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Record W2606547955 · doi:10.3389/fpubh.2017.00058

Overweight and Obesity in Children under 5 Years: Surveillance Opportunities and Challenges for the WHO European Region

2017· review· en· W2606547955 on OpenAlexaff
Rebecca Jones, Jo Jewell, Rhea Saksena, Ximena Ramos Salas, João Breda

Bibliographic record

VenueFrontiers in Public Health · 2017
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Alberta
FundersWorld Health Organization
KeywordsOverweightObesityEnvironmental healthMedicinePediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: Many children who have overweight or obesity before puberty can develop obesity in early adulthood, which is associated with increased morbidity and mortality. The preschool years (ages 0-5) represents a point of opportunity for children to be active, develop healthy eating habits, and maintain healthy growth. Surveillance of childhood overweight and obesity in this age group can help inform future policies and interventions. OBJECTIVE: To review and report available prevalence data in WHO European Region Member States and determine how many countries can accurately report on rates of overweight and obesity in children under 5 years. METHODS: We conducted a rapid review of studies reporting on overweight and obesity prevalence in children ages 0-5 in the WHO European region member states from 1998 to 2015. RESULTS: Currently, 35 of the 53 member states have data providing prevalence rates for overweight and obesity for children under 5 years. There was little consistency in study methods, impacting comparability across countries. The prevalence of overweight and obesity in children under 5 years ranges from 1 to 28.6% across member states. CONCLUSION: Although measuring overweight and obesity in this age group may be challenging, there is an opportunity to leverage existing surveillance resources in the WHO European Region.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.230
GPT teacher head0.355
Teacher spread0.124 · 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 designOther design
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

Citations54
Published2017
Admission routes1
Has abstractyes

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