Birth Weight and Childhood Psychopathology in the ABCD Cohort: Association is Strongest for Attention Problems and is Moderated by Sex
Bibliographic record
Abstract
Many studies have shown low birth weight is associated with psychopathology later in life, particularly attention-deficit/hyperactivity disorder (ADHD). The association is well-replicated, independent from a variety of potential familial confounds, and follows a dose-response curve (decreasing birth weight linked with increasing odds of disorder). However, the specificity of the association to attention problems is called into question by the extent of comorbidity in ADHD, and recent findings that the association is stronger for autism than ADHD. We test the relative dose-response strength of birth weight on multiple aspects of behavior to explore specificity of the effect to attention problems. We also test recent suggestions that the association between birth weight and attention problems is driven by males. Our sample consisted of 9,076 children aged 9-10 from the United States (Adolescent Brain Cognitive Development study). Outcomes included 9 problem-scales and the total problems scale from the Child Behavior Checklist (CBCL). Attention problems were the most strongly associated with birth weight after controlling for gestational age, potential familial confounds, and multiple testing, supporting the outcome-specificity of this association. Contrary to recent registry-based findings, an association between birth weight and an autism scale was not observed. Sex moderated the effect of birth weight on total problems, attention problems and aggressive behavior such that these inverse associations were strongly driven by males. Our findings have strong implications for sex-specific prediction and etiological models of childhood psychopathology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".