Type 2 Diabetes and Comorbid Symptoms of Depression and Anxiety: Longitudinal Associations With Mortality Risk
Bibliographic record
Abstract
OBJECTIVE: Depression is strongly linked to increased mortality in individuals with type 2 diabetes. Despite high rates of co-occurring anxiety and depression, the risk of death associated with comorbid anxiety in individuals with type 2 diabetes is poorly understood. This study documented the excess mortality risk associated with symptoms of depression and/or anxiety comorbid with type 2 diabetes. RESEARCH DESIGN AND METHODS: Using data for 64,177 Norwegian adults from the second wave of the Nord-Trøndelag Health Study (HUNT2), with linkage to the Norwegian Causes of Death Registry, we assessed all-cause mortality from survey participation in 1995 through to 2013. We used Cox proportional hazards models to examine mortality risk over 18 years associated with type 2 diabetes status and the presence of comorbid affective symptoms at baseline. RESULTS: Three clear patterns emerged from our findings. First, mortality risk in individuals with diabetes increased in the presence of depression or anxiety, or both. Second, mortality risk was lowest for symptoms of anxiety, higher for comorbid depression-anxiety, and highest for depression. Lastly, excess mortality risk associated with depression and anxiety was observed in men with diabetes but not in women. The highest risk of death was observed in men with diabetes and symptoms of depression only (hazard ratio 3.47, 95% CI 1.96, 6.14). CONCLUSIONS: This study provides evidence that symptoms of anxiety affect mortality risk in individuals with type 2 diabetes independently of symptoms of depression, in addition to attenuating the relationship between depressive symptoms and mortality in these individuals.
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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 | 0.003 |
| 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".