Lee Siang Ing, Hope Holly, O'Reilly Dermot, Kent Lisa, Santorelli Gillian, Subramanian Anuradhaa, Moss Ngawai, Azcoaga-Lorenzo Amaya, Fagbamigbe Adeniyi Francis, Nelson-Piercy Catherine, Yau Christopher, McCowan Colin, Kennedy Jonathan Ian, Phillips Katherine, Singh Megha, Mhereeg Mohamed, Cockburn Neil, Brocklehurst Peter, Plachcinski Rachel, Riley Richard D, Thangaratinam Shakila, Brophy Sinead, Hemali Sudasinghe Sudasing Pathirannehelage Buddhika, Agrawal Utkarsh, Vowles Zoe, Abel Kathryn Mary, Nirantharakumar Krishnarajah, Black Mairead, Eastwood Kelly-Ann
Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Centre for Women's Mental Health, Faculty of Biology Medicine & Health, The University of Manchester, Manchester, UK.
BMJ Open. 2023 Feb 24;13(2):e068718. doi: 10.1136/bmjopen-2022-068718.
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).
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.
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.
在英国，五分之一的孕妇患有多种既往长期疾病。研究表明，孕产妇的多种长期疾病与不良结局相关。这项观察性研究旨在比较患有多种长期疾病的孕妇与未患有多种长期疾病（0种或1种长期疾病）的孕妇的母婴结局。
纳入2000年至2019年在英国受孕、年龄在15至49岁之间的孕妇，并随访至2019年。数据来源将是英国四个地区的常规健康记录（英格兰的临床实践研究数据链、威尔士的安全匿名信息链接、苏格兰的常规健康记录以及北爱尔兰的产妇系统）以及布拉德福德出生队列。两种或更多种既往存在的长期身体或心理健康状况的暴露将根据由女性和临床医生预先确定的健康状况列表来定义。将研究孕产妇的多种长期疾病与（a）产前、（b）围产期、（c）产后及长期以及（d）女性及其子女的心理健康结局之间的关联。感兴趣的结局将由一个核心结局集来指导。使用修正的泊松回归和Cox回归对患有和未患有多种长期疾病的孕妇进行比较。广义估计方程将考虑有不止一次怀孕经历的女性的聚类效应。在适当的情况下，将使用链式方程多重插补法处理缺失数据。将对每个数据集进行联合分析，并使用随机效应荟萃分析汇总结果。
已获得英国每个地区各自数据源的批准。研究结果将提交至同行评审期刊发表，并在重要会议上展示。
