Gestational weight gain and neonatal biometry during the COVID-19 Pandemic

Authors

Mahmoud Abdelwahab, West Virginia University, Morgantown, United States.
Jessica de Voest, The George Washington University Biostatistics Center, Rockville, United States.
Torri Metz, University of Utah Health Sciences Center, Salt Lake City, United States.
Brenna Hughes, Duke University Hospital, Durham, United States.
William A. Grobman, Obstetrics and Gynecology, The Ohio State University Wexner Medical Center, Columbus, United States.
George Saade, OB-GYN, EVMS, Norfolk, United States.
Tracy Manuck, The University of North Carolina at Chapel Hill, Chapel Hill, United States.
Monica Longo
Hyagriv Simhan, Ob/Gyn, University of Pittsburgh School of Medicine, Pittsburgh, United States.
Dwight J. Rouse, Brown University, Providence, United States.
Hector Mendez-Figueroa, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Texas McGovern Medical School, Houston, United States.
Cynthia Gyamfi-Bannerman, University of San Diego, San Diego, United States.
Jennifer Bailit, MetroHealth Medical Center, Cleveland, United States.
Maged M. Costantine, Maternal-Fetal Medicine, Ohio State University Wexner Medical Center, Columbus, United States.
Harish Sehdev, Obstetrics and Gynecology, Pennsylvania Hospital, Philadelphia, United States.
Alan Tita, Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, United States.

Document Type

Journal Article

Publication Date

5-29-2024

Journal

American journal of perinatology

DOI

10.1055/a-2335-2480

Abstract

OBJECTIVE: To assess whether being pregnant and delivering during the COVID-19 pandemic was associated with changes in gestational weight gain (GWG) or frequency of small- (SGA) or large-for-gestational-age (LGA) neonates. STUDY DESIGN: Secondary analysis of a multicenter observational cohort comparing pregnant people who delivered during the COVID-19 pandemic (June-December 2020) to people who delivered prior to the pandemic (March-December 2019). Those with multiple gestations, fetuses with major congenital anomalies, implausible GWG values, unavailable body mass index (BMI), or who were SARS-CoV-2 positive were excluded. The primary outcome was frequency of optimal recommended GWG based on pre-pregnancy BMI. Neonatal outcomes included birthweight, ponderal index, and frequency of SGA, LGA and small head circumference for livebirths. Multivariable regression analysis was used to assess associations between exposure to the pandemic and outcomes. RESULTS: The 4,225 pregnant people exposed to the pandemic were older and more likely to have gestational diabetes compared with the 6,492 people who delivered prior to the COVID-19 pandemic. The frequency of appropriate GWG was 28.0% during the pandemic and 27.6% before the pandemic (aOR 1.02, 95% CI 0.93-1.11). Excessive GWG was more likely (aOR 1.08, 95% CI 1.001-1.17) and inadequate GWG was less likely during the pandemic (aOR 0.86, 95% CI 0.77-0.95). The frequency of SGA was 5.4% during the pandemic and 6.1% before the pandemic (aOR 0.90, 95% CI 0.76-1.06), and the frequency of LGA was 16.0% during the pandemic vs 15.0% before the pandemic (aOR 1.06, 95% CI 0.95-1.18). Other neonatal outcomes including birthweight percentile (62.1 vs 60.2), ponderal index (2.6 g/cm3 in both groups), and small head circumference for livebirths (8.2% vs 8.1%) were similar between groups as well. CONCLUSION: Being pregnant and delivering during the COVID-19 pandemic was associated with a higher likelihood of excessive GWG and a lower likelihood of inadequate GWG.

APA Citation

Abdelwahab, Mahmoud; de Voest, Jessica; Metz, Torri; Hughes, Brenna; Grobman, William A.; Saade, George; Manuck, Tracy; Longo, Monica; Simhan, Hyagriv; Rouse, Dwight J.; Mendez-Figueroa, Hector; Gyamfi-Bannerman, Cynthia; Bailit, Jennifer; Costantine, Maged M.; Sehdev, Harish; and Tita, Alan, "Gestational weight gain and neonatal biometry during the COVID-19 Pandemic" (2024). GW Authored Works. Paper 4872.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/4872

Department

Biostatistics and Bioinformatics