Gender difference in health expectancy trends in Greenland
Bibliographic record
Abstract
BACKGROUND: The population of Greenland comprises almost 31,000 Inuit Greenlanders aged 20-65. The purpose of this study was to estimate trends in expected life years between age 20 and 65 in good and poor health, and to compare changes between men and women since the mid-1990s. METHODS: Partial life expectancy was calculated and combined with prevalence data on self-rated health, longstanding illness and musculoskeletal diseases derived from health surveys carried out in 1993-94, 1999-2001 and 2005-10. Trends for men and women were compared and changes were decomposed into contributions from changes in mortality and disability. RESULTS: Partial life expectancy increased by 2.2 years for men and 0.8 years for women during the entire period. However, expected lifetime in self-rated good health decreased by 3.3 years for men and by 4.6 years for women (p<0.01). For men, life expectancy without longstanding illness increased by 4.7 years (p<0.001). The increase for women by 1.4 years was non-significant (p=0.29). Expected lifetime without musculoskeletal diseases increased significantly by 4.5 years for men and by 1.9 years for women. CONCLUSIONS: The development of expected lifetime without longstanding illness supports the theory of compression of morbidity, but as the trend direction differs according to which measure for health is used, a definite conclusion cannot be drawn. The different rate of development of partial life expectancy and expected lifetime in good health between men and women is remarkable, and has reduced the gender gap. The results call for special concern about the women's health in Greenland.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".