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Sina-et-al_2021_Media use trajectories.pdf 982,87KB
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1000 Titel
  • Media use trajectories and risk of metabolic syndrome in European children and adolescents: the IDEFICS/I.Family cohort
1000 Autor/in
  1. Sina, Elida |
  2. Buck, Christoph |
  3. Veidebaum, Toomas |
  4. Siani, Alfonso |
  5. Reisch, Lucia |
  6. Pohlabeln, Hermann |
  7. Pala, Valeria |
  8. Moreno, Luis A. |
  9. Molnár, Dénes |
  10. Lissner, Lauren |
  11. Kourides, Yiannis |
  12. De Henauw, Stefaan |
  13. Eiben, Gabriele |
  14. Ahrens, Wolfgang |
  15. Hebestreit, Antje |
1000 Mitwirkende/r
  1. The IDEFICS and I.Family consortia |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-10-18
1000 Erschienen in
1000 Quellenangabe
  • 18:134
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12966-021-01186-9 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521295/ |
1000 Ergänzendes Material
  • https://ijbnpa.biomedcentral.com/articles/10.1186/s12966-021-01186-9#Sec21 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • BACKGROUND: Media 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. METHODS: Children 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−1) and homeostasis model assessment for insulin resistance (HOMA-IR). Unfavorable monitoring levels of MetS and its components were identified (cut-off: ≥ 90th percentile of each score). Children aged 2–16 years with ≥ 2 observations (W1/W2; W1/W3; W2/W3; W1/W2/W3) were eligible for the analysis. A two-step procedure was conducted: first, individual age-dependent DM trajectories were calculated using linear mixed regressions based on random intercept (hours/day) and linear slopes (hours/day/year) and used as exposure measures in association with MetS at a second step. Trajectories were further dichotomized if children increased their DM duration over time above or below the mean. RESULTS: 10,359 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. CONCLUSIONS: Digital 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.
1000 Sacherschließung
lokal Adolescents
lokal Children
lokal Screen-time
lokal Sedentary behavior
lokal Physical activity
lokal Metabolic disorders
lokal Diet quality
lokal Longitudinal study
lokal Digital media
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-2926-2480|https://orcid.org/0000-0003-0261-704X|https://frl.publisso.de/adhoc/uri/VmVpZGViYXVtLCBUb29tYXM=|https://frl.publisso.de/adhoc/uri/U2lhbmksIEFsZm9uc28=|https://frl.publisso.de/adhoc/uri/UmVpc2NoLCBMdWNpYQ==|https://orcid.org/0000-0002-9575-1119|https://frl.publisso.de/adhoc/uri/UGFsYSwgVmFsZXJpYQ==|https://frl.publisso.de/adhoc/uri/TW9yZW5vLCBMdWlzIEEu|https://frl.publisso.de/adhoc/uri/TW9sbsOhciwgRMOpbmVz|https://frl.publisso.de/adhoc/uri/TGlzc25lciwgTGF1cmVu|https://frl.publisso.de/adhoc/uri/S291cmlkZXMsIFlpYW5uaXM=|https://frl.publisso.de/adhoc/uri/RGUgSGVuYXV3LCBTdGVmYWFu|https://frl.publisso.de/adhoc/uri/RWliZW4sIEdhYnJpZWxl|https://orcid.org/0000-0003-3777-570X|https://orcid.org/0000-0001-7354-5958|https://frl.publisso.de/adhoc/uri/VGhlIElERUZJQ1MgYW5kIEkuRmFtaWx5IGNvbnNvcnRpYQ==
1000 Label
1000 Förderer
  1. Sixth Framework Programme |
  2. Seventh Framework Programme |
1000 Fördernummer
  1. 016181 (FOOD)
  2. 266044
1000 Förderprogramm
  1. -
  2. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Sixth Framework Programme |
    1000 Förderprogramm -
    1000 Fördernummer 016181 (FOOD)
  2. 1000 joinedFunding-child
    1000 Förderer Seventh Framework Programme |
    1000 Förderprogramm -
    1000 Fördernummer 266044
1000 Objektart article
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1000 @id frl:6431133.rdf
1000 Erstellt am 2022-01-14T11:37:10.101+0100
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1000 Bearbeitet von 317
1000 Zuletzt bearbeitet Fri Jan 21 15:12:38 CET 2022
1000 Objekt bearb. Fri Jan 14 11:38:24 CET 2022
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1000 Oai Id
  1. oai:frl.publisso.de:frl:6431133 |
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