Bibliographic record
Abstract
This paper reviews the ethnographic, historical, and recent epidemiological evidence of obesity among the Inuit/Eskimo in the circumpolar region. The Inuit are clearly at higher risk for obesity than other populations globally, if "universal" measures based on body mass index (BMI) and waist circumference and criteria such as those of WHO are used. Inuit women in particular have very high mean waist circumference levels in international comparisons. Given the limited trend data, BMI-defined obesity is more common today than even as recently as three decades ago. Inuit are not immune from the health hazards associated with obesity. However, the "dose-response" curves for the impact of obesity on metabolic indicators such as plasma lipids and blood pressure are lower than in other populations. Long-term, follow-up studies are needed to determine the metabolic consequences and disease risks of different categories of obesity. At least in one respect, the higher relative sitting height among Inuit, obesity measures based on BMI may not be appropriate for the Inuit. Ultimately, it is important to go beyond simple anthropometry to more accurate determination of body composition studies, and also localization of body fat using imaging techniques such as ultrasound and computed tomography. Internationally, there is increasing recognition of the need for ethnospecific obesity criteria. Notwithstanding the need for better quality epidemiological data, there is already an urgent need for action in the design and evaluation of community-based health interventions, if the emerging epidemic of obesity and other chronic diseases are to be averted.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".