Data Preparation of the nuMoM2b Dataset

Goretsky, Anton; Dmitrienko, Anastasia; Tang, Irene; Lari, Nicolae; Kunhardt, Owen; Khan, Rehan; Marcussen, Cassandra; Catto, Adam; Mallia, Daniel; Leshchenko, Alisa; Lin, Adam Yuh; Raja, Anita; Salleb-Aouissi, Ansaf; Pe’er, Itsik; Wapner, Ronald J.; Gyamfi-Bannerman, Cynthia

doi:10.1101/2021.08.24.21262142

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…We conducted a secondary analysis of data from the nuMoM2b prospective cohort study of nulliparous women. 15,16 The study recruited women from hospitals affiliated with eight clinical centers and collected data on each participant over the course of four study visits via in-clinic interviews, self-administered questionnaires, clinical measurements, and chart abstractions. The cohort included 9,289 participants who consented to the release of their data.…”

Section: Study Populationmentioning

confidence: 99%

Racial/ethnic differences in pre-pregnancy conditions and adverse maternal outcomes in the nuMoM2b cohort: a population-based cohort study

Meredith

Steimle

Platner

et al. 2022

Preprint

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Background: Adverse maternal outcomes and multimorbidity affect a growing proportion of pregnant individuals in the United States and with racial and ethnic disparities in the rates of multimorbidity. There is limited research on multimorbidity, measured as the co-occurrence of two or more chronic conditions, and how it impacts adverse maternal outcomes. Objectives: We sought to: (1) determine how pre-pregnancy conditions and their combined effects contribute to racial disparities in adverse maternal outcomes; and (2) incorporate conditions and their combined effects into predictive modeling algorithms to improve risk prediction using information available in the first trimester, specifically for racial minority subgroups. Study Design: We used data from the 'Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be' (nuMoM2b) observational cohort study. We defined multimorbidity as the co-occurrence of two or more pre-pregnancy conditions. The primary outcomes of interest were severe preeclampsia, postpartum readmission, and blood transfusion during pregnancy or up to 14 days postpartum. We used weighted Poisson regression with robust variance to estimate adjusted risk ratios and 95% confidence intervals, and we used mediation analysis to evaluate the contribution of the combined effects of pre-pregnancy conditions to racial/ethnic disparities. We also evaluated the performance of our models by racial subgroup using the area under the receiver operating characteristic curve (AUC) metric. Results: In the nuMoM2b cohort (n=8729), 3.6% (n=318) experienced severe preeclampsia, 1.8% (n=157) experienced blood transfusion, and 1.8% (n=154) experienced postpartum readmission. 22.8% of all participants experienced two or more co-occurring pre-pregnancy conditions. Cardiovascular conditions were associated with an increased relative risk for severe preeclampsia (aRR, 1.71; CI, 1.59-1.84), and this risk was additionally exacerbated when hematologic conditions were co-occurring with cardiovascular conditions (aRR, 1.34; CI, 1.12-1.60). The mediation analysis results were not statistically significant; however, cardiovascular conditions explained 36.6% of non-Hispanic Black individuals' association with increased risk for severe preeclampsia (p=0.07). The addition of pre-pregnancy conditions increased AUC for the prediction of blood transfusion and severe preeclampsia, and moreover, the multiracial subgroup experienced the greatest improvement in predictive performance of blood transfusion due to this addition (an increase in AUC 0.51 to 0.69). The best subgroup performance was in predicting severe preeclampsia in multiracial individuals using confounders and condition types, with an AUC of 0.74. Conclusion: Though there is a greater burden of some pre-pregnancy conditions and co-occurring conditions among minority individuals, these conditions alone do not fully explain the higher rates of adverse maternal outcomes. However, some conditions and their combined effects are associated with adverse maternal outcomes. The incorporation of pre-pregnancy multimorbidity improves the performance of some risk prediction models, especially for correctly classifying individuals of minority race.

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Section: Study Populationmentioning

confidence: 99%

Racial/ethnic differences in pre-pregnancy conditions and adverse maternal outcomes in the nuMoM2b cohort: a population-based cohort study

Meredith

Steimle

Platner

et al. 2022

Preprint

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“…Motivated by the need to study large cohorts to understand the complexity of the PTB mechanism, we selected the CDC Natality data to bridge this gap. 7 Despite this data being publicly available and not having as fine-grained feature availability as other natality datasets, such as the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b), 8 , 9 this data have been recorded across nearly sixty years for millions of women each year, thereby making it incredibly rich as a longitudinal cohort study for stakeholders. As the CDC keeps updating this data yearly to incorporate new birth records, this additional data will continue to inspire the development of our CDC NatView tool, encouraging a continued exploration of this rich data for the foreseeable future.…”

Section: Introductionmentioning

confidence: 99%

Diving into CDC pregnancy data in the United States: longitudinal study and interactive application

Clark-Sevilla,

Lin,

Saxena

et al. 2024

JAMIA Open

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Objective Preterm birth (PTB) is a major determinant of neonatal mortality, morbidity, and childhood disability. In this article, we present a longitudinal analysis of the risk factors associated with PTB and how they have varied over the years: starting from 1968 when the CDC first started, reporting the natality data, up until 2021. Along with this article, we are also releasing an RShiny web application that will allow for easy consumption of this voluminous dataset by the research community. Further, we hope this tool can aid clinicians in the understanding and prevention of PTB. Materials and Methods This study used the CDC Natality data from 1968 to 2021 to analyze trends in PTB outcomes across the lens of various features, including race, maternal age, education, and interval length between pregnancies. Our interactive RShiny web application, CDC NatView, allows users to explore interactions between maternal risk factors and maternal morbidity conditions and the aforementioned features. Results Our study demonstrates how CDC data can be leveraged to conduct a longitudinal analysis of natality trends in the United States. Our key findings reveal an upward trend in late PTBs, which is concerning. Moreover, a significant disparity exists between African American and White populations in terms of PTB. These disparities persist in other areas, such as education, body-mass index, and access to prenatal care later in pregnancy. Discussion Another notable finding is the increase in maternal age over time. Additionally, we confirm that short interpregnancy intervals (IPIs) are a risk factor for PTBs. To facilitate the exploration of pregnancy risk factors, infections, and maternal morbidity, we developed an open-source RShiny tool called CDC NatView. This software offers a user-friendly interface to interact with and visualize the CDC natality data, which constitutes an invaluable resource. Conclusion In conclusion, our study has shed light on the rise of late PTBs and the persistent disparities in PTB rates between African American and White populations in the US. The increase in maternal age and the confirmation of a short IPI as a risk factor for PTB are noteworthy findings. Our open-source tool, CDC NatView, can be a valuable resource for further exploration of the CDC natality data to enhance our understanding of pregnancy risk factors and the interaction of PTB outcomes and maternal morbidities.

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“…By precisely characterizing different aspects of over 10,000 pregnancies, the nuMoM2b cohort has already yielded valuable insights into the factors that contribute to APOs 8,9,10 .…”

Section: Introductionmentioning

confidence: 99%

“…By precisely characterizing different aspects of over 10,000 pregnancies, the nuMoM2b cohort has already yielded valuable insights into the factors that contribute to APOs 8,9,10 . Additionally, the availability of biospecimens provides a unique opportunity to study the genetic underpinnings of APOs.…”

Section: Introductionmentioning

confidence: 99%

Genetic Polymorphisms Associated with Adverse Pregnancy Outcomes in Nulliparas

Guerrero

Khan

Wapner

et al. 2022

Preprint

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BackgroundAdverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet, the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions.ObjectiveTo search for genetic risk markers for four APOs, we performed genome-wide association studies (GWAS) for preterm birth, preeclampsia, gestational diabetes, and pregnancy loss.Study DesignA total of 9,757 nulliparas from the nuMoM2b study were genotyped. We clustered participants by their genetic ancestry and focused our analyses on the three sub-cohorts with the largest sample sizes: European (EUR, n=6,082), African (AFR, n=1,425), and American (AMR, n=846). Association tests were carried out separately for each sub-cohort and brought together via meta-analysis. Four APOs were tested by GWAS: preeclampsia (n=7,909), gestational length (n=4,781), gestational diabetes (n=7,617), and pregnancy loss (n=7,809). Using the results of the genome-wide associations for each APO, SNP-based heritability of these traits was inferred using LDscore. Putative regulatory effects were inferred by transcriptome-wide association analysis.ResultsTwo variants were significantly associated with pregnancy loss (rs62021480: OR = 3.29, P = 7.83×10−11, and rs142795512: OR = 4.72, P = 9.64×10−9), implicating genes TRMU and RGMA in this APO. An intronic variant was significantly associated with gestational length (rs73842644: beta = -0.667, P = 4.9×10−8). Three loci were significantly associated with gestational diabetes (rs72956265: OR = 3.09, P = 2.98×10−8, rs10890563: OR = 1.88, P = 3.53×10−8, rs117689036: OR = 3.15, P = 1.46×10−8), located on or near ZBTB20, GUCY1A2, and MDGA2, respectively. Several loci previously correlated with preterm birth (in genes WNT4, EBF1, PER3, IL10, and ADCY5), gestational diabetes (in TCF7L2), and preeclampsia (in MTHFR) were found to be associated with these outcomes in our cohort as well.ConclusionOur study identified genetic associations with gestational diabetes, pregnancy loss, and gestational length. We also confirm correlations of several previously identified variants with these APOs.Disclosure StatementThe authors declare no conflict of interestSource of financial supportPrecision Health Initiative of Indiana University, National Institutes of Health award R01HD101246 to DMH and PR. Cooperative agreement funding from the National Heart, Lung, and Blood Institute and the Eunice Kennedy Shriver National Institute of Child Health and Human Development: grant U10-HL119991 to RTI International; grant U10-HL119989 to Case Western Reserve University; grants U10-HL120034 and R01LM013327 to Columbia University; grant U10-HL119990 to Indiana University; grant U10-HL120006 to the University of Pittsburgh; grant U10-HL119992 to Northwestern University; grant U10-HL120019 to the University of California, Irvine; grant U10-HL119993 to University of Pennsylvania; and grant U10-HL120018 to the University of Utah. National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health to Clinical and Translational Science Institutes at Indiana University (grant UL1TR001108) and University of California, Irvine (grant UL1TR000153).

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Data Preparation of the nuMoM2b Dataset

Cited by 6 publications

References 2 publications

Racial/ethnic differences in pre-pregnancy conditions and adverse maternal outcomes in the nuMoM2b cohort: a population-based cohort study

Racial/ethnic differences in pre-pregnancy conditions and adverse maternal outcomes in the nuMoM2b cohort: a population-based cohort study

Diving into CDC pregnancy data in the United States: longitudinal study and interactive application

Genetic Polymorphisms Associated with Adverse Pregnancy Outcomes in Nulliparas

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