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Record W2014699606 · doi:10.1177/1059840511435248

Impact of Pubertal Development and Physical Activity on Heart Rate Variability in Overweight and Obese Children in Taiwan

2012· article· en· W2014699606 on OpenAlexaff
Su‐Ru Chen, Hung‐Wen Chiu, Yann-Jinn Lee, Tzong-Chi Sheen, Chii Jeng

Bibliographic record

VenueThe Journal of School Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsOverweightAutonomic nervous systemHeart rate variabilityObesityMedicineHeart rateInternal medicineEndocrinologyBlood pressure

Abstract

fetched live from OpenAlex

Child obesity is frequently associated with dysfunction of autonomic nervous system. Children in pubertal development were suggested to be vulnerable to autonomic nervous system problems such as decrease of heart rate variability from dysregulation of metabolic control. This study explored the influence of pubertal development on autonomic nervous system function in overweight and obese children and the concurrent effects of their physical activity. Eighty-four overweight or obese children and 87 normal weighted controls were recruited. Autonomic nervous system function was studied by measuring heart rate variability. Results showed that the overweight/obese children had significantly lower heart rate variability. Overweight/obese children in puberty had significantly lower heart rate variability which was positively correlated with their physical activity levels. In conclusion, overweight/obesity adversely affects the autonomic nervous system function of children especially during their pubertal development. Overweight/obese children should be encouraged to engage in physical activities during puberty to improve their autonomic nervous system function.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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

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 head0.017
GPT teacher head0.312
Teacher spread0.295 · 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 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

Citations25
Published2012
Admission routes1
Has abstractyes

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