Vitamin B12, B6, or Folate and Cognitive Function in Community-Dwelling Older Adults: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Previous studies have indicated that B vitamin deficiencies are an essential cause of neurological pathology. There is a need to provide evidence of the benefit of B vitamins for the prevention of cognitive decline in community-dwelling older adults. OBJECTIVE: To examine the association between intake and plasma levels of vitamins B12, B6, and folate and cognitive function in older populations through a systematic review and meta-analysis. METHODS: Medline (PubMed), EMBASE, and Cochrane databases were used to search the literature though August 8, 2019. We included observational population-based studies evaluating the association between concentrations or intake levels of vitamins B6, B12, or folate and cognition in older adults aged ≥45 years. The quality of all studies was assessed by the modified Newcastle-Ottawa Scale. Odds ratios (ORs) and hazard ratios (HRs) were analyzed by the random-effects model. Sensitivity analyses were conducted by excluding the studies with significant heterogeneity. RESULTS: Twenty-one observational studies with sample sizes ranging from 155-7030 were included in the meta-analysis. Higher levels of vitamin B12 (OR = 0.77, 95% CI = 0.61-0.97) and folate concentration (OR = 0.68, 95% CI = 0.51-0.90) were associated with better cognition in cross-sectional studies, but not in sensitivity analyses or prospective studies. High vitamin B6 concentrations showed no significant benefit on cognition and dementia risk. Prospective studies did not provide substantial evidence for the relationship. CONCLUSION: The results from our meta-analysis suggest that vitamins B12, B6, and folate may not be modifiable risk factors for slowing cognitive decline among community-dwelling older individuals.
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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.038 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".