Evidence map›Paper›PMID 36627526›Full record

ArticleJournal of general internal medicine2023

Screen Time from Adolescence to Adulthood and Cardiometabolic Disease: a Prospective Cohort Study.

Jason M Nagata, Christopher M Lee, Feng Lin, Kyle T Ganson, Kelley Pettee Gabriel, Alexander Testa, Dylan B Jackson, Erin E Dooley, Holly C Gooding, Eric Vittinghoff

Open access · hybridAbstract read
In one paragraph

Article in Journal of general internal medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
14.9field-weighted citation impact, top 1% of its field
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

20 citing papers in PubMed, 34 citations in OpenAlex.

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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

10 authors at 6 institutions in 2 countries.

Jason M NagataDepartment of Pediatrics, University of California, San Francisco, 550 16th Street, 4th Floor, Box 0503, San Francisco, CA, 94143, USA. jason.nagata@ucsf.edu.ORCID 0000-0002-6541-0604
Christopher M LeeDepartment of Pediatrics, University of California, San Francisco, 550 16th Street, 4th Floor, Box 0503, San Francisco, CA, 94143, USA.
Feng LinDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, USA.
Kyle T GansonFactor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada.
Kelley Pettee GabrielDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Alexander TestaDepartment of Management, Policy and Community Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
Dylan B JacksonDepartment of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Erin E DooleyDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Holly C GoodingDivision of General Pediatrics and Adolescent Medicine, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
Eric VittinghoffFactor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada.
University of California, San Francisco · USUniversity of Alabama at Birmingham · USUniversity of Toronto · CAEmory University · USJohns Hopkins University · USThe University of Texas Health Science Center at Houston · US

Funding

Wave IV Data CollectionP01HD031921 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HARRIS, KATHLEEN MULLAN · 1994 to 2020
$86.1M
Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI James O Hill · 2000 to 2026
$31.9M
Informing national guidelines on adolescent and young adult physical activity and sedentary behavior to prevent cardiovascular diseaseK08HL159350 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NAGATA, JASON M · 2021 to 2025
$869k
Doris Duke Charitable Foundation 2022056NHLBI NIH HHS K08 HL159350NICHD NIH HHS P01 HD031921NIDDK NIH HHS P30 DK056336
6 · The paper itself

Abstract

backgroundPrevious studies have analyzed the relationship between screen time and cardiometabolic disease risk factors among adolescents, but few have examined the longitudinal effects of screen time on cardiometabolic health into adulthood using nationally representative data.

objectiveTo determine prospective associations between screen time and later cardiometabolic disease over a 24-year period using a nationally representative adolescent cohort.

designLongitudinal prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) collected from 1994 to 2018.

participantsAdolescents aged 11-18 years old at baseline (1994-1995) followed for 24 years. MAIN MEASURES: Predictors: screen time (five repeated measures of self-reported television and video watching from adolescence to adulthood). OUTCOMES: Five repeated measures of body mass index (BMI); two repeated measures of waist circumference, hypertension, hyperlipidemia, and diabetes collected at 15- and 24-year follow-up exams. KEY

resultsFor the 7105 adolescents in the sample (49.7% female, 35.0% non-white), the baseline adolescent average screen time per day was 2.86 ± 0.08 hours per day, which generally declined through 24-year follow-up. Average BMI at baseline was 22.57 ± 0.13 kg/m

conclusionsIn this prospective cohort study, higher screen time in adolescence was associated with higher odds of select indicators of cardiometabolic disease in adulthood.

Indexed as

HypertensionObesityAdolescentAdultBody Mass IndexChildFemaleHumansLongitudinal StudiesMaleProspective StudiesAdolescentsDiabetesHyperlipidemiaHypertensionObesityScreen timeTechnologyTelevisionVideos

Identifiers

PMID36627526
PMCPMC10272026
OpenAlexW4315489248

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.