Adverse childhood experiences and binge-eating disorder in early adolescents
Bibliographic record
Abstract
BACKGROUND: Adverse childhood experiences (ACEs) are common and linked to negative health outcomes. Previous studies have found associations between ACEs and binge-eating disorder (BED), though they have mainly focused on adults and use cross-sectional data. The objective of this study was to examine the associations between ACEs and BED in a large, national cohort of 9-14-year-old early adolescents in the US. METHODS: We analyzed prospective cohort data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 10,145, 2016-2020). Logistic regression analyses were used to determine the associations between self-reported ACEs and BED based on the Kiddie Schedule for Affective Disorders and Schizophrenia at two-year follow-up, adjusting for sex, race/ethnicity, baseline household income, parental education, site, and baseline binge-eating disorder. RESULTS: In the sample, (49% female, 46% racial/ethnic minority), 82.8% of adolescents reported at least one ACE and 1.2% had a diagnosis of BED at two-year follow-up. The mean number of ACEs was higher in those with a diagnosis of BED compared to those without (2.6 ± 0.14 vs 1.7 ± 0.02). The association between number of ACEs and BED in general had a dose-response relationship. One ACE (adjusted odds ratio [aOR] 3.48, 95% confidence interval [CI] 1.11-10.89), two ACEs (aOR 3.88, 95% CI 1.28-11.74), and three or more ACEs (aOR 8.94, 95% CI 3.01-26.54) were all associated with higher odds of BED at two-year follow-up. When stratified by types of ACEs, history of household mental illness (aOR 2.18, 95% 1.31-3.63), household violence (aOR 2.43, 95% CI 1.42-4.15), and criminal household member (aOR 2.14, 95% CI 1.23-3.73) were most associated with BED at two-year follow-up. CONCLUSIONS: Children and adolescents who have experienced ACEs, particularly household challenges, have higher odds of developing BED. Clinicians may consider screening for ACEs and providing trauma-focused care when evaluating patients for BED.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".