Increased odds of metabolic syndrome among adults with depressive symptoms or antidepressant use
Bibliographic record
Abstract
Metabolic syndrome (MetS) is a condition that includes a cluster of risk factors for cardiovascular disease. In this paper, we aimed to evaluate the association between depressive symptoms, antidepressant use, duration of antidepressant use, antidepressant type and MetS. Data from the 2005-2018 National Health and Nutrition Examination Surveys were used in this study. Adults were included if they responded to the depressive symptoms and prescription medications questionnaires and had measures of blood pressure, waist circumference, triglycerides, high-density lipoprotein, and fasting plasma glucose. Participants were categorized by their antidepressant use (yes/no), type, and duration. This study included 14,875 participants (50.45% females), with 3616 (23.45%) meeting the criteria for MetS. Participants with higher depressive symptom scores (aOR = 1.04, 95% CI: 1.02, 1.05, p < 0.001) or those with depressive symptoms (aOR = 1.42, 95% CI: 1.17, 1.73, p = 0.001) had higher odds of MetS. A similar associations was seen among those who were on antidepressants compared to those who were not on antidepressants (aOR = 1.24, 95% CI: 1.03, 1.50, p = 0.025). Duration of antidepressant use was not significantly associated with MetS. Participants on tricyclic antidepressants had greater odds of MetS compared to those not taking any antidepressants (aOR = 2.27, 95% CI: 1.31, 3.93, p = 0.004). Our study provides evidence of the association between depressive symptoms, antidepressant use, and MetS, highlighting the importance of monitoring metabolic and cardiovascular alterations in individuals of depression.
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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 | 0.000 | 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".