Validation of the Entrainment Signal Regularity Index and associations with children's changes in BMI

Abstract

Objective: This study examined the validity of a novel metric of circadian health, the Entrainment Signal Regularity Index (ESRI), and its relationship to changes in BMI during the school year and summer. Methods: In a longitudinal observational data set, this study examined the relationship between ESRI score and children's (n = 119, 5-to 8-year-olds) sleep and physical activity levels during the school year and summer, differences in ESRI score during the school year and summer, and the association of ESRI score during the school year and summer with changes in BMI across those time periods. Results: The ESRI score was higher during the school year (0.70 AE 0.10) compared with summer (0.63 AE 0.11); t(111) = 5.484, p < 0.001. Whereas the ESRI score at the beginning of the school year did not significantly predict BMI change during the school year (β = 0.05 AE 0.09 SE, p = 0.57), having a higher ESRI score during summer predicted smaller increases in BMI during summer (β = À0.22 AE 0.10 SE, p = 0.03).Conclusions: Overall, children demonstrated higher entrainment regularity during the school year compared with the summer. During summer, having a higher entrainment signal was associated with smaller changes in summertime BMI. This effect was independent of the effects of children's sleep midpoint, sleep regularity, and physical activity on children's BMI.

Wake up! It's time to recognize the importance of sleep in metabolic health

“…The authors concluded that nightly deviations in both the timing and duration of sleep in adolescents related to adverse metabolic outcomes, and they put forth important next steps to elucidate the direct and indirect effects of night‐to‐night variability in sleep duration and irregularity of sleep timing. Building on aspects of that review, Moreno and colleagues developed and validated a novel approach to modeling intraindividual temporal trends in circadian regularity by using information on light exposure and activity from a wearable device to calculate the Entrainment Signal Regularity Index (ESRI) [29]. The authors postulated that the ESRI may be better suited than other measures of sleep regularity to capture health effects of less granular, more systematic deviations in sleep schedules over time.…”