Assessing the relationship between multimorbidity and depression in older men and women: the International Mobility in Aging Study (IMIAS)
Bibliographic record
Abstract
Objectives: Our study aims to assess whether multimorbidity is an independent risk factor for the development of depression in older adults living in Canada, Brazil, Colombia, and Albania and examines differences in incidence of depression regarding social and psychosocial characteristics.Methods: The longitudinal International Mobility Aging Study (IMIAS) collected information from adults between 65–74 years old. Depression was defined by a 16 or higher score assessed by the Centre for Epidemiological Studies Depression (CES-D) Scale. Multimorbidity was defined as having two or more chronic conditions, which were self-reported by participants using a list of eight physical chronic conditions. Poisson regression was performed to estimate the relative risk of depression in older adults with multimorbidity compared to those living with 0–1 chronic conditions, adjusting for sex, age, education, number of doctor visits, degree of assistance needed, social support, and smoking status. The analysis was stratified by study region (Canada; Latin America; Albania).Results: Crude and adjusted models showed no statistically significant associations between multimorbidity and the incidence of depression in any of the study regions, confirmed by sensitivity analyses. However, the incidence of depression varied across study region, confirmed by the intra-class correlation coefficient which indicated that 13% of variations in depression incidence were due to geographic differences.Conclusion: Multimorbidity does not appear to increase the risk of developing depression in older adults between 65–74. Higher rates of depression in Latin America and Albania (compared to Canada) may be attributed to lifecourse exposures to social and economic adversity in these regions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".