Maternal altitude and risk of low birthweight: A systematic review and meta-analyses
Bibliographic record
Abstract
Previous studies conducted in high altitude regions showed that maternal altitude was associated with low birth weight. The effect size of birth weight reduction is inclusive with unknown effects due to preterm birth. We systematically reviewed the literature and synthesize evidence on associations between altitude elevation from sea level and birth weight. We searched MEDLINE/PubMed, Embase, Scopus, Web of Science, and Cochrane database, from inception to May 5, 2020 for studies that reported maternal altitude and birth weight. Bayesian multilevel effect models were employed to estimate the effect size on birth weight (and gestational age) associated with altitude. Bayesian multilevel effect models were employed to estimate the effect size on birth weight (and gestational age) associated with altitude. The systematic search identified 1020 articles, with 52 articles meeting the inclusion criteria providing 207 estimates for the association of altitude and birth weight (n = 4,428,563), and with 22 articles providing 71 estimates for gestational age (n = 2,149,627). A reduction in mean birth weight of 96.98 g was associated with every 1000 m increase in altitude across 52 studies. A statistically significant but numerically minimal effect of maternal altitude elevation was observed on the gestational age (0.3 days), corresponding to a negligible estimation of 5 g lower birth weight. A relatively high heterogeneity of between-study association (I2>84.1%) and small study effect was found. A clinically meaningful birth weight reduction was associated with maternal altitude elevation beginning from sea level. Future longitudinal studies are needed to elucidate the causal association and to understand the late effect of maternal altitude.
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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) | 0.009 | 0.001 |
| 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".