Differences in the prevalence of diabetes risk-factors among First Nation, Métis and non-Aboriginal adults attending screening clinics in rural Alberta, Canada
Bibliographic record
Abstract
INTRODUCTION: Populations that are developing (westernizing) are suffering the highest rates of increases in diabetes incidence and prevalence worldwide, with the most notable and documented increases in Canada seen among the First Nations. Less is known about the Métis (mixed blood) or the rural populations in general. To date, no studies have assessed the contributions of ethnicity to diabetes risk-factors. Our objective was to examine diabetes risk factors in First Nations, Métis and non-Aboriginal individuals residing in rural or remote locations, investigating whether ethnicity contributed to any differences. METHODS: From the databases of three separate community-based diabetes screening projects in Alberta we created a unique subject pool of 3148 adults without diabetes (1790 First Nation, 867 Métis, and 491 non-Aboriginals). Age, body mass index (BMI), waist circumference, reported history of gestational diabetes (GDM) or babies over nine pounds (females only), hemoglobin A1c (A1c) fasting plasma glucose (FPG) or random plasma glucose (RPG) were assessed. Chi-square tests and logistic regression analysis were used to identify between-group differences. RESULTS: The highest mean values for waist circumference (104.7 cm) and BMI (31.2) were found in First Nations subjects (p<0.01). First Nations individuals had the highest prevalence of overweight/obesity (84.4%), abnormal waist circumference (76.8%) and history of GDM (9.0%) (p<0.01). The RPG was also higher in First Nations, but there were no differences between groups with respect to mean FPG and A1c levels, and there were no differences with respect to the prevalence of pre-diabetes or undiagnosed diabetes. Métis (OR 0.80; p = 0.01) and non-Aboriginal individuals (OR 0.62; p< 0.01) were less likely to be obese after age/gender adjustment, compared with First Nations. Métis (OR 0.70; p<0.01) and non-Aboriginals (OR 0.35; p<0.01) were also less likely than the First Nations group to have abnormal waist circumferences. Individuals in the non-Aboriginal group had a lower prevalence of pre-diabetes (OR 0.50; p = 0.01) compared with both the Métis and First Nations groups. CONCLUSIONS: First Nations individuals had more risk factors for diabetes than Métis and non-Aboriginal individuals, although Métis rates appeared intermediate. While these risk-factor differences did not translate to more undiagnosed diabetes or pre-diabetes, they are consistent with known rates of diagnosed diabetes in Alberta.
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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 | 0.000 |
| 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".