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The epidemiologic literature estimating the indirect or secondary effects of the coronavirus disease 2019 (COVID-19) pandemic on pregnant people and gestation continues to grow. Our assessment of this scholarship, however, leads us to suspect that the methods most commonly used may lead researchers to spurious inferences. This suspicion arises because the methods do not account for temporal patterning in perinatal outcomes when deriving counterfactuals, or estimates of the outcomes had the pandemic not occurred. We illustrate the problem in 2 ways. First, using monthly data from US birth certificates, we describe temporal patterning in 5 commonly used perinatal outcomes. Notably, for all but 1 outcome, temporal patterns appear more complex than much of the emerging literature assumes. Second, using data from France, we show that using counterfactuals that ignore this complexity produces spurious results. We recommend that subsequent investigations on COVID-19 and other perturbations use widely available time-series methods to derive counterfactuals that account for strong temporal patterning in perinatal outcomes.

BackgroundThe infant mortality rate (IMR) serves as a key indicator of population health.MethodsWe used data from the French National Institute of Statistics and Economic Studies on births and deaths during the first year of life from 2001 to 2019 to calculate IMR aggregated by month. We ran joinpoint regressions to identify inflection points and assess the linear trend of each segment. Exploratory analyses were performed for overall IMR, as well as by age at death subgroups (early neonatal [D0-D6], late neonatal [D7-27], and post-neonatal [D28-364]), and by sex. We performed sensitivity analyses by excluding deaths at D0 and using other time-series modeling strategies.ResultsOver the 19-year study period, 53,077 infant deaths occurred, for an average IMR of 3·63/1000 (4·00 in male, 3·25 in female); 24·4% of these deaths occurred during the first day of life and 47·8% during the early neonatal period. Joinpoint analysis identified two inflection points in 2005 and 2012. The IMR decreased sharply from 2001 to 2005 (slope: -0·0167 deaths/1000 live births/month; 95%CI: -0·0219 to -0·0116) and then decreased slowly between 2005 and 2012 (slope: -0·0041; 95%CI: -0·0065 to -0·0016). From 2012 onwards, a significant increase in IMR was observed (slope: 0·0033; 95%CI: 0·0011 to 0·0056). Subgroup analyses indicated that these trends were driven notably by an increase in the early neonatal period. Sensitivity analyses provided consistent results.InterpretationThe recent historic increase in IMR since 2012 in France should prompt urgent in-depth investigation to understand the causes and prepare corrective actions.FundingNo financial relationships with any organizations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.

BackgroundSome scholars posit that attempts to avert stillbirth among extremely preterm gestations may result in a live birth but an early neonatal death. The literature, however, reports no empirical test of this potential form of left truncation. We examine whether annual cohorts delivered at extremely preterm gestational ages show an inverse correlation between their incidence of stillbirth and early neonatal death.MethodsWe retrieved live birth and infant death information from the California Linked Birth and Infant Death Cohort Files for years 1989 to 2015. We defined the extremely preterm period as delivery from 22 to

Accurate determination of pre-pregnancy weight is essential for optimal pregnancy monitoring and antenatal care. Determining pre-pregnancy weight in limited-resources settings is challenging for both clinical practice and public health research. From a 2014–2017 pre-pregnancy cohort in Benin, we evaluated the agreement between the measured pre-pregnancy weight (MPPW) and two proxies: (i) the first trimester pregnancy weight (FTPW) and (ii) the estimated pre-pregnancy weight (EPPW) using Thomas & al. formula. We analysed data from 302 pregnant women with both pre-pregnancy weight measured within 3 months before conception and weight measured during the first trimester. Using segmented linear regression, we first assessed up to which gestational age the weight measured during the first trimester could reasonably estimate the MPPW. Then the Bland & Altman method was used to assess agreement between MPPW and the two proxies. Additional analyses were performed to assess the sensitivity of results to the timing of measurement of either MPPW or the two proxies. On average, FTPW did not feature significant difference with MPPW up to 13.03 (11.99–14.06) weeks of gestational age. FTPW, measured on average at 7 ± 2.4 weeks of gestation, and the EPPW showed similar Bland & Altman limits of agreement with the MPPW. However, while the FTPW slightly underestimated the MPPW by a mean of—0.16 (-0.08; +0.39) kg, the EPPW overestimated it by a mean of + 0.43 (+0.20; +0.66) kg. Minor differences in these results were observed when the MPPW was assessed earlier or within three months before pregnancy, or according to the gestational age at the time of the proxy's measurement. In conclusion, in Southern Benin and up to 12–14 weeks of pregnancy, the FTPW appeared to be a good proxy of the MPPW while using Thomas' formula did not enhance pre-pregnancy weight estimation. [ABSTRACT FROM AUTHOR]

Background: Preterm birth (before 37 completed weeks of gestation) is associated with an increased risk of adverse health and developmental outcomes relative to birth at term. Existing guidelines for data collection in cohort studies of individuals born preterm are either limited in scope, have not been developed using formal consensus methodology, or did not involve a range of stakeholders in their development. Recommendations meeting these criteria would facilitate data pooling and harmonisation across studies. Objectives: To develop a Core Dataset for use in longitudinal cohort studies of individuals born preterm. Methods: This work was carried out as part of the RECAP Preterm project. A systematic review of variables included in existing core outcome sets was combined with a scoping exercise conducted with experts on preterm birth. The results were used to generate a draft core dataset. A modified Delphi process was implemented using two stages with three rounds each. Three stakeholder groups participated: RECAP Preterm project partners; external experts in the field; people with lived experience of preterm birth. The Delphi used a 9‐point Likert scale. Higher values indicated greater importance for inclusion. Participants also suggested additional variables they considered important for inclusion which were voted on in later rounds. Results: An initial list of 140 data items was generated. Ninety‐six participants across 22 countries participated in the Delphi, of which 29% were individuals with lived experience of preterm birth. Consensus was reached on 160 data items covering Antenatal and Birth Information, Neonatal Care, Mortality, Administrative Information, Organisational Level Information, Socio‐economic and Demographic information, Physical Health, Education and Learning, Neurodevelopmental Outcomes, Social, Lifestyle and Leisure, Healthcare Utilisation and Quality of Life. Conclusions: This core dataset includes 160 data items covering antenatal care through outcomes in adulthood. Its use will guide data collection in new studies and facilitate pooling and harmonisation of existing data internationally. [ABSTRACT FROM AUTHOR]

Background Despite concerns about worsening pregnancy outcomes resulting from healthcare restrictions, economic difficulties and increased stress during the COVID-19 pandemic, preterm birth (PTB) rates declined in some countries in 2020, while stillbirth rates appeared stable. Like other shocks, the pandemic may have exacerbated existing socioeconomic disparities in pregnancy, but this remains to be established. Our objective was to investigate changes in PTB and stillbirth by socioeconomic status (SES) in European countries. Methods The Euro-Peristat network implemented this study within the Population Health Information Research Infrastructure (PHIRI) project. A common data model was developed to collect aggregated tables from routine birth data for 2015–2020. SES was based on mother's educational level or area-level deprivation/maternal occupation if education was unavailable and harmonized into low, medium and high SES. Country-specific relative risks (RRs) of PTB and stillbirth for March to December 2020, adjusted for linear trends from 2015 to 2019, by SES group were pooled using random effects meta-analysis. Results Twenty-one countries provided data on perinatal outcomes by SES. PTB declined by an average 4% in 2020 {pooled RR: 0.96 [95% confidence intervals (CIs): 0.94–0.97]} with similar estimates across all SES groups. Stillbirths rose by 5% [RR: 1.05 (95% CI: 0.99–1.10)], with increases of between 3 and 6% across the three SES groups, with overlapping confidence limits. Conclusions PTB decreases were similar regardless of SES group, while stillbirth rates rose without marked differences between groups. [ABSTRACT FROM AUTHOR]

Objective To determine whether delivery hospitals that perform poorly for women also perform poorly for high-risk infants and to what extent Black and Hispanic women receive care at hospitals that perform poorly for both women and infants. Methods We examined the correlation between hospital rankings for severe maternal morbidity and very preterm morbidity and mortality in New York City Hospitals using linked birth certificate and state discharge data for 2010-2014. We used mixed-effects logistic regression with a random hospital-specific intercept to generate risk standardized severe maternal morbidity rates and very preterm birth neonatal morbidity and mortality rates for each hospital. We ranked hospitals separately by these risk-standardized rates. We used k-means cluster analysis to categorize hospitals based on their performance on both metrics and risk-adjusted multinomial logistic regression to estimate adjusted probabilities of delivering in each hospital-quality cluster by race/ethnicity. Results Hospital rankings for severe maternal morbidity and very preterm neonatal morbidity-mortality were moderately correlated (r = .32; p = .05). A 5-cluster solution best fit the data and yielded the categories for hospital performance for women and infants: excellent, good, fair, fair to poor, poor. Black and Hispanic versus White women were less likely to deliver in an excellent quality cluster (adjusted percent of 11%, 18% vs 28%, respectively, p < .001) and more likely to deliver in a poor quality cluster (adjusted percent of 28%, 20%, vs. 4%, respectively, p < .001). Conclusions for Practise Hospital performance for maternal and high-risk infant outcomes is only moderately correlated but Black and Hispanic women deliver at hospitals with worse outcomes for both women and very preterm infants., Author(s): Elizabeth A. Howell [sup.1] [sup.2] [sup.3] , Teresa Janevic [sup.1] [sup.2] [sup.3] , James Blum [sup.3] [sup.4] , Jennifer Zeitlin [sup.5] , Natalia N. Egorova [sup.2] [sup.3] , Amy [...]