• Nevin Hammam, Dorna Sadeghi, Valerie Carson, Sukhpreet K Tamana, Victor E Ezeugwu, Joyce Chikuma, Charmaine van Eeden, Jeffrey R Brook, Diana L Lefebvre, Theo J Moraes, Padmaja Subbarao, Allan B Becker, Stuart E Turvey, Malcolm R Sears, and Piushkumar J Mandhane.
• Department of Pediatrics, University of Alberta, Edmonton, AB, Canada.
• Sleep. 2020 Dec 14; 43 (12).

Study ObjectivesMachine learning (ML) may provide insights into the underlying sleep stages of accelerometer-assessed sleep duration. We examined associations between ML-sleep patterns and behavior problems among preschool children.MethodsChildren from the CHILD Cohort Edmonton site with actigraphy and behavior data at 3-years (n = 330) and 5-years (n = 304) were included. Parent-reported behavior problems were assessed by the Child Behavior Checklist. The Hidden Markov Model (HMM) classification method was used for ML analysis of the accelerometer sleep period. The average time each participant spent in each HMM-derived sleep state was expressed in hours per day. We analyzed associations between sleep and behavior problems stratified by children with and without sleep-disordered breathing (SDB).ResultsFour hidden sleep states were identified at 3 years and six hidden sleep states at 5 years using HMM. The first sleep state identified for both ages (HMM-0) had zero counts (no movement). The remaining hidden states were merged together (HMM-mov). Children spent an average of 8.2 ± 1.2 h/day in HMM-0 and 2.6 ± 0.8 h/day in HMM-mov at 3 years. At age 5, children spent an average of 8.2 ± 0.9 h/day in HMM-0 and 1.9 ± 0.7 h/day in HMM-mov. Among SDB children, each hour in HMM-0 was associated with 0.79-point reduced externalizing behavior problems (95% CI -1.4, -0.12; p < 0.05), and a 1.27-point lower internalizing behavior problems (95% CI -2.02, -0.53; p < 0.01).ConclusionsML-sleep states were not associated with behavior problems in the general population of children. Children with SDB who had greater sleep duration without movement had lower behavioral problems. The ML-sleep states require validation with polysomnography.© Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

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