0005 Validation and Comparison of Mathematical Models to Predict Circadian Phase Among Preschoolers
Abstract
Having a later circadian phase is linked to risks for childhood obesity, which often persists into adulthood and is strongly related to metabolic disease risk-associated conditions, now increasingly observed in early childhood. However, accurately assessing circadian phase in young children is challenging. Mathematical models within applied mathematics provide a promising approach. This study aimed to validate and compare two models, the physics-based Forger and physiologically informed Hannay model, to advance circadian phase predictions using activity inputs in preschoolers.
As part of an ongoing randomized controlled trial, 69 parents of 4-year-old preschoolers (55.6% male, Latino 37.5%) completed 7-day wrist-worn actigraphy before a lab visit, during which dim light melatonin onset (DLMO) was assessed. Salivary melatonin was sampled hourly under dim-light conditions (< 5 lx). Actigraphy data were used to predict circadian phase. Model simulations were conducted using Runge-Kutta 45 numerical integration written in Python. Lin’s Concordance Correlation Coefficient (LinCCC) was used to assess agreement between model-predicted DLMO and salivary DLMO. The Mean Absolute Error (MAE) and percentage of participants with a predicted DLMO within 1hr of measured DLMO were calculated. The Bland-Altman method was used to evaluate bias between two methods and to estimate an agreement interval within which 95% of the differences fall. A sensitivity test was also conducted, excluding…
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Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
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