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Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK

Authors :
Christopher Yau
Catherine Nelson-Piercy
Krishnarajah Nirantharakumar
Richard D Riley
Anuradhaa Subramanian
Peter Brocklehurst
Sinead Brophy
Maria Loane
Helen Dolk
Shakila Thangaratinam
Muhammad Usman
Dermot O’Reilly
Jingya Wang
Colin McCowan
Louise Locock
Holly Hope
Francesca Crowe
Siang Ing Lee
Rachel Plachcinski
Utkarsh Agrawal
Amaya Azcoaga-Lorenzo
Gillian Santorelli
Beck Taylor
Mairead Black
Adeniyi Francis Fagbamigbe
Christine Damase-Michel
Ngawai Moss
Katherine Phillips
Kelly-Ann Eastwood
Astha Anand
Jonathan Ian Kennedy
Kathryn Mary Abel
Lisa Kent
Steven Wambua
Sharon McCann
Megha Singh
Mohamed Mhereeg
Neil Cockburn
Sudasing Pathirannehelage Buddhika Hemali Sudasinghe
Zoe Vowles
Charles Gadd
Stephanie Hanley
Natalia Hong
Source :
BMJ Open, Vol 13, Iss 2 (2023)
Publication Year :
2023
Publisher :
BMJ Publishing Group, 2023.

Abstract

Introduction One in five pregnant women has multiple pre-existing long-term conditions in the UK. Studies have shown that maternal multiple long-term conditions are associated with adverse outcomes. This observational study aims to compare maternal and child outcomes for pregnant women with multiple long-term conditions to those without multiple long-term conditions (0 or 1 long-term conditions).Methods and analysis Pregnant women aged 15–49 years old with a conception date between 2000 and 2019 in the UK will be included with follow-up till 2019. The data source will be routine health records from all four UK nations (Clinical Practice Research Datalink (England), Secure Anonymised Information Linkage (Wales), Scotland routine health records and Northern Ireland Maternity System) and the Born in Bradford birth cohort. The exposure of two or more pre-existing, long-term physical or mental health conditions will be defined from a list of health conditions predetermined by women and clinicians. The association of maternal multiple long-term conditions with (a) antenatal, (b) peripartum, (c) postnatal and long-term and (d) mental health outcomes, for both women and their children will be examined. Outcomes of interest will be guided by a core outcome set. Comparisons will be made between pregnant women with and without multiple long-term conditions using modified Poisson and Cox regression. Generalised estimating equation will account for the clustering effect of women who had more than one pregnancy episode. Where appropriate, multiple imputation with chained equation will be used for missing data. Federated analysis will be conducted for each dataset and results will be pooled using random-effects meta-analyses.Ethics and dissemination Approval has been obtained from the respective data sources in each UK nation. Study findings will be submitted for publications in peer-reviewed journals and presented at key conferences.

Subjects

Subjects :
Medicine

Details

Language :
English
ISSN :
20446055
Volume :
13
Issue :
2
Database :
Directory of Open Access Journals
Journal :
BMJ Open
Publication Type :
Academic Journal
Accession number :
edsdoj.9c21af0acc38474e8c74434ca4f9b4a9
Document Type :
article
Full Text :
https://doi.org/10.1136/bmjopen-2022-068718