The association of depression with metabolic syndrome parameters and malondialdehyde (MDA) in obese women: A case-control study
Bibliographic record
Abstract
Background: There is evidence for a bidirectional association between obesity and depression, and obesity is the main risk factor for metabolic syndrome (MetS). This study aimed to compare oxidative stress and MetS features between depressed and non-depressed obese women and study the association of depressive symptoms, oxidative stress, and components of MetS. Methods: In this case-control study conducted in Tabriz (East Azarbaijan, Iran), obese women (body mass index [BMI]: 30-40 kg/m2 ) with a primary diagnosis of major depressive disorder (MDD; based on diagnostic interview with a psychiatrist; n=75) and their age-matched non-depressed controls (n=150) were enrolled. Beck Depression Inventory-version II (BDI-II) was used to assess depressive symptoms in both groups. Anthropometric parameters, blood pressure, fasting blood sugar (FBS), lipid profile and malondialdehyde (MDA) were measured. Results: No significant differences in anthropometric parameters and blood pressure were observed between the two groups. However, FBS of the MDD group was significantly higher than the control (P<0.05). FBS was significantly correlated with BDI-II scores (r=0.158, P=0.017). No significant difference in lipid profile was observed between the groups. Serum MDA level was significantly lower in the MDD group and was inversely associated with BDI-II scores (r=-0.328, P<0.001). Overall, MDD was not significantly associated with MetS in our study (OR=0.848, 95% CI: 0.484, 1.487; P=0.566). Conclusion: Although we found a correlation between higher depressive symptoms and some adverse metabolic outcomes, our findings do not support a significant association between MDD and MetS.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".