Prevalence of obesity among Inuit in Greenland and temporal trend by social position
Bibliographic record
Abstract
OBJECTIVES: The purpose of the study was to analyze the temporal trend of obesity among Inuit in Greenland during 1993-2010 according to sex and relative social position. METHODS: Data (N = 5,123) were collected in cross-sectional health surveys among the Inuit in Greenland in 1993-1994, 1999-2001, and 2005-2010. Sociodemographic information was obtained by interview. Information on obesity (body mass index (BMI) and waist circumference) was obtained by clinical examination and in 1993-1994 by interview. Statistics included multiple linear regression and Univariate General Linear Models. RESULTS: Among men the prevalence of overweight (BMI 25-29.9) decreased while general obesity (BMI ≥ 30) did not change. Central obesity increased from 16.0% in 1993-1994 to 25.4% in 2005-2010 (P < 0.001). Among women general and central obesity increased. Central obesity increased from 31.3% in 1993-1994 to 54.2% in 2005-2010 (P < 0.001). In 2005-2010 both general and central obesity showed significantly increasing trends with social position (general obesity: P < 0.001 for men, P = 0.04 for women; central obesity: P < 0.001 for both men and women). The social trend was absent in the earlier surveys. CONCLUSION: General and central obesity is increasing among the Inuit in Greenland. There is an increasing positive association of obesity with social position for both men and women. The high prevalence of obesity is a serious public health problem that is expected to affect the already high prevalence of Type 2 diabetes and its complications.
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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 | 0.000 | 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".