MétaCan
Menu
Back to cohort
Record W2776934437 · doi:10.1111/obr.12637

Association of eating while television viewing and overweight/obesity among children and adolescents: a systematic review and meta‐analysis of observational studies

2017· review· en· W2776934437 on OpenAlexaff
Saeed Ghobadi, Zahra Hassanzadeh-Rostami, Mohammad Salehi‐Marzijarani, Nick Bellissimo, Neil R. Brett, Julia O. Totosy de Zepetnek

Bibliographic record

VenueObesity Reviews · 2017
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of ReginaToronto Metropolitan University
FundersShiraz UniversityShiraz University of Medical Sciences
KeywordsOverweightMeta-analysisObservational studyObesityMedicineOdds ratioConfidence intervalChildhood obesityAnthropometrySystematic reviewDemographyMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

The objective of this systematic review and meta-analysis was to examine the association between eating while television viewing (TVV) and overweight or obesity in children (<18 years). A systematic search of PubMed, Scopus, Web of science, PreQuest and Embase was conducted up to April 2017; pooled odds ratio (OR) and 95% confidence intervals (CI) were calculated using a random effects model. Of 4,357 articles identified, 20 observational studies met inclusion criteria (n = 84,825) and 8 of these 20 (n = 41,617) reported OR. Eating while TVV was positively associated with obesity-related anthropometric measurements in 15 studies (75%). The meta-analysis revealed that eating while TVV was positively associated with being overweight (OR = 1.28; 95% CI: 1.17, 1.39). Subgroup analyses showed similar positive associations in both girls and boys, as well as in children who ate dinner while TVV. There was no evidence of publication bias. The present systematic review and meta-analysis suggests that eating while TVV could be a risk factor for being overweight or obese in childhood and adolescents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0210.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.164
GPT teacher head0.387
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations61
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueObesity ReviewsSame topicObesity, Physical Activity, DietFrench-language works237,207