The Effects of Vitamin D Insufficiency and Seasonal Decrease on Cognition
Bibliographic record
Abstract
BACKGROUND: Vitamin D3 (cholecalciferol) deficiency has been associated with dementia and cognitive decline. Which cognitive domains are most associated with D3 levels and how seasonal fluctuations in levels relate to cognition is unclear. We addressed these questions using a prospective observational study examining associations between D3 levels and cognition among individuals living in northern latitudes (54°N) in summer and winter. METHODS: Healthy adult participants underwent testing in summer and winter of D3 levels and cognition, using the Symbol digit Modalities test, phonemic fluency, digit Span and CANTAB battery. RESULTS: Of 32 participants tested in the summer, 46% were D3 insufficient (<75 nmol/L) and performed worse on digit Span Backward (DS-B) (μ=5.8, SD=2) than those who were sufficient (μ=7.9, SD=2), p=0.018. In multivariate analyses, sufficiency status was an independent predictor of dS-B, (b=0.41, p=0.02). The majority (63%) of 19 participants tested in winter were D3 insufficient, with levels declining by a median of 15 nmol/L overall. Those with insufficient levels performed worse (i.e., higher scores) on the CANTAB Spatial Working Memory (SWM) task (μ=36.1, SD=6 versus μ=29.3, SD=8), p=0.05). Those with larger drops in levels (≥15 nmol/L) showed decline/less improvement on the CANTAB one touch Stockings of Cambridge (OTS) task, (μ=0.50, SD=1.9 versus μ=-2.11, SD=2.6, p=0.01), a test of working memory/executive functioning. CONCLUSIONS: Vitamin D3 insufficiency and seasonal declines ≥15 nmol/L were associated with inferior working memory/executive functioning. While our findings require confirmation, they suggest that sufficient D3 levels should be maintained year-round, likely necessitating supplementation, at least during winter at higher latitudes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".