Fat Distribution and Glucose Intolerance Among Greenland Inuit
Bibliographic record
Abstract
OBJECTIVE: A high amount of subcutaneous fat is suggested to explain the observation of lower obesity-associated metabolic risk among Inuit than among Europeans. We examined the association between measures of obesity (visceral adipose tissue [VAT], subcutaneous adipose tissue [SAT], BMI, waist circumference [WC], and percentage of body fat) and the indices of glucose metabolism (fasting and 2-h glucose levels, insulin resistance per homeostasis model assessment [HOMA-IR], and the insulin sensitivity index [ISI0,120]) among Greenland Inuit. RESEARCH DESIGN AND METHODS: A total of 3,108 adult Inuit participated in a population-based study. The examination included a 75-g oral glucose tolerance test and anthropometric measurements. VAT and SAT were measured by ultrasound according to a validated protocol. Information on sociodemographic characteristics and health behaviors was obtained by interview. RESULTS: Mean SATs were 1.8 and 3.5 cm in men and women, respectively. Mean VATs were 7.0 and 6.3 cm in men and women, respectively. The total prevalence of type 2 diabetes was 9%. Percentage of body fat generally was most strongly associated with all outcomes. Both SAT and VAT were significantly associated with glucose intolerance, fasting and 2-h plasma glucose levels, HOMA-IR, and ISI0,120. VAT was more strongly associated with all outcomes than was SAT. After further adjustment for BMI or WC, VAT was associated with glucose intolerance and insulin resistance, whereas there was a trend toward a negative or no association with SAT. CONCLUSIONS: High mean values of SAT may to a large extent explain the high WC in Inuit populations, and this is suggested to contribute to the lower observed metabolic risk for a given level of obesity.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".