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Bone Mineral Accretion is Increased During Winter and is Positively Related to Lean Mass Accretion and Calcium Intake in Healthy Children 2–8 y

2017· article· en· W4389020689 on OpenAlexafffundabout
Neil R. Brett, Catherine A. Vanstone, Hope A. Weiler

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsMcGill University
FundersDairy Farmers of Canada
KeywordsBone mineralMedicineVitamin D and neurologyLean body massAnthropometryAnimal scienceDemographicsInternal medicineOsteoporosisDemographyBody weightBiology

Abstract

fetched live from OpenAlex

In young children, it is not well understood how bone mineral accretion is related to lean mass accretion and vitamin D metabolites. Thus, the objective of this study was to explore over 12 mo how bone parameters relate to lean mass parameters and vitamin D metabolites in children 2–8 y. This was a secondary analysis of data from 2 clinical trials (clinicaltrials.gov: NCT02097160, NCT02387892) in Montreal. Children 2–8 y consumed their normal vitamin D intake for 12 mo starting in Apr 2014 (n=21) with 4 study visits (Apr and Oct 2014, Jan and Apr 2015). At all 4 time-points, serum vitamin D status (total serum 25(OH)D: Liaison, Diasorin and LC-MS/MS) was measured and at 6, 9 and 12 mo, bone biomarkers were measured (Liaison, Diasorin, IDS iSYS) followed by standardized anthropometry, demographics plus activity and dietary questionnaires. Whole body bone mineral content (BMC) bone mineral density (BMD), and body composition parameters were measured at baseline, 6 and 12 mo and lumbar spine (L1–L4) BMC and BMD was available at 6 and 12 mo using dual-energy x-ray absorptiometry (Hologic Discovery, APEX software version 13.3). Linear regression and a mixed model ANOVA were used. In Apr 2014, children were 5.0 ± 1.9 y (range 2.2 – 7.7 y), 52% (11/21) male, with BMI Z-score of 0.79 ± 0.90. All but 1 child had 12 mo average physical activity meeting the 60 min/d guidelines. Fifty percent of children (10/20) had 12 mo average calcium intakes meeting the RDA and no children had 12 mo average vitamin D intakes meeting the RDA. However, 80% (16/20) of children maintained serum 25(OH)D ≥ 50 nmol/L over the 12 mo. Height velocity was not significantly different between summer and winter (0–6 mo: 0.61 ± 0.09 cm/mo, 6–12 mo: 0.57 ± 0.13 cm/mo). The % change in whole body BMC increased (p<0.01) during winter (Figure 1A). Mean winter % change of the lumbar spine BMC was also positive (whole body: 6.5 ± 2.8%, lumbar spine: 8.0 ± 5.8%). In line with this, bone formation biomarkers increased from 6–12 mo (p< 0.05) (Figure 1B, C) whilst bone resorption markers did not change (p> 0.05) (Figure 1D, E). Using linear regression, there was a 5.5% higher winter lumbar spine bone mineral accretion for every 5% increment of summer % change in lean mass (r2=0.76). Similarly, there was a 2.5% higher winter whole body BMC % change for every 5% increment in 12 mo % change in lean mass (r2=0.77). In regression models for lumbar spine winter % change (r2=0.76) and 12 mo whole body % change (r2=0.62) in BMC, for every increment of 200 mg of calcium intake/1000 kcal, BMC % change was higher by 1%. Twelve month changes in 25(OH)D (Figure 1F) were relatively homogenous among children, which may explain why 25(OH)D was not a significant contributor to changes in whole body and lumbar spine BMC. Our results suggest that winter bone mineral accretion may be positively and temporarily related to lean mass accretion in the preceding seasons, in addition to dietary calcium intake in children 2–8 y. Studies are needed to further elucidate the extent of delays in bone mineral accrual in response to lean mass accrual in young children. Support or Funding Information Funding from Dairy Farmers of Canada, The Canada Foundation for Innovation and Canada Research Chairs Bone mineral (BMC) % Δ (Panel A) in summer and winter. Osteocalcin, type 1 procollagen N-terminus propepetide (P1NP) and c-terminal telopeptide (CTX) at 6, 9 and 12 mo (Panels B–D). Parathyroid hormone (PTH) and 25(OH)D at all 4 time points (Panels E, F). a,b Different superscripts depict significant differences (p< 0.05), using a mixed model ANOVA. Apr 2014, Oct 2014 and Jan 2015: n=21, Apr 2015: n=19. Data are mean (SD) as a group and individual participant data over time.

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)0.001
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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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".

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Citations1
Published2017
Admission routes3
Has abstractyes

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