Background: The impact of coronavirus disease 2019 (COVID-19) on maternal and newborn health is unclear. We aimed to evaluate the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during pregnancy and adverse pregnancy outcomes. Methods: We conducted a systematic review and meta-analysis of observational studies with comparison data on SARS-CoV-2 infection and severity of COVID-19 during pregnancy. We searched for eligible studies in MEDLINE, Embase, ClinicalTrials.gov, medRxiv and Cochrane databases up to Jan. 29, 2021, using Medical Subject Headings terms and keywords for “severe acute respiratory syndrome coronavirus 2 OR SARS-CoV-2 OR coronavirus disease 2019 OR COVID-19” AND “pregnancy.” We evaluated the methodologic quality of all included studies using the Newcastle–Ottawa Scale. Our primary outcomes were preeclampsia and preterm birth. Secondary outcomes included stillbirth, gestational diabetes and other pregnancy outcomes. We calculated summary odds ratios (ORs) or weighted mean differences with 95% confidence intervals (CI) using random-effects meta-analysis. Results: We included 42 studies involving 438 548 people who were pregnant. Compared with no SARS-CoV-2 infection in pregnancy, COVID-19 was associated with preeclampsia (OR 1.33, 95% CI 1.03 to 1.73), preterm birth (OR 1.82, 95% CI 1.38 to 2.39) and stillbirth (OR 2.11, 95% CI 1.14 to 3.90). Compared with mild COVID-19, severe COVID-19 was strongly associated with preeclampsia (OR 4.16, 95% CI 1.55 to 11.15), preterm birth (OR 4.29, 95% CI 2.41 to 7.63), gestational diabetes (OR 1.99, 95% CI 1.09 to 3.64) and low birth weight (OR 1.89, 95% CI 1.14 to 3.12). Interpretation: COVID-19 may be associated with increased risks of preeclampsia, preterm birth and other adverse pregnancy outcomes.

Congenital heart defects are the most common anomalies in infants, affecting every 8 births per 1000.¹ Heart defects are a major cause of infant morbidity and mortality despite significant advancements in medical care.^2,3 Increased survival has resulted in higher prevalence of heart defects in adults (5.78 per 1000)⁴ and greater health care costs.^5,6 The causes and risk factors for congenital heart defects are mostly unknown. Only 15% are attributed to genetic anomalies; a smaller percentage, to maternal infections, drugs, or environmental exposures.⁷ A better understanding of the origins of congenital heart defects is needed for prevention and earlier detection.⁷

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

Background: Congenital heart defects may be environmentally related, but the association with elevated ambient temperature has received little attention. Objectives: We studied the relationship between outdoor heat during the first trimester of pregnancy and risk of congenital heart defects. Methods: We carried out a retrospective cohort study of 704,209 fetuses between 2 and 8 weeks postconception from April to September in Quebec, Canada, 1988–2012. We calculated the prevalence of congenital heart defects at birth according to the number of days women were exposed to maximum temperature ≥ 30°C. In log-binomial regression models, we estimated prevalence ratios (PR) and 95% confidence intervals (CI) for the relationship of temperature with seven critical and eight noncritical heart defects, adjusted for pregnancy characteristics. Results: Prevalence of congenital heart defects was 979.5 per 100,000 for 10 days or more of temperature ≥ 30°C compared with 878.9 per 100,000 for 0 days of exposure. Temperature was more precisely associated with noncritical than critical defects, which had lower prevalence. Fetuses exposed to 15 days of temperature ≥ 30°C between 2 and 8 weeks postconception had 1.06 times the risk of critical defects (95% CI: 0.67, 1.67) and 1.12 times the risk of noncritical defects (95% CI: 0.98, 1.29) relative to 0 days. Associations were higher for atrial septal defects (PR 1.37, 95% CI: 1.10, 1.70) than for other noncritical defects. For atrial septal defects, associations with elevated temperatures began the 3rd week postconception. Conclusions: Extreme heat exposure during the first trimester may be associated with noncritical heart defects, especially of the atrial septum. Citation: Auger N, Fraser WD, Sauve R, Bilodeau-Bertrand M, Kosatsky T. 2017. Risk of congenital heart defects after ambient heat exposure early in pregnancy. Environ Health Perspect 125:8–14; http://dx.doi.org/10.1289/EHP171

Objective To determine the association between recurrent pre-eclampsia and long-term cardiovascular hospitalisation. Methods This study identified cardiovascular hospitalisations up to 25 years after pregnancy for all women who delivered between 1989 and 2013 in Québec, Canada. Exposures included recurrent and non-recurrent pre-eclampsia in women with two deliveries or more (N=606 820), and pre-eclampsia in women with only one delivery (N=501 761). Incidence, timing and risk of cardiovascular complications were calculated using accelerated failure time models adjusted for age, pre-existing disease, socioeconomic deprivation and period. Outcomes included a range of cardiovascular hospitalisations and procedures. Results Women with recurrent pre-eclampsia had higher incidence of cardiovascular hospitalisation (281.4 per 1000) than women with non-recurrent (167.7 per 1000) or no pre-eclampsia (72.6 per 1000). Mean time to cardiovascular hospitalisation was 10.5 years for recurrent, 11.6 years for non-recurrent and 12.7 years for no pre-eclampsia, a difference of 17.3% for recurrent and 8.7% for non-recurrent relative to no pre-eclampsia. Compared with no pre-eclampsia, recurrent pre-eclampsia was associated with 2 times the risk of heart disease (95% CI 1.69 to 2.29) and 3 times the risk of cerebrovascular disease (95% CI 2.25 to 4.05). Pre-eclampsia in women with one delivery was associated with 3 times greater risk of cardiovascular hospitalisation compared with no pre-eclampsia in women with two deliveries or more (95% CI 2.96 to 3.25). Conclusions Recurrent pre-eclampsia is associated with higher risk of future cardiovascular hospitalisation compared with no pre-eclampsia, and significantly shorter time to first cardiovascular event. Cardiovascular screening should be performed earlier for women with recurrent pre-eclampsia.