Inequalities in the burden of disease due to dementia, including Alzheimer disease, in British Columbia, Canada, from 2001 to 2022
Bibliographic record
Abstract
INTRODUCTION: Disability-adjusted life-years (DALYs) integrate mortality and prevalence (or incidence) data. DALYs can be used as a surveillance measure to assess dementia burden and inequalities. METHODS: We utilized dementia case and mortality counts from linked administrative data to estimate incidence, prevalence, cause-specific mortality and DALYs in people aged 65 years and older, from 2001 to 2022, in British Columbia, Canada. Dementiaspecific mortality rates adjusted for changes in death certification practices over time were estimated using logistic regression that incorporated multiple cause-of-death data from vital statistics records. All measures were stratified by sex; DALYs were also stratified by age and area-based socioeconomic status (SES) quintiles. Average annual percent change (AAPC) in rates was estimated using joinpoint regression. RESULTS: Age-standardized dementia incidence and prevalence have declined since 2013, while mortality has increased by, on average, 1.6% per year since 2001 (95% CI: 1.4% to 1.8%). Age-standardized DALYs have increased by, on average, 1.4% per year (95% CI: 1.3% to 1.4%). DALY rates are highest in females aged 90 years and older but are increasing more rapidly in males. DALYs have declined for those in the least deprived SES quintile (AAPC: -0.6%; 95% CI: -1.0% to -0.3%) and conversely, have increased - with recent rates the highest - in the most deprived quintile (AAPC: 2.9%; 95% CI: 2.5% to 3.2%). CONCLUSION: The socioeconomic gap in dementia disease burden has widened over time in British Columbia. DALYs are highest in females aged 90 years and older, but the overall gap between males and females has declined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".