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Record W2121630782 · doi:10.55016/ojs/sppp.v8i1.42520

D-fence Against the Canadian Winter: Making Insufficient Vitamin D Levels a Higher Priority for Public Health

2015· article· en· W2121630782 on OpenAlexaffabout
Jennifer Zwicker

Bibliographic record

VenueThe School of Public Policy Publications · 2015
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFence (mathematics)Public healthEnvironmental healthEnvironmental scienceMedicineEngineeringNursing

Abstract

fetched live from OpenAlex

With most of the country situated above the latitude of the 42nd parallel north, there is a significant portion of the Canadian population that is not getting enough of the sunshine vitamin during the winter. Vitamin D is naturally produced when skin is exposed to sunlight, however during the winter months in Canada the sun is too low in the sky for this to occur. A full quarter of the Canadian population is estimated to have vitamin D levels so low as to be considered insufficient or deficient by Health Canada guidelines. Increasing vitamin D intake should be considered a public health priority. Vitamin D deficiency is known to be linked to rickets in children and osteomalacia in adults (bone softening and malformation) as well as osteoporosis (loss of bone density, increasing susceptibility to fractures). However a growing body of evidence also suggests that vitamin D may have a role in the prevention of chronic diseases such as heart disease, high blood pressure, diabetes, cancer, cognitive decline, Parkinson’s disease, multiple sclerosis and arthritis. There is, of course, no way to change Canada’s proximity to the equator. But there are ways to help Canadians get more vitamin D through dietary intake. Improving the vitamin D status of the Canadian population through food fortification and dietary supplements represents an inexpensive intervention that can improve the health of the population, but debate remains over how much vitamin D the Canadian population needs and how to ensure the population adheres to whatever recommendations are made. Food fortification has already demonstrated its effectiveness in improving vitamin D levels (as it has for other public health priorities, such as with iodized salt). Decades ago, the prevalence of rickets in Canadian children led health professionals to lobby for, and win, legislation making vitamin D fortification mandatory for milk. Other foods, such as orange juice, milk of plant origin and margarine are sometimes also fortified with vitamin D. However many Canadians do not consume milk or the other fortified foods or do not take dietary supplements at the current recommended levels, increasing their risk of vitamin D insufficiency. It is clear there is a need to gain a better understanding of the benefits and the costs of strategies associated with vitamin D intake in the general population. There have been longstanding concerns about the risk of people consuming too much vitamin D (leading to hypercalcemia). More recently there has emerged great disagreement in the scientific and regulatory communities over what constitutes an excessive dosage of vitamin D, and even what constitutes the optimal blood-serum level for vitamin D. The inability to settle on firm guidelines is paralyzing any movement towards increasing vitamin D intake in the Canadian population. Fortification and public health strategies are needed to ensure current vitamin D targets are met. Health Canada’s proposal to allow greater levels of vitamins and minerals to be added to foods, to meet consumer demand (within maximum limits), has been on the table since 2005. A decade later, the Canadian winters have grown no shorter, and the solar zenith angle has not changed. It is becoming an increasingly urgent matter of public health to reach a consensus on updated guidelines for vitamin D intake levels and limits, to better inform Canadians.

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)0.008
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.053
Threshold uncertainty score0.383

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0180.011
Scholarly communication0.0100.006
Open science0.0060.008
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0290.006

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 head0.232
GPT teacher head0.417
Teacher spread0.186 · 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 designNot applicable
Domainnot available
GenreCommentary

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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Citations0
Published2015
Admission routes2
Has abstractyes

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