Trajectories of Depressive Symptoms and Incident Diabetes: A Prospective Study
Bibliographic record
Abstract
BACKGROUND: Elevated depressive symptoms are associated with an increased risk for diabetes. Depression is a heterogeneous and chronic condition in which symptoms may remit, emerge, lessen, or intensify over time. PURPOSE: The purpose of this study was to determine if trajectories of depressive symptoms measured at five time points over 8 years predicted incident diabetes over an 8-year follow-up in middle-aged and older adults. A secondary aim was to determine if trajectories of depressive symptoms predict incident diabetes, above and beyond depressive symptoms measured at a single time point. METHODS: Data came from the Health and Retirement Study (n = 9,233). Depressive symptoms were measured biennially from 1998 to 2006. Self-reported incident diabetes was measured during an 8-year follow-up. RESULTS: Five trajectories of depressive symptoms were identified (no depressive symptoms, low depressive symptoms, low-moderate depressive symptoms, moderate depressive symptoms, elevated and increasing depressive symptoms). Compared to the no depressive symptoms trajectory group (referent), all other trajectory groups were at higher risk of developing diabetes after adjusting for covariates. In most cases, trajectory group membership was associated with incident diabetes after controlling for depressive symptoms at a single time point. CONCLUSIONS: Patterns of depressive symptoms over time were associated with incident diabetes. Patterns of depressive symptoms may be more predictive of diabetes incidence than depressive symptoms measured at a single time point.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".