Socioeconomic disparities in cognitive impairment, quality of life, and mortality among older adults in Germany.
Bibliographic record
Abstract
BACKGROUND: The global older population is increasing, leading to a rise in non-communicable diseases and disabilities, particularly in Western countries. With the aging population expanding and the number of older adults with cognitive impairments expected to rise, there is increasing interest in understanding the socioeconomic disparities associated with cognitive impairment. This study investigates the relationships between socioeconomic status (SES), cognitive impairment, quality of life, and mortality among older adults in Germany. METHODS: Data from the senior cohort (N = 1,069) of the German Gutenberg Health Study (2017-2024) were analyzed, focusing on older adults aged 75-85 years. Regression modeling with sequential adjustment for covariates was employed to determine the association between various domains of SES (SES index comprising educational background, occupational status, and household net-income) and cognitive impairment (Montreal Cognitive Assessment), quality of life (EUROHIS-QOL), and all-cause mortality. RESULTS: Cognitive impairment scores varied significantly by SES with higher SES being associated with better cognitive performance. Among the SES domains, the household net-income score was the strongest predictor of cognitive impairment. Likewise, higher SES was significantly associated with higher quality of life, whereas no association between cognitive impairment and quality of life was found. Additionally, cognitive impairment was significantly associated with higher all-cause mortality, whereas SES did not show a significant association with mortality. No significant interactions between SES and cognitive impairment were observed in relation to quality of life or all-cause mortality. CONCLUSION: Among older adults, SES is strongly associated with cognitive impairment. However, cognitive impairment emerges as a more significant risk factor for all-cause mortality than SES. These findings suggest the need for public health strategies to prioritize cognitive health monitoring and targeted interventions, while simultaneously addressing social inequalities, to reduce the burden of these adverse outcomes.
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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 | 0.001 | 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".