Evidence map›Paper›PMID 39680594›Full record

ArticlePloS one2024

The effect of Internet use on body weight in Chinese adolescents: Evidence from a nationally longitudinal survey.

Junqi Ma, Li Sheng

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

2 authors.

Junqi MaSchool of Public Administration, Chongqing Technology and Business University, Chongqing, China.ORCID 0000-0002-4213-4512
Li ShengSchool of Foreign Languages, Chongqing Technology and Business University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevalence of overweight and obesity among adolescents has been increasing steadily. This study aims to investigates the causal effect and underlying mechanisms between Internet use and body weight among Chinese adolescents. Using data from China Health and Nutrition Survey (CHNS) spanning from 2004 to 2015, the analytical sample includes 3054 participants (aged 11-19, 48% females). We exploit ordinary least squares (OLS) and two-stage least squares (2SLS) models, obtained causal effect of Internet use on body mass index (BMI), overweight and obesity among adolescents. We find a significant positive effect of Internet use on BMI (β = 0.499, p < 0.05) and probability of overweight (β = 0.061, p < 0.05). Specifically, Internet use increases BMI by 2.56%, and increases the probability of being overweight by 6.1%. But no evidence shows that Internet use significantly increases the probability of obesity (p > 0.1). The mechanism is that Internet use increases sedentary activities (mainly screen time) and food consumption behavior, which results in an imbalance between energy intake and expenditure that in turn increases BMI and overweight. Furthermore, the longer the time spent playing games online, the greater the probability of adolescents being overweight (β = 0.012, p < 0.1), whereas time spent watching movies online, surfing online, and chatting online is not significantly associated with body weight. Heterogeneity analyses show that the adverse effects of Internet use on adolescents' body weight is more pronounced in rural areas and among the male group. This study suggests that reducing time spent playing games online, and increasing physical activity and cultivating healthy eating behaviour can reduce the risk of overweight and obesity in adolescents.

Indexed as

Body Mass IndexBody WeightInternet UseAdolescentChildChinaEast Asian PeopleFemaleHumansInternetLongitudinal StudiesMaleObesityOverweightPediatric ObesityYoung Adult

Identifiers

PMID39680594
PMCPMC11649103

What OpenQuestion holds

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LicenceCC BY
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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.