Evidence map›Paper›PMID 41551284›Full record

ArticleFrontiers in public health2025

Age-specific effects of screen time on overweight/obese: a structural equation model of children and adolescents in Western Maharashtra, India.

Shraddha Thorat, Rupeshkumar Deshmukh, Saibal Adhya

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shraddha ThoratDepartment of Community Medicine, Bharati Vidyapeeth (Deemed to be University) Medical College, Pune, India.
Rupeshkumar DeshmukhDepartment of Community Medicine, Bharati Vidyapeeth (Deemed to be University) Medical College, Pune, India.
Saibal AdhyaDepartment of Community Medicine, Bharati Vidyapeeth (Deemed to be University) Medical College, Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The rapid increase in digital technology use has led to unprecedented screen time levels among children and adolescents, raising concerns about overweight/obesity, especially in urban settings. Despite growing global evidence, limited data exists for Indian cities like Pune. Objectives: This cross-sectional study assessed the relationship between screen time duration and overweight/obesity in children's (6-11 years) and adolescents (12-19 years) in Pune, India, accounting for dietary patterns, physical activity, and sociodemographic factors. Methods: A sample of 3,920 students from urban Pune schools was evaluated for screen time, physical activity, diet, BMI, and sociodemographic variables. Multinomial logistic regression and structural equation modeling identified associations between these factors and overweight/obesity, stratified by age groups (6-11 and 12-19 years). Results: Overweight/obesity prevalence was 27.1%. Excessive screen time was strongly associated with higher overweight and obesity risk. Children with 2-4 h daily screen time had 35.69 times higher Adj. OR ( Conclusion: High screen time is a major modifiable risk factor for obesity among urban children and adolescents in Pune. Age-specific and family-centered interventions targeting reduced screen time and improved physical activity are urgently needed for effective obesity prevention and health promotion.

Indexed as

OverweightPediatric ObesityScreen TimeAdolescentAge FactorsBody Mass IndexChildCross-Sectional StudiesExerciseFemaleHumansIndiaLatent Class AnalysisMalePrevalenceYoung Adultadolescentage-specificchildrenoverweight/obesescreen time

Identifiers

PMID41551284
PMCPMC12808472

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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.