MétaCan
Menu
Back to cohort

Meta-Analysis: The Effect of Screen Time and Fast-Food Intake on Obesity in Children and Adolescents

2021· article· en· W4205164122 on OpenAlexaboutno aff
Salwa Annisaa, Yulia Lanti Retno Dewi, Eti Poncorini Pamungkasari

Bibliographic record

VenueJournal of Health Promotion and Behavior · 2021
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsObesityScreen timeChildhood obesityFood intakePsychologyMedicineEnvironmental healthDevelopmental psychologyFood sciencePediatricsEndocrinologyOverweightBiology

Abstract

fetched live from OpenAlex

Background: Obesity has reached epidemic proportions worldwide, making obesity a serious global public health challenge. Obesity is not only found in adults but also in children and adoles­cents which can lead to various physical and mental health problems that are detrimental to the quality of life and are very risky into adulthood. Obesity in children and adolescents today is caused by a lifestyle that makes a person increase in consuming fast food, lack of sleep and the longer duration of screen time. This study aims to analyze the effect of screen time and fast food on obesity in children and adolescents. Subjects and Method: This was a systematic review and meta-analysis. Population= children and adolescents, Intervention= screen time and fast food, Comparison= no screen time and no fast food, Outcome= obesity. Article searches through journal databases include: PubMed, Science Direct, Google Scholar and Springerlink. The articles used in this study are articles that have been published from 2011-2021. The keywords used are obesity OR obese OR overweight AND “fast foods” OR snacks OR “fried foods” AND “social media” OR “screen time” OR television AND child OR adolescent. Articles were selected with the help of PRISMA flow diagrams. The inclusion criteria included full-text articles with a cross-sectional study design. The analysis used logistic regression with adjusted odds ratio and published in English. Articles that have met the requirements are analyzed using the Revman 5.3 application. Results: Fifteen articles came from Nepal, China, Pakistan, Canada, Darussalam, Ethiopia, Italy, Australia, Indonesia. Meta-analysis of 8 cross-sectional studies showed that screen time 3 hours/ day can affect obesity in children and adolescents 2.4 times compared to screen time < 3 hours/ day. The results of the meta-analysis in 8 cross-sectional studies showed that fast food 3 times/ week had an effect on obesity in children and adolescents by 2.74 times compared to fast food < 3 times/week. Conclusion: The long duration of screen time and the frequency of consuming fast food often increase the risk of obesity in children and adolescents. Keywords: obesity, screen time, fast foods, meta-analysis Correspondence: Salwa Annisaa. Masters Program in Public Health. Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta 57126, Central Java, Indonesia. Email: salwaannisaa@gmail.com. Mobile: 0815411­80488. Journal of Health Promotion and Behavior (2021), 06(02): 164-175 DOI: https://doi.org/10.26911/thejhpb.2021.06.03.01

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.049
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.060
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.043
GPT teacher head0.333
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Health Promotion and BehaviorSame topicObesity, Physical Activity, DietFrench-language works237,207