0386 School Matters: How School Schedules Impact Adolescent Sleep and Cardiometabolic Health

Abstract Introduction Adolescents experience shifts in circadian timing that conflict with early school start times, often leading to chronic sleep restriction and irregular patterns, which have been linked to adverse cardiometabolic outcomes. Multidimensional sleep health (MSH) frameworks offer a comprehensive approach to evaluating sleep. We previously developed a data-driven, multivariable MSH framework, BEDReST, and in this study, we examined associations between MSH scores and metabolic syndrome (MetS), comparing BEDReST to RU-SATED and evaluating whether assessment context (in-school vs. on-break) modifies these associations. Methods Data from 341 adolescents (16.3±2.2 yr; 47% female; 22.8% racial/ethnic minority) were analyzed. Two MSH scores were examined: RU-SATED and BEDReST (Breathing, Efficiency, Duration, Regularity, Satisfaction, and Timing), measured by polysomnography, actigraphy, and self-report. Both scores ranged from 0 to 6, with higher values indicating better sleep health. Linear regression models examined associations between MSH scores and a continuous metabolic syndrome (cMetS) score, where higher values indicate greater metabolic burden, stratified by assessment timing (in-school vs. on-break). Additional models assessed associations with key cardiometabolic markers, including blood pressure, fasting glucose and insulin, glucose-to-insulin ratio (GIR), and LDL cholesterol. All models were adjusted for age, sex, race/ethnicity, and socioeconomic status. Results MSH assessed while in-school showed stronger inverse associations with cMetS with BEDReST demonstrating larger effects (B = –0.60, p< 0.05) than RU-SATED (B = -0.21, p>0.05). BEDReST was also associated with lower waist circumference (B = -2.82, p< 0.05), while RU-SATED was not (B = -0.84, p>0.05). While on-break, both MSH scores were associated with improved insulin sensitivity, though BEDReST consistently showed stronger effects (BEDReST: HOMA-IR B = -0.15, p< 0.05; GIR B = 2.71, p=0.05; RU-SATED: HOMA-IR B = -0.11, p< 0.05; GIR B = 1.70, p=0.07), whereas associations with all other outcomes were weaker. Conclusion MSH assessed while in-school showed stronger associations with MetS and waist circumference than on-break, with BEDReST consistently demonstrating larger effects than RU-SATED. While on-break, both frameworks captured associations with insulin sensitivity, with BEDReST showing stronger effects. These findings highlight the importance of contextual factors and demonstrate the added value of a multivariable, data-driven approach to assessing MSH in adolescents. Support (if any) R01HL136587, UL1TR002014, TL1TR002016

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Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0386
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
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article

0386 School Matters: How School Schedules Impact Adolescent Sleep and Cardiometabolic Health

Duanping Liao, Alexandros Vgontzas, Jason Liao, Edward Bixler et al.
SLEEP
Cardiovascular Health and Risk Factors
article

0386 School Matters: How School Schedules Impact Adolescent Sleep and Cardiometabolic Health

Duanping Liao, Alexandros Vgontzas, Jason Liao, Edward Bixler, Susan Calhoun, Casandra Nyhuis, Julio Fernandez-Mendoza
article en

Abstract

Abstract Introduction Adolescents experience shifts in circadian timing that conflict with early school start times, often leading to chronic sleep restriction and irregular patterns, which have been linked to adverse cardiometabolic outcomes. Multidimensional sleep health (MSH) frameworks offer a comprehensive approach to evaluating sleep. We previously developed a data-driven, multivariable MSH framework, BEDReST, and in this study, we examined associations between MSH scores and metabolic syndrome (MetS), comparing BEDReST to RU-SATED and evaluating whether assessment context (in-school vs. on-break) modifies these associations. Methods Data from 341 adolescents (16.3±2.2 yr; 47% female; 22.8% racial/ethnic minority) were analyzed. Two MSH scores were examined: RU-SATED and BEDReST (Breathing, Efficiency, Duration, Regularity, Satisfaction, and Timing), measured by polysomnography, actigraphy, and self-report. Both scores ranged from 0 to 6, with higher values indicating better sleep health. Linear regression models examined associations between MSH scores and a continuous metabolic syndrome (cMetS) score, where higher values indicate greater metabolic burden, stratified by assessment timing (in-school vs. on-break). Additional models assessed associations with key cardiometabolic markers, including blood pressure, fasting glucose and insulin, glucose-to-insulin ratio (GIR), and LDL cholesterol. All models were adjusted for age, sex, race/ethnicity, and socioeconomic status. Results MSH assessed while in-school showed stronger inverse associations with cMetS with BEDReST demonstrating larger effects (B = –0.60, p< 0.05) than RU-SATED (B = -0.21, p>0.05). BEDReST was also associated with lower waist circumference (B = -2.82, p< 0.05), while RU-SATED was not (B = -0.84, p>0.05). While on-break, both MSH scores were associated with improved insulin sensitivity, though BEDReST consistently showed stronger effects (BEDReST: HOMA-IR B = -0.15, p< 0.05; GIR B = 2.71, p=0.05; RU-SATED: HOMA-IR B = -0.11, p< 0.05; GIR B = 1.70, p=0.07), whereas associations with all other outcomes were weaker. Conclusion MSH assessed while in-school showed stronger associations with MetS and waist circumference than on-break, with BEDReST consistently demonstrating larger effects than RU-SATED. While on-break, both frameworks captured associations with insulin sensitivity, with BEDReST showing stronger effects. These findings highlight the importance of contextual factors and demonstrate the added value of a multivariable, data-driven approach to assessing MSH in adolescents. Support (if any) R01HL136587, UL1TR002014, TL1TR002016

SLEEPVol. 49(Supplement_1)
Pennsylvania State University (US), Johns Hopkins University (US), Penn State Milton S. Hershey Medical Center (US)
Openalex Percentile: Top 5%
Cardiovascular Health and Risk Factors
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