Dynamic changes in postnatal growth predict adolescent mental health problems in survivors of extremely low birth weight (ELBW)
Bibliographic record
Abstract
Abstract Although individuals born at extremely low birth weight (ELBW; ≤1000 g) are known to be at greater risk for mental health problems than individuals born at normal birth weight (NBW; ≥2500 g), contributions of postnatal growth to these relations have not been fully explored. We compared individual differences in the Ponderal Index [(PI; weight(kg)/height(m 3 )] and head circumference (HC) in predicting internalizing and externalizing behaviors in childhood and adolescence in a cohort of ELBW survivors ( N = 137) prospectively followed since birth. Baseline models indicated that infants who were born thinner or with smaller HC showed greater PI or HC growth in the first 3 years. Latent difference score (LDS) models showed that compensatory HC growth in the first year (ΔHC = 20.72 cm), controlled for birth HC, predicted ADHD behaviors in adolescence in those born with smaller HC. LDS models also indicated that the PI increased within the first year (ΔPI = 1.568) but decreased overall between birth and age 3 years (net ΔPI = −4.597). Modeling further showed that larger increases in the PI in the first year and smaller net decreases over 3 years predicted more internalizing behaviors in adolescence. These findings suggest early growth patterns prioritizing weight over height may have negative effects on later mental health in ELBW survivors, consistent with developmental programming theories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".