The association of diet and depression: an analysis of dietary measures in depressed, non-depressed, and healthy youth
Bibliographic record
Abstract
Background The association of diet quality with depression among the pediatric age group has been inconsistent. This may be due, in part, to varying dietary assessment methods. The current study sought to examine this association, and its reliability, using four dietary measures previously studied in children and adolescents.Methods Dietary habits among 139 children and adolescents (10–18 years, 66% female) with major depressive disorder [MDD (n = 77)], non-MDD psychiatric conditions (PSYCH; n = 31), or without psychiatric illness (healthy controls [HC]; n = 31) were examined. Using self-reported dietary intake, diet quality was characterized using the Youth Healthy Eating Index (YHEI), Dietary Questionnaire (DQ), Health Behaviour of Teenagers (HBT), and the Healthy Eating Habits Scale (HEHS). Multivariate Analysis of Covariances examined the association between depression status and dietary habits across measures controlling for participant age.Results The multivariate effect was significant by diet measures, F (16, 256) = 1.9, p = .02, partial η2 = 0.12, with significant differences across groups on consumption of healthy dietary practices and minimal variability across measures. In subgroup analyses, MDD children had decreased consumption of healthy foods compared with PSYCH and HC children on three out of four measures. There was no difference in consumption of unhealthy foods across diagnostic groups.Limitations Cross-sectional design.Conclusions Children with MDD consume fewer healthy foods than non-MDD children, with little variation by dietary measure. Research examining the directionality of this association and specific dietary deficits among MDD youth is needed to elucidate potential preventative targets for intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".