Accelerometry‐assessed sleep clusters and cardiometabolic risk factors in adolescents

Abstract

AbstractObjectiveThis study aimed to identify sleep clusters based on objective multidimensional sleep characteristics and test their associations with adolescent cardiometabolic health.MethodsThe authors included 1090 participants aged 14.3 to 16.4 years (mean = 15.2 years) who wore 7‐day accelerometers during the 15‐year follow‐up of the German Infant Study on the influence of Nutrition Intervention PLUS environmental and genetic influences on allergy development (GINIplus) and the Influence of Lifestyle factors on the development of the Immune System and Allergies in East and West Germany (LISA) birth cohorts. K‐means cluster analysis was performed across 12 sleep characteristics reflecting sleep quantity, quality, schedule, variability, and regularity. Cardiometabolic risk factors included fat mass index (FMI), blood pressure, triglycerides, high‐density lipoprotein cholesterol, high‐sensitivity C‐reactive protein, and insulin resistance (n = 505). Linear and logistic regression models were examined.ResultsFive sleep clusters were identified: good sleep (n = 337); delayed sleep phase (n = 244); sleep irregularity and variability (n = 108); fragmented sleep (n = 313); and prolonged sleep latency (n = 88). The “prolonged sleep latency” cluster was associated with increased sex‐scaled FMI (β = 0.39, 95% CI: 0.15–0.62) compared with the “good sleep” cluster. The “sleep irregularity and variability” cluster was associated with increased odds of high triglycerides only in male individuals (odds ratio: 9.50, 95% CI: 3.22–28.07), but this finding was not confirmed in linear models.ConclusionsThe prolonged sleep latency cluster was associated with higher FMI in adolescents, whereas the sleep irregularity and variability cluster was specifically linked to elevated triglycerides (≥1.7 mmol/L) in male individuals.