No abstract

International migrants comprised 14% of the UK’s population in 2020; however, their health is rarely studied at a population level using primary care electronic health records due to difficulties in their identification. We developed a migration phenotype using country of birth, visa status, non-English main/first language and non-UK-origin codes and applied it to the Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country-of-birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997 to 2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified: 178,749 (1.11%) had foreign-country-of-birth or visa -status codes, 216,731 (1.35%) non-English-main/first-language codes, and 8288 (0.05%) non-UK-origin codes. The cohort was similarly distributed versus ONS data by sex and region of birth. Migration recording improved over time and younger migrants were better represented than those aged ≥50. The validated phenotype identified a large migrant cohort for use in migration health research in CPRD GOLD to inform healthcare policy and practice. The under-recording of migration status in earlier years and older ages necessitates cautious interpretation of future studies in these groups.

No abstract

An estimated 14.2% (9.34 million people) of people living in the UK in 2019 were international migrants. Despite this, there are no large-scale national studies of their healthcare resource utilisation and little is known about how migrants access and use healthcare services. One ongoing study of migration health in the UK, the Million Migrants study, links electronic health records (EHRs) from hospital-based data, national death records and Public Health England migrant and refugee data. However, the Million Migrants study cannot provide a complete picture of migration health resource utilisation as it lacks data on migrants from Europe and utilisation of primary care for all international migrants. Our study seeks to address this limitation by using primary care EHR data linked to hospital-based EHRs and national death records.  Our study is split into a feasibility study and a main study. The feasibility study will assess the validity of a migration phenotype, a transparent reproducible algorithm using clinical terminology codes to determine migration status in Clinical Practice Research Datalink (CPRD), the largest UK primary care EHR. If the migration phenotype is found to be valid, the main study will involve using the phenotype in the linked dataset to describe primary care and hospital-based healthcare resource utilisation and mortality in migrants compared to non-migrants. All outcomes will be explored according to sub-conditions identified as research priorities through patient and public involvement, including preventable causes of inpatient admission, sexual and reproductive health conditions/interventions and mental health conditions. The results will generate evidence to inform policies that aim to improve migration health and universal health coverage.

International migrants comprised 14% of the UK population in 2020, but migrant health in the UK has rarely been studied at a population level using primary care electronic health records (EHRs). Given the difficulty of determining migration status using EHRs, this study developed a migration phenotype and assessed its validity. We developed a phenotyping algorithm using codes for country of birth, visa status, non-English main/first language and non-UK origin. It was applied to a Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country of birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997-2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified using the phenotype. 178,749 (1.11%) of these migrants were identified by codes indicating foreign country of birth or visa status, 216,731 (1.35%) a non-English main/first language, and 8,288 (0.05%) non-UK origin. The cohort was similarly distributed compared to ONS migration statistics in terms of sex and region of birth. Recording of migration improved from identifying approximately one-tenth of the expected proportion of migrants according to the ONS in 2004 to a quarter in 2018. Younger migrants were better represented than those aged 50 and over. The migration phenotype identified a large number of migrants and can be used to undertake large-scale migration health research in CPRD GOLD to inform healthcare policy, practice and action. While the cohort was representative of the UK migrant population in terms of sex and region of birth, migration status was under-recorded in earlier years and older ages, and future studies for these groups should therefore be interpreted with caution.

1,2 , Martie van Tongeren (https://orcid.org/0000-0002-1205-1898) 5, Anne M Johnson (https://orcid.org/0000-0003-1330-7100) 6 , Robert W Aldridge (https://orcid.org/0000-0003-0542-0816) 1 and Andrew Hayward (https://orcid.org/0000-0002-3549-6232) 2 * on behalf of the Virus Watch Collaborative 7

An estimated 14.2% (9.34 million people) of people living in the UK in 2019 were international migrants. Despite this, there are no large-scale national studies of their healthcare resource utilisation and little is known about how migrants access and use healthcare services. One ongoing study of migration health in the UK, the Million Migrants study, links electronic health records (EHRs) from hospital-based data, national death records and Public Health England migrant and refugee data. However, the Million Migrants study cannot provide a complete picture of migration health resource utilisation as it lacks data on migrants from Europe and utilisation of primary care for all international migrants. Our study seeks to address this limitation by using primary care EHR data linked to hospital-based EHRs and national death records.  Our study is split into a feasibility study and a main study. The feasibility study will assess the validity of a migration phenotype, a transparent reproducible algorithm using clinical terminology codes to determine migration status in Clinical Practice Research Datalink (CPRD), the largest UK primary care EHR. If the migration phenotype is found to be valid, the main study will involve using the phenotype in the linked dataset to describe primary care and hospital-based healthcare resource utilisation and mortality in migrants compared to non-migrants. All outcomes will be explored according to sub-conditions identified as research priorities through patient and public involvement, including preventable causes of inpatient admission, sexual and reproductive health conditions/interventions and mental health conditions. The results will generate evidence to inform policies that aim to improve migration health and universal health coverage.

Background: Migrants are over-represented in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections globally; however, evidence is limited for migrants in England and Wales. Household overcrowding is a risk factor for SARS-CoV-2 infection, with migrants more likely to live in overcrowded households than UK-born individuals. We aimed to estimate the total effect of migration status on SARS-CoV-2 infection and to what extent household overcrowding mediated this effect. Methods: We included a sub-cohort of individuals from the Virus Watch prospective cohort study during the second SARS-CoV-2 wave (1st September 2020-30th April 2021) who were aged at least 18 years, self-reported the number of rooms in their household and had no evidence of SARS-CoV-2 infection pre-September 2020. We estimated total, indirect and direct effects using Buis logistic decomposition regression controlling for age, sex, ethnicity, clinical vulnerability, occupation, income and whether they lived with children. Results: In total, 23,478 individuals were included. 9.07% (187/2,062) of migrants had evidence of infection during the study period versus 6.27% (1,342/21,416) of UK-born individuals. Migrants had 22% higher odds of infection during the second wave (total effect; OR:1.22, 95%CI:1.01-1.47). Household overcrowding accounted for approximately 32% of these increased odds (indirect effect, OR:1.07, 95%CI:1.03-1.12; proportion accounted for: indirect effect[7]/total effect[22]=0.32). Conclusion: Migrants had higher odds of SARS-CoV-2 infection during the second wave compared with UK-born individuals and household overcrowding explained 32% of these increased odds. Policy interventions to reduce household overcrowding for migrants are needed as part of efforts to tackle health inequalities during the pandemic and beyond.