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Record W2913304673 · doi:10.7202/1055442ar

To Supplement or Not to Supplement: Are Inuit Getting Enough Vitamin D?

2019· article· en· W2913304673 on OpenAlexvenueaboutno aff
Peter Fröst

Bibliographic record

VenueÉtudes/Inuit/Studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsRicketsVitamin D and neurologyOsteomalaciaBreastfeedingWeaningVitaminBreast milkMedicineSun exposureEnvironmental healthPhysiologyBiologyEndocrinologyPediatrics

Abstract

fetched live from OpenAlex

Inuit have vitamin D blood levels that generally fall within the range of insufficiency, even when they live on a traditional diet of fish and game meat. Without this vitamin, bones soften and become deformed, a condition called rickets in children and osteomalacia in adults. Until recent times, however, this condition was much rarer among Inuit than among non-Inuit, even when the latter included people living near Inuit communities under similar conditions of climate and housing. This rarity was attributed to extended breastfeeding and a high-meat/low-cereal diet. The situation subsequently reversed, with Inuit becoming more at risk of developing rickets, first in Labrador during the 1920s and later elsewhere. To reduce this excess risk, researchers have recommended vitamin D supplementation, arguing that breast milk has too little vitamin D and that even a traditional diet cannot provide the recommended daily intake. We should ask, however, whether the problem is definitional. Inuit may have lower levels of vitamin D because they need less, having adapted culturally and physiologically to an environment where this vitamin is less easily synthesized in the skin. These adaptations include a diet that enhances calcium bioavailability (by means of β-casein in breast milk, certain unknown substances in meat, and absence of phytic acid), as well as genetic changes that enable vitamin D to be used more efficiently. Although Inuit are today more at risk of developing rickets than are non-Inuit, this excess risk is nonetheless small and seems to have a dietary cause—namely, early weaning and abandonment of a high-meat/low-cereal diet.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.006

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 head0.084
GPT teacher head0.425
Teacher spread0.341 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations8
Published2019
Admission routes2
Has abstractyes

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