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Introduction: Although insufficient sleep is a known risk factor for metabolic syndrome (MetS), the circadian timing of sleep is also involved in cardiometabolic risk. Prior studies have shown that circadian misalignment, which is highly prevalent during adolescence, impacts the association of visceral adiposity (VAT) with MetS burden in youth. However, whether lifestyle behaviors mediate this effect remains unknown. Hypothesis: We hypothesize that diet and physical activity will mediate the impact of circadian misalignment on the relationship between VAT and MetS in adolescents. Methods: We analyzed data from 277 population-based adolescents from the Penn State Child Cohort (median 16.2 years; 48% female; 22% racial/ethnic minority) who had 5-night actigraphy (ACT) and were evaluated while in-school (n=177) or on-break (n=100). They also had 9-h polysomnography (PSG), a dual-energy X-ray absorptiometry (DXA) scan, ACT-measured physical activity, and dietary assessment (DA-80). DXA-measured VAT was the predictor. MetS score (i.e., age/sex-adjusted z-scores of waist circumference, blood pressure, HOMA-IR, triglycerides, and HDL cholesterol) was the outcome. ACT-measured sleep midpoint (SM), sleep irregularity (SI), and social jetlag (SJL) were the effect modifiers. Linear regression models were first adjusted for essential covariates (i.e., sex, race/ethnicity, age, ACT-sleep duration, ACT-sleep variability, and PSG-apnea/hypopnea index), and, thereafter, for potential mediators (i.e., total caloric intake, protein, fat, carbohydrates, bouts and amount of sedentary behavior, and moderate-to-vigorous physical activity). Results: Significant effect modifications were found between VAT and SM, SI and SJL while in-school on MetS after adjusting for essential covariates (interaction effects: 0.61 (0.25) p=0.014, 0.37 (0.16) p=0.018, and 0.58 (0.23) p=0.011, respectively). Despite SM, SI or SJL being associated with caloric intake (e.g., r=0.160, P=0.017 for carbohydrates) or physical activity (e.g., r=0.217, P=0.003 for bouts of sedentary behavior), these effect modifications were not significantly impacted by further adjusting for caloric intake, including carbohydrates interaction effects: 0.52 (0.24) p=0.030, 0.36 (0.15) p=0.017, and 0.59 (0.21) p=0.005, respectively, or physical activity, including bouts of sedentary behavior interaction effects: 0.61 (0.25) p=0.015, 0.38 (0.16) p=0.017, and 0.58 (0.23) p=0.012, respectively. Conclusions: Lifestyle factors such as nutrition or physical activity do not significantly account for the role that circadian misalignment has in increasing the impact of VAT on MetS burden in adolescents. Therefore, other pathways, biological or behavioral, may be involved in how circadian misalignment contributes to the development of cardiometabolic sequelae associated with central obesity.
Morales‐Ghinaglia et al. (Tue,) studied this question.