Obesity Comorbidity in Unipolar Major Depressive Disorder
Bibliographic record
Abstract
OBJECTIVE: While a significant body of research has demonstrated high comorbidity rates between depression and obesity, the vast majority of this work has considered depression as a unitary diagnosis. Given that increased appetite and weight gain are highly characteristic of the "atypical" subtype of depression, while classic depression is characterized by decreased appetite and weight loss, it would be important to examine whether increased obesity risk is consistent across the major vegetative subtypes of depression or is limited to the atypical subtype. METHOD: Using data from the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), we identified 5,092 US adults with past or current major depression based on DSM-IV-TR criteria and 1,500 gender-matched controls. Each depressed subject was designated as having classic, atypical, or undifferentiated depression based on core vegetative symptoms. Logistic regression models examined rates of current obesity (defined as a current body mass index [kg/m2] > 30) across the 3 depressive subgroups and nondepressed controls, adjusting for demographic differences. To limit the possible effect of current depressive symptoms on observed obesity rates, secondary analyses were completed in individuals with past depression only. RESULTS: Subjects with atypical depression had markedly elevated obesity rates compared to population controls and to other depressed subjects, with corresponding pairwise odds ratios consistently greater than 2.0 (P < .001). In contrast, obesity rates were not significantly different in subjects with classic depression and nondepressed controls. These results were manifest in individuals with either current or past depression and were independent of gender and age. CONCLUSIONS: While many individuals with classic depression will present with obesity due to the high prevalence of both disorders, only atypical depression is associated with an elevated risk of obesity relative to the population at large. Refining the target phenotype(s) for future work on depression and obesity might improve our understanding, prevention, and treatment of this complex clinical problem.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".