Multimorbidity is when a person has two or more long-term health problems. It can be difficult for people with multimorbidity to manage their conditions. They may have to coordinate appointments with different specialists and their medications need to be managed carefully.
Multimorbidity is becoming more common in pregnancy. However, we don't understand why this is and what the consequences are for the pregnancy, the birth of the baby and the mother and babys long-term health. If we understand what makes a pregnant woman more likely to have multimorbidity, we can find ways to prevent it and design health services tailored to their specific needs.
We will look at electronic health records to find out how many pregnant women have multimorbidity and what illnesses they have. We will examine if factors such as age, weight or social background influence whether a pregnant woman has multimorbidity. We will also examine which illnesses group together (cluster) and which clusters are most common. We will then compare what happens to mother (and child) with/without multimorbidity, such as pregnancy complications and development of medical conditions. To begin with, we will focus on preterm birth as an outcome. We will also examine whether long-term health conditions and pregnancy complications are well recorded in general practice and hospital electronic health records.
To understand how medications affect the health of the mother and the baby during pregnancy, we will examine which medications / common combinations of medications women take during different time points of the pregnancy. This knowledge will help doctors prescribe safely during pregnancy.
The aim of the study is to understand how multimorbidity affects pregnancy. We will describe the epidemiology of pre-existing multimorbidity in pregnancy, multimorbidity clusters, prescription pattern in pregnancy, investigate the association of multimorbidity with adverse outcomes and validate the recording of maternal morbidities and pregnancy complications in primary and secondary care database.
This will be a retrospective cohort study of women with recorded pregnancies between 2000 to 2020 in the CPRD Pregnancy Register. The exposure will be multimorbidity. A list of >90 exposure morbidities were determined through the literature and through a stakeholder workshop. Example disease categories include cardiovascular disease (hypertension, atrial fibrillation, etc), cancer, mental health condition (anxiety, depression, etc), respiratory disease (asthma, pulmonary fibrosis, etc), gastrointestinal disease (inflammatory bowel disease etc) and endocrine disease (diabetes mellitus etc).
The proportion of pregnancies affected by this predefined list of morbidities will be estimated. Determinants of multimorbidity status and clusters will be investigated through subgroup descriptive analysis. Latent class analysis, Multiple Correspondence Analysis and Deep Learning methodologies will be performed to examine morbidity clusters, the sequence in which pre-existing long-term conditions accumulate, and predict future risks.
Descriptive analysis will also be performed for prescription records for drugs catalogued by BNF chapters. This will be stratified by the different time point in the pregnancy. The association of multimorbidity with outcomes will be investigated using logistic and cox regression. Generalised Estimating Equations will be used to account for clustering where a woman has more than one pregnancy.
Validation of maternal morbidities and pregnancy complications recording in primary (CPRD) and secondary care database (HES) will be conducted using capture and recapture methods and comparison with previous literature. Pregnancy complications to be studied will be prioritised with stakeholders, examples will include still birth, preterm birth, pre-eclampsia and post-partum haemorrhage.
(1) Proportion of pregnancies affected by defined morbidities, multimorbidity and multimorbidity clusters
(2) Multimorbidity and sequence clustering of pre-existing long-term conditions in pregnant women
(3) Proportion of pregnancies with records of prescriptions at different timepoints of the pregnancy
(4) Odds of pregnancies with pre-existing multimorbidity resulting in pregnancy complications, post-partum complications or long-term adverse health outcomes for mother/child as follow:
i. preterm birth
ii. Mortality & pregnancy loss:
- maternal mortality (death up to 6 weeks, and 1 year, after childbirth or end of pregnancy);
- neonatal mortality (death within 28 days of birth);
- stillbirth / late fetal loss (baby born without signs of life);
- miscarriage
iii. Metabolic complications:
- gestational diabetes
- hypertensive disorder of pregnancy: gestational hypertension, pre-eclampsia, eclampsia, HELLP syndrome
iv. neurodevelopmental disorder of the offspring
v. postnatal depression, puerperal psychosis
These outcomes have been identified to be important by our women representatives and specialists in maternal medicine, obstetrics and perinatal mental health in the study team. These outcomes were also amongst those that have been listed as core outcome measures in pregnancy and maternity care 11 13. Although current literature supports the association with these outcomes when single chronic conditions are present for the pregnant women, we are less clear of their association with multimorbidity;6 21-23 we anticipate the effect size to be higher. The latest UK national maternal mortality review, MBBRACE, has noted that 90% of maternal death within a year occurred in women with multiple health / social problems 15.
Quantifying outcomes associated with pregnancy affected by multimorbidity will provide information to help pregnant women with multimorbidity and clinicians make informed decisions in pregnancy planning, as well as add weight to calls to tailor the maternity care pathway for pregnant women with multimorbidity.
Krishnarajah Nirantharakumar - Chief Investigator - University of Birmingham
Siang Ing Lee - Corresponding Applicant - University of Birmingham
Anuradhaa Subramanian - Collaborator - University of Birmingham
Astha Anand - Collaborator - University of Birmingham
Charles Gadd - Collaborator - University of Birmingham
Holly Hope - Collaborator - University of Birmingham
Krishna Gokhale - Collaborator - University of Birmingham
Siang Ing Lee - Collaborator - University of Birmingham
Tom Taverner - Collaborator - University of Birmingham
CPRD Mother-Baby Link;HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation;Pregnancy Register