Evidence map›Paper›PMID 34663352›Full record

ArticleThe international journal of behavioral nutrition and physical activity2021

Media use trajectories and risk of metabolic syndrome in European children and adolescents: the IDEFICS/I.Family cohort.

Elida Sina, Christoph Buck, Toomas Veidebaum, Alfonso Siani, Lucia Reisch, Hermann Pohlabeln, Valeria Pala, Luis A Moreno, Dénes Molnar, Lauren Lissner and 6 more

Abstract read
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Article in The international journal of behavioral nutrition and physical activity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Elida SinaLeibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstraße 30, 28359, Bremen, Germany.
Christoph BuckLeibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstraße 30, 28359, Bremen, Germany.
Toomas VeidebaumDepartment of Chronic Diseases, National Institute for Health Development, Tallinn, Estonia.
Alfonso SianiInstitute of Food Sciences, National Research Council, Avellino, Italy.
Lucia ReischDepartment of Management, Society and Communication, Copenhagen Business School, Copenhagen, Denmark.
Hermann PohlabelnLeibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstraße 30, 28359, Bremen, Germany.
Valeria PalaDepartment of Preventive and Predictive Medicine, Fondazione IRCCS, Istituto Nazionale Dei Tumori, Milan, Italy.
Luis A MorenoGENUD (Growth, Exercise, Nutrition and Development) Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad Y Nutrición (CIBERObn), University of Zaragoza, Zaragoza, Spain.
Dénes MolnarDepartment of Pediatrics, Medical School, University of Pécs, Pécs, Hungary.
Lauren LissnerSchool of Public Health and Community Medicine, University of Gothenburg, Gothenburg, Sweden.
Yiannis KouridesResearch and Education Institute of Child Health, Strovolos, Cyprus.
Stefaan De HenauwDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Gabriele EibenDepartment of Public Health, School of Health Sciences, University of Skövde, Skövde, Sweden.
Wolfgang AhrensLeibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstraße 30, 28359, Bremen, Germany.
Antje HebestreitLeibniz Institute for Prevention Research and Epidemiology-BIPS, Achterstraße 30, 28359, Bremen, Germany. sec-epi@leibniz-bips.de.
IDEFICS, I.Family consortia

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedia use may influence metabolic syndrome (MetS) in children. Yet, longitudinal studies are scarce. This study aims to evaluate the longitudinal association of childhood digital media (DM) use trajectories with MetS and its components.

methodsChildren from Belgium, Cyprus, Estonia, Germany, Hungary, Italy, Spain and Sweden participating in the IDEFICS/I.Family cohort were examined at baseline (W1: 2007/2008) and then followed-up at two examination waves (W2: 2009/2010 and W3: 2013/2014). DM use (hours/day) was calculated as sum of television viewing, computer/game console and internet use. MetS z-score was calculated as sum of age- and sex-specific z-scores of four components: waist circumference, blood pressure, dyslipidemia (mean of triglycerides and HDL-cholesterol

results10,359 children and adolescents (20,075 total observations, 50.3% females, mean age = 7.9, SD = 2.7) were included. DM exposure increased as children grew older (from 2.2 h/day at 2 years to 4.2 h/day at 16 years). Estonian children showed the steepest DM increase; Spanish children the lowest. The prevalence of MetS at last follow-up was 5.5%. Increasing media use trajectories were positively associated with z-scores of MetS (slope: β = 0.54, 95%CI = 0.20-0.88; intercept: β = 0.07, 95%CI = 0.02-0.13), and its components after adjustment for puberty, diet and other confounders. Children with increasing DM trajectories above mean had a 30% higher risk of developing MetS (slope: OR = 1.30, 95%CI = 1.04-1.62). Boys developed steeper DM use trajectories and higher risk for MetS compared to girls.

conclusionsDigital media use appears to be a risk factor for the development of MetS in children and adolescents. These results are of utmost importance for pediatricians and the development of health policies to prevent cardio-metabolic disorders later in life.

trial registrationISRCTN, ISRCTN62310987 . Registered 23 February 2018- retrospectively registered.

Indexed as

Metabolic SyndromeAdolescentBody Mass IndexChildCohort StudiesCross-Sectional StudiesFemaleHumansInternetMaleRisk FactorsWaist CircumferenceAdolescentsChildrenDiet qualityDigital mediaLongitudinal studyMetabolic disordersPhysical activityScreen-timeSedentary behavior

Identifiers

PMID34663352
PMCPMC8521295

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.