Cortical thickness and childhood eating behaviors: differences according to sex and age, and relevance for eating disorders
Bibliographic record
Abstract
PURPOSE: This study investigated the association between childhood eating behaviors and cortical morphology, in relation to sex and age, in a community sample. METHODS: Neuroimaging data of 71 children (mean age = 9.9 ± 1.4 years; 39 boys/32 girls) were obtained from the Nathan Kline Institute-Rockland Sample. Emotional overeating, food fussiness, and emotional undereating were assessed using the Children's Eating Behavior Questionnaire. Cortical thickness was obtained at 81,924 vertices covering the entire cortex. Generalized Linear Mixed Models were used for statistical analysis. RESULTS: There was a significant effect of sex in the association between cortical thickness and emotional overeating (localized at the right postcentral and bilateral superior parietal gyri). Boys with more emotional overeating presented cortical thickening, whereas the opposite was observed in girls (p < 0.05). Different patterns of association were identified between food fussiness and cortical thickness (p < 0.05). The left rostral middle frontal gyrus displayed a positive correlation with food fussiness from 6 to 8 years, but a negative correlation from 12 to 14 years. Emotional undereating was associated with cortical thickening at the left precuneus, left middle temporal gyrus, and left insula (p < 0.05) with no effect of sex or age. CONCLUSIONS: Leveraging on a community sample, findings support distinct patterns of associations between eating behaviors and cortical thickness, depending on sex and age.
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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 | 0.001 |
| 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 | 0.000 | 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".