Bibliographic record
Abstract
BACKGROUND: Vascular diseases, including heart disease and stroke, are some of the leading contributors to dementia worldwide. This aim of this study is to provide an update on the prevalence of dementia, heart disease, and stroke in Canadian households. Targeting all three conditions simultaneously may be key to disease prevention and health promotion efforts for dementia. METHODS: Using nationally representative household data from the Canadian Community Health Survey, we calculated age standardized prevalence rates of self-reported dementia, heart disease and stroke in Canadian adults aged 18 years and over, from 2016 to 2021. Additionally, we examined sex differences in age standardized prevalence rates of all three conditions. Poisson regression models were used to determine statistically significant trends and sex differences in trends over time. RESULTS: Approximately 1% (~130,000 – 170,000 individuals) of Canadians reported living at home with dementia, 4.6%-5.2% (~135,000 – 154,000 individuals) reported heart disease, and 1.3% (~36,000 – 39,000 individuals) reported stroke from 2016-2020. Overall, age standardized prevalence rates minimally decreased for stroke (p=0.007) but remain unchanged for heart disease (p=0.10) and dementia (p=0.37) from 2016 to 2021. Prevalence rates of dementia changed significantly from 2016 to 2021 in males and females independently (p=0.009 and p=0.0009 respectively). CONCLUSION: Overall, there has been no significant improvements in the prevalence dementia, heart disease, or stroke over the past six years in Canadian households. Reducing the national burden of these conditions will require greater disease prevention efforts at the level of the community including, but not limited to, screening and early detection of risk factors, lifestyle modifications and support for caregivers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".