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

Siang Ing Lee; Holly Hope; Dermot O'Reilly; Lisa Kent; Gillian Santorelli; Anuradhaa Subramanian; Ngawai Moss; Amaya Azcoaga-Lorenzo; Adeniyi Francis Fagbamigbe; Catherine Nelson-Piercy; Christopher Yau; Colin McCowan; Jonathan Ian Kennedy; Katherine Phillips; Megha Singh; Mohamed Mhereeg; Neil Cockburn; Peter Brocklehurst; Rachel Plachcinski; Richard D Riley; Shakila Thangaratinam; Sinead Brophy; Sudasing Pathirannehelage Buddhika Hemali Sudasinghe; Utkarsh Agrawal; Zoe Vowles; Kathryn Mary Abel; Krishnarajah Nirantharakumar; Mairead Black; Kelly-Ann Eastwood; MuM-PreDiCT

doi:10.1136/bmjopen-2022-068718

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

Siang Ing Lee, Holly Hope, Dermot O'Reilly, Lisa Kent, Gillian Santorelli, Anuradhaa Subramanian, Ngawai Moss, Amaya Azcoaga-Lorenzo, Adeniyi Francis Fagbamigbe, Catherine Nelson-Piercy, Christopher Yau, Colin McCowan, Jonathan Ian Kennedy, Katherine Phillips, Megha Singh, Mohamed Mhereeg, Neil Cockburn, Peter Brocklehurst, Rachel Plachcinski, Richard D RileyShakila Thangaratinam, Sinead Brophy, Sudasing Pathirannehelage Buddhika Hemali Sudasinghe, Utkarsh Agrawal, Zoe Vowles, Kathryn Mary Abel, Krishnarajah Nirantharakumar, Mairead Black, Kelly-Ann Eastwood, MuM-PreDiCT

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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.

Original language	English
Article number	e068718
Journal	BMJ Open
Volume	13
Issue number	2
DOIs	https://doi.org/10.1136/bmjopen-2022-068718
Publication status	Published - 24 Feb 2023

Bibliographical note

Keywords

Female
Pregnancy
Child
Humans
Adolescent
Young Adult
Adult
Middle Aged
Pregnant Women
Scotland
England
Mental Disorders
Wales
Observational Studies as Topic

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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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
Copyright 2023 the authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Final published version, 1.14 MBLicence: CC BY

Cite this

Lee, S. I., Hope, H., O'Reilly, D., Kent, L., Santorelli, G., Subramanian, A., Moss, N., Azcoaga-Lorenzo, A., Fagbamigbe, A. F., Nelson-Piercy, C., Yau, C., McCowan, C., Kennedy, J. I., Phillips, K., Singh, M., Mhereeg, M., Cockburn, N., Brocklehurst, P., Plachcinski, R., ... MuM-PreDiCT (2023). Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK. BMJ Open, 13(2), Article e068718. https://doi.org/10.1136/bmjopen-2022-068718

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

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.",

keywords = "Female, Pregnancy, Child, Humans, Adolescent, Young Adult, Adult, Middle Aged, Pregnant Women, Scotland, England, Mental Disorders, Wales, Observational Studies as Topic",

author = "Lee, {Siang Ing} and Holly Hope and Dermot O'Reilly and Lisa Kent and Gillian Santorelli and Anuradhaa Subramanian and Ngawai Moss and Amaya Azcoaga-Lorenzo and Fagbamigbe, {Adeniyi Francis} and Catherine Nelson-Piercy and Christopher Yau and Colin McCowan and Kennedy, {Jonathan Ian} and Katherine Phillips and Megha Singh and Mohamed Mhereeg and Neil Cockburn and Peter Brocklehurst and Rachel Plachcinski and Riley, {Richard D} and Shakila Thangaratinam and Sinead Brophy and {Hemali Sudasinghe}, {Sudasing Pathirannehelage Buddhika} and Utkarsh Agrawal and Zoe Vowles and Abel, {Kathryn Mary} and Krishnarajah Nirantharakumar and Mairead Black and Kelly-Ann Eastwood and MuM-PreDiCT",

note = "{\textcopyright} Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.",

year = "2023",

month = feb,

day = "24",

doi = "10.1136/bmjopen-2022-068718",

language = "English",

volume = "13",

journal = "BMJ Open",

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Lee, SI, Hope, H, O'Reilly, D, Kent, L, Santorelli, G, Subramanian, A, Moss, N, Azcoaga-Lorenzo, A, Fagbamigbe, AF, Nelson-Piercy, C, Yau, C, McCowan, C, Kennedy, JI, Phillips, K, Singh, M, Mhereeg, M, Cockburn, N, Brocklehurst, P, Plachcinski, R, Riley, RD, Thangaratinam, S, Brophy, S, Hemali Sudasinghe, SPB, Agrawal, U, Vowles, Z, Abel, KM, Nirantharakumar, K, Black, M, Eastwood, K-A & MuM-PreDiCT 2023, 'Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK', BMJ Open, vol. 13, no. 2, e068718. https://doi.org/10.1136/bmjopen-2022-068718

TY - JOUR

T1 - Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK

AU - Lee, Siang Ing

AU - Hope, Holly

AU - O'Reilly, Dermot

AU - Kent, Lisa

AU - Santorelli, Gillian

AU - Subramanian, Anuradhaa

AU - Moss, Ngawai

AU - Azcoaga-Lorenzo, Amaya

AU - Fagbamigbe, Adeniyi Francis

AU - Nelson-Piercy, Catherine

AU - Yau, Christopher

AU - McCowan, Colin

AU - Kennedy, Jonathan Ian

AU - Phillips, Katherine

AU - Singh, Megha

AU - Mhereeg, Mohamed

AU - Cockburn, Neil

AU - Brocklehurst, Peter

AU - Plachcinski, Rachel

AU - Riley, Richard D

AU - Thangaratinam, Shakila

AU - Brophy, Sinead

AU - Hemali Sudasinghe, Sudasing Pathirannehelage Buddhika

AU - Agrawal, Utkarsh

AU - Vowles, Zoe

AU - Abel, Kathryn Mary

AU - Nirantharakumar, Krishnarajah

AU - Black, Mairead

AU - Eastwood, Kelly-Ann

AU - MuM-PreDiCT

PY - 2023/2/24

Y1 - 2023/2/24

N2 - 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.

AB - 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.

KW - Female

KW - Pregnancy

KW - Child

KW - Humans

KW - Adolescent

KW - Young Adult

KW - Adult

KW - Middle Aged

KW - Pregnant Women

KW - Scotland

KW - England

KW - Mental Disorders

KW - Wales

KW - Observational Studies as Topic

U2 - 10.1136/bmjopen-2022-068718

DO - 10.1136/bmjopen-2022-068718

M3 - Article

C2 - 36828655

SN - 2044-6055

VL - 13

JO - BMJ Open

JF - BMJ Open

IS - 2

M1 - e068718

ER -

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

Abstract

Bibliographical note

Keywords

UN SDGs

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Cite this