Laura Jelliffe-Pawlowski
PhD MS
laura.jelliffe.pawlowski@nyu.edu 1 212 998 9020433 First Ave
New York, NY 10010
United States
Laura Jelliffe-Pawlowski's additional information
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Laura Jelliffe-Pawlowski, PhD, MS, is a Professor at NYU Rory Meyers College of Nursing. Prof. Jelliffe-Pawlowski’s research interests focus on understanding and addressing the drivers and consequences of adverse pregnancy outcomes with a special emphasis on preterm birth and associated racial/ethnic and socioeconomic inequities. Her work is highly transdisciplinary and looks at the interplay of biomolecular, social, and policy factors in observed patterns and outcomes. Her teaching and mentorship activities reflect this transdisciplinary approach with an emphasis on motivating the translation of research findings into action.
Jelliffe-Pawlowski leads a number of statewide, national, and international research efforts funded by the National Institutes of Health, the Bill and Melinda Gates Foundation, the March of Dimes, the State of California, and other entities. These includes, notably, the “Healthy Outcomes of Pregnancy for Everyone (HOPE)” consortium and study which focuses on understanding the experience of pregnant people and their infants pre- and post-COVID 19 pandemic. HOPE examines how biomolecular, social, and community factors affect the well-being and outcomes of mothers and infants and includes enrollment during pregnancy with outcome follow-up to 18-months after birth. Other ongoing projects include, for example, the NIH funded “Prediction Of Maturity, Morbidity, and Mortality in PreTerm Infants (PROMPT)”, study which focuses on examining the metabolic profiles of newborns with early preterm birth and associated outcomes, the “Transforming Health and Reducing PerInatal Anxiety through Virtual Engagement (THRIVE)”, randomized control trial (RCT), funded by the State of California which examines whether digital cognitive behavior therapy delivered by mobile app can assist in reducing anxiety symptoms in pregnant people and also examines participant acceptability of the application. Ongoing efforts also include leading the “California Prediction of Poor Outcomes of Pregnancy (CPPOP)” cohort study which focuses on investigating multi-omic drivers of preterm birth. The study interrogates biomolecular signals associated with preterm birth and includes full genome sequencing and mid-pregnancy biomolecular signaling related to metabolic, immune, stress, and placental function in hundreds of pregnancies with and without preterm birth.
Prior to her joining NYU Rory Meyers College of Nursing, Jelliffe-Pawlowski was a Professor of Epidemiology & Biostatistics, Chief of the Division of Lifecourse Epidemiology, a Professor in the Institute of Global Health Sciences, and Director of Discovery and Precision Health for the UCSF California Preterm Birth Initiative in the University of California San Francisco (UCSF) School of Medicine. She has a lifetime appointment as an Emeritus Professor of Epidemiology & Biostatistics in the UCSF School of Medicine and continues to work closely with the new Center for Birth Equity at UCSF. Prior to her appointment at UCSF, she was a leader at the Genetic Disease Screening Program within the California Department of Public Health.
Jelliffe-Pawlowski efforts have been highlighted in numerous academic and lay articles including in the New York Times, in WIRED Magazine, in the Atlantic, on CNN, and on MSNBC. In 2023, she was recognized by Forbes Magazine as one of the top 50 over 50 Innovators in the United States. She is also a Phase I and Phase II Bill and Melinda Gates Foundation Grand Challenges awardee for her work in the United States and Uganda which focused on the development and validation of newborn metabolic profile as a novel measure of gestational age in infants.
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PhD in Human Development, University of California DavisMS in Child Development, University of California DavisBA in Psychology, University of California Los Angeles
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Preterm Birth
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Faculty Honors Awards
Forbes 50 over 50 awardee in Innovation (2023)Delegate, African Academy of Sciences (2016)Awardee, Bill and Melinda Bates Foundation, Gates Grand Challenges Phase I and IIGovernor Brown Appointee for the California Department of Public Health, Interagency Coordinating Council on Early Intervention -
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Publications
Mediation of Adverse Pregnancy Outcomes in Autoimmune Conditions by Pregnancy Complications : A Mediation Analysis of Autoimmune Conditions and Adverse Pregnancy Outcomes
AbstractBandoli, G., Singh, N., Strouse, J., Baer, R. J., Donovan, B. M., Feuer, S. K., Nidey, N., Ryckman, K. K., Jelliffe-Pawlowski, L., & Chambers, C. D. (2020). In Arthritis and Rheumatism (Vols. 72, Issues 2, pp. 256-264). 10.1002/acr.24037AbstractObjective: Autoimmune conditions are associated with an increased risk of adverse pregnancy complications and outcomes, suggesting that pregnancy complications may mediate the excess risk. We performed a causal mediation analysis to quantify the mediated effects of autoimmune conditions on adverse pregnancy outcomes. Methods: We queried a California birth cohort created from linked birth certificates and hospital discharge summaries. From 2,963,888 births, we identified women with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), psoriasis, and inflammatory bowel disease (IBD). Pregnancy complications included preeclampsia/hypertension, gestational diabetes mellitus, and infection in pregnancy. Adverse pregnancy outcomes were preterm birth, cesarean delivery, and small for gestational age. We performed a mediation analysis to estimate the total effects of each autoimmune condition and adverse pregnancy outcome and the indirect effects through pregnancy complications. Results: All 4 autoimmune conditions were associated with preterm birth and cesarean delivery, and RA, SLE, and IBD were associated with offspring that were small for gestational age. The strongest mediator of RA, SLE, and psoriasis was preeclampsia/hypertension, accounting for 20–33% of the excess risk of preterm births and 10–19% of excess cesarean deliveries. Gestational diabetes mellitus and infections generally mediatedPreterm birth and nativity among Black women with gestational diabetes in California, 2013-2017 : A population-based retrospective cohort study
AbstractScott, K. A., Chambers, B. D., Baer, R. J., Ryckman, K. K., McLemore, M. R., & Jelliffe-Pawlowski, L. (2020). In BMC Pregnancy and Childbirth (Vols. 20, Issue 1). 10.1186/s12884-020-03290-3AbstractBackground: Despite the disproportionate prevalence of gestational diabetes (GDM) and preterm birth (PTB) and their associated adverse perinatal outcomes among Black women, little is known about PTB among Black women with GDM. Specifically, the relationship between PTB by subtype (defined as indicated PTB and spontaneous PT labor) and severity, GDM, and nativity has not been well characterized. Here we examine the risk of PTB by severity (early < 34 weeks, late 34 to 36 weeks) and early term birth (37 to 38 weeks) by nativity among Black women with GDM in California. Methods: This retrospective cohort study used linked birth certificate and hospital discharge data for 8609 of the 100,691 self-identifying non-Hispanic Black women with GDM who had a singleton live birth between 20 and 44 weeks gestation in California in 2013-2017. Adjusted odds ratios (aOR) and 95% confidence intervals (CIs) were examine risks for PTB, by severity and subtype, and early term birth using multivariate regression modeling. Results: Approximately, 83.9% of Black women with GDM were US-born and 16.1% were foreign-born. The overall prevalence of early PTB, late PTB, and early term birth was 3.8, 9.5, and 29.9%, respectively. Excluding history of prior PTB, preeclampsia was the greatest overall risk factor for early PTB (cOR = 6.7, 95%, CI 5.3 to 8.3), late PTB (cOR = 4.3, 95%, CI 3.8 to 5.0), and early term birth (cOR = 1.8, 95%, CI 1.6 to 2.0). There was no significant difference in the prevalence of PTB by subtypes and nativity (p = 0.5963). Overall, 14.2% of US-compared to 8.9% of foreign-born women had a PTB (early PTB: AOR = 0.56, 95%, CI 0.38 to 0.82; late PTB: AOR = 0.57, 95%, CI 0.45 to 0.73; early term birth: AOR = 0.67, 95%, CI 0.58 to 0.77). Conclusions: Foreign-born status remained protective of PTB, irrespective of severity and subtype. Preeclampsia, PTB, and GDM share pathophysiologic mechanisms suggesting a need to better understand differences in perinatal stress, chronic disease, and vascular dysfunction based on nativity in future epidemiologic studies and health services research.Replication of pre-pregnancy or first-trimester risk scoring to identify women at high risk of preterm birth
AbstractBaer, R. J., Jasper, E., Dagle, J., Ryckman, K. K., & Jelliffe-Pawlowski, L. (2020). In European Journal of Obstetrics and Gynecology and Reproductive Biology (Vols. 245, pp. 210-211). 10.1016/j.ejogrb.2019.11.034Abstract~The association of polymorphisms in circadian clock and lipid metabolism genes with 2nd trimester lipid levels and preterm birth
AbstractKovac, U., Jasper, E. A., Smith, C. J., Baer, R. J., Bedell, B., Donovan, B. M., Weathers, N., Zmrzljak, U. P., Jelliffe-Pawlowski, L., Rozman, D., & Ryckman, K. K. (2019). In Frontiers in Genetics (Vols. 10, Issue JUN). 10.3389/fgene.2019.00540AbstractDeregulation of the circadian system in humans and animals can lead to various adverse reproductive outcomes due to genetic mutations and environmental factors. In addition to the clock, lipid metabolism may also play an important role in influencing reproductive outcomes. Despite the importance of the circadian clock and lipid metabolism in regulating birth timing few studies have examined the relationship between circadian genetics with lipid levels during pregnancy and their relationship with preterm birth (PTB). In this study we aimed to determine if single nucleotide polymorphisms (SNPs) in genes from the circadian clock and lipid metabolism influence 2nd trimester maternal lipid levels and if this is associated with an increased risk for PTB. We genotyped 72 SNPs across 40 genes previously associated with various metabolic abnormalities on 930 women with 2nd trimester serum lipid measurements. SNPs were analyzed for their relationship to levels of total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL) and triglycerides (TG) using linear regression. SNPs were also evaluated for their relationship to PTB using logistic regression. Five SNPs in four genes met statistical significance after Bonferroni correction (p < 1.8 × 10-4) with one or more lipid levels. Of these, four SNPs were in lipid related metabolism genes: rs7412 in APOE with total cholesterol, HDL and LDL, rs646776 and rs599839 in CELSR2-PSRC1-SORT1 gene cluster with total cholesterol, HDL and LDL and rs738409 in PNPLA3 with HDL and TG and one was in a circadian clock gene: rs228669 in PER3 with TG. Of these SNPs only PER3 rs228669 was marginally associated with PTB (p = 0.02). In addition, PER3 rs228669 acts as an effect modifier on the relationship between TG and PTB.Association of Revised WIC Food Package with Perinatal and Birth Outcomes : A Quasi-Experimental Study
AbstractHamad, R., Collin, D. F., Baer, R. J., & Jelliffe-Pawlowski, L. (2019). In JAMA Pediatrics (Vols. 173, Issues 9, pp. 845-852). 10.1001/jamapediatrics.2019.1706AbstractImportance: The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) serves more than one-quarter of pregnant and postpartum women. In October 2009, the WIC food package underwent revisions to improve nutritional content. No studies have investigated the downstream effects of this revision on maternal and infant health. Objective: To investigate whether the revised WIC food package improved perinatal and birth outcomes among recipients. Design, Setting, and Participants: We conducted a quasi-experimental difference-in-differences analysis, comparing WIC recipients (the treatment group) before and after the package revisions while accounting for temporal trends among nonrecipients (the control group). Multivariable linear regressions were adjusted for sociodemographic covariates. This study was conducted using linked birth certificate and hospital discharge data from California from January 2007 to December 2012. Analysis began July 2018. Exposures: Whether pregnant women received the revised WIC package, which included more whole grains, fruit, vegetables, and low-fat milk. Main Outcomes and Measures: Measures of maternal and infant health, including maternal preeclampsia, gestational diabetes, and gestational weight gain as well as infant gestational age, birth weight, and hospitalizations. Results: The sample included 2897537 infants born to 2441658 mothers. WIC recipients were more likely to be Hispanic, less educated, of greater parity, and younger than nonrecipients. The revised WIC food package was associated with reductions in maternal preeclampsia (-0.6% points; 95% CI, -0.8 to -0.4) and more than recommended gestational weight gain (-3.2% points; 95% CI, -3.6 to -2.7), increased likelihood of as recommended (2.3% points; 95% CI, 1.8 to 2.8) and less than recommended (0.9% points; 95% CI, 0.5 to 1.2) gestational weight gain, and longer gestational age (0.2 weeks; 95% CI, 0.001 to 0.034). Among infants, an increased likelihood of birth weight that was appropriate for gestational age was observed (0.9% points; 95% CI, 0.5 to 1.3). Although birth weight itself was reduced (-0.009 SDs; 95% CI, -0.016 to -0.001), this was accompanied by reductions in small for gestational age (-0.4% points; 95% CI, -0.7 to -0.1), large for gestational age (-0.5% points; 95% CI, -0.8 to -0.2), and low-birth-weight infants (-0.2% points; 95% CI, -0.4 to -0.004), suggesting that the revised food package improved distributions of birth weight. Conclusions and Relevance: The revised WIC food package, intended to improve women's nutrition during pregnancy, was associated with beneficial impacts on maternal and child health. This suggests that WIC policy may be an important lever to reduce health disparities among high-risk women and children at a critical juncture in the life course.Associations between unstable housing, obstetric outcomes, and perinatal health care utilization
AbstractPantell, M. S., Baer, R. J., Torres, J. M., Felder, J. N., Gomez, A. M., Chambers, B. D., Dunn, J., Parikh, N. I., Pacheco-Werner, T., Rogers, E. E., Feuer, S. K., Ryckman, K. K., Novak, N. L., Tabb, K. M., Fuchs, J., Rand, L., & Jelliffe-Pawlowski, L. (2019). In American Journal of Obstetrics and Gynecology MFM (Vol. 1, Issues 4). 10.1016/j.ajogmf.2019.100053AbstractBackground: While there is a growing interest in addressing social determinants of health in clinical settings, there are limited data on the relationship between unstable housing and both obstetric outcomes and health care utilization. Objective: The objective of the study was to investigate the relationship between unstable housing, obstetric outcomes, and health care utilization after birth. Study Design: This was a retrospective cohort study. Data were drawn from a database of liveborn neonates linked to their mothers’ hospital discharge records (2007–2012) maintained by the California Office of Statewide Health Planning and Development. The analytic sample included singleton pregnancies with both maternal and infant data available, restricted to births between the gestational age of 20 and 44 weeks, who presented at a hospital that documented at least 1 woman as having unstable housing using the International Classification of Diseases, ninth edition, codes (n = 2,898,035). Infants with chromosomal abnormalities and major birth defects were excluded. Women with unstable housing (lack of housing or inadequate housing) were identified using International Classification of Diseases, ninth edition, codes from clinical records. Outcomes of interest included preterm birth (2 days; cesarean delivery, >4 days), emergency department visit within 3 months and 1 year after delivery, and readmission within 3 months and 1 year after delivery. We used exact propensity score matching without replacement to select a reference population to compare with the sample of women with unstable housing using a one-to-one ratio, matching for maternal age, race/ethnicity, parity, prior preterm birth, body mass index, tobacco use during pregnancy, drug/alcohol abuse during pregnancy, hypertension, diabetes, mental health condition during pregnancy, adequacy of prenatal care, education, and type of hospital. Odds of an adverse obstetric outcome were estimated using logistic regression. Results: Of 2794 women with unstable housing identified, 83.0% (n = 2318) had an exact propensity score–matched control. Women with an unstable housing code had higher odds of preterm birth (odds ratio, 1.2, 95% confidence interval, 1.0–1.4, P < .05), preterm labor (odds ratio, 1.4, 95% confidence interval, 1.2–1.6, P < .001), long length of stay (odds ratio, 1.6, 95% confidence interval, 1.4–1.8, P < .001), emergency department visits within 3 months (odds ratio, 2.4, 95% confidence interval, 2.1–2.8, P < .001) and 1 year after birth (odds ratio, 2.7, 95% confidence interval, 2.4–3.0, P < .001), and readmission within 3 months (odds ratio, 2.7, 95% confidence interval, 2.2–3.4, P < .0014) and 1 year after birth (odds ratio, 2.6, 95% confidence interval, 2.2–3.0, P < .001). Conclusion: Unstable housing documentation is associated with adverse obstetric outcomes and high health care utilization. Housing and supplemental income for pregnant women should be explored as a potential intervention to prevent preterm birth and prevent increased health care utilization.Combining newborn metabolic and DNA analysis for second-tier testing of methylmalonic acidemia
AbstractPeng, G., Shen, P., Gandotra, N., Le, A., Fung, E., Jelliffe-Pawlowski, L., Davis, R. W., Enns, G. M., Zhao, H., Cowan, T. M., & Scharfe, C. (2019). In Genetics in Medicine (Vols. 21, Issues 4, pp. 896-903). 10.1038/s41436-018-0272-5AbstractPurpose: Improved second-tier tools are needed to reduce false-positive outcomes in newborn screening (NBS) for inborn metabolic disorders on the Recommended Universal Screening Panel (RUSP). Methods: We designed an assay for multiplex sequencing of 72 metabolic genes (RUSPseq) from newborn dried blood spots. Analytical and clinical performance was evaluated in 60 screen-positive newborns for methylmalonic acidemia (MMA) reported by the California Department of Public Health NBS program. Additionally, we trained a Random Forest machine learning classifier on NBS data to improve prediction of true and false-positive MMA cases. Results: Of 28 MMA patients sequenced, we found two pathogenic or likely pathogenic (P/LP) variants in a MMA-related gene in 24 patients, and one pathogenic variant and a variant of unknown significance (VUS) in 1 patient. No such variant combinations were detected in MMA false positives and healthy controls. Random Forest–based analysis of the entire NBS metabolic profile correctly identified the MMA patients and reduced MMA false-positive cases by 51%. MMA screen-positive newborns were more likely of Hispanic ethnicity. Conclusion: Our two-pronged approach reduced false positives by half and provided a reportable molecular finding for 89% of MMA patients. Challenges remain in newborn metabolic screening and DNA variant interpretation in diverse multiethnic populations.Cross-Generational Contributors to Preterm Birth in California : Singletons Based on Race/Ethnicity
AbstractFrancois, L. N., Yang, J., Baer, R. J., Chung, P. J., Jelliffe-Pawlowski, L., & Coker, T. R. (2019). In American Journal of Perinatology (Vols. 36, Issues 4, pp. 383-392). 10.1055/s-0038-1668554AbstractObjective: Multiple studies have examined cross-generational patterns of preterm birth (PTB), yet results have been inconsistent and generally focused on primarily white populations. We examine the cross-generational PTB risk across racial/ethnic groups. Study Design Retrospective study of 388,474 grandmother-mother-infant triads with infants drawn from birth registry of singleton live births between 2005 and 2011 in California. Using logistic regression (odds ratios [ORs] and confidence intervals [CIs]), we examined the risk of preterm delivery by gestational age, sociodemographic, socioeconomic, and obstetric clinical characteristics stratified by maternal race/ethnicity. Results The risk of having a preterm infantDevelopment and validation of a clinical model for preconception and early pregnancy risk prediction of gestational diabetes mellitus in nulliparous women
AbstractDonovan, B. M., Breheny, P. J., Robinson, J. G., Baer, R. J., Saftlas, A. F., Bao, W., Greiner, A. L., Carter, K. D., Oltman, S. P., Rand, L., Jelliffe-Pawlowski, L., & Ryckman, K. K. (2019). In PloS one (Vols. 14, Issues 4). 10.1371/journal.pone.0215173AbstractImplementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007–2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009–2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman’s risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.An Evaluation of Sexually Transmitted Infection and Odds of Preterm or Early-Term Birth Using Propensity Score Matching
AbstractBaer, R. J., Chambers, C. D., Ryckman, K. K., Oltman, S. P., Rand, L., & Jelliffe-Pawlowski, L. (2019). In Sexually Transmitted Diseases (Vols. 46, Issues 6, pp. 389-394). 10.1097/OLQ.0000000000000985AbstractFew studies have examined the relationship between sexually transmitted infections (STIs) and preterm birth ( -
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