The Emergence of Obesity among Indigenous Siberians
Bibliographic record
Abstract
Once considered a disease of affluence and confined to industrialized nations, obesity is currently emerging as a major health concern in nearly every country in the world. Available data suggest that the prevalence rate of obesity has reached unprecedented levels in most developing countries, and is increasing at a rate that far outpaces that of developed nations. This increase in obesity has also been documented among North American circumpolar populations and is associated with lifestyle changes related to economic development. While obesity has not been well studied among indigenous Siberians, recent anthropological studies indicate that obesity and its associated comorbidities are important health problems.The present study examines recent adult body composition data from four indigenous Siberian populations (Evenki, Ket, Buriat, and Yakut) with two main objectives: 1) to determine the prevalence of overweight and obesity among these groups, and 2) to assess the influence of lifestyle and socioeconomic factors on the development of excess body fat. The results of this study indicate that obesity has emerged as an important health issue among indigenous Siberians, and especially for women, whose obesity rates are considerably higher than those of men (12% vs. 7%). The present study investigated the association between lifestyle and body composition among the Yakut, and documented substantial sex differences in lifestyle correlates of obesity. Yakut men with higher incomes and who owned more luxury consumer goods were more likely to have excess body fat while, among Yakut women, affluence was not strongly associated with overweight and obesity.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".