Stillbirths: contribution of preterm birth and size-for-gestational age for 119.6 million total births from nationwide records in 12 countries, 2000 to 2020
Bibliographic record
Abstract
ABSTRACT Objective To examine the contribution of preterm birth and size-for-gestational age in stillbirths using six ‘newborn types’. Design Population-based multi-country analyses. Setting Births collected through routine data systems in 12 countries. Sample 119,644,788 total births from 22 +0 to 44 +6 weeks gestation identified from 2000 to 2020. Methods We included 605,557 stillbirths from 22 +0 weeks gestation from 12 countries. We classified all births, including stillbirths, by six ‘newborn types’ based on gestational age information (preterm, PT, <37 +0 weeks vs term, T, ≥37 +0 weeks) and size-for-gestational age defined as small (SGA, <10 th centile), appropriate (AGA, 10 th -90 th centiles), or large (LGA, >90 th centile) for gestational age, according to the international newborn size for gestational age and sex INTERGROWTH-21 st standards. Main Outcome Measures Distribution of stillbirths, stillbirth rates and rate ratios according to six newborn types. Results 605,557 (0.50%) of the 119,644,788 total births resulted in stillbirth after 22 +0 weeks. Most stillbirths (74.3%) were preterm. Around 21.0% were SGA types (PT+SGA (16.0%), T+SGA (5.0%)) and 14.3% were LGA types (PT+LGA (10.1%), T+LGA (4.2%)). The median rate ratio (RR) for stillbirth was highest in PT+SGA babies (RR=78.8, interquartile range (IQR), 68.2, 111.5) followed by PT+AGA (RR=24.5, IQR, 19.3, 29.4), PT+LGA (RR=23.0, IQR,13.7, 29.0) and T+SGA (RR=5.5, IQR, 5.0, 6.0) compared with T+AGA. Stillbirth rate ratios were similar for T+LGA vs T+AGA (RR=0.7, IQR, 0.7, 1.1). At the population level, 21.5% of stillbirths were attributable to small-for-gestational-age. Conclusions In these high-quality data from high/middle income countries, almost three quarters of stillbirths were born preterm and a fifth were small-for-gestational age, with the highest stillbirth rates associated with the coexistence of preterm and SGA. Further analyses are needed to better understand patterns of gestation-specific risk in these populations, and also patterns in lower-income contexts, especially those with higher rates of intrapartum stillbirth and SGA. Funding The Children’s Investment Fund Foundation, 1803-02535 KEY FINDINGS 1. WHAT WAS KNOWN? Stillbirth (pregnancy loss after 22 +0 weeks) is a devastating outcome. Global estimates indicating 1.9 million late gestation stillbirths (≥28 +0 weeks) worldwide in 2021 underestimate the overall burden. Many of the pathways to stillbirth result in fetal death before term (preterm stillbirth, <37 +0 weeks of gestational age). In addition, babies with fetal growth restriction (frequently assessed using the proxy small for gestational age (SGA, <10 th centile)) are at higher risk of stillbirth than their appropriately grown peers. Stillbirths are therefore more likely to be low birthweight (LBW, <2,500g). Being large for gestational age (LGA, >90 th centile) at term may also be associated with increased risk of stillbirth. 2. WHAT WAS DONE THAT IS NEW? Combining information on gestational age (preterm (PT), or term (T)) and attained size for-gestational-age (small-for-gestational-age (SGA), appropriate-for-gestational age (AGA), large-for-gestational age (LGA)) we defined six ‘newborn types’: four small (PT+SGA, PT+AGA, PT+LGA, T+SGA), one large (T+LGA), and one reference (T+AGA). We compiled livebirth and stillbirth data from 15 high- and middle-income countries as part of the Vulnerable Newborn Collaboration. A total of 119,039,231 livebirths and 605,557 stillbirths ≥22 +0 weeks from 12 countries between 2000 and 2020 met the inclusion criteria. We examined the distribution of stillbirths by these ‘newborn types’, and calculated type-specific stillbirth rates and rate ratios. 3. WHAT WAS FOUND? Most stillbirths (74.3%) were preterm, compared to fewer than 1-in-10 (9.0%) livebirths. A fifth (21.0%) of stillbirths were SGA compared to 1-in-20 (5.4%) livebirths. Preterm SGA had 78.8 times higher stillbirth rates compared to term AGA (Rate ratio (RR)=78.8, interquartile range (IQR), 68.2,111.5). Overall, preterm types had a 25 times higher stillbirth rate than term types (RR=25.0, IQR,20.1, 29.5). At the population level, over a fifth of stillbirths (21.5%) were attributable to being SGA, indicating a substantial impact of growth restriction on stillbirth in these settings. 14.3% of stillbirths and 17.5% of livebirths were LGA. There was no evidence of increased stillbirth rates for LGA types. The distribution of these ‘newborn types’ are similar amongst stillbirths and neonatal deaths. 4. WHAT NEXT? Categorisation of all births, including stillbirths, into these ‘newborn types’ was analytically possible using routinely collected data in these 12 upper-middle- or high-income contexts and led to programmatic relevant findings. However, as the majority (98%) of the world’s stillbirths are in low-and middle-income countries, more data are needed to improve understanding of patterns in stillbirths in a wider range of contexts, especially in settings with higher rates of intrapartum stillbirth and those with very high SGA rates such as South Asia. Further analyses, including assessing gestational age-specific risk, could provide more information on pathways to stillbirth and enable targeted interventions to underlying causes such as infection and obstetric complications. When analysing these vulnerability pathways, omitting stillbirths neglects an important part of the burden and its effects on families and society.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".