Cardiovascular risk amongst migrant and non-migrant Greenland Inuit in a gender perspective
Bibliographic record
Abstract
AIMS: The effects of migration on cardiovascular risk factors are often gender specific. The purpose of the present study was to analyse the association of migration from Greenland to Denmark with cardiovascular risk factors in a gender-specific perspective. METHODS: Cross-sectional population surveys among adult Inuit in Greenland and Inuit migrants in Denmark (n = 1542). General Linear Models adjusted for age, smoking, diet (seal, fish, and fruit), and alcohol consumption. RESULTS: Blood pressure was significantly higher among Inuit migrants of either sex than among the Inuit in Greenland. Among women, HDL-cholesterol concentrations were 1.59 mmol/l in Greenland and 1.83 among migrants (p<0.001), while obesity and HbA(1c) were significantly lower among the migrants. Blood lipids, HbA(1c), and obesity did not differ between men in Greenland and migrants. Smoking, diet, and alcohol consumption differed significantly among migrants and non-migrants. Adjusted for the consumption of seal meat and alcohol, the difference in HDL cholesterol for men (1.44 and 1.66 mmol/l; p = 0.002) was of a similar magnitude to that of women. CONCLUSIONS: Migration was associated with cardiovascular risk factors in different ways among men and women. Some of the gender difference could be explained by dietary differences among male and female migrants and non-migrants, or in the case of HDL cholesterol by a different association with the consumption of seal meat for men and women, but a large unexplained residual remained. Overall cardiovascular risk was higher among migrant than non-migrant males, while for women some risk factors were better and some worse among the migrants.
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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 | 0.000 |
| 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 | 0.001 | 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".