Neil Cockburn
Ethnic and Socioeconomic Variation in Pre-Conception Long-Term Conditions: A Cross-Sectional Electronic Health Record Study of 3.4 Million Pregnancies in Cprd Aurum
Cockburn, Neil; Singh, Megha; Wambua, Steven; Gonzalez-Izquierdo, Arturo; Ing Lee, Siang; Phillips, Katherine; Elsmore, Amy; Ilaalagan, Ragave; Holland, Robyn; Hanley, Stephanie J.; Laws, Elinor; Hodgetts-Morton, Victoria; Gibbon, Marion; Judd, Nathan A.; Seymour, Rowland G.; Taylor, Beck; Singh Chandan, Joht; Parry-Smith, William; Nirantharakumar, Krishnarajah
Authors
Megha Singh
Steven Wambua
Arturo Gonzalez-Izquierdo
Siang Ing Lee
Katherine Phillips
Amy Elsmore
Ragave Ilaalagan
Robyn Holland
Stephanie J. Hanley
Elinor Laws
Victoria Hodgetts-Morton
Marion Gibbon
Nathan A. Judd
Rowland G. Seymour
Beck Taylor
Joht Singh Chandan
Professor William Parry-Smith w.r.parry-smith@keele.ac.uk
Krishnarajah Nirantharakumar
Contributors
N. Cockburn
Other
M. Singh
Other
S. Wambua
Other
A. Gonzalez-Izquierda
Other
S.I. Lee
Other
K. Phillips
Other
A. Elsmore
Other
R. Ilaalagan
Other
R. Holland
Other
S.J. Hanley
Other
E. Laws
Other
V. Hodgetts-Morton
Other
M. Gibbon
Other
N.A. Judd
Other
R.G. Seymour
Other
B. Taylor
Other
J.S. Chandan
Other
Professor William Parry-Smith w.r.parry-smith@keele.ac.uk
Other
K. Nirantharakumar
Other
Abstract
Background: Inequalities in pregnancy outcomes between different ethnic groups and backgrounds of deprivation have been observed in the UK and elsewhere for several decades. Pre-existing long-term health conditions increase risks of adverse outcomes and require focussed action to diagnose, prevent, and manage these conditions. We aimed to estimate differences in the prevalence of pre-conception long-term conditions between different groups to assess health needs.
Methods: This was a cross-sectional study conducted in primary care using Clinical Practice Research Datalink (CPRD) Aurum data. Diagnostic information was extracted from CPRD Aurum at the beginning of all eligible pregnancies for 79 conditions between 2000 and 2021. Age-standardised was estimated and risk ratios calculated between the overall population, and ethnic groups and Index of Multiple Deprivation quintiles. Statistical process control was used to detect conditions with elevated prevalence within groups..
Findings: In 2021, at the start of a pregnancy, women from ethnic minority groups were less likely to have been diagnosed with any one of the 79 conditions than the general population. Women from mixed ethnic groups were 4% more likely to be diagnosed, and from white ethnic groups 2% more likely to be diagnosed. Women from black groups were 5% less likely to be diagnosed, from Asian groups 26%, other ethnic groups 32%, and women missing ethnic group information 13%. Women living in the most deprived quintile of areas were 8% more likely to have been diagnosed than the overall population, and from least deprived areas 8% less likely to have been diagnosed.
Interpretation: Pre-existing long-term conditions are a major driver of maternal morbidity and mortality, but the healthcare needs and policy priorities differ substantially between ethnic and socially disadvantaged groups. Universal health policies that narrow inequalities and targeted action are both needed to meet health needs equitably.
Citation
Cockburn, N., Singh, M., Wambua, S., Gonzalez-Izquierdo, A., Ing Lee, S., Phillips, K., Elsmore, A., Ilaalagan, R., Holland, R., Hanley, S. J., Laws, E., Hodgetts-Morton, V., Gibbon, M., Judd, N. A., Seymour, R. G., Taylor, B., Singh Chandan, J., Parry-Smith, W., & Nirantharakumar, K. (2025). Ethnic and Socioeconomic Variation in Pre-Conception Long-Term Conditions: A Cross-Sectional Electronic Health Record Study of 3.4 Million Pregnancies in Cprd Aurum
Working Paper Type | Preprint |
---|---|
Publication Date | Jan 23, 2025 |
Deposit Date | May 19, 2025 |
DOI | https://doi.org/10.2139/ssrn.5103707 |
Public URL | https://keele-repository.worktribe.com/output/1238716 |
Publisher URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5103707 |
You might also like
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search