A Systematic Review and Meta-Analysis of The Effect of Low Vitamin D on Cognition
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE:With an aging populationand no cure for dementia on the horizon, risk factor modi-fication prior to disease onset is an urgent health priority.Therefore, this review examined the effect of low vitaminD status or vitamin D supplementation on cognition inmidlife and older adults without a diagnosis of dementia.DESIGN:Systematic review and random effect meta-ana-lysis.SETTING:Observational (cross-sectional and longitudinalcohort) studies comparing low and high vitamin D statusand interventions comparing vitamin D supplementationwith a control group were included in the review andmeta-analysis.PARTICIPANTS:Studies including adults and olderadults without a dementia diagnosis were included.MEASUREMENTS:Medline (PubMed), AMED, PsychINFO, and Cochrane Central databases were searched forarticles until August 2016. The Newcastle-Ottawa Scaleand Physiotherapy Evidence Database assessed method-ological quality of all studies.RESULTS:Twenty-six observational and three interven-tion studies (n=19–9,556) were included in the meta-ana-lysis. Low vitamin D was associated with worse cognitiveperformance (OR=1.24, CI=1.14–1.35) and cognitivedecline (OR=1.26, CI=1.09–1.23); with cross-sectionalyielding a stronger effect compared to longitudinal studies.Vitamin D supplementation showed no significant benefiton cognition compared with control (SMD=0.21,CI= 0.05 to 0.46).CONCLUSION:Observational evidence demonstrateslow vitamin D is related to poorer cognition; however,interventional studies are yet to show a clear benefit fromvitamin D supplementation. From the evidence to date,there is likely a therapeutic age window relevant to thedevelopment of disease and therefore vitamin D therapy.Longitudinal lifespan studies are necessary to depict theoptimal timing and duration in which repletion of vitaminD may protect against cognitive decline and dementia inaging, to better inform trials and practice towards a suc-cessful therapy.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".