The Incidence and Prevalence of Dementia Among Ontario Adults With and Without Intellectual and Developmental Disabilities
Bibliographic record
Abstract
OBJECTIVES: There are more than 66,000 Ontario adults living with intellectual and developmental disabilities (IDD). While the risk of dementia is well established among those with Down Syndrome (DS), there is limited research in persons with IDD excluding DS (Non-DS IDD). This study aimed to compare the incidence and prevalence of dementia in Ontario adults with and without IDD over time and by demographic information. METHODS: Administrative data were used to calculate and compare the annual age- and sex-adjusted cumulative incidence and period prevalence of dementia from fiscal years 2011/12 to 2020/21 in three cohorts: (1) Non-DS IDD, (2) DS, and (3) No IDD. RESULTS: Compared to persons without IDD, cumulative incidence of dementia was on average 4.27 and 5.33 times higher in persons with Non-DS IDD and DS respectively and period prevalence of dementia was on average 4.87 and 5.93 times higher in persons with Non-DS IDD and DS respectively. CONCLUSIONS: Given the increased rates of dementia within the IDD population, it is imperative that early dementia screening take place, appropriate health and social services are implemented and more actions are taken to delay the onset of dementia, while considering the needs of this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".