A large UK study has found that pregnant women living with two or more pre-existing long-term physical or mental health conditions face substantially higher risks of serious complications, including miscarriage, venous thromboembolism, pre-eclampsia, severe nausea and vomiting, gestational diabetes, and antenatal anxiety and depression. The research, co-led by King’s College London and published in The Lancet Public Health, suggests that the combined burden of multiple conditions is an important pregnancy risk factor in its own right. The findings challenge a maternity-care system that has traditionally been organised around individual diagnoses rather than the overlapping physical and psychological needs of the same patient.
Researchers analysed more than 2.2 million pregnancies and birth events recorded between 2000 and 2022. The data came from five large health-record datasets covering England, Scotland, Wales and Northern Ireland, allowing the investigators to compare outcomes across the entire UK. The analysis was conducted by the MuM-PreDiCT consortium, a research partnership established to improve care for pregnant women with multiple long-term health conditions. Around one in five pregnant women in the UK is estimated to begin pregnancy with at least two such conditions, although the effects of this combination have remained poorly understood.
Compared with women who entered pregnancy without long-term conditions, those with multiple conditions had a 20% higher risk of miscarriage. They also had a 69% higher risk of hyperemesis or other severe nausea and vomiting during pregnancy, a condition that can cause dehydration, nutritional deficiencies, weight loss and hospital admission. The researchers further identified approximately four times the risk of antenatal anxiety and depression. These mental-health findings are particularly significant because psychological conditions may be under-recorded in routine medical data, while symptoms can be mistaken for normal emotional changes associated with pregnancy.
The study also found a more than twofold increase in venous thromboembolism among women with multiple long-term conditions. Venous thromboembolism occurs when a clot forms in a vein, most commonly in the leg as deep vein thrombosis, and may become life-threatening if it travels to the lungs, causing pulmonary embolism. Pregnancy itself creates a more clot-prone physiological state through changes in coagulation, blood flow and pressure on pelvic veins. Additional conditions, reduced mobility, inflammation, obesity, previous clotting events or certain medications can further increase this risk. Among women with three or more long-term conditions, the risk was more than three-and-a-half times higher than among women with no recorded long-term conditions.
Pre-eclampsia was 42% more common in women with multiple conditions. This pregnancy complication is characterised by new-onset high blood pressure and evidence of organ dysfunction, often involving the kidneys or liver, after 20 weeks of gestation. It can restrict blood flow through the placenta and threaten the health of both mother and fetus. The researchers also observed a 32% higher risk of placental abruption, in which the placenta separates from the uterine wall before birth, and a 26% higher risk of gestational diabetes. Placental abruption can cause severe bleeding and compromise fetal oxygen supply, while gestational diabetes may increase the likelihood of excessive fetal growth, birth complications and later metabolic disease.
The risks did not simply distinguish women with multiple conditions from those with none; they generally increased as the number of conditions rose. This dose-response pattern strengthens the possibility that multimorbidity itself is clinically meaningful, rather than the results being explained only by one particularly influential diagnosis. Long-term conditions may interact through several biological pathways, including chronic inflammation, vascular dysfunction, altered immune responses, metabolic disturbances and medication effects. They can also affect access to care, mobility, nutrition, sleep and the ability to recognise or report emerging symptoms. However, because the investigation was observational, it cannot establish that multimorbidity directly caused each outcome.
Dr Steven Wambua, Research Fellow in Health Data Science at King’s College London and joint first author, said maternity care remains largely structured around single health conditions even though a substantial proportion of women enter pregnancy with several. By harmonising five datasets from all four UK nations, the researchers were able to identify consistent patterns across a wider range of outcomes than previous studies. The use of routinely collected health records also allowed the team to examine pregnancy at a scale that would be difficult to achieve through a conventional clinical trial, although the approach depends on the accuracy and completeness of information entered into health systems.
The authors argue that women with multiple long-term conditions should be identified as a distinct antenatal-risk group at maternity booking. Booking appointments usually collect information about previous pregnancies, current medications and known diagnoses, but a fragmented approach can leave responsibility divided between obstetricians, general practitioners, mental-health professionals and other specialists. A coordinated assessment could bring physical and mental health needs together, review potentially interacting medicines, evaluate clotting and blood-pressure risks, and establish clear routes for urgent advice. Such care would also need to be flexible, because the same combination of conditions may produce very different risks and priorities in different pregnancies.
Ngawai Moss, who has experienced pregnancy with long-term health conditions and is a Patient and Public Involvement co-investigator on MuM-PreDiCT, said patients should not have to coordinate their own care or determine which questions to ask and which specialists to contact. The researchers say that patient-centred care must account for the practical burden of navigating multiple services, particularly when symptoms of physical illness and psychological distress overlap. Professor Krishnarajah Nirantharakumar, the consortium’s principal investigator and a joint senior author, described the near fourfold increase in antenatal anxiety and depression as an urgent signal for integrated perinatal mental-health support. Dr Kelly-Ann Eastwood, a joint senior author from Bristol NHS Foundation Trust and Queen’s University Belfast, said the findings also underline the need to address healthcare inequalities and improve support for women with pre-existing mental-health conditions.
The study’s investigators caution that routinely collected records may under-record some diagnoses and pregnancy outcomes, and that coding practices can differ between regions and over time. The analysis may also be affected by factors such as age, socioeconomic circumstances, ethnicity, smoking, body weight, medication use and the severity of individual conditions, even when statistical adjustments are applied. Further work will examine birth and child outcomes and determine which combinations of conditions carry the greatest risk. Funded by the UKRI Strategic Priorities Fund and the Department of Health and Social Care through the National Institute for Health and Care Research and delivered by the Medical Research Council, the research provides one of the clearest UK-wide signals yet that multimorbidity should be treated as a central feature of pregnancy care rather than an administrative collection of separate diagnoses.
Subject of Research: The impact of multiple pre-existing long-term physical and mental health conditions on pregnancy outcomes.
Web References: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(26)00148-9/fulltext
Keywords: pregnancy, multimorbidity, maternal health, miscarriage, pre-eclampsia, venous thromboembolism, gestational diabetes, placental abruption, hyperemesis, antenatal anxiety, antenatal depression, perinatal mental health, maternity care, health data science, King’s College London, MuM-PreDiCT
