A Review of vitamin D deficiency during pregnancy: who is affected?
Bibliographic record
Abstract
OBJECTIVES: Vitamin D deficiencies have been documented in several populations, including aboriginal Canadians from isolated northern communities. Such deficiencies can impact the health of both the mother and her infant. This review was performed to determine how widespread vitamin deficiency is during pregnancy. STUDY DESIGN: Electronic literature search. METHODS: A Medline search was conducted using the Mesh terms "pregnancy" and "vitamin D". Those studies meeting the inclusion criteria were reviewed. RESULTS: 35 of 76 studies reported deficient mean, or median, concentrations of 25(OH)D. Low concentrations were reported among different ethnic groups around the world. In addition, deficient concentrations were identified in 3 northern First Nations communities in Manitoba. CONCLUSIONS: Such deficiencies are of concern, as the developing fetus acquires its 25(OH)D across the placenta and may influence infant health. Future research is required to resolve the discourse surrounding ambiguous threshold values for vitamin D deficiencies and insufficiencies and to identify effective strategies to improve the vitamin D status of expectant women. Vitamin D supplementation may be necessary for many women during pregnancy, especially those in northern regions where endogenous synthesis may be constrained.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".