Is the Association Between Pregnancy Weight Gain and Fetal Size Causal?
Bibliographic record
Abstract
BACKGROUND: Observational cohort studies have consistently shown that maternal weight gain in pregnancy is positively associated with fetal size, but it is unknown whether the association is causal. This study investigated the effect of pregnancy weight gain on fetal growth using a sibling comparison design to control for unmeasured confounding by genetic and shared environmental factors. METHODS: Our study population included 44,457 infants (21,680 women) with electronic medical records in the Stockholm-Gotland Obstetrical Database, 2008-2014. We standardized pregnancy weight gain into gestational age-specific z-scores. Fetal size was classified as birthweight (gram), and as small- and large-for-gestational-age birth (birthweight <10th or >90th percentiles, respectively). Our sibling comparison analyses used multivariable linear fixed effects models for birthweight and hybrid logistic fixed effects models for small- and large-for-gestational-age birth (SGA and LGA). We repeated analyses using conventional (unmatched) regression models. RESULTS: Sibling comparison analyses showed a clinically meaningful association between weight gain and fetal size (e.g., adjusted difference of +89 g birthweight [95% CI = 82, 95 g]; adjusted risk ratios [aRR] for SGA of 0.80 [95% CI = 0.75, 0.86] per 1 z-score increase in weight gain for a woman of body mass index [BMI] = 25). These findings were consistent across the range of BMI. Estimates were only modestly attenuated compared with conventional approach (+97 g [95% CI = 92, 102 g], aRR for SGA of 0.70 [95% CI = 0.67, 0.73] per 1 z-score increase in weight gain). CONCLUSION: The positive association between pregnancy weight gain and fetal size we found using a sibling comparison design suggests that this relation has minimal confounding by familial factors that remain constant between pregnancies.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".