Relationship between obesity and depression, anxiety and psychological distress among Iranian health-care staff
Bibliographic record
Abstract
BACKGROUND: Psychological-related disorders such as obesity are a key contributor to morbidity and mortality. AIMS: To assess the association between general and abdominal obesity with depression and anxiety among Iranian health-care staff. METHODS: This cross-sectional study was conducted under the framework of the Study on the Epidemiology of Psychological Alimentary Health and Nutrition. A total of 4361 Iranian health-care staff were analysed for general obesity and 3213 for central obesity. Overweight and obesity was defined as body mass index 25.0-29.9 and ≥ 30.0 kg/m², respectively. Abdominal obesity was defined as waist circumference (WC) ≥ 88 cm for females and ≥ 102 cm for males. The Iranian validated versions of the Hospital Anxiety and Depression Scale and the General Health Questionnaire were used to assess depression and anxiety. RESULTS: Stratified analysis by sex revealed no significant relationship between general obesity, depression and anxiety among males. However, we found an inverse association between abdominal obesity (WC > 102 cm) and severe depression among males. In females, abdominal obesity was significantly associated with anxiety, before and after taking confounders into account. No significant association was seen between abdominal obesity and psychological distress in either sex after controlling for potential confounders. CONCLUSIONS: Abdominal obesity was associated with anxiety in Iranian adult females but not in males. Further studies, particularly prospective research, are required to confirm these findings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".