Trends of Dementia among Community-Dwelling Adults in Ontario, Canada, 2010–2015
Bibliographic record
Abstract
BACKGROUND: There are increasing numbers of people living with dementia (PLWD) and most reside in community settings. Characterizing the number of individuals affected with dementia and their transitions are important to understand in order to plan for their healthcare needs. Using administrative health data in Ontario, Canada, we examined recent trends in the prevalence and incidence of dementia among the community-dwelling population, described their characteristics, and investigated admissions to long-term care (LTC) and overall survival. METHODS: Using a validated case ascertainment algorithm, we performed a population-based retrospective cohort study of community-dwelling PLWD aged 40-105 years old between 2010 and 2015. We assessed crude and age- and sex-adjusted prevalence and incidence, cohort characteristics, and time to LTC admission and survival. RESULTS: Between 2010 and 2015, the adjusted community prevalence increased by 9.5% (p < 0.001), while the incidence decreased by 15.8% (p < 0.001). Demographic and socioeconomic characteristics remained similar over time, while the prevalence of comorbidities increased significantly from 2010 to 2015. There was no difference in the time to LTC admission for individuals diagnosed in 2014 when compared to 2010 (p = 0.06). A lower risk of 2-year mortality was observed for individuals diagnosed in 2015 compared to 2010 (HR 0.93, 95% CI 0.90-0.97, p < 0.001). CONCLUSION: There was an increase in the prevalence of dementia despite decreasing incidence among community-dwelling PLWD. Lower rates of mortality indicate that PLWD are surviving longer following diagnosis. Adequate resources and planning are required to support this growing population, considering the changing population size and characteristics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".