Preterm birth and stillbirth rates associated with socioeconomic disparities during COVID-19 pandemic: a population-based cross-sectional study
Bibliographic record
Abstract
Background Conflicting evidence exists on the impact of the COVID-19 pandemic restrictions on preterm birth (PTB) and stillbirth rates. We aimed to evaluate changes in PTB and stillbirth rates before and during the pandemic period and assess the potential effect modification of socioeconomic status (SES). Methods Using the linked administrative health databases from Manitoba, Canada, we conducted a cross-sectional study among all pregnant women, comparing 3.5 years pre-pandemic (1 October 2016 to 29 February 2020) to the first year of the pandemic (1 March 2020 to 31 March 2021). We used generalised linear models to assess the quarterly rates of PTB (<37 weeks) and stillbirths. We calculated the predicted trends based on pre-pandemic period data. Finally, we evaluated the PTB and stillbirth rates among lower and higher SES pregnant women (average annual household income) using subgroup analysis and interaction models. Results We examined 70 931 pregnancies in Manitoba during the study period. The risk of PTB increased by 7.7% (95%CI 1.01 to 1.13) and stillbirths by 33% (95% CI 1.08 to 1.64) during the pandemic period. Following COVID-19 restrictions implemented in March 2020, there were increases in the quarterly rates of both PTB (immediate increase (β2)=1.37; p=0.0247) and stillbirths (immediate increase (β2)=0.12; p=0.4434). Among the lower income groups, the pandemic restrictions resulted in an immediate relative increase in PTB and stillbirth rates by 20.12% (immediate increase (β2)=3.17; p=0.0057) and 27.19% (immediate increase (β2)=0.48; p=0.0852). However, over the pandemic, the overall PTB rate significantly decreased as a rebound effect by 0.85% per quarter (p=0.0004), whereas the overall stillbirth rate did not decrease significantly (slope decrease (β3) =−0.01; p=0.8296) compared with the pre-pandemic period. The quarterly rates during the pandemic among the higher income group decreased by 0.39% (p=0.1296) for PTB and increased by 0.07% (p=0.1565) for stillbirth. We observed an effect modification by SES for PTB rates (p=0.047). Conclusion While the onset of COVID-19 pandemic restrictions was not associated with significant effects on stillbirth rates, we observed an immediate and rebound effect on PTB rates. The impact of COVID-19 on preterm birth was dependent on SES, with higher influence on families with lower SES. Further studies are needed to detect future trend changes during pandemic waves after 2021 and assess potential underlying mechanisms.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".