Lifetime risk of diabetes among First Nations and non–First Nations people
Bibliographic record
Abstract
BACKGROUND: Lifetime risk is a relatively straightforward measure used to communicate disease burden, representing the cumulative risk of an outcome during the remainder of an individual's life starting from a disease-free index age. We estimated the lifetime risk of diabetes among men and women in both First Nations and non-First Nations populations using a cohort of adults in a single Canadian province. METHODS: We used a population-based cohort consisting of Alberta residents from 1997 to 2008 who were free of diabetes at cohort entry to estimate the lifetime risk of diabetes among First Nations and non-First Nations people. We calculated age-specific incidence rates with the person-year method in 5-year bands. We estimated the sex- and index-age-specific lifetime risk of incident diabetes, after adjusting for the competing risk of death. RESULTS: The cohort included 70 631 First Nations and 2 732 214 non-First Nations people aged 18 years or older. The lifetime risk of diabetes at 20 years of age was 75.6% among men and 87.3% among women in the First Nations group, as compared with 55.6% among men and 46.5% among women in the non-First Nations group. The risk was higher among First Nations people than among non-First Nations people for all index ages and for both sexes. Among non-First Nations people, men had a higher lifetime risk of diabetes than women across all index ages. In contrast, among First Nations people, women had a higher lifetime risk than men across all index ages. INTERPRETATION: About 8 in 10 First Nations people and about 5 in 10 non-First Nations people of young age will develop diabetes in their remaining lifetime. These population-based estimates may help health care planners and decision-makers set priorities and increase public awareness and interest in the prevention of diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".