ABSTRACT

Background Screen time in children and adolescents may be linked to cardiometabolic and cardiovascular risk. This study examines the relationship between screen time and cardiometabolic risk (CMR) factors.

Methods We analysed data from over 1,000 participants in the Copenhagen Prospective Studies on Asthma in Childhood cohorts (COPSAC2010 and COPSAC2000). This longitudinal study utilised objective measures of physical activity, sleep, pubertal development, and dietary intake as covariates, and assessed mediating and moderating effects of lifestyle factors on parental- and self- and reported discretionary screen time. Our primary outcome of interest was a CMR score which was made from standardised z-scores of metabolic syndrome components (waist circumference, systolic blood pressure, HDL cholesterol, triglycerides, and glucose), adjusted for sex and age. Secondary outcomes were insulin resistance, inflammation, atherogenic lipoproteins, and anthropometric measures. We utilised supervised machine learning modelling of blood NMR metabolomics to identify a unique metabolic signature of screen time. Finally, we assess screen time associations with a predicted Cardiovascular Risk Score derived from Cox proportional hazards models of 10-year CVD events trained in the UK Biobank.

Results Increased screen time was significantly associated with CMR in children and adolescents, with each additional hour of screen time linked to a higher CMR z-score (children at 10-years: 0.08 [0.01 - 0.14], p=0.021; adolescents at 18-years: 0.13 [0.07 - 0.2], p=0.001). In childhood, sleep duration (p=0.029) and time of onset (p=0.009) significantly moderated the relationship between screen time and CMR; less sleep combined with high screen time significantly increased cardiometabolic risk. In adolescence, sleep duration likewise significantly moderated the association between screen time and CMR (p=0.012), replicating the findings from childhood. A supervised machine learning model trained in the childhood cohort identified a unique metabolic signature in the blood NMR metabolome associated with screen time, which was validated in the adolescent cohort (0.14 [0.03-0.26], p=0.014). CVD-risk scores modelled from CVD-events were directionally associated with screen time in childhood (0.06 [−0.02 - 0.13], p=0.15) and significantly associated with screen time in adolescence (0.07 [0.01 - 0.13], p=0.017) in fully adjusted models.

Conclusion Increased screen time is significantly associated with higher cardiometabolic risk in children and adolescents, with sleep duration moderating this relationship. A unique metabolic signature of screen time was validated across cohorts, and screen time was associated with higher cardiovascular risk scores in adolescence. These findings underscore the importance of considering screen time and sleep duration in addressing cardiometabolic and cardiovascular risks.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

All funding received by COPSAC is listed on www.copsac.com. The Lundbeck Foundation (Grant no R16-A1694 and R269-2017-5); The Ministry of Health (Grant no 903516); Danish Council for Strategic Research (Grant no 0603-00280B) and The Capital Region Research Foundation have provided core support to the COPSAC research centre. This project has received funding from the European Research Council (ERC) under the European Union?s Horizon 2020 research and innovation programme (grant agreement No. 946228) (BC). MAR is funded by the Novo Nordisk Foundation (Grant no NNF21OC0068517).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Not Applicable

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

We are aware of and comply with recognized codes of good research practice, including the Danish Code of Conduct for Research Integrity. We comply with national and international rules on the safety and rights of patients and healthy subjects, including Good Clinical Practice (GCP) as defined in the EU's Directive on Good Clinical Practice, the International Conference on Harmonisation's (ICH) good clinical practice guidelines and the Helsinki Declaration. Privacy is important to us which is why we follow national and international legislation on General Data Protection Regulation (GDPR), the Danish Act on Processing of Personal Data and the practice of the Danish Data Inspectorate.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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Footnotes

Source of Funding: All funding received by COPSAC is listed on www.copsac.com. The Lundbeck Foundation (Grant no R16-A1694 and R269-2017-5); The Ministry of Health (Grant no 903516); Danish Council for Strategic Research (Grant no 0603-00280B) and The Capital Region Research

Foundation have provided core support to the COPSAC research centre. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 946228) (BC). MAR is funded by the Novo Nordisk Foundation (Grant no NNF21OC0068517).

Conflicts of interest: Authors declare no potential, perceived, or real conflict of interest regarding the content of this manuscript. The funding agencies did not have any role in design and conduct of the study; collection, management, and interpretation of the data; or preparation, review, or approval of the manuscript. No pharmaceutical company was involved in the study.

Governance: We are aware of and comply with recognized codes of good research practice, including the Danish Code of Conduct for Research Integrity. We comply with national and international rules on the safety and rights of patients and healthy subjects, including Good Clinical Practice (GCP) as defined in the EU’s Directive on Good Clinical Practice, the International Conference on Harmonisation’s (ICH) good clinical practice guidelines and the Helsinki Declaration. Privacy is important to us which is why we follow national and international legislation on General Data Protection Regulation (GDPR), the Danish Act on Processing of Personal Data and the practice of the Danish Data Inspectorate.

Data Availability

Participant-level personally identifiable data are protected under the Danish Data Protection Act and European Regulation 2016/679 of the European Parliament and of the Council (GDPR) that prohibit distribution even in pseudo-anonymized form. However, participant-level data can be made available under a data transfer agreement as part of a collaboration effort.

AbbreviationsADHDAttention-deficit/hyperactivity disorderADHD-RSADHD Rating ScaleApoBApolipoprotein BASRSAdult ADHD Self-Report ScaleBIABioelectrical impedance analysisBMIBody mass indexCMRCardiometabolic riskCOPSAC2000COpenhagen Prospective Studies on Asthma in Childhood mother-child cohort 2000COPSAC2010COpenhagen Prospective Studies on Asthma in Childhood mother-child cohort 2010CVDCardiovascular diseaseFFMFat-free massFMIFat mass indexFFMIFat-free mass indexFSHFollicle stimulating hormoneHDLHigh-density lipoproteinHOMA-IRHomeostatic Model Assessment for Insulin Resistancehs-CRPHigh-sensitivity CRPLHLuteinizing hormonen3-LCPUFAOmega-3 long-chain polyunsaturated fatty acidsSBPSystolic Blood PressuresPLSSparse partial least square