COVID-19 pandemic impact on preterm birth and stillbirth rates associated with socioeconomic disparities: A quasi-experimental study
Bibliographic record
Abstract
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 quasi-experimental 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 interrupted time series analysis using autoregressive integrated moving average 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 lower and higher SES (average annual household income) using subgroup analysis and interaction models. Results We examined 70,931 pregnancies in Manitoba during the study period. Following the implementation of COVID-19 restrictions in March 2020, there were no statistically significant changes in the rates of both PTB (p=0.094) and stillbirths (p=0.958). However, over the pandemic, the PTB rate significantly decreased as a rebound effect by 0.63% per quarter(p=0.005); whereas the stillbirth rate did not change significantly (p=0.878) compared to pre-pandemic period. During the first quarter of 2021, the absolute differences in the observed and expected PTB and stillbirth percentages were 2.05% and 0.04%, respectively. We observed a statistically significant 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 PTB and stillbirth rates, we observed a statistically significant 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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".