Tea intake or consumption and the risk of dementia: a meta-analysis of prospective cohort studies
Bibliographic record
Abstract
Purpose Dementia affects as many as 130 million people, which presents a significant and growing medical burden globally. This meta-analysis aims to assess whether tea intake, tea consumption can reduce the risk of dementia, Alzheimer’s disease (AD) and Vascular dementia (VD). Patients and methods Cochrane Library, PubMed and Embase were searched for cohort studies from inception to November 1, 2022. The Newcastle Ottawa Quality Assessment Scale (NOS) was applied to evaluate the risk of bias of the included studies. We extracted the data as the relative risks (RRs) for the outcome of the interest, and conducted the meta-analysis utilizing the random effect model due to the certain heterogeneity. Sensitivity analysis were performed by moving one study at a time, Subgroup-analysis was carried out according to different ages and dementia types. And the funnel plots based on Egger’s and Begger’s regression tests were used to evaluate publication bias. All statistical analyses were performed using Stata statistical software version 14.0 and R studio version 4.2.0. Results Seven prospective cohort studies covering 410,951 individuals, which were published from 2009 and 2022 were included in this meta-analysis. The methodological quality of these studies was relatively with five out of seven being of high quality and the remaining being of moderate. The pooling analysis shows that the relationship between tea intake or consumption is associated with a reduced risk of all-cause dementia (RR = 0.71, 95% CI [0.57–0.88], I 2 = 79.0%, p < 0.01). Further, the subgroup-analysis revealed that tea intake or consumption is associated with a reduced risk of AD (RR = 0.88, 95% CI [0.79–0.99], I 2 = 52.6%, p = 0.024) and VD (RR = 0.75, 95% CI [0.66–0.85], I = 0.00%, p < 0.001). Lastly, tea intake or consumption could reduce the risk of all-cause dementia to a greater degree among populations with less physical activity, older age, APOE carriers, and smokers. Conclusion Our meta-analysis demonstrated that tea (green tea or black tea) intake or consumption is associated with a significant reduction in the risk of dementia, AD or VD. These findings provide evidence that tea intake or consumption should be recognized as an independent protective factor against the onset of dementia, AD or VD.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".