Patterns of mortality among adults with intellectual and developmental disabilities in the Canadian province of Manitoba
Bibliographic record
Abstract
Abstract Objectives The goals of this study were to examine and compare (a) the annual adult mortality rates and (b) the most commonly reported underlying causes of death between a cohort of Manitobans with intellectual and developmental disabilities (IDD) and a matched comparison group without IDD. Methods Using linked health and nonhealth administrative data, a cohort of Manitoba adults with IDD, aged 25–99 years in 2012, was identified. Each person in the study cohort was matched with three persons without IDD based on age, sex, region of residence, and morbidity level. The two groups were followed for three years (2013–2015). Crude annual adult mortality rates and avoidable premature mortality rates were calculated. The leading causes of death over the 3‐year study period were tabulated by ICD‐10 chapter. Coding of the underlying causes of death was reviewed. Results The crude annual mortality rates for Manitoba adults with IDD were 1.8–2.4 times higher than those for the matched comparison group and remained stable over time. Disparities in mortality rates for the IDD cohort relative to the matched comparison group decreased with increasing age. No significant sex differences were found. The leading causes of death among the IDD cohort were diseases of the circulatory system, cancer, and diseases of the respiratory system. Avoidable premature deaths were 2.3–3.3 times more prevalent among Manitoba adults with IDD compared to the matched comparison group. An IDD diagnostic code was reported as cause of death in 2.11% of cases. Conclusions The excess mortality among adults with IDD should be monitored in Manitoba and all other jurisdictions and attention paid to the causes of death and their coding.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".