Association between functional limitation and quality of life among older adults with multimorbidity in Luxembourg
Bibliographic record
Abstract
Abstract Introduction Multimorbidity, defined as the co-existence of two or more chronic conditions, is affecting an increasing number of Europeans, leading to poorer quality of life (QoL). This study assessed how functional limitation affects the QoL trajectories in a cohort of older individuals having multimorbidity, and whether there are any gender differences in these effects. Methods We used a longitudinal cohort of 906 multimorbid respondents 50 years of age or older from Luxembourg who participated in four waves of the Survey of Health, Ageing, and Retirement in Europe (2013-2020). We used the Control, Autonomy, Self-Realization, and Pleasure scale (CASP-12) to assess QoL and the Global Activity Limitation Indicator (GALI) to measure functional limitation. Multigroup latent growth curve (LGC) modeling techniques were employed to assess how the measures of functional limitation over time are related to QoL trajectories and whether or not these effects are different by sex. Results In 2013, over 60% of older residents of Luxembourg were affected by multimorbidity. The results from the LGC models suggest that both men and women with multimorbidity experienced a statistically significant decline in QoL between 2013 and 2020 at a constant rate; there were no significant differences in the rate of this change between men and women. The level of QoL at baseline and over time was significantly lower for individuals reporting functional limitation. However, functional limitation had no significant impact on the rate of decline in QoL for both men and women. Discussion and conclusions As an increasing number of individuals in Europe are becoming vulnerable to more years lived with multiple chronic conditions, there is a growing need to identify factors that may lead to improvements in QoL among people affected by multimorbidity. Gaining more knowledge on the role of functional limitation may be particularly important for planning comprehensive care for patients with multimorbidity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".