impact factor: 11.609

Review 5.  Chronobesity: role of the circadian system in the obesity epidemic.

Authors:  J Laermans; I Depoortere
Journal:  Obes Rev       Date:  2015-12-23       Impact factor: 9.213

6.  The dim light melatonin onset following fixed and free sleep schedules.

Authors:  Helen J Burgess; Charmane I Eastman
Journal:  J Sleep Res       Date:  2005-09       Impact factor: 3.981

Review 7.  The role of actigraphy in the study of sleep and circadian rhythms.

Authors:  Sonia Ancoli-Israel; Roger Cole; Cathy Alessi; Mark Chambers; William Moorcroft; Charles P Pollak
Journal:  Sleep       Date:  2003-05-01       Impact factor: 5.849

8.  The wrist is not the brain: Estimation of sleep by clinical and consumer wearable actigraphy devices is impacted by multiple patient- and device-specific factors.

Authors:  Rachel Danzig; Mengxi Wang; Amit Shah; Lynn Marie Trotti
Journal:  J Sleep Res       Date:  2019-10-17       Impact factor: 3.981

9.  Circadian rest-activity patterns in bipolar disorder and borderline personality disorder.

Authors:  Niall M McGowan; Guy M Goodwin; Amy C Bilderbeck; Kate E A Saunders
Journal:  Transl Psychiatry       Date:  2019-08-20       Impact factor: 6.222

Review 10.  Overview of circadian rhythms.

Authors:  M H Vitaterna; J S Takahashi; F W Turek
Journal:  Alcohol Res Health       Date:  2001
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  1 in total

1.  Evaluation of a Circadian Rhythm and Sleep-Focused Mobile Health Intervention for the Prevention of Accelerated Summer Weight Gain Among Elementary School-Age Children: Protocol for a Randomized Controlled Feasibility Study.

Authors:  Jennette P Moreno; Hafza Dadabhoy; Salma Musaad; Tom Baranowski; Debbe Thompson; Candice A Alfano; Stephanie J Crowley
Journal:  JMIR Res Protoc       Date:  2022-05-16
  1 in total

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