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Record W2943184274 · doi:10.1002/oby.22424

Leisure‐Time Sedentary Behavior and Obesity Among 116,762 Adolescents Aged 12‐15 Years from 41 Low‐ and Middle‐Income Countries

2019· article· en· W2943184274 on OpenAlexafffund
Garcia Ashdown‐Franks, Davy Vancampfort, Joseph Firth, Nicola Veronese, Sarah E. Jackson, Lee Smith, Brendon Stubbs, Ai Koyanagi

Bibliographic record

VenueObesity · 2019
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Toronto
FundersEuropean Regional Development FundMitacsInstituto de Salud Carlos IIINational Institute for Health and Care Research
KeywordsObesityMedicineOddsLow and middle income countriesPsychological interventionOdds ratioSedentary behaviorDemographyCross-sectional studyEnvironmental healthSedentary lifestyleAdolescent ObesityLogistic regressionGerontologyDeveloping countryOverweightEndocrinologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Rates of adolescent obesity are increasing worldwide, with steeper increases being observed in low- and middle-income countries (LMICs). Sedentary behavior (SB) has been associated with various physical and mental health conditions. Little is known about the association between SB and obesity among adolescents in LMICs. This cross-sectional study explored the associations between SB and obesity in adolescents from 41 LMICs. METHODS: Obesity was measured using BMI; SB was assessed through self-report and was considered for all times except when subjects were at school or doing homework. RESULTS: Data from the Global School-based Student Health Survey were analyzed in 116,762 adolescents (mean [SD] age 13.8 [1.0] years; 48.6% female). The overall prevalence of obesity was 4%, and the prevalence of ≥ 3 h/d of SB was 26%. The prevalence of obesity and SB were lowest in low-income countries and highest in upper-middle-income countries. SB for ≥ 3 h/d was associated with higher odds of obesity in 32 countries. This relationship was strongest among low-income countries. CONCLUSIONS: Being sedentary for ≥ 3 h/d is associated with increased odds of obesity in adolescence. Future longitudinal data are required to confirm these findings and to inform interventions targeting SB among adolescents in LMICs, thereby reducing the prevalence of obesity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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 designObservational
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

Citations40
Published2019
Admission routes2
Has abstractyes

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