Maternal underweight and the risk of preterm birth and low birth weight: a systematic review and meta-analyses
Bibliographic record
Abstract
BACKGROUND: Despite the current obesity epidemic, maternal underweight remains a common occurrence with potential adverse perinatal outcomes. Our objective was to determine the relationship between maternal underweight and preterm birth (PTB) and low birth weight (LBW) in singleton pregnancies in developing and developed countries. METHODS: We followed the MOOSE consensus statement. We searched MEDLINE and EMBASE from their inceptions. We included studies that assessed the effect of maternal underweight compared with normal weight according to body mass index in singleton gestations on our two primary outcomes: PTB (<37 weeks) and LBW (<2500 g). Two assessors independently reviewed citations, extracted data and assessed quality. RESULTS: A total of 78 studies were included involving 1 025 794 women. The overall risk of PTB was increased in the cohort studies of underweight women [adjusted relative risk (RR) 1.29, 95% confidence interval (CI) 1.15-1.46], as were the risks of spontaneous PTB (adjusted RR 1.32, 95% CI 1.10-1.57) and induced PTB (adjusted RR 1.21, 95% CI 1.07-1.36). Underweight women had an increased risk of an LBW infant (adjusted RR 1.64, 95% CI 1.38-1.94). In developed countries, underweight women had an increased risk of PTB (RR 1.22, 95% CI 1.15-1.30) but not in developing countries (RR 0.99, 95% CI 0.67-1.45). In both developed and developing countries, underweight women were at increased risk of having an LBW infant (RR 1.48, 95% CI 1.29-1.68, and RR 1.52, 95% CI 1.25-1.85, respectively). CONCLUSIONS: In this systematic review and meta-analyses, we determined that singletons born to underweight women have higher risks of PTB (overall, spontaneous and induced) and LBW than those born to women with normal weight.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".