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Association between sleep patterns and glucose and lipid metabolism among adolescents: a cluster analysis.

Created on 24 Jul 2026

Authors

Dan Yang, Rema Ramakrishnan, Zhao-Cong He, Ke Xiao, Nian-Nian Chen, Feng-Juan Zhou, Min-Shan Lu, Yan-Na Zhu, Jian-Rong He

Published in

Journal of clinical lipidology. Jul 03, 2026. Epub Jul 03, 2026.

Abstract

The high prevalence of glucose and lipid disorders in adolescents underscores the need to identify modifiable risk factors. While sleep is crucial for health, evidence linking multidimensional sleep characteristics to glucose and lipid metabolism in adolescents remains limited and inconsistent.
To investigate the associations between multidimensional sleep variables, derived sleep patterns, and glucose and lipid metabolism in US adolescents.
This study included 1259 adolescents aged 16 to 19 years. Exposure included sleep time (ST), wake time (WT), sleep midpoint (MST), sleep duration, sleep debt, and social jetlag. Outcomes included glucose and lipid profiles. Analyses included cluster analysis, linear regression, and restricted cubic spline (RCS) regression.
Social jetlag, relative sleep debt (RSD) (β, 0.06; 95% CI, 0.003, 0.12), and late ST (β, 0.26; 95% CI, 0.03, 0.49) were associated with higher glucose. Low or high (vs medium) RSD, WT (β, -0.04; 95% CI, -0.08, -0.01), ST (β, -0.05; 95% CI, -0.09, -0.01), MST (β, -0.05; 95% CI, -0.09, -0.01), early or late (vs medium) ST, late WT (β, -0.23; 95% CI, -0.35, -0.10) and late MST (β, -0.26; 95% CI, -0.49, -0.03) were associated with lower high-density lipoprotein cholesterol (HDL-C). RCS regression showed potential nonlinear associations between sleep variables and HDL-C. "Weekend catch-up sleep" pattern was associated with higher glucose.
Multidimensional sleep characteristics, particularly timing variables, are significantly associated with adverse glucose and lipid profiles in adolescents. Weekend catch-up sleep is linked to dysregulated glucose metabolism, highlighting the importance of healthy sleep for metabolic health.

PMID:
42493324
Bibliographic data and abstract were imported from PubMed on 24 Jul 2026.

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