Increased postpartum anxiety symptoms after perinatal SARS-CoV-2 infection in a large, prospective pregnancy cohort in New York City.

COVID-19 pandemic Perinatal mental health Postpartum anxiety Postpartum depression Prenatal infection SARS-CoV-2

Journal

Journal of psychiatric research
ISSN: 1879-1379
Titre abrégé: J Psychiatr Res
Pays: England
ID NLM: 0376331

Informations de publication

Date de publication:
18 Dec 2023
Historique:
received: 23 06 2023
revised: 15 11 2023
accepted: 12 12 2023
medline: 22 12 2023
pubmed: 22 12 2023
entrez: 22 12 2023
Statut: aheadofprint

Résumé

Numerous studies reported an increase of postpartum mood symptoms during the COVID-19 pandemic. Yet, the link between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and perinatal mental health is less well understood. We investigated the associations between prenatal SARS-CoV-2 infection and postpartum depressive and anxiety symptoms, including examinations of infection timing and pandemic timeline. We included 595 participants from Generation C, a prospective pregnancy cohort in New York City (2020-2022). Prenatal SARS-CoV-2 infection was determined via laboratory or medical diagnosis. Depression and anxiety symptoms were measured 4-12 weeks postpartum using the Edinburgh Postnatal Depression Scale (EPDS) and Generalized Anxiety Disorder questionnaire (GAD), respectively. Quantile regressions were conducted with prenatal SARS-CoV-2 infection as exposure and continuously measured EPDS and GAD scores as outcomes. We reran the analyses in those with COVID-19-like symptoms in the trimester during which infection occurred. 120 (20.1%) participants had prenatal SARS-CoV-2 infection. After adjusting for socio-demographic, obstetric and other maternal health factors, prenatal SARS-CoV-2 infection was associated with higher median postpartum anxiety scores (b = 0.55, 95% CI = 0.15; 0.96). Late gestation infection (b = 1.15, 95% CI = 0.22; 2.09) and symptomatic infection (b = 1.15, 95% CI = 0.12; 2.18) were also associated with higher median postpartum anxiety scores. No associations were found with depressive symptoms. The associations were not moderated by time since the start of the pandemic. This study suggests that prenatal SARS-CoV-2 infection increases the risk of postpartum anxiety symptoms among participants reporting median anxiety symptoms. Given that this association was not affected by pandemic timing and that SARS-CoV-2 transmission continues, individuals infected with SARS-CoV-2 during pregnancy should be monitored for postpartum anxiety symptoms.

Identifiants

pubmed: 38134722
pii: S0022-3956(23)00584-8
doi: 10.1016/j.jpsychires.2023.12.020
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

130-137

Informations de copyright

Copyright © 2023. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

Declaration of competing interest The Icahn School of Medicine at Mount Sinai has filed patent applications relating to SARS-CoV-2 serological assays and NDV-based SARS-CoV-2 vaccines which list Florian Krammer as co-inventor. Mount Sinai has spun out a company, Kantaro, to market serological tests for SARS-CoV-2. Florian Krammer has consulted for Merck and Pfizer (before 2020), and is currently consulting for Pfizer, Seqirus, 3rd Rock Ventures and Avimex and he is a co-founder and scientific advisory board member of CastleVax. The Krammer laboratory is also collaborating with Pfizer on animal models of SARS-CoV-2. M. Mercedes Perez-Rodriguez has received consulting fees from Alkermes, Inc and Neurocrine Biosciences, for work unrelated to this manuscript. The other authors have nothing to report.

Auteurs

Juliana Castro (J)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: Juliana.CamachoCastro@mssm.edu.

Frederieke A J Gigase (FAJ)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands. Electronic address: f.gigase@erasmusmc.nl.

Nina M Molenaar (NM)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Department of Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands. Electronic address: ninamolenaar@gmail.com.

Erona Ibroçi (E)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: eronaibr@gmail.com.

M Mercedes Perez-Rodriguez (MM)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: mercedes.perez@mssm.edu.

Whitney Lieb (W)

Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Blavatnik Family Women's Health Research Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: whitney.lieb@mssm.edu.

Teresa Janevic (T)

Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: teresa.janevic@mountsinai.org.

Lot D de Witte (LD)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: lotje.dewitte@mssm.edu.

Veerle Bergink (V)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City, NY, USA; Department of Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands. Electronic address: veerle.bergink@mssm.edu.

Anna-Sophie Rommel (AS)

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA. Electronic address: anna.rommel@mssm.edu.

Classifications MeSH