Prevalence of diabetes mellitus in aboriginal and nonaboriginal people living in the
Bibliographic record
Abstract
Background:Type2diabetesmellitus affects an estimated 4.8% of the Canadian adult population. Diabetes prevalence rates for British Columbia’s aboriginal people have been reported as being lower than those reported for other aboriginal groups, and lower than the overall Canadian rate. The purpose of this study was to determine the prevalence rate of diabetes among the aboriginal and nonaboriginal populations living in the Bella Coola Valley. The relationships between age, gender, weight, body mass index and aboriginal status and having diabetes mellitus were also examined. Methods: Retrospective populationbasedmedicalchartreviewwasconducted using the charts of people living in the Bella Coola Valley and having a chart at the Bella Coola Medical Clinic as of September 2001. Results:Afteradjustmentsweremade for age, the data revealed the prevalence of type 2 diabetes among aboriginals to be 12.5%. Among nonaboriginals, the prevalence rate was similar to that reported for the general population of Canada (4.8%). It was determined that age, weight, body mass index, and aboriginal status were all significant contributors to the risk of developing type 2 diabetes. Conclusion:Given the wide variation in prevalence rates observed and reported for aboriginal people residing in British Columbia to date, the findings in this report indicate the need for individual study of different First Nations groups.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".