A Comparison of the Metabolic Response to Abdominal Obesity in Two Canadian Inuit and First Nations Population
Bibliographic record
Abstract
Inuit and Cree populations are known for high obesity rates despite markedly different rates of type 2 diabetes (T2DM). To document this apparent discrepancy we evaluated the impact of body size parameters and fasting insulin (FI) on several T2DM risk factors among Inuit and Cree populations (Québec, Canada). A total of 1,104 adults (≥18 years) Inuit and Cree individuals participated in a cross-sectional investigation. Interestingly, across both genders, across all levels of waist circumference (WC), Inuit showed lower levels of FI (age-adjusted, P < 0.0001) and fasting glucose (P < 0.0001) than Cree individuals. In both groups, a comparison of multi-sample structural equation models confirmed the predominant influence of WC on other traditional risk factors, compared to BMI. A preponderant direct impact of WC was observed on blood pressure (BP) parameters (P < 0.0001), high-density lipoprotein cholesterol (HDL-C) (P < 0.0001), and FI (P < 0.0001). Fasting glucose level appear to be influenced by WC via FI in both ethnic groups (P < 0.0001), while triacylglycerol (TAG) level was predominantly impacted by WC via FI, but only in Cree individuals (P < 0.0001). The main ethnic difference found was the strength of the impact of WC on FI, which was considerably higher among the Cree (λ = 2.4, P < 0.0001) than the Inuit (λ = 1.8, P < 0.0001). These results confirm the predominant role of abdominal adiposity in the complex and tenuous links of different traditional T2DM determinants. However, the ethnic difference in the impact of abdominal obesity on insulin levels across all WCs needs to be explored further.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".