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Vitamin D status in an ethnically diverse population of young Canadian adults

2011· article· en· W3174557424 on OpenAlexafffundabout
Bibiana García‐Bailo, Alaa Badawi, Darren Brenner, Daiva E. Nielsen, Hyeon‐Joo Lee, Mohamed A. Karmali, Ahmed El‐Sohemy

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsPublic Health Agency of CanadaUniversity of Toronto
FundersPublic Health Agency of CanadaAdvanced Foods and Materials Network
KeywordsMedicinevitamin D deficiencyEthnic groupDemographyPopulationIncidence (geometry)Dark skinEnvironmental healthVitamin D and neurologyInternal medicine

Abstract

fetched live from OpenAlex

Vitamin D deficiency, defined as serum 25(OH)D <27.5 nmol/L, has been linked to risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). Vitamin D can be synthesized in the skin after exposure to ultraviolet (UV) radiation. Individuals in latitudes with seasonal shortages of exposure to UV radiation are at higher risk of vitamin D deficiency, especially certain ethnic groups. The objective was to determine vitamin D status in an ethnically diverse population (n=1027) of young Canadian adults aged 20–29 years. We found overall differences in deficiency prevalence among different ethnic groups, with 44% of South Asians being deficient, compared to 6% of Caucasians and 16% of East Asians. The prevalence of vitamin D deficiency varied by season. In winter, deficiency ranged from 12% in Caucasians, to 25% in East Asians and 51% in South Asians. In spring, deficiency was 1% in Caucasians, 4% in East Asians and 26% in South Asians. In summer, deficiency was 1% in Caucasians, 10% in East Asians and 50% in South Asians. In fall, deficiency was 9% in Caucasians, 35% in East Asians and 55% in South Asians. We have shown that vitamin D deficiency is common in young Canadian adults, particularly in South Asians. This deficiency may partly explain the high incidence of T2D and CVD in this group later in life. Research Support from the Public Health Agency of Canada and the Advanced Foods and Materials Network. Grant Funding Source : Public Health Agency of Canada, Advanced Foods and Materials Network

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 score0.987
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.000
Scholarly communication0.0010.000
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 head0.049
GPT teacher head0.311
Teacher spread0.262 · 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

Citations0
Published2011
Admission routes3
Has abstractyes

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