Evolution of the burden of diabetes among adults and children in Québec, Canada, from 2001 to 2019: A population-based longitudinal surveillance study
Bibliographic record
Abstract
Many developed countries, including Canada, have observed reductions in incidence of diabetes. Given the latest improvements in the case definition of diabetes for the younger population Quebec, Canada, we sought to examine the evolution of diabetes among adults and children in Quebec, between 2001 and 2019. Crude and age-standardized incidence and prevalence of diabetes among individuals ≥1 year were calculated using data from the Quebec Integrated Chronic Disease Surveillance System (n≈8,351,500 in 2019), using two case definitions for adults and the youth respectively. Age-standardized all-cause hospitalizations and mortality proportions were calculated among the population ≥20 years. Between 2001 and 2019, age-standardized incidence decreased by 30%, with a crude incidence of 4.6 per 1,000 in 2019. Incidence rates decreased from age group ≥50 years but increased by 25% for the group of 1-19 years. Age-standardized prevalence increased by 42% (crude prevalence in 2019: 8.1%). Males had higher incidence and prevalence of diabetes, with an incremental gap between sexes increasing with age. All-cause hospitalization and mortality proportions among individuals with diabetes declined by 21% and 29% respectively between 2001 and 2019. Age-standardized hospitalizations and mortality ratios for individuals with/without diabetes remained stable and were 2.7 (99% Confidence Intervals [CI]: 2.7-2.8) and 2.2 (99% CI: 2.1-2.3) in 2019, respectively. Despite the reduction of incidence among adults, diabetes incidence increased among the youth and remained high among adults, especially for males. These results highlight the importance of improving earlier preventive care and initiatives for reducing the diabetes burden in Quebec.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".