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Record W2914377367 · doi:10.1210/js.2018-00349

Relationship Between Vitamin D Status From Childhood to Early Adulthood With Body Composition in Young Australian Adults

2019· article· en· W2914377367 on OpenAlexafffund
Kun Zhu, Wendy H. Oddy, Patrick G. Holt, Wendy Chan She Ping‐Delfos, Joanne McVeigh, Leon Straker, Trevor A. Mori, Stephen J. Lye, Craig E. Pennell, John P. Walsh

Bibliographic record

VenueJournal of the Endocrine Society · 2019
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersCancer Council VictoriaNational Health and Medical Research CouncilCanadian Institutes of Health ResearchWomen and Infants Research Foundation
KeywordsVitamin D and neurologyOffspringInternal medicineLean body massAdipose tissueEndocrinologyCohortvitamin D deficiencyMedicineYoung adultComposition (language)VitaminPregnancyDemographyPhysiologyBiologyBody weight

Abstract

fetched live from OpenAlex

CONTEXT: Vitamin D plays a role in the differentiation and metabolism of skeletal muscle and, possibly, adipose tissue; however, the relationship between vitamin D status during growth and body composition in early adulthood is unclear. OBJECTIVE: We examined associations between vitamin D status in childhood, adolescence, and early adulthood with body composition at age 20 years. DESIGN SETTING PARTICIPANTS: We studied 821 offspring (385 females) of the Western Australian Pregnancy Cohort Study who had ≥3 serum 25-hydroxyvitamin D [25(OH)D] at age 6, 14, 17, and 20 years and body composition assessed at age 20 using dual-energy x-ray absorptiometry. The participants were grouped into four vitamin D status trajectories: consistently lower, decreasing, increasing, and consistently higher. RESULTS: < 0.05 for all). CONCLUSIONS: In the present predominantly white, relatively vitamin D-replete cohort, a higher vitamin D status trajectory from childhood to early adulthood was associated with a greater LBM in males and lower FBM in both sexes at age 20.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.014
GPT teacher head0.291
Teacher spread0.278 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

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