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Record W2061113754 · doi:10.1016/j.pmedr.2014.11.002

Association between leg length-to-height ratio and metabolic syndrome in Chinese children aged 3 to 6years

2014· article· en· W2061113754 on OpenAlexafffund
Gongshu Liu, Jian Liu, Nan Li, Zhe-ying Tang, Fengrong Lan, Lei Pan, Xilin Yang, Gang Hu, Zhijie Yu

Bibliographic record

VenuePreventive Medicine Reports · 2014
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsDalhousie UniversityBrock University
FundersTianjin Women's and Children's Health CenterChinese Diabetes SocietyBrock UniversityEuropean Foundation for the Study of Diabetes
KeywordsQuartileMedicineOdds ratioWaistAnthropometryConfidence intervalMetabolic syndromeDemographyInternal medicineBody mass indexWaist-to-height ratioLogistic regressionWaist–hip ratioObesity

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study is to investigate the association between leg-length-to-height ratio (LLHR) and metabolic syndrome (MetS) among Chinese children. METHODS: 1236 children (619 obese and 617 nonobese children) aged 3-6 years participated in a cross-sectional survey in 2005 in Tianjin, China. Information on body adiposity, metabolic traits, and related covariates was obtained using a standardized protocol. LLHR was calculated as the ratio of leg length to stature. RESULTS: In the multivariable logistic regression analyses, compared with those in the lowest quartile, odds ratios (OR) and 95% confidence intervals (CI) of MetS among children in the second through the highest quartiles of LLHR Z-score were 0.89 (95% CI, 0.64-1.25), 0.45 (95% CI, 0.32-0.63), and 0.37 (95% CI, 0.26-0.53), respectively, (P for trend < 0.0001 across LLHR Z-score quartiles). Compared with children with both higher levels of LLHR and lower levels of adipose indices, the corresponding ORs of MetS for those with both lower levels of LLHR and higher levels of anthropometric indices were 4.51 (95% CI, 3.08-6.62) for BMI Z-score, 3.86 (95% CI, 2.60-5.73) for waist circumference, and 2.75 (95% CI, 1.85-4.10) for waist-to-hip ratio, respectively. CONCLUSIONS: Greater LLHR is inversely associated with MetS in Chinese children.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 integrity0.0000.000
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 head0.012
GPT teacher head0.293
Teacher spread0.282 · 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.

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

Citations8
Published2014
Admission routes2
Has abstractyes

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