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Record W2793315047 · doi:10.1111/ijpo.12276

Thresholds of physical activity associated with obesity by level of sedentary behaviour in children

2018· article· en· W2793315047 on OpenAlexaff
Jean‐Philippe Chaput, Joel D. Barnes, Mark S. Tremblay, Mikael Fogelholm, Gang Hu, Estelle V. Lambert, Carol Maher, José Maia, Tim Olds, Vincent Onywera, Olga L. Sarmiento, Martyn Standage, Catrine Tudor‐Locke, Peter T. Katzmarzyk

Bibliographic record

VenuePediatric Obesity · 2018
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersCoca-Cola Foundation
KeywordsMedicineObesitySedentary behaviorWaistPhysical activityScreen timeChildhood obesitySedentary lifestyleCross-sectional studyDemographyReceiver operating characteristicPhysical therapyOverweightInternal medicine

Abstract

fetched live from OpenAlex

Summary Background It is unknown whether moderate‐to‐vigorous physical activity (MVPA) thresholds for obesity should be adapted depending on level of sedentary behaviour in children. Objective The objective of the study is to determine the MVPA thresholds that best discriminate between obese and non‐obese children, by level of screen time and total sedentary time in 12 countries. Methods This multinational, cross‐sectional study included 6522 children 9–11 years of age. MVPA and sedentary time were assessed using waist‐worn accelerometry, while screen time was self‐reported. Obesity was defined according to the World Health Organization reference data. Results Receiver operating characteristic curve analyses showed that the best thresholds of MVPA to predict obesity ranged from 53.8 to 73.9 min d −1 in boys and from 41.7 to 58.7 min d −1 in girls, depending on the level of screen time. The MVPA cut‐offs to predict obesity ranged from 37.9 to 75.9 min d −1 in boys and from 32.5 to 62.7 min d −1 in girls, depending on the level of sedentary behaviour. The areas under the curve ranged from 0.57 to 0.73 (‘fail’ to ‘fair’ accuracy), and most sensitivity and specificity values were below 85%, similar to MVPA alone. Country‐specific analyses provided similar findings. Conclusions The addition of sedentary behaviour levels to MVPA did not result in a better predictive ability to classify children as obese/non‐obese compared with MVPA alone.

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 score0.041
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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