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Record W2948005746 · doi:10.1093/pch/pxz066.057

58 Effect of high vs. standard dose wintertime vitamin D supplementation on adiposity in young healthy children: A secondary analysis of a pragmatic RCT

2019· article· en· W2948005746 on OpenAlexaff
Erika Gibson, Mary Aglipay, Charles Keown‐Stoneman, Catherine S. Birken, Kevin E. Thorpe, Deborah L. O’Connor, Patricia C. Parkin, Jonathon L. Maguire

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineRandomized controlled trialWaistInternal medicineAnthropometryVitamin D and neurologyVitaminBody mass indexCholesterolStandard scorePediatricsGastroenterologyEndocrinology

Abstract

fetched live from OpenAlex

Observational research has demonstrated an inverse relationship between vitamin D status and adiposity in children. However, no randomized controlled trials have evaluated the effect of high dose vitamin D supplementation on anthropometric and cardiovascular disease risk factors in healthy children. The primary objective of this study was to determine if high-dose (2000 IU/d) vitamin D supplementation over 4–8 winter months resulted in a decrease in mean BMI z-score (zBMI) when compared to standard-dose supplementation (400 IU/d) in healthy children aged 1–5 years. Secondary objectives were to determine if high-dose supplementation resulted in a decrease in mean waist circumference z-score (zWC), total serum cholesterol (TC), LDL cholesterol, non-HDL cholesterol, or an increase in HDL cholesterol, when compared to standard-dose supplementation. This was a pre-specified secondary analysis of a double-blinded randomized controlled trial. Healthy children aged 1 to 5 years were randomized to receive either ‘high-dose’ (2000 IU/day) or ‘standard-dose’ (400 IU/day) vitamin D supplementation over 4–8 winter months. For this analysis, linear regression adjusted for baseline zBMI was utilized to determine the effect of high-dose vs. standard-dose supplement on zBMI at follow-up. Similarly, linear regression adjusted for baseline values was used to examine the effect of high- vs. standard-dose supplementation on zWC, TC, non-HDL, LDL, and HDL. 542 children were included in the analysis (n = 272, 50.2% in the 2000 IU/d group). Mean age of participants was 2.55 years (SD = 1.51 years) and 56% (n= 302) were male. There was a non-significant trend towards lower zBMI in the high- vs. standard-dose group at followup (adjusted difference: 0.10, 95%CI: -0.02–0.22, p = 0.09). Waist circumference z-score (zWC) was significantly lower in the high- vs. standard- dose group at followup (adjusted difference: 0.17, 95%CI: 0.047–0.29, p = 0.007). Serum lipids were not different in the high- vs. standard-dose groups at followup (p=0.20, 0.35, 0.22 and 0.42, for TC, LDL, non-HDL, and HDL, respectively). In this secondary analysis of a large RCT, high-dose (2000 IU/day) vitamin D supplementation resulted in lower measures of waist circumference, but not serum lipid levels, than standard-dose supplementation (400 IU/day) after 4–8 winter months. Wintertime high-dose vitamin D supplementation may have a role in minimizing wintertime adiposity gains in healthy 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 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)0.019
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.015
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.002
GPT teacher head0.247
Teacher spread0.245 · 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 designRandomized trial
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

Citations1
Published2019
Admission routes1
Has abstractyes

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