Relationship Between Socioeconomic Status and Depression in Older Adults: The Roles of Cognitive Function and Sleep Quality
Bibliographic record
Abstract
Yilin Zheng,1 Yu Zhang,2 Mingzhu Ye,2 Zhiwang Qian,2 Guohua Zheng2 1Shanghai Institute for Global City, Shanghai Normal University, Shanghai, 200234, People’s Republic of China; 2School of Nursing and Health Management, Shanghai University of Medicine & Health Sciences, Shanghai, 201318, People’s Republic of ChinaCorrespondence: Guohua Zheng, School of Nursing and Health Management, Shanghai University of Medicine & Health Sciences, Shanghai, 201318, People’s Republic of China, Tel +86-021-6588-3683, Email zhenggh@sumhs.edu.cnBackground: Socioeconomic status (SES) is an important social factor associated with a wide range of health outcomes, but this relationship could be influenced by individual’s intrinsic factors. The aim of this study was to examine the relationship between SES and depressive symptoms, the mediating role of cognitive function, and the moderating role of sleep quality in community-dwelling older adults.Methods: A total of 1000 community-dwelling older adults were recruited for the cross-sectional study. Socioeconomic factors, cognitive function, sleep quality, and related covariates were investigated or assessed. Mediating and moderating effects were analyzed using R 4.2.2 and SPSS 25.0 software.Results: The results showed that SES was negatively associated with depressive symptoms (β=− 0.234, p< 0.001) and positively associated with cognitive function (β=0.566, p< 0.001) after controlling for covariates; cognitive function played a partial mediating role between SES and depressive symptoms, and the indirect effect was β=− 0.09 (95% CI: − 0.129~ − 0.06, p< 0.001), accounting for 38.5% of the total effect; and sleep quality positively moderated the mediating effect of cognitive function on relationship between SES and depressive symptoms (βsleep ×cognition =− 0.015, p< 0.05).Conclusion: Depressive symptoms in community-dwelling older adults are affected by their SES and cognitive function. Improving individual cognitive ability and sleep quality can effectively reduce depression in community-dwelling older adults with low SES.Keywords: socioeconomic status, depressive symptoms, cognitive function, sleep quality, cross-sectional study
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".