Differences in healthcare based on ethnic and economic backgrounds have a substantial impact on women's health. We are not using what we know about pregnancy problems and how they link to future health issues enough to reduce these inequalities. For example, problems during pregnancy, like high blood pressure and diabetes, can lead to long-term heart and metabolic issues. Mental health during and after pregnancy can also affect future mental health.
To understand how women's health is affected by pregnancy, we want to use hospital records of women who have and have not given birth, linked to records before and after birth from primary and secondary care and mortality records.
We plan to use the data to understand what happens to women with pregnancy problems or complications in the months and years after giving birth. We'll use statistical tests and models to understand the relationship between health and complications in pregnancy and long-term health. Understanding these links and how they are influenced by women’s characteristics, including their ethnic and socioeconomic group, will enable better identification of women at risk of future health problems. This can lead to better ways of helping women stay healthy through new clinical and policy interventions.
Technical summary (300 words)
Ethnic and socioeconomic disparities in healthcare disproportionately affect women's health. Currently, limited use is made of the knowledge that pregnancy complications have strong associations with long-term health outcomes. Areas in which links have been shown include gestational hypertension and long-term cardiovascular health; gestational diabetes and long-term metabolic health; perinatal mental health and subsequent mental health conditions. Understanding the interaction between pregnancy complications and socioeconomic diversity and their combined role in long-term health offers opportunities to improve risk assessment and potentially improve women’s health across the life course.
In this study, we will assess the relationship between women’s health before, during and after pregnancy using routine electronic health records. To do this, the study will address two overall objectives. First, we will develop and phenotype a study cohort of women in England who have and have not given birth. Hospital Episode Statistics (HES) admission data will be used to determine birth records for women and babies, including details about their birth and any complications; we will then link this to information before during and after pregnancy in primary (CPRD) and secondary (HES) care and mortality (ONS) records. We will comprehensively profile this cohort, including its representativeness and any risk of bias. Second, for women with pregnancy conditions (including hypertension, diabetes, and mental illness) and complications (such as preterm birth, fetal growth restriction, and stillbirth) and their babies, we will look at clinical precursors and ongoing morbidity after birth. We plan to explore these using simple tests of association, regression and survival analyses.
An understanding of these associations, and how they interact with other risk factors such as age and ethnicity, could underpin better and timely identification of women at risk of long-term poor health, and development of clinical and policy interventions to improve women’s health.
(1) Pregnancy outcomes, including preterm birth, stillbirth, fetal growth restriction, mode of birth (caesarean, instrumental, spontaneous vaginal), and the development of specific complications in pregnancy (hypertensive disorders, gestational diabetes, intrahepatic cholestasis of pregnancy, antenatal and postnatal depression, peripartum psychosis).
(2) Maternal health outcomes after birth, including all-cause and specific-cause mortality, cardiovascular outcomes, diabetes, and mental health outcomes.
Jennifer Jardine - Chief Investigator - Queen Mary University of London
Jennifer Jardine - Corresponding Applicant - Queen Mary University of London
Fabiola Eto - Collaborator - Queen Mary University of London
Rebecca Lissmann - Collaborator - Queen Mary University of London
Rohini Mathur - Collaborator - Queen Mary University of London
Stamatina Iliodromiti - Collaborator - Queen Mary University of London
Iona Hindes - Collaborator - Barts and the London Queen Mary's School of Medicine and Dentistry
Moonsun Bharj - Collaborator - Queen Mary University of London
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation;CPRD Aurum Ethnicity Record;CPRD Aurum Mother-Baby Link;CPRD Aurum Pregnancy Register