Longitudinal Associations of Obesity With Affective Disorders and Suicidality in the Baltimore Epidemiologic Catchment Area Follow-up Study
Bibliographic record
Abstract
Our aim was to examine the longitudinal associations between obesity and mental health variables (psychiatric diagnoses and suicidal behaviors). Data were from waves 3 and 4 of the Baltimore Epidemiologic Catchment Area study (N = 1071). Participants were aged 30 to 86 years at wave 3 (mean, 47.6 years; SD, 12.8). The prevalence of obesity increased from 27.6% to 39.1% during the follow-up. Logistic regression analyses revealed no associations between baseline obesity and onset of mental disorders or suicidal behaviors between waves 3 and 4 in fully adjusted models; however, baseline obesity predicted new-onset suicide attempts in models adjusted for sociodemographics and mental disorders. Baseline depression predicted weight gain during the 11-year follow-up period (F = 4.014, p < 0.05), even after controlling for important confounders. Overall, most mental health variables were not associated with obesity, suggesting that clinicians and others should be wary of "weight-ism" and avoid making the assumption that higher body weight relates to mental health problems.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".