Evidence map›Paper›PMID 39533232›Full record

ArticleBMC public health2024

Screen time and obesity prevalence in adolescents: an isotemporal substitution analysis.

Dohyun Byun, Yujin Kim, Hajin Jang, Hannah Oh

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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.

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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

4 authors.

Dohyun Byun *Interdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, Republic of Korea.
Yujin Kim *Interdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, Republic of Korea.
Hajin JangInterdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, Republic of Korea.
Hannah OhInterdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, Republic of Korea. hannahoh@korea.ac.kr.

Funding

National Research Foundation of Korea 2023S1A5C2A03095169National Research Foundation of Korea RS-2023-00219289
6 · The paper itself

Abstract

backgroundWe examined the associations between screen time and adolescent obesity and the associations of reallocating screen time to other activities using isotemporal substitution models. Understanding the association between screen time and obesity may provide additional insights into effective obesity prevention strategies in adolescents.

methodsWe conducted a cross-sectional analysis of 5,180 adolescents (4th and 7th grade students) from the Korean Children and Youth Panel Survey 2018. Participants reported their height, weight, and average time spent watching television, using computer, using smartphone, and other after-school activities. Obesity was defined as BMI-for-age and -sex ≥ 95th percentile based on the 2017 Korean National Growth Charts. We performed multivariable logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity prevalence, adjusting for potential confounders.

resultsProlonged smartphone use (≥ 180 vs. <60 m/d: OR [95% CI] = 2.75 [2.06, 3.68]) was associated with a higher obesity prevalence. Television watching (≥ 120 vs. <60 min/d) was positively associated with obesity prevalence among 4th grade students (2.09 [1.51, 2.89]) but the association was not observed among 7th grade students (0.97 [0.63, 1.49]). One-hour increments of any non-screen time activities, with a simultaneous 1-hour decrease in combined screen time, were associated with a lower obesity prevalence (physical activity: 0.75 [0.65, 0.85]; sleeping: 0.69 [0.62, 0.78]; hanging out with friends: 0.80 [0.71, 0.89]; reading: 0.82 [0.69, 0.97]; studying: 0.84 [0.78, 0.90]; chatting with parents: 0.89 [0.88, 0.98]).

conclusionsOur data suggest that public health strategies that reduce screen time and increase time for non-screen time activities, such as physical activity, may be effective in lowering adolescent obesity prevalence.

Indexed as

Pediatric ObesityScreen TimeAdolescentChildCross-Sectional StudiesFemaleHumansMalePrevalenceRepublic of KoreaSedentary BehaviorSmartphoneTelevisionAdolescentBody mass indexChildrenComputerInternetMediaOverweightSmartphoneTeenagerTelevision

Identifiers

PMID39533232
PMCPMC11555804

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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.