Associations of fetal and postnatal growth trajectories with child cognition: the GUSTO cohort study
Bibliographic record
Abstract
BACKGROUND: Using longitudinal ultrasounds as an improved fetal growth marker, we aimed to investigate if increased postnatal growth following fetal abdominal circumference (AC) growth deceleration is associated with improved child cognition. METHODS: Among 797 term-born singletons in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort, we derived 2nd-3rd trimester fetal AC growth z-score, fetal AC growth deceleration, standardized height, weight, and body mass index (BMI) growth at early infancy (0-4 months), late infancy (4-15 months), toddlerhood (15-37 months), and early childhood (3-7 years), and investigated their associations with intelligence quotient (IQ) at ages 4.5 years (verbal, non-verbal) and 7 years (non-verbal-block design, matrix reasoning), adjusting for socio-demographic and biological confounders. RESULTS: Among term-born newborns, 23.3% experienced fetal AC growth deceleration, which was associated with lower non-verbal IQ (4.5 years) [β (95% CI), -4.00 (-7.49, -0.51)]. Higher 0-7 years z-BMI gain was associated with lower non-verbal IQ (block design) (7 years) [-1.33 (-2.51, -0.14)]. Higher late infancy z-BMI gain was associated with higher verbal IQ (4.5 years) [3.36 (0.82,5.90)] but lower non-verbal IQ (matrix reasoning) (7 years) [-2.32 (-4.48, -0.17)]. Among those with fetal AC growth deceleration, higher 0-7 years z-weight gain was associated with lower non-verbal IQ (block design) (7 years) (P-interaction = .049); at z-weight gain of +2 standard deviation score (SDS), those with fetal AC growth deceleration had lower IQ [margins (95% CI), -2.6 (-7.1,1.9)]. On average, children with fetal AC growth deceleration caught up in z-height, z-weight, and z-BMI by 7 years. CONCLUSION: Fetal AC growth deceleration was associated with lower cognition scores at preschool age. Increased weight or BMI growth from 0-7 years following fetal AC growth deceleration might not be favorable to cognition among generally well-nourished term-born children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".