Increasing rates of diabetes and cardiovascular risk in Métis settlements in northern Alberta
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence of diabetes (using secondary data analysis), as well as undiagnosed diabetes and pre-diabetes (using primary research methods) among adult Métis Settlement dwellers in northern Alberta. We also sought to identify cardiovascular risk factors. STUDY DESIGN: Quantitative research study utilizing both population census and community-based diabetes screening data. METHODS: Self-reported diabetes was analyzed from the results of the Métis Settlement specific censuses in 1998 and 2006. Mobile clinics travelled into each of the 8 Métis Settlement communities in Alberta recruiting 693 subjects for screening for undiagnosed diabetes, pre-diabetes and metabolic syndrome. Logistic regression analyses (adjusted for age and sex) were used to identify associated factors. RESULTS: According to the censuses, 4,312 Métis individuals were living on Settlements in 1998 and 5,059 in 2006. Self-reported age-adjusted prevalence of diabetes increased significantly from 5.1% in 1998 to 6.9% in 2006 (p < 0.01), with a crude prevalence increase of 66% (p < 0.01). In 2006, diabetes prevalence was higher among females than males, 7.8% vs. 6.1% respectively (p < 0.05). Of the 266 adults screened in the fasting state, 5.3% had undiagnosed diabetes, whereas 20.3% (Canadian Diabetes Association criteria) and 51.9% (American Diabetes Association criteria) had pre-diabetes. Rates of obesity and metabolic syndrome were 49.4% (n = 693) and 46.4% (n = 266), respectively. Hemoglobin A1c > 6.1% was strongly associated with diabetes, pre-diabetes and metabolic syndrome. CONCLUSIONS: Our results indicate high rates of diabetes, undiagnosed diabetes, pre-diabetes and metabolic syndrome among adult Alberta Métis Settlement dwellers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".