Multiwave Associations Between Depressive Symptoms and Endothelial Function in Adolescent and Young Adult Females
Bibliographic record
Abstract
OBJECTIVE: Depression has been linked to endothelial dysfunction, and some research suggests that past depressive episodes are associated with a lasting, negative impact on the endothelium. However, investigations in this area have been predominantly cross-sectional, raising questions about the direction of these associations. Using a multiwave design, we sought to extend previous research in this area by examining whether depressive symptoms have a lasting negative influence on endothelial function. METHODS: A total of 135 adolescent and young adult females with no known or suspected major health problems were followed for 2½ years. Endothelial function was assessed at three time points throughout the study. The Beck Depression Inventory was administered, and information about health practices was collected every 6 months. RESULTS: Self-reported depressive symptoms covaried with endothelial functioning on a within-person basis (β = -0.23, p < .05). As a participant's depression symptoms rose beyond her typical level, her endothelial function declined commensurately. This association persisted after controlling for health practices and adiposity. There was no evidence that depressive symptoms predicted endothelial function at later time points or interacted with time to predict the trajectories of endothelial function over the follow-up period. CONCLUSIONS: Depressive symptoms were concurrently associated with endothelial function in this cohort of healthy adolescent girls and young women. On visits when participants endorsed depressive symptoms that were higher than their mean level of depression, they tended to have worse endothelial function. We did not observe a lasting negative effect of depression on endothelial function.
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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 | 0.001 |
| 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) | 0.001 | 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".