Depressive symptoms and body mass index: co-morbidity and direction of association in a British birth cohort followed over 50 years
Bibliographic record
Abstract
BACKGROUND: An unhealthy body mass index (BMI) has been associated with depression but the direction of association is uncertain. Our aim was to estimate the co-morbidity and direction of association between BMI and depressive symptoms at several ages, from childhood to mid-adulthood. METHOD: The data were from 18,558 individuals born in 1 week in March 1958, in England, Scotland and Wales, with follow-up at ages 7, 11, 16, 23, 33, 42, 45 and 50 years. Depression (scores>or=90th percentile) was identified from child/adolescent (teacher questionnaires) and adult (self-complete questionnaires and clinical interview) measures. BMI (kg/m2) measured in child/adolescence and adulthood was classified as underweight, normal, overweight or obese. RESULTS: In cross-sectional analyses, obesity and underweight (not overweight) from 11 to 45 years were associated respectively with 1.3-2.1 and 1.5-2.3 times the risk of depression compared with normal weight. Using the time-lagged generalized estimating equation (GEE) approach, we tested (a) whether underweight or obesity at prior ages (7 to 45 years) predicted subsequent risk of depression (11 to 50 years), adjusting for baseline depression; and (b) whether depression at prior ages (7 to 42 years) predicted subsequent risk of underweight or obesity (11 to 45 years), adjusting for baseline BMI. In longitudinal analyses, underweight predicted subsequent depression in both sexes [odds ratio (OR) 1.25, 95% confidence interval (CI) 1.11-1.40] and depression predicted subsequent underweight in males only (OR 1.84, 95% CI 1.52-2.23). Obesity predicted subsequent depressive symptoms in females only (OR 1.34, 95% CI 1.14-1.56), but depression did not predict obesity. CONCLUSIONS: Clinicians should consider screening routinely for depression patients with unhealthy BMI, namely underweight and obesity, and vice versa.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".