Association Between Gestational Weight Gain and Autism Spectrum Disorder in Offspring: A Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: This study aimed to quantitatively examine the association between gestational weight gain (GWG) and risk of autism spectrum disorder (ASD) in offspring. METHODS: Electronic databases were searched for studies of excessive or inadequate GWG, as compared with recommended GWG, in relation to the risk of ASD in offspring. Measures of the association from primary studies were pooled using a meta-analytic approach and expressed as weighted odds ratios (ORs) with 95% CIs. RESULTS: Nine studies were identified, including 323,253 participants with 4,135 cases of ASD from five cohort studies and 1,462 cases and 3,265 controls from four case-control studies. Evidence from cohort studies indicates that both excessive and inadequate GWG was significantly associated with a higher risk for ASD in offspring. The pooled OR of ASD was 1.10 (95% CI: 1.02-1.18) for excessive GWG and 1.13 (95% CI: 1.04-1.24) for inadequate GWG using recommended GWG as the reference. Evidence from case-control studies suggests that excessive GWG (1.38 [95% CI: 1.19-1.62]) but not inadequate GWG (0.87 [95% CI: 0.72-1.04]) was significantly associated with a higher risk for ASD. CONCLUSIONS: The accumulated evidence has supported that gaining weight outside the recommended GWG is associated with a higher risk for ASD in offspring.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 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".