Depression and emotional eating in children and adolescents: A systematic review and meta-analysis
Bibliographic record
Abstract
Major Depressive Disorder in youth is associated with obesity and adult cardiovascular disease (CVD) risk. Eating in response to emotions (emotional eating) is a potential contributing factor to this association. Although emotional eating is associated with Major Depressive Disorder in adults, findings in children and adolescents are mixed. This systematic review and meta-analysis aims to determine the association between depression and emotional eating in children and adolescents. Systematic searches were conducted in seven databases. Studies were included if the study population had a mean age of ≤18 years and assessed both depression and emotional eating using validated measures. The search generated 12,241 unique studies, of which 37 met inclusion criteria. Random-effects meta-analyses of study outcomes were performed. Thirty-seven studies (26,026 participants; mean age = 12.4 years, SD = 3.1) were included. The mean effect size was significant for both cross-sectional and longitudinal data (Hedges' g = 0.48, p < 0.0001; g = 0.37, p = 0.002, respectively), revealing a positive moderately strong association between depressive symptoms and emotional eating in youth. Among longitudinal studies, the association was stronger when depressive symptoms and emotional eating were assessed using child and adolescent self-report versus parent-report. No studies examined youth with a clinical diagnosis of depression. Meta-analyses revealed that depressive symptoms and emotional eating are positively associated in children and adolescents. However, further research in clinical samples is needed. Results raise the possibility for the importance of emotional eating in the link between depression and early CVD risk, though further examination is required to determine whether emotional eating is a potential treatment target to decrease CVD risk among adolescents with increased depression symptoms.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.026 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".