Mothers Seeking Sanctuary in Wales: a Cohort Profile

People seeking sanctuary, including asylum seekers and refugees, can face obstacles in accessing maternity care and may experience higher rates of adverse perinatal outcomes. However, a lack of data disaggregated by immigration status can hinder research regarding experiences and outcomes of maternity care for refugees and asylum seekers.

The aim of our study was to examine the maternity care service use and perinatal outcomes of refugees and asylum seekers in Wales by comparing them to a group of non-refugee UK-born mothers. In this publication, our objectives were to describe how we built the study cohort and key characteristics of the cohort members.

Working with the SAIL Databank, we linked multiple datasets and selected individuals recorded as refugees or asylum seekers in general practitioner records to conduct a retrospective cohort study. We produced cross-tabulations for variables related to the characteristics of the cohort members and performed chi-squared tests to identify statistically significant differences (p < 0.05) between the refugee or asylum seeker group and the comparator group of non-refugee UK-born women.

Our study cohort comprises 602 mothers categorised as refugees or asylum seekers and a comparator group of 146 665 non-refugee UK-born mothers who have given birth in Wales since April 2014. Our findings indicate that the two groups have distinct profiles: mothers seeking sanctuary are more likely to be part of a minority ethnic group (84.8% vs 3.1%) and to live in an area categorised as the most deprived quintile (56.0% vs 24.7%) and less likely to be obese (19.0% vs 29.9%) than UK-born mothers.

Using general practitioner records allowed us to select a cohort of mothers seeking sanctuary and a comparator group of non-refugee UK-born mothers. Our descriptive analysis of the cohort member characteristics revealed several differences between the two groups. The novel use of GP records to specifically examine refugee and asylum seeker groups in large-scale datasets highlights the potential of routine health data and dataset linkage to investigate health disparities.