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Effects of race and ethnicity on perinatal outcomes in high-income and uppper-middle-income countries: an individual participant data meta-analysis of 2 198 655 pregnancies
https://doi.org/10.1016/S0140-6736(22)01191-6
Background
Existing evidence on the effects of race and ethnicity on pregnancy outcomes is restricted to individual studies done within specific countries and health systems. We aimed to assess the impact of race and ethnicity on perinatal outcomes in high-income and upper-middle-income countries, and to ascertain whether the magnitude of disparities, if any, varied across geographical regions.
Methods
For this individual participant data (IPD) meta-analysis we used data from the International Prediction of Pregnancy Complications (IPPIC) Network of studies on pregnancy complications; the full dataset comprised 94 studies, 53 countries, and 4 539 640 pregnancies. We included studies that reported perinatal outcomes (neonatal death, stillbirth, preterm birth, and small-for-gestational-age babies) in at least two racial or ethnic groups (White, Black, south Asian, Hispanic, or other). For our two-step random-effects IPD meta-analysis, we did multiple imputations for confounder variables (maternal age, BMI, parity, and level of maternal education) selected with a directed acyclic graph. The primary outcomes were neonatal mortality and stillbirth. Secondary outcomes were preterm birth and a small-for-gestational-age baby. We estimated the association of race and ethnicity with perinatal outcomes using a multivariate logistic regression model and reported this association with odds ratios (ORs) and 95% CIs. We also did a subgroup analysis of studies by geographical region.
Findings
51 studies from 20 high-income and upper-middle-income countries, comprising 2 198 655 pregnancies, were eligible for inclusion in this IPD meta-analysis. Neonatal death was twice as likely in babies born to Black women than in babies born to White women (OR 2·00, 95% CI 1·44–2·78), as was stillbirth (2·16, 1·46–3·19), and babies born to Black women were at increased risk of preterm birth (1·65, 1·46–1·88) and being small for gestational age (1·39, 1·13–1·72). Babies of women categorised as Hispanic had a three-times increased risk of neonatal death (OR 3·34, 95% CI 2·77–4·02) than did those born to White women, and those born to south Asian women were at increased risk of preterm birth (OR 1·26, 95% CI 1·07–1·48) and being small for gestational age (1·61, 1·32–1·95). The effects of race and ethnicity on preterm birth and small-for-gestational-age babies did not vary across regions.
Interpretation
Globally, among underserved groups, babies born to Black women had consistently poorer perinatal outcomes than White women after adjusting for maternal characteristics, although the risks varied for other groups. The effects of race and ethnicity on adverse perinatal outcomes did not vary by region.
External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol
doi: https://doi.org/10.1186/s41512-017-0016-z
Background
Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management.
Methods/design
We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests.
Discussion
Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia.
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