Diabetes Complications and Depressive Symptoms: Prospective Results From the Montreal Diabetes Health and Well-Being Study
Bibliographic record
Abstract
OBJECTIVE: Prospective studies testing the potential impact of diabetes complications on depression are limited. The present study examined the longitudinal associations between diabetes complications and the risk and recurrence/persistence of depressive symptoms. METHODS: Data were from a prospective community cohort telephone survey of adults with diabetes (N = 1314). Diabetes complications and depressive symptoms were assessed via self-report (Diabetes Complications Index and Patient Health Questionnaire-9, respectively) at baseline and annually for 5 years. Statistical models adjusted for sociodemographic, lifestyle, and diabetes characteristics. RESULTS: The number of diabetes complications at baseline was positively associated with a greater risk of elevated depressive symptoms, with the highest risk found for those with four to six complications at baseline (risk ratio = 2.73, 95% confidence interval = 1.64-4.56). Cerebrovascular disease was the complication most strongly associated with incident depressive symptoms (risk ratio = 2.22, 95% confidence interval = 1.59-3.10). Coronary artery disease, peripheral vascular disease, and neuropathy were also associated with the risk of depression, whereas foot problems and eye problems were not. In addition, a greater number of diabetes complications were associated with recurrent/persistent depression, though with a small effect size (Δr = .02). A parallel process latent growth curve model indicated that increases in diabetes complications were associated with increases in depressive symptoms during the course of the follow-up period (β = .74, p < .001). CONCLUSIONS: This study demonstrates the temporal relation between diabetes complications and depressive symptoms and underscores the psychological burden of diabetes complications by prospectively demonstrating the increased risk and recurrence of depressive symptoms associated with diabetes complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".