Mediation and moderated mediation in the relationships among income condition, depression, cognition and residence among older adults in China
Bibliographic record
Abstract
AIM: A better income condition has always been associated with better cognition; however, studies that have demonstrated the pathway of this relationship are limited. We aim to evaluate the mediation effect of depression in this association, and whether this mediation is moderated by the place of residence. METHODS: We conducted a face-to-face study, including 3230 older adults aged >60 years in Xiamen, China, in 2016. The income condition of participants was categorized into three groups: income less than expenditure, income equals expenditure and income more than expenditure. Depression was measured using the Geriatric Depression Scale and cognition was evaluated using the Montreal Cognitive Assessment tool. We first examined a simple mediation model where depression was a mediator between income condition and cognition. Furthermore, residence was systematically integrated into the model as a moderator, and the model was adjusted for age, gender, number of year of education, hypertension and diabetes. All mediation and moderated mediation effects were estimated by the plug-in "PROCESS" in SPSS. RESULTS: In total, 2852 participants were finally included. Depression partially mediated the relationship between income condition and cognition (indirect effect = 0.25, total effect = 0.72). Moderated mediation analyses indicated that a direct effect only existed among urban older adults (B = 0.92; 95% confidence interval [CI]: [0.47-1.38]), whereas an indirect effect was stronger for individuals in urban (B = 0.28; 95% CI: [0.18-0.41]) rather than rural environments (B = 0.17; 95% CI: [0.11-0.26]). CONCLUSIONS: A better income condition is a protective factor for cognition and it partially benefits work through milder depressive symptoms, particularly in older adults in urban residences. Geriatr Gerontol Int 2020; 20: 860-866.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".