Evidence map›Paper›PMID 39097317›Full record

ArticleBMJ open2024

Exploring ethnicity dynamics in Wales: a longitudinal population-scale linked data study and development of a harmonised ethnicity spine.

Ashley Akbari, Fatemeh Torabi, Stuart Bedston, Emily Lowthian, Hoda Abbasizanjani, Richard Fry, Jane Lyons, Rhiannon K Owen, Kamlesh Khunti, Ronan Lyons

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  8. Antipsychotic management in general practice: serial cross-sectional study (2011-2020).The British journal of general practice : the journal of the Royal College of General Practitioners · 2025
    Article
  9. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ashley Akbari *Population Data Science, Swansea University Medical School, Swansea, UK A.Akbari@Swansea.ac.uk.ORCID 0000-0003-0814-0801
Fatemeh Torabi *Population Data Science, Swansea University Medical School, Swansea, UK.ORCID 0000-0002-5853-4625
Stuart BedstonPopulation Data Science, Swansea University Medical School, Swansea, UK.
Emily LowthianPopulation Data Science, Swansea University Medical School, Swansea, UK.ORCID 0000-0001-9362-0046
Hoda AbbasizanjaniPopulation Data Science, Swansea University Medical School, Swansea, UK.
Richard FryPopulation Data Science, Swansea University Medical School, Swansea, UK.ORCID 0000-0002-7968-6679
Jane LyonsPopulation Data Science, Swansea University Medical School, Swansea, UK.ORCID 0000-0002-4407-770X
Rhiannon K OwenPopulation Data Science, Swansea University Medical School, Swansea, UK.
Kamlesh KhuntiDiabetes Research Centre, University of Leicester, Leicester, UK.
Ronan LyonsPopulation Data Science, Swansea University Medical School, Swansea, UK.ORCID 0000-0001-5225-000X

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectiveThis study aims to create a national ethnicity spine based on all available ethnicity records in linkable anonymised electronic health record and administrative data sources.

designA longitudinal study using anonymised individual-level population-scale ethnicity data from 26 data sources available within the Secure Anonymised Information Linkage Databank.

settingThe national ethnicity spine is created based on longitudinal national data for the population of Wales-UK over 22 years (between 2000 and 2021). PROCEDURE AND

participantsA total of 46 million ethnicity records for 4 297 694 individuals have been extracted, harmonised, deduplicated and made available within a longitudinal research ready data asset. OUTCOME MEASURES: (1) Comparing the distribution of ethnicity records over time for four different selection approaches (latest, mode, weighted mode and composite) across age bands, sex, deprivation quintiles, health board and residential location and (2) distribution and completeness of records against the ONS census 2011.

resultsThe distribution of the dominant group (white) is minimally affected based on the four different selection approaches. Across all other ethnic group categorisations, the mixed group was most susceptible to variation in distribution depending on the selection approach used and varied from a 0.6% prevalence across the latest and mode approach to a 1.1% prevalence for the weighted mode, compared with the 3.1% prevalence for the composite approach. Substantial alignment was observed with ONS 2011 census with the Latest group method (kappa=0.68, 95% CI (0.67 to 0.71)) across all subgroups. The record completeness rate was over 95% in 2021.

conclusionIn conclusion, our development of the population-scale ethnicity spine provides robust ethnicity measures for healthcare research in Wales and a template which can easily be deployed in other trusted research environments in the UK and beyond.

Indexed as

EthnicityAdolescentAdultAgedChildChild, PreschoolElectronic Health RecordsFemaleHumansInfantInfant, NewbornLongitudinal StudiesMaleMiddle AgedWalesYoung AdultEPIDEMIOLOGYHealth policyPUBLIC HEALTH

Identifiers

PMID39097317
PMCPMC11733787

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.