Muscular strength, mobility in daily life and mental wellbeing among older adult Inuit in Greenland. The Greenland population health survey 2018
Bibliographic record
Abstract
The purpose was to analyse the association of muscular strength, muscle pain and reduced mobility in daily life with mental wellbeing among older Inuit men and women in Greenland. Data (N = 846) was collected as part of a countrywide cross-sectional health survey in 2018. Hand grip strength and 30-seconds chair stand test were measured according to established protocols. Mobility in daily life was assessed by five questions about the ability to perform specific activities of daily living. Mental wellbeing was assessed by questions about self-rated health, life satisfaction and Goldberg's General Health Questionnaire. In binary multivariate logistic regression models adjusted for age and social position, muscular strength (OR 0.87-0.94) and muscle pain (OR 1.53-1.79) were associated with reduced mobility. In fully adjusted models, muscle pain (OR 0.68-0.83) and reduced mobility (OR 0.51-0.55) but were associated with mental wellbeing. Chair stand score was associated with life satisfaction (OR 1.05). With an increasingly sedentary lifestyle, increasing prevalence of obesity and increasing life expectancy the health consequences of musculoskeletal dysfunction are expected to grow. Prevention and clinical handling of poor mental health among older adults need to consider reduced muscle strength, muscle pain and reduced mobility as important determinants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".