Cohort-specific disability trajectories among older women and men in Europe 2004–2017
Bibliographic record
Abstract
As the population of Europe grows older, one crucial issue is how the incidence and prevalence of disabilities are developing over time in the older population. In this study, we compare cohort-specific disability trajectories in old age across subsequent birth cohorts in Europe, during the period 2004-2017.We used data from seven waves of data from the Survey of Health, Ageing and Retirement in Europe (SHARE). Mixed effects logistic regression models were used to model trajectories of accumulation of ADL limitations for subsequent birth cohorts of older women and men in different European regions. The results showed that there were sex differences in ADL and IADL limitations in all regions for most cohorts. Women reported more limitations than men, particularly in Eastern and Southern rather than Northern and Western Europe. Among men in Eastern, Northern and Western Europe, later born cohorts reported more disabilities than did earlier born birth cohorts at the same ages. Similar patterns were observed for women in Northern and Western Europe. In contrast, the risk of disabilities was lower in later born cohorts than in earlier born birth cohorts among women in Eastern Europe. Overall, results from this study suggest that disability trajectories in different cohorts of men and women were by and large similar across Europe. The trajectories varied more depending on sex, age and region than depending on cohort. Supplementary Information: The online version contains supplementary material available at 10.1007/s10433-022-00684-4.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".