Each additional hour of daily screen time in childhood and adolescence was statistically associated with modest increases in cardiometabolic risk and a distinct blood-based metabolic signature, according to a recent study.
The analysis utilized data from two longitudinal Danish birth cohorts: Copenhagen Prospective Studies on Asthma in Childhood mother–child cohort 2010 (COPSAC2010), which included 630 children assessed at ages 6 and 10 years, and Copenhagen Prospective Studies on Asthma in Childhood mother–child cohort 2000 (COPSAC2000), which included 364 adolescents evaluated at age 18 years. Discretionary screen time was reported by parents or adolescents and assessed in relation to a composite cardiometabolic risk (CMR) score derived from waist circumference, systolic blood pressure, high-density lipoprotein cholesterol, triglycerides, and glucose. Secondary outcomes included insulin resistance, inflammatory markers, anthropometric data, and a predicted cardiovascular risk score calculated using nuclear magnetic resonance metabolomics models trained on UK Biobank data.
Across both cohorts, greater screen time was associated with higher CMR scores. In COPSAC2010, each additional hour of screen time corresponded with an increase in CMR in children. In adolescents from COPSAC2000, screen time was more strongly associated with adverse outcomes, including higher waist circumference by 1.3 cm, elevated systolic blood pressure by 0.6 mm Hg, and increased apolipoprotein B. The study also found stronger associations between screen time and CMR in boys overall, though girls showed particular vulnerability when combined with later bedtimes. Screen time also correlated with elevated triglycerides and lower high-density lipoprotein cholesterol in both cohorts.
The researchers, led by David Homer of COPSAC, Copenhagen Prospective Studies on Asthma in Childhood Herlev and Gentofte Hospital, University of Copenhagen Denmark, and colleagues, developed a machine learning model to identify a screen time–related metabolic signature using 173 nuclear magnetic resonance-based biomarkers. The resulting 37-metabolite panel successfully predicted screen time in both cohorts, confirming the reproducibility of the metabolic pattern across developmental stages.
Full disclosures can be found in the published study.