The relationship between depression and risk of metabolic syndrome: a meta‐analysis of observational studies
Bibliographic record
Abstract
INTRODUCTION: The link between metabolic syndrome and depression has always been controversial. Different studies that have examined the relationship between metabolic syndrome and depression have reported different results. Therefore, the goal of the present study was to examine the association between depression and MetS by meta-analysis. METHODS: Embase, Scopus, PubMed, and ISI were searched for publications in English from January 1990 to February 2020. Search included cohort and cross-sectional studies aimed at examining the association between depression and MetS. The risk of bias was assessed by Newcastle-Ottawa Scale. Heterogeneity and publication bias were tested, subgroup analysis and meta-regression were conducted. RESULTS: 49 studies with total sample size 399,494 were analyzed. Results indicated the odds of MetS was higher in depressed compared to non-depressed individuals [OR: 1.48; 95 %CI: 1.33-1.64) vs. (OR: 1.38; 95 %CI: 1.17-1.64)]. For cross-sectional studies, depressed patients in Europe (OR = 1.35; 95 %CI: 1.47-1.99) were at higher odds of MetS compared to those in America and Asia. For cohort studies, depressed patients in America (OR = 1.46; 95 %CI: 1.16-1.84) were at higher odds of MetS than those in Europe. Cross-sectional studies indicated women with depression were at higher odds of MetS (OR = 1.95; 95 %CI: 1.38-2.74) compared to men. In both types of studies, the odds of MetS decreased with age. CONCLUSIONS: Metabolic syndrome is more common in depressed compared to non-depressed individuals.
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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 | 0.001 | 0.003 |
| 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".