Laura Jelliffe-Pawlowski

Faculty

Jelliffe-Pawlowski Headsot

Laura Jelliffe-Pawlowski

PhD MS

Florence S. and William H. Downs Professor in Nursing Research
Senior Associate Dean of Research

1 212 998 9020

433 First Ave
New York, NY 10010
United States

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.

PhD in Human Development, University of California Davis
MS in Child Development, University of California Davis
BA in Psychology, University of California Los Angeles
Preterm Birth
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 II
Governor Brown Appointee for the California Department of Public Health, Interagency Coordinating Council on Early Intervention

Association of maternal prenatal copper concentration with gestational duration and preterm birth : a multicountry meta-analysis

INTERBIO-21st Study Consortium, A., GARBH-Ini study team, A., Monangi, N. K., Xu, H., Fan, Y. M., Khanam, R., Khan, W., Deb, S., Pervin, J., Price, J. T., Kaur, L., Villar, J., McGready, R., Barros, F. C., Victora, C. G., Munim, S., Papageorgh, A. T., Ochieng, R., Craik, R., … Jelliffe-Pawlowski, L. (2024). In American Journal of Clinical Nutrition (Vols. 119, Issue 1, pp. 221-231). 10.1016/j.ajcnut.2023.10.011
Abstract
Abstract
Background: Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). Objectives: This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. Methods: Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. Results: The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. Conclusions: Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB.

Early Newborn Metabolic Patterning and Sudden Infant Death Syndrome

Oltman, S. P., Rogers, E. E., Baer, R. J., Amsalu, R., Bandoli, G., Chambers, C. D., Cho, H., Dagle, J. M., Karvonen, K. L., Kingsmore, S. F., McKenzie-Sampson, S., Momany, A., Ontiveros, E., Protopsaltis, L. D., Rand, L., Kobayashi, E. S., Steurer, M. A., Ryckman, K. K., & Jelliffe-Pawlowski, L. (2024). In JAMA Pediatrics (Vols. 178, Issues 11, pp. 1183-1191). 10.1001/jamapediatrics.2024.3033
Abstract
Abstract
Importance: Sudden infant death syndrome (SIDS) is a major cause of infant death in the US. Previous research suggests that inborn errors of metabolism may contribute to SIDS, yet the relationship between SIDS and biomarkers of metabolism remains unclear. Objective: To evaluate and model the association between routinely measured newborn metabolic markers and SIDS in combination with established risk factors for SIDS. Design, Setting, and Participants: This was a case-control study nested within a retrospective cohort using data from the California Office of Statewide Health Planning and Development and the California Department of Public Health. The study population included infants born in California between 2005 and 2011 with full metabolic data collected as part of routine newborn screening (NBS). SIDS cases were matched to controls at a ratio of 1:4 by gestational age and birth weight z score. Matched data were split into training (2/3) and testing (1/3) subsets. Data were analyzed from January 2005 to December 2011. Exposures: Metabolites measured by NBS and established risk factors for SIDS. Main Outcomes and Measures: The primary outcome was SIDS. Logistic regression was used to evaluate the association between metabolic markers combined with known risk factors and SIDS. Results: Of 2276578 eligible infants, 354 SIDS (0.016%) cases (mean [SD] gestational age, 38.3 [2.3] weeks; 220 male [62.1%]) and 1416 controls (mean [SD] gestational age, 38.3 [2.3] weeks; 723 male [51.1%]) were identified. In multivariable analysis, 14 NBS metabolites were significantly associated with SIDS in a univariate analysis: 17-hydroxyprogesterone, alanine, methionine, proline, tyrosine, valine, free carnitine, acetyl-L-carnitine, malonyl carnitine, glutarylcarnitine, lauroyl-L-carnitine, dodecenoylcarnitine, 3-hydroxytetradecanoylcarnitine, and linoleoylcarnitine. The area under the receiver operating characteristic curve for a 14-marker SIDS model, which included 8 metabolites, was 0.75 (95% CI, 0.72-0.79) in the training set and was 0.70 (95% CI, 0.65-0.76) in the test set. Of 32 infants in the test set with model-predicted probability greater than 0.5, a total of 20 (62.5%) had SIDS. These infants had 14.4 times the odds (95% CI, 6.0-34.5) of having SIDS compared with those with a model-predicted probability less than 0.1. Conclusions and Relevance: Results from this case-control study showed an association between aberrant metabolic analytes at birth and SIDS. These findings suggest that we may be able to identify infants at increased risk for SIDS soon after birth, which could inform further mechanistic research and clinical efforts focused on monitoring and prevention.

Impact of being underweight before pregnancy on preterm birth by race/ethnicity and insurance status in California : an analysis of birth records

Diamond-Smith, N., Baer, R. J., & Jelliffe-Pawlowski, L. (2024). In Journal of Maternal-Fetal and Neonatal Medicine (Vols. 37, Issue 1). 10.1080/14767058.2024.2321486
Abstract
Abstract
Background: The US still has a high burden of preterm birth (PTB), with important disparities by race/ethnicity and poverty status. There is a large body of literature looking at the impact of pre-pregnancy obesity on PTB, but fewer studies have explored the association between underweight status on PTB, especially with a lens toward health disparities. Furthermore, little is known about how weight, specifically pre-pregnancy underweight status, and socio-economic-demographic factors such as race/ethnicity and insurance status, interact with each other to contribute to risks of PTB. Objectives: The objective of this study was to measure the association between pre-pregnancy underweight and PTB and small for gestational age (SGA) among a large sample of births in the US. Our secondary objective was to see if underweight status and two markers of health disparities–race/ethnicity and insurance status (public vs. other)–on PTB. Study design: We used data from all births in California from 2011 to 2017, which resulted in 3,070,241 singleton births with linked hospital discharge records. We ran regression models to estimate the relative risk of PTB by underweight status, by race/ethnicity, and by poverty (Medi-cal status). We then looked at the interaction between underweight status and race/ethnicity and underweight and poverty on PTB. Results: Black and Asian women were more likely to be underweight (aRR = 1.0, 95% CI: 1.01, 1.1 and aRR = 1.4, 95% CI: 1.4, 1.5, respectively), and Latina women were less likely to be underweight (aRR = 0.7, 95% CI: 0.7, 0.7). Being underweight was associated with increased odds of PTB (aRR = 1.3, 95% CI 1.3–1.3) and, after controlling for underweight, all nonwhite race/ethnic groups had increased odds of PTB compared to white women. In interaction models, the combined effect of being both underweight and Black, Indigenous and People of Color (BIPOC) statistically significantly reduced the relative risk of PTB (aRR = 0.9, 95% CI: 0.8, 0.9) and SGA (aRR = 1.0, 95% CI: 0.9, 1.0). The combined effect of being both underweight and on public insurance increased the relative risk of PTB (aRR = 1.1, 95% CI: 1.1, 1.2) but there was no additional effect of being both underweight and on public insurance on SGA (aRR = 1.0, 95% CI: 1.0, 1.0). Conclusions: We confirm and build upon previous findings that being underweight preconception is associated with increased risk of PTB and SGA–a fact often overlooked in the focus on overweight and adverse birth outcomes. Additionally, our findings suggest that the effect of being underweight on PTB and SGA differs by race/ethnicity and by insurance status, emphasizing that other factors related to inequities in access to health care and poverty are contributing to disparities in PTB.

Impact of being underweight before pregnancy on preterm birth by race/ethnicity and insurance status in California: an analysis of birth records

Jelliffe-Pawlowski, L., Diamond-Smith, N., Baer, R. J., & Jelliffe-Pawlowski, L. (2024). In The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians (Vols. 37, Issue 1, p. 2321486).
Abstract
Abstract
The US still has a high burden of preterm birth (PTB), with important disparities by race/ethnicity and poverty status. There is a large body of literature looking at the impact of pre-pregnancy obesity on PTB, but fewer studies have explored the association between underweight status on PTB, especially with a lens toward health disparities. Furthermore, little is known about how weight, specifically pre-pregnancy underweight status, and socio-economic-demographic factors such as race/ethnicity and insurance status, interact with each other to contribute to risks of PTB.

Longitudinal urine metabolic profiling and gestational age prediction in human pregnancy

Shen, X., Chen, S., Liang, L., Avina, M., Zackriah, H., Jelliffe-Pawlowski, L., Rand, L., & Snyder, M. P. (2024). In Briefings in Bioinformatics (Vols. 26, Issue 1). 10.1093/bib/bbaf059
Abstract
Abstract
Pregnancy is a vital period affecting both maternal and fetal health, with impacts on maternal metabolism, fetal growth, and long-term development. While the maternal metabolome undergoes significant changes during pregnancy, longitudinal shifts in maternal urine have been largely unexplored. In this study, we applied liquid chromatography-mass spectrometry-based untargeted metabolomics to analyze 346 maternal urine samples collected throughout pregnancy from 36 women with diverse backgrounds and clinical profiles. Key metabolite changes included glucocorticoids, lipids, and amino acid derivatives, indicating systematic pathway alterations. We also developed a machine learning model to accurately predict gestational age using urine metabolites, offering a non-invasive pregnancy dating method. Additionally, we demonstrated the ability of the urine metabolome to predict time-to-delivery, providing a complementary tool for prenatal care and delivery planning. This study highlights the clinical potential of urine untargeted metabolomics in obstetric care.

Longitudinal urine metabolic profiling and gestational age prediction in human pregnancy

Jelliffe-Pawlowski, L., Shen, X., Chen, S., Liang, L., Avina, M., Zackriah, H., Jelliffe-Pawlowski, L., Rand, L., & Snyder, M. P. (2024). In Briefings in bioinformatics (Vols. 26, Issue 1).
Abstract
Abstract
Pregnancy is a vital period affecting both maternal and fetal health, with impacts on maternal metabolism, fetal growth, and long-term development. While the maternal metabolome undergoes significant changes during pregnancy, longitudinal shifts in maternal urine have been largely unexplored. In this study, we applied liquid chromatography-mass spectrometry-based untargeted metabolomics to analyze 346 maternal urine samples collected throughout pregnancy from 36 women with diverse backgrounds and clinical profiles. Key metabolite changes included glucocorticoids, lipids, and amino acid derivatives, indicating systematic pathway alterations. We also developed a machine learning model to accurately predict gestational age using urine metabolites, offering a non-invasive pregnancy dating method. Additionally, we demonstrated the ability of the urine metabolome to predict time-to-delivery, providing a complementary tool for prenatal care and delivery planning. This study highlights the clinical potential of urine untargeted metabolomics in obstetric care.

Maternal Mental Health Diagnoses and Infant Emergency Department Use, Hospitalizations, and Death

Abe, N., Baer, R. J., Jelliffe-Pawlowski, L., Chambers, C. D., & Bandoli, G. (2024). In Academic Pediatrics (Vols. 24, Issues 3, pp. 451-460). 10.1016/j.acap.2023.11.021
Abstract
Abstract
Background: The period surrounding childbirth is a uniquely vulnerable time for women and their mental health. We sought to describe the association between maternal mental health diagnoses in the year prior and after birth and infant Emergency Department (ED) utilization, hospitalization, and death. Methods: We studied mothers who gave singleton live birth in California (2011–2017) and their infants using linked infant birth and death certificates and maternal and infant discharge records. Maternal mental health diagnoses in the year before and after birth were identified using International Classification of Diseases (ICD) codes. We abstracted infant ED visits, hospitalizations, discharge diagnoses, deaths, and causes of death. Log-linear regression was used to compare relative risks of infant outcomes between mothers with and without mental health diagnoses, adjusting for maternal variables. Results: Of the 3,067,069 mother-infant pairs, 85,047 (2.8%) mothers had at least one mental health diagnosis in the year before and after birth. Infants of mothers with mental health diagnoses were more likely to visit the ED (aRR 1.2, CI:1.1–1.2), have three or more ED visits (aRR 1.4, CI:1.3–1.4), be hospitalized (aRR 1.1, CI:1.04–1.1), and die (aRR 1.7, CI:1.6–1.8) in the first year of life. These infants were also more likely to be diagnosed with accidental injuries, nonaccidental trauma, and non-specific descriptive diagnosis (fussiness/fatigue/brief resolved unexplained event). Conclusion: This large administrative cohort study showed associations between maternal mental health diagnoses and infant acute ED visits, hospitalization, and death. This study underscores the urgent need to understand what is driving these findings and how to mitigate this risk.

Pregnancies complicated by bulimia nervosa are at increased risk of chorioamnionitis, anemia, and preterm birth

Baer, R. J., Bandoli, G., Jelliffe-Pawlowski, L., Rhee, K. E., & Chambers, C. D. (2024). In American Journal of Obstetrics and Gynecology (Vols. 231, Issues 2, pp. e57-e66). 10.1016/j.ajog.2024.03.006
Abstract
Abstract
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Racial and Ethnic Inequities in Therapeutic Hypothermia and Neonatal Hypoxic-Ischemic Encephalopathy: A Retrospective Cohort Study

Jelliffe-Pawlowski, L., Fall, C., Baer, R. J., Jelliffe-Pawlowski, L., Matoba, N., Lee, H. C., Chambers, C. D., & Bandoli, G. (2024). In The Journal of pediatrics (Vols. 269, p. 113966).
Abstract
Abstract
To investigate racial inequities in the use of therapeutic hypothermia (TH) and outcomes in infants with hypoxic-ischemic encephalopathy (HIE).

Racial and Ethnic Inequities in Therapeutic Hypothermia and Neonatal Hypoxic–Ischemic Encephalopathy : A Retrospective Cohort Study

Fall, C., Baer, R. J., Jelliffe-Pawlowski, L., Matoba, N., Lee, H. C., Chambers, C. D., & Bandoli, G. (2024). In Journal of Pediatrics (Vols. 269). 10.1016/j.jpeds.2024.113966
Abstract
Abstract
Objective: To investigate racial inequities in the use of therapeutic hypothermia (TH) and outcomes in infants with hypoxic–ischemic encephalopathy (HIE). Study design: We queried an administrative birth cohort of mother–baby pairs in California from 2010 through 2019 using International Classification of Diseases codes to evaluate the association between race and ethnicity and the application of TH in infants with HIE. We identified 4779 infants with HIE. Log-linear regression was used to calculate risk ratios (RR) for TH, adjusting for hospital transfer, rural location, gestational age between 35 and 37 weeks, and HIE severity. Risk of adverse infant outcome was calculated by race and ethnicity and stratified by TH. Results: From our identified cohort, 1338 (28.0%) neonates underwent TH. White infants were used as the reference sample, and 410 (28.4%) received TH. Black infants were significantly less likely to receive TH with 74 (20.0%) with an adjusted risk ratio (aRR) of 0.7 (95% CI 0.5-0.9). Black infants with any HIE who did not receive TH were more likely to have a hospital readmission (aRR 1.36, 95% CI 1.10-1.68) and a tracheostomy (aRR 3.07, 95% CI 1.19-7.97). Black infants with moderate/severe HIE who did not receive TH were more likely to have cerebral palsy (aRR 2.72, 95% CI 1.07-6.91). Conclusions: In this study cohort, Black infants with HIE were significantly less likely to receive TH. Black infants also had significantly increased risk of some adverse outcomes of HIE. Possible reasons for this inequity include systemic barriers to care and systemic bias.