Migraine and the risk of all‐cause dementia, Alzheimer's disease, and vascular dementia: A prospective cohort study in community‐dwelling older adults
Bibliographic record
Abstract
OBJECTIVES: Dementia is the most common neurological disease in older adults; headaches, including migraines, are the most common neurological disorder across all ages. The objective of this study was to explore the relationship between migraines and dementia, including Alzheimer's disease (AD) and vascular dementia (VaD). METHODS: Analyses were based on 679 community-dwelling participants 65+ years from the Manitoba Study of Health and Aging, a population-based, prospective cohort study. Participants screened as cognitively intact at baseline had complete data on migraine history and all covariates at baseline and were assessed for cognitive outcomes (all-cause dementia, AD, and VaD) 5 years later. The association of exposure (lifetime history of migraines), confounding (age, gender, education, and depression), and intervening variables (hypertension, myocardial infarction, other heart conditions, stroke, and diabetes) with all-cause dementia and dementia subtypes (AD and VaD) was assessed using multiple logistic regression models. RESULTS: A history of migraines was significantly associated with both all-cause dementia (odds ratio [OR]=2.97; 95% confidence interval [CI]=1.25-6.61) and AD (OR=4.22; 95% CI=1.59-10.42), even after adjustment for confounding and intervening variables. Migraines were not significantly associated with VaD either before (OR=1.83; 95% CI=0.39-8.52) or after (OR=1.52; 95% CI=0.20-7.23) such adjustment. CONCLUSIONS: Migraines were a significant risk factor for AD and all-cause dementia. Despite the vascular mechanisms involved in migraine physiology, migraines were not significantly associated with VaD in this study. Recognition of the long-term detrimental consequences of migraines for AD and dementia has implications for migraine management, as well as for our understanding of AD etiology.
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 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 | 0.001 | 0.000 |
| 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) | 0.000 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".