23 datasets found
  1. s

    Persistent low income

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Sep 17, 2025
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    Race Disparity Unit (2025). Persistent low income [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/pay-and-income/low-income/latest
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    csv(81 KB), csv(302 KB)Available download formats
    Dataset updated
    Sep 17, 2025
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Between 2019 and 2023, people living in households in the Asian and ‘Other’ ethnic groups were most likely to be in persistent low income before and after housing costs

  2. s

    Stop and search

    • ethnicity-facts-figures.service.gov.uk
    • monwebsite.ch
    csv
    Updated Jul 3, 2024
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    Race Disparity Unit (2024). Stop and search [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/crime-justice-and-the-law/policing/stop-and-search/latest
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    csv(3 MB)Available download formats
    Dataset updated
    Jul 3, 2024
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England and Wales
    Description

    Between April 2022 and March 2023, there were 24.5 stop and searches for every 1,000 black people in England and Wales. There were 5.9 for every 1,000 white people.

  3. Health Inequalities Dashboard: March 2023 data update

    • gov.uk
    Updated Aug 30, 2023
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    Office for Health Improvement and Disparities (2023). Health Inequalities Dashboard: March 2023 data update [Dataset]. https://www.gov.uk/government/statistics/health-inequalities-dashboard-march-2023-data-update
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    Dataset updated
    Aug 30, 2023
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Office for Health Improvement and Disparities
    Description

    The https://fingertips.phe.org.uk/profile/inequality-tools">Health Inequalities Dashboard presents data on health inequalities for England, English regions and local authorities. It presents measures of inequality for 19 indicators, mostly drawn from the https://fingertips.phe.org.uk/profile/public-health-outcomes-framework">Public Health Outcomes Framework (PHOF).

    Data are available for a number of dimensions of inequality. Most indicators show socio-economic inequalities, including by level of deprivation, and some indicators show inequalities between ethnic groups. For smoking prevalence, data are presented for a wider range of dimensions, including sexual orientation and religion.

  4. Table_2_Improving adult behavioural weight management services for diverse...

    • frontiersin.figshare.com
    • figshare.com
    docx
    Updated Nov 23, 2023
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    Maria J. Maynard; Oritseweyinmi Orighoye; Tanefa Apekey; Ellouise Simpson; Margie van Dijk; Elizabeth Atherton; Jamie Blackshaw; Louisa Ells (2023). Table_2_Improving adult behavioural weight management services for diverse UK Black Caribbean and Black African ethnic groups: a qualitative study of insights from potential service users and service providers.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2023.1239668.s003
    Explore at:
    docxAvailable download formats
    Dataset updated
    Nov 23, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Maria J. Maynard; Oritseweyinmi Orighoye; Tanefa Apekey; Ellouise Simpson; Margie van Dijk; Elizabeth Atherton; Jamie Blackshaw; Louisa Ells
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Africa, United Kingdom
    Description

    BackgroundA significantly higher proportion of UK Black ethnic adults live with overweight or obesity, compared to their White British counterparts. The role of obesity in excess infection rates and mortality from COVID-19 has increased the need to understand if weight management interventions are appropriate and effective for Black ethnic groups. There is a paucity of existing research on weight management services in Black populations, and whether anticipated or experienced institutional and interpersonal racism in the healthcare and more widely affects engagement in these services. Understanding the lived experience of target populations and views of service providers delivering programmes is essential for timely service improvement.MethodsA qualitative study using semi-structured interviews was conducted in June–October 2021 among 18 Black African and Black Caribbean men and women interested in losing weight and 10 weight management service providers.ResultsThe results highlighted a positive view of life in the United Kingdom (UK), whether born in the UK or born abroad, but one which was marred by racism. Weight gain was attributed by participants to unhealthy behaviours and the environment, with improving appearance and preventing ill health key motivators for weight loss. Participants relied on self-help to address their overweight, with the role of primary care in weight management contested as a source of support. Anticipated or previously experienced racism in the health care system and more widely, accounted for some of the lack of engagement with services. Participants and service providers agreed on the lack of relevance of existing services to Black populations, including limited culturally tailored resources. Community based, ethnically matched, and flexibly delivered weight management services were suggested as ideal, and could form the basis of a set of recommendations for research and practice.ConclusionCultural tailoring of existing services and new programmes, and cultural competency training are needed. These actions are required within systemic changes, such as interventions to address discrimination. Our qualitative insights form the basis for advancing further work and research to improve existing services to address the weight-related inequality faced by UK Black ethnic groups.

  5. u

    An ESRC/NIH health disparities study of discrimination and disparities in...

    • datacatalogue.ukdataservice.ac.uk
    Updated Jul 14, 2017
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    Hatch, S, King's College London; Hotopf, M, King's College London (2017). An ESRC/NIH health disparities study of discrimination and disparities in health; health service use in the UK and US [Dataset]. http://doi.org/10.5255/UKDA-SN-851973
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    Dataset updated
    Jul 14, 2017
    Authors
    Hatch, S, King's College London; Hotopf, M, King's College London
    Area covered
    United Kingdom
    Description

    This archive contains the ESRC funded data collection (UK data) only.

    The data collection contains a state file consisting of 902 variables, 677 observations. The codebook available in the data collection provides detailed descriptions of variables and data codes (missing etc). For more information please contact stephani.hatch@kcl.ac.uk

    Research from the United Kingdom and the United States shows wide health inequalities by race/ethnicity and socio-economic status. So far we do not clearly understand the roles that discrimination and social context play in creating these inequalities.

    Research teams at King's College London (UK) and Columbia University (USA) will carry out studies to investigate:

    the roles that the historical social context and policy play in shaping observed patterns of health inequalities;

    differences in anticipated and perceived experiences of discrimination;

    how discrimination contributes to inequalities in everyday social functioning, mental health, physical health, and use of health services.

    Comparisons will be made with 1600 adults from two larger studies, (i) the UK National Institute for Health Research-funded South East London Community Health study at the Biomedical Research Centre for Mental Health, and (ii) the US National Institute of Health-funded Child Health and Development Disparities Study in the East Bay Area of California. UK and US researchers, health practitioners, and community members will be invited to participate in developing the social and historical contextual narratives and in planning the dissemination of our research findings.

  6. Improving ethnic data collection for equality and diversity monitoring -...

    • ckan.publishing.service.gov.uk
    Updated Dec 10, 2011
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    ckan.publishing.service.gov.uk (2011). Improving ethnic data collection for equality and diversity monitoring - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/improving_ethnic_data_collection_for_equality_and_diversity_monitoring
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    Dataset updated
    Dec 10, 2011
    Dataset provided by
    CKANhttps://ckan.org/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Addressing ethnic inequalities in health requires accurate and complete information to support monitoring and health improvement. This publication relates to the quality and completeness of information on ethnicity in hospital discharge and new outpatient appointment data. Source agency: ISD Scotland (part of NHS National Services Scotland) Designation: Official Statistics not designated as National Statistics Language: English Alternative title: Equality and diversity monitoring

  7. n

    Perceived barriers and motivators to physical activity in children from...

    • figshare.northumbria.ac.uk
    docx
    Updated Feb 21, 2025
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    JOYCE OMOJOR-OCHE; Florentina Hettinga; Gavin Tempest; Kandianos Sakalidis; Nicola McCullogh (2025). Perceived barriers and motivators to physical activity in children from ethnic minority group: A qualitative systematic review [Dataset]. http://doi.org/10.25398/rd.northumbria.28452347.v1
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    docxAvailable download formats
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    Northumbria University
    Authors
    JOYCE OMOJOR-OCHE; Florentina Hettinga; Gavin Tempest; Kandianos Sakalidis; Nicola McCullogh
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The benefits of physical activity (PA) are well-known, as is the importance of being active from an early age. However, many children, especially children from ethnic minority groups, do not meet recommended PA guidelines, putting them at a higher risk of developing non-communicable diseases such as diabetes and cardiovascular disease in later life. This study aims to identify the perceived barriers and motivators to PA among children from ethnic minority groups living in the United Kingdom and countries with similar socio-economic characteristics, through a qualitative systematic literature review.  

  8. Data from: Investigating ethnic inequalities in hearing aid use in England...

    • tandf.figshare.com
    docx
    Updated May 31, 2023
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    Harry Taylor; Piers Dawes; Dharmi Kapadia; Nick Shryane; Paul Norman (2023). Investigating ethnic inequalities in hearing aid use in England and Wales: a cross-sectional study [Dataset]. http://doi.org/10.6084/m9.figshare.17207131.v1
    Explore at:
    docxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Taylor & Francishttps://taylorandfrancis.com/
    Authors
    Harry Taylor; Piers Dawes; Dharmi Kapadia; Nick Shryane; Paul Norman
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    To establish whether ethnic inequalities exist in levels of self-reported hearing difficulty and hearing aid use among middle-aged adults. Cross-sectional data from the UK Biobank resource. 164,460 participants aged 40–69 who answered hearing questions at an assessment centre in England or Wales. After taking into account objectively assessed hearing performance and a corresponding correction for bias in non-native English speakers, as well as a range of correlates including demographic, socioeconomic, and health factors, there were lower levels of hearing aid use for people from Black African (OR 0.36, 95% CI 0.17–0.77), Black Caribbean (OR 0.38, 95% CI 0.22–0.65) and Indian (OR 0.60, 95% CI 0.41–0.86) ethnic groups, compared to the White British or Irish group. Men from most ethnic minority groups and women from Black African, Black Caribbean and Indian groups were less likely to report hearing difficulty than their White British or Irish counterparts. For equivalent levels of hearing loss, the use of hearing aids is lower among ethnic minority groups. Inequalities are partly due to lower levels of self-reported hearing difficulty among minority groups. However, even when self-reported hearing difficulty is considered, hearing aid use remains lower among many ethnic minority groups.

  9. Gender and Ethnicity Pay Gap Report as at 31 March 2023

    • gov.uk
    Updated Apr 23, 2024
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    Regulator of Social Housing (2024). Gender and Ethnicity Pay Gap Report as at 31 March 2023 [Dataset]. https://www.gov.uk/government/publications/gender-and-ethnicity-pay-gap-report-as-at-31-march-2024
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    Dataset updated
    Apr 23, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Regulator of Social Housing
    Description

    Contents

    Gender pay gap

    Ethnicity pay gap

    Foreword

    This report reflects our gender and ethnicity pay gap data as of March 2023, which we annually report in arrears.

    Although our staff count falls below the 250-employee threshold for mandatory gender pay gap reporting, we have voluntarily chosen to publish our findings for the fifth year, believing it aligns with best practices and promotes transparency in pay across the public sector.

    We continue to strive for an inclusive, welcoming, and fair environment for all members of our team. These plans encompass various aspects of our operations, from recruitment and promotions to training and mentorship, all aimed at eliminating barriers and promoting equal opportunities. The ultimate goal is to ensure that every member of our organisation is provided with a fair and equal path to success to support the regulator in driving change in the social housing sector to deliver more and better social housing.

    Gender Identity

    In accordance with the current requirements for reporting on the gender pay gap, our approach involves categorising gender into male and female within our data classification.

    It is important to note that we define gender in accordance with the classifications provided by His Majesty’s Revenue and Customs (HMRC), which categorise individuals as male or female, in our data.

    In the context of this report, we have employed the terms ‘gender,’ ‘male,’ and ‘female,’ understanding that they typically relate to biological sex. However, it’s important to acknowledge that for some individuals, these terms may not fully encapsulate their gender identity.

    How the Gender Pay Gap is worked out

    In 2017, the government introduced a statutory requirement for organisations with 250 or more employees to report annually on their gender pay gap. Government departments are covered by the https://www.legislation.gov.uk/uksi/2017/353/contents/made">Equality Act 2010 (Specific Duties and Public Authorities) Regulations 2017 which came into force on 31 March 2017. These regulations underpin the Public Sector Equality Duty and require the relevant organisations to annually publish their gender pay gap data on:

    • Mean and median gender pay gap in hourly pay,
    • Mean and median bonus gender pay gap,
    • Proportion of men and women receiving a bonus payment; and
    • Proportion of men and women in each pay quartile.

    The gender pay gap shows the difference in the average pay between all men and women in a workforce. Mean and median gender pay gap figures are based on a comparison of men and women’s hourly pay across the organisation irrespective of grade, which means that the gap shows the difference in the average pay between all men and women in the organisation’s workforce.

    • The mean figure is the percentage difference between the mean average hourly rates of men and women’s pay.

    • The median figure is the percentage difference between the midpoints in the ranges of men and women’s pay.

    • The bonus gap refers to bonus payments paid to men and women employees during the 12 months period prior to the snapshot date.

    Our gender pay gap at 31 March 2023

    Our figures at 31 March 2023

    https://assets.publishing.service.gov.uk/media/662773a0838212a903a7e529/s960_gender_pay_gap_comparative_years.png" alt="">

    Data table

    <t

    Mar-20Mar-21Mar-22Mar-23
    Mean Pay Gap
  10. COVID-19 Health Inequalities Monitoring in England tool (CHIME)

    • s3.amazonaws.com
    • gov.uk
    Updated Sep 15, 2022
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    Office for Health Improvement and Disparities (2022). COVID-19 Health Inequalities Monitoring in England tool (CHIME) [Dataset]. https://s3.amazonaws.com/thegovernmentsays-files/content/183/1836757.html
    Explore at:
    Dataset updated
    Sep 15, 2022
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Office for Health Improvement and Disparities
    Area covered
    England
    Description

    The COVID-19 Health Inequalities Monitoring in England (CHIME) tool brings together data relating to the direct impacts of coronavirus (COVID-19) on factors such as mortality rates, hospital admissions, confirmed cases and vaccinations.

    By presenting inequality breakdowns – including by age, sex, ethnic group, level of deprivation and region – the tool provides a single point of access to:

    • show how inequalities have changed during the course of the pandemic and what the current cumulative picture is
    • bring together data in one tool to enable users to access and use the intelligence more easily
    • provide indicators with a consistent methodology across different data sets to facilitate understanding
    • support users to identify and address inequalities within their areas, and identify priority areas for recovery

    In the September 2022 update, data have been updated for deaths, hospital admissions and vaccinations. Data for confirmed cases are no longer being updated in the tool and March 2022 remains the most recent data point.

    Confirmed cases for ethnic groups, which had previously only been available to December 2021, have now been updated to March 2022. Two changes have been implemented for confirmed cases by ethnic group. The change in https://ukhsa.blog.gov.uk/2022/02/04/changing-the-covid-19-case-definition/" class="govuk-link">COVID-19 case definition, which was made in February 2022, has now been implemented. The method of assigning an ethnic group for confirmed cases has also changed. These changes have resulted in revisions to the trends reported for confirmed cases for all ethnic groups. Methods of assigning ethnicity for data within CHIME are documented

    Changes have also been made to the confirmed case rates presented for all ages, with age-standardised rates replaced by crude mortality rates.

    The next updates will be 09:30 on 15 December 2022.

  11. h

    Qualitative Interviews with NHS Staff During the Pandemic: An Investigation...

    • harmonydata.ac.uk
    • datacatalogue.ukdataservice.ac.uk
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    Qualitative Interviews with NHS Staff During the Pandemic: An Investigation into Ethnic Inequalities Experienced During the Pandemic, 2020-2022 [Dataset]. http://doi.org/10.5255/UKDA-SN-856172
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    Time period covered
    Jul 12, 2020 - Jan 12, 2022
    Description

    Prior to COVID-19, the NHS England Workforce Race Equalities Standard (WRES) found that ethnic minority staff experience considerably greater levels of workplace harassment and discrimination, lower pay, less control and poorer working conditions than White British staff [1]. Since the outbreak, these adverse working conditions have been exacerbated. Ethnic minority staff experience increased exposure to these workplace adversities, placement in more vulnerable positions, and disempowerment from complaining about deleterious working conditions. These ethnic disparities need to be addressed if we are to avoid the social, economic, and moral costs of excessive adverse mental health and occupational outcomes for ethnic minority staff.

    This study aims to identify ethnic inequalities in mental health and occupational outcomes amongst NHS staff during the COVID-19 pandemic. Interviews will be conducted with i) participants of the CHECK survey, ii) London healthcare practitioners (HCPs, e.g., nurses and healthcare assistants) who were interviewed as part of the Tackling Inequalities and Discrimination Experiences (TIDES) study before COVID-19, and iii) NHS managers and senior staff nationally. Findings will be used to develop education and training materials to support BAME NHS staff nationally through collaboration with psychologists (KCL Virtual Reality (VR) Lab), medical educators (e.g., Maudsley Learning) and equality and diversity professionals (Challenge Consultancy).Prior to COVID-19, the NHS England Workforce Race Equalities Standard (WRES) found that ethnic minority staff experience considerably greater levels of workplace harassment and discrimination, lower pay, less control and poorer working conditions than White British staff [1]. Since the outbreak, these adverse working conditions have been exacerbated. Ethnic minority staff experience increased exposure to these workplace adversities, placement in more vulnerable positions, and disempowerment from complaining about deleterious working conditions. These ethnic disparities need to be addressed if we are to avoid the social, economic, and moral costs of excessive adverse mental health and occupational outcomes for ethnic minority staff. This study aims to identify ethnic inequalities in mental health and occupational outcomes amongst NHS staff during the COVID-19 pandemic.

  12. Data_Sheet_1_Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    pdf
    Updated Jun 6, 2023
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    Esther Puyol-Antón; Bram Ruijsink; Jorge Mariscal Harana; Stefan K. Piechnik; Stefan Neubauer; Steffen E. Petersen; Reza Razavi; Phil Chowienczyk; Andrew P. King (2023). Data_Sheet_1_Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation.pdf [Dataset]. http://doi.org/10.3389/fcvm.2022.859310.s001
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    pdfAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Esther Puyol-Antón; Bram Ruijsink; Jorge Mariscal Harana; Stefan K. Piechnik; Stefan Neubauer; Steffen E. Petersen; Reza Razavi; Phil Chowienczyk; Andrew P. King
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundArtificial intelligence (AI) techniques have been proposed for automation of cine CMR segmentation for functional quantification. However, in other applications AI models have been shown to have potential for sex and/or racial bias. The objective of this paper is to perform the first analysis of sex/racial bias in AI-based cine CMR segmentation using a large-scale database.MethodsA state-of-the-art deep learning (DL) model was used for automatic segmentation of both ventricles and the myocardium from cine short-axis CMR. The dataset consisted of end-diastole and end-systole short-axis cine CMR images of 5,903 subjects from the UK Biobank database (61.5 ± 7.1 years, 52% male, 81% white). To assess sex and racial bias, we compared Dice scores and errors in measurements of biventricular volumes and function between patients grouped by race and sex. To investigate whether segmentation bias could be explained by potential confounders, a multivariate linear regression and ANCOVA were performed.ResultsResults on the overall population showed an excellent agreement between the manual and automatic segmentations. We found statistically significant differences in Dice scores between races (white ∼94% vs. minority ethnic groups 86–89%) as well as in absolute/relative errors in volumetric and functional measures, showing that the AI model was biased against minority racial groups, even after correction for possible confounders. The results of a multivariate linear regression analysis showed that no covariate could explain the Dice score bias between racial groups. However, for the Mixed and Black race groups, sex showed a weak positive association with the Dice score. The results of an ANCOVA analysis showed that race was the main factor that can explain the overall difference in Dice scores between racial groups.ConclusionWe have shown that racial bias can exist in DL-based cine CMR segmentation models when training with a database that is sex-balanced but not race-balanced such as the UK Biobank.

  13. f

    Data_Sheet_1_Exploring Black and South Asian women’s experiences of...

    • frontiersin.figshare.com
    docx
    Updated Jun 2, 2023
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    Maev Conneely; Katy C. Packer; Sarah Bicknell; Jelena Janković; Harpreet Kaur Sihre; Rosemarie McCabe; Alex Copello; Kiren Bains; Stefan Priebe; Amy Spruce; Nikolina Jovanović (2023). Data_Sheet_1_Exploring Black and South Asian women’s experiences of help-seeking and engagement in perinatal mental health services in the UK.docx [Dataset]. http://doi.org/10.3389/fpsyt.2023.1119998.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers
    Authors
    Maev Conneely; Katy C. Packer; Sarah Bicknell; Jelena Janković; Harpreet Kaur Sihre; Rosemarie McCabe; Alex Copello; Kiren Bains; Stefan Priebe; Amy Spruce; Nikolina Jovanović
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Background and aimsIn the United Kingdom (UK), Black and South Asian women are less likely than White British women to access support from perinatal mental health services, despite experiencing similar, or higher, levels of distress. This inequality needs to be understood and remedied. The aim of this study was to answer two questions: how do Black and South Asian women experience (1) access to perinatal mental health services and (2) care received from perinatal mental health services?MethodSemi-structured interviews were conducted with Black and South Asian women (n = 37), including four women who were interviewed with an interpreter. Interviews were recorded and transcribed line-by-line. Data were analyzed using framework analysis, by an ethnically diverse multidisciplinary team of clinicians, researchers and people with lived experience of perinatal mental illness.ResultsParticipants described a complex interplay of factors that impacted on seeking, and receiving help, and benefiting from services. Four themes emerged that captured the highly varied experiences of individuals: (1) Self-identity, social expectations and different attributions of distress deter help-seeking; (2) Hidden and disorganized services impede getting support; (3) The role of curiosity, kindness and flexibility in making women feel heard, accepted and supported by clinicians; (4) A shared cultural background may support or hinder trust and rapport.ConclusionWomen described a wide range of experiences and a complex interplay of factors impacting access to, and experience of, services. Women described services as giving them strength and also leaving them disappointed and confused about where to get help. The main barriers to access were attributions related to mental distress, stigma, mistrust and lack of visibility of services, and organizational gaps in the referral process. These findings describe that many women feel heard, and supported by services, reporting that services provide a high quality of care that was inclusive of diverse experiences and understandings of mental health problems. Transparency around what PMHS are, and what support is available would improve the accessibility of PMHS.

  14. c

    Intergroup Contact and the Construction of Racial Inequality and Injustice...

    • datacatalogue.cessda.eu
    Updated Nov 28, 2024
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    Durrheim, K.; Dixon, J., Lancaster University (2024). Intergroup Contact and the Construction of Racial Inequality and Injustice in Post-Apartheid South Africa, 2006-2007 [Dataset]. http://doi.org/10.5255/UKDA-SN-6315-1
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    Dataset updated
    Nov 28, 2024
    Dataset provided by
    Unknown Affiliation
    Department of Psychology
    Authors
    Durrheim, K.; Dixon, J., Lancaster University
    Area covered
    South Africa
    Variables measured
    Individuals, National
    Measurement technique
    Telephone interview
    Description

    Abstract copyright UK Data Service and data collection copyright owner.


    Two surveys were conducted in post-apartheid South Africa to explore, among other factors, attitudes towards race-targeted policies, perceptions of racial justice and discrimination, and racial prejudice. The surveys also examined people's experiences of inter-racial contact in terms of both its frequency and its quality and were designed to explore the relationship between such contact and various kinds of political attitudes. Survey One sampled black, coloured, Indian and white South Africans. Survey Two sampled white and black South Africans. Both surveys employed a computer assisted, random digit dialling methodology to recruit respondents.

    Further information is available from the ESRC Award web page.

    Main Topics:

    Survey One focused on attitudes towards a variety of policies designed to achieve racial equality in post-apartheid South Africa. It also explored racial attitudes and other variables such as stratification beliefs. Survey Two focused on perceptions of racial discrimination and justice, and included measures of racial prejudice and racial contact.

    Standard measures:

    Racial stereotyping
    Perceptions of injustice measured using Cantrill Ladder technique (both on Survey Two)

  15. u

    Care, Inequality and Wellbeing in Transnational Families in Europe,...

    • portalinvestigacion.udc.gal
    • datacatalogue.ukdataservice.ac.uk
    Updated 2025
    + more versions
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    Evans, Ruth; Mas Giralt, Rosa; Oso, Laura; Baby-Collin, Virginie; Suter, Brigitte; Souto, Andrea; Palash, Polina; Mozetic, Katarina; Limbu, Amrita; Walker, Grady; Dahdah, Assaf; Capstick, Tony; Lloyd-Evans, Sally; Evans, Ruth; Mas Giralt, Rosa; Oso, Laura; Baby-Collin, Virginie; Suter, Brigitte; Souto, Andrea; Palash, Polina; Mozetic, Katarina; Limbu, Amrita; Walker, Grady; Dahdah, Assaf; Capstick, Tony; Lloyd-Evans, Sally (2025). Care, Inequality and Wellbeing in Transnational Families in Europe, 2022-2024 [Dataset]. https://portalinvestigacion.udc.gal/documentos/682b0441e0cd0116a732ecee
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    Dataset updated
    2025
    Authors
    Evans, Ruth; Mas Giralt, Rosa; Oso, Laura; Baby-Collin, Virginie; Suter, Brigitte; Souto, Andrea; Palash, Polina; Mozetic, Katarina; Limbu, Amrita; Walker, Grady; Dahdah, Assaf; Capstick, Tony; Lloyd-Evans, Sally; Evans, Ruth; Mas Giralt, Rosa; Oso, Laura; Baby-Collin, Virginie; Suter, Brigitte; Souto, Andrea; Palash, Polina; Mozetic, Katarina; Limbu, Amrita; Walker, Grady; Dahdah, Assaf; Capstick, Tony; Lloyd-Evans, Sally
    Area covered
    Europe
    Description

    This research project investigated the relationships between care, inequalities and wellbeing among different generations of transnational families in the UK, Spain, France and Sweden.

    ‘Transnational families’ are family groups where one or more family members spend all or most of their time geographically separated across borders, but share a collective sense of connection as a ‘family’. This project established a new transnational interdisciplinary network across the four partner countries. The network built the capacity of migrants and practitioners through developing research skills and co-producing knowledge. It also built the capacity of early career and established academics through mutual learning in participatory and ethnographic approaches.

    The consortium facilitated comparative research that is influencing policy and practice changes to improve the equality and wellbeing of migrant carers of different generations. The research has shown that transnational families simultaneously manage multiple caring responsibilities, both proximately for family members, and by caring at a distance for kin living in other countries. Families’ opportunities and access to social protection are shaped by intersecting inequalities based on legal status, nationality, race and ethnicity, disability/chronic illness, socio-economic status, language-related inequalities, gender and generation.

    The physical and mental health, economic, social and emotional impacts of the COVID-19 pandemic were interlinked for migrants and led to the further marginalisation of transnational families, particularly those with insecure legal status and low socio-economic status. The deficits of migration and care regimes, alongside the absence of kin, create the need for children and youth to take on caring roles in transnational families. Children’s care work is often invisible, but may be crucial in enabling parents/relatives to fill gaps in care provision, facilitating access to public services through language and digital brokering. The accelerated shift towards digital technology becoming the primary gateway to access public services particularly affects older generations and those with low levels of literacy or language proficiency in the dominant societal language and increases the reliance on younger generations.

    The research highlighted several barriers to accessing affordable, appropriate and high-quality language education provision. Negative impacts of caregiving were evidenced among middle and younger generations in terms of their education, employment and finances, family relationships, social participation, health and wellbeing. Such impacts could have significant implications for carers’ long term opportunities and wellbeing, especially among transnational families with high care needs who were already facing financial hardships and insecurity.

    Policy recommendations focus on levelling out inequalities, expanding the definition of ‘family’ in reunification policies, recognising children’s care work in transnational families, making public services more accessible, welcoming and inclusive for migrant carers and their families.

    The findings across the four countries have been published in an open access Report (Summary also available in French, Spanish and Swedish), 4 Policy Briefs and 11 academic articles to date, 13 accessible film outputs and disseminated through regional workshops, an international Symposium and professional networks. We guest-edited a special issue of Population, Space and Place journal on ‘Intergenerational care, inequalities and wellbeing among transnational families in Europe’, which includes 5 papers based on the findings.

  16. s

    GCSE results (Attainment 8)

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Nov 7, 2024
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    Race Disparity Unit (2024). GCSE results (Attainment 8) [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/education-skills-and-training/11-to-16-years-old/gcse-results-attainment-8-for-children-aged-14-to-16-key-stage-4/latest
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    csv(490 KB), csv(138 KB)Available download formats
    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    In the 2022 to 2023 school year, pupils from the Chinese ethnic group had the highest Attainment 8 score out of all ethnic groups (65.5 out of 90.0).

  17. u

    Inequality in the American City : Census Data for Atlanta, Georgia, USA,...

    • datacatalogue.ukdataservice.ac.uk
    Updated Jan 1, 1981
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    Smith, D. M., University of London, Queen Mary College (1981). Inequality in the American City : Census Data for Atlanta, Georgia, USA, 1960-1970 [Dataset]. http://doi.org/10.5255/UKDA-SN-1463-1
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    Dataset updated
    Jan 1, 1981
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Authors
    Smith, D. M., University of London, Queen Mary College
    Time period covered
    Jan 1, 1960 - Jan 1, 1970
    Area covered
    United States
    Description

    To examine trends in race and space inequality in the American city of Atlanta, Georgia, over the 10 year period 1960 to 1970.

  18. g

    NCL Cancer Screening Inequality Analysis Camden Jan 2022 Report

    • gimi9.com
    • ckan.publishing.service.gov.uk
    Updated Jan 19, 2022
    + more versions
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    (2022). NCL Cancer Screening Inequality Analysis Camden Jan 2022 Report [Dataset]. https://gimi9.com/dataset/eu_ncl-cancer-screening-inequality-analysis-camden-jan-2022-report
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    Dataset updated
    Jan 19, 2022
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    New analysis on cancer screening inequality (January 2022) The Camden and Islington Public Health Intelligence team has recently completed an equity analysis to explore existing disparities in cancer screenings looking at the North Central London population groups before the COVID-19 pandemic. This analysis highlights the differences in both bowel screening coverage and cervical screening coverage between certain groups (for example, by gender, age, race/ethnicity and disability status) and GP practice level. There is also an association with deprivation, and lower bower screening coverage is seen in those who smoke, those who are obese, and those with a mental health condition (both depression or severe mental health). This analysis will help identify opportunities for local strategies and prevention to help improve overall cancer screening, and reduce inequity gaps.

  19. m

    Project online exhibition: Cultures of Anti-Racism in Latin America

    • figshare.manchester.ac.uk
    • figshare.com
    bin
    Updated Aug 7, 2023
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    Peter Wade; Ignacio Aguiló; Lúcia Sá; Carlos Correa Angulo; Ana Vivaldi; Jamille Pinheiro Dias (2023). Project online exhibition: Cultures of Anti-Racism in Latin America [Dataset]. http://doi.org/10.48420/23837169.v1
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    binAvailable download formats
    Dataset updated
    Aug 7, 2023
    Dataset provided by
    University of Manchester
    Authors
    Peter Wade; Ignacio Aguiló; Lúcia Sá; Carlos Correa Angulo; Ana Vivaldi; Jamille Pinheiro Dias
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Area covered
    Latin America
    Description

    The exhibition presents works by artists with whom we built up collaborative relationships during the project “Cultures of Anti-Racism in Latin America”. The project aimed to explore how artists in Argentina, Brazil and Colombia address racial diversity and how they use their art to challenge racism and deeply entrenched racial inequality. The project took place at a time when, despite recent policy shifts towards multiculturalism, racism was intensifying and becoming increasingly violent. Over about twelve months, overshadowed by the Covid pandemic, CARLA researchers developed collaborations with artists using diverse creative media, including painting, photography, dance, theatre, musical performance, poetry and performance.The artists we worked with in Brazil all self-identified as Indigenous. In Colombia, the artists mainly self-identified as Afro-Colombian or Black, but we also worked with artists who did not identify in these ways. In Argentina, we worked with Black and Mapuche Indigenous artists, but also with a collective whose members self-identified as marrón (brown, chestnut) and as descendants of Indigenous and peasant farmer ancestors.The exhibition is organised by country and, within each country section, by the artist or art collective, as follows:Argentina:Teatro en Sepia (Alejandra Egido)El Grupo de Teatro Mapuche “El Katango” (Miriam Alvarez and Lorena Cañuqueo)Identidad Marrón (including América Canela, Abril Carissimo, Flora Alvarado, Alejandro Mamani, Rebe López, David Gudiño, Daniela Ruiz, Euge Choque)Eskina Qom (Brian and Nahuel López)Brazil:Arissana PataxóNaine TerenaDenilson BaniwaJaider EsbellOwerá (previously known as Kunumi MC)Olinda Yawar TupinambaColombia:Corporación Cultural Afrocolombiana Sankofa DanzafroPedro BlasHanna RamírezAshanti DinahWilson BorjaLas Emperadoras de la Champeta (Mily Martinez Iriarte, Eucaris Torres Gutiérrez, Carmen Elena de Hoyos Pabuena, Natalia "Nativa" Díaz Padilla, Carmen Elena de Hoyos Pabuena, Margarita Cecilia García Villalba, Lidis Paternina, Erika Lucía Ochoa Durán, Diana Guardo Caraballo, Marcela Rocío Gómez Cortes, Leonor Moreno Palomino, Saray Lorduy Lombana)Margarita Ariza AguilarYeison RiascosLiliana Angulo CortésColectivo Aguaturbia (Liliana Angulo Cortés, Laura Asprilla Carrillo, Wilson Borja Marroquín, Paola Lucumi, Loretta M. Moreno, Natalia Mosquera Valencia, Leonardo Rua Puerta)Corporación Afrocolombiana de Desarrollo Social y Cultural – CARABANTÚ

  20. d

    Health Survey England Additional Analyses

    • digital.nhs.uk
    Updated Jul 6, 2021
    + more versions
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    (2021). Health Survey England Additional Analyses [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-england-additional-analyses
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    Dataset updated
    Jul 6, 2021
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 2011 - Dec 31, 2018
    Description

    This report presents findings on the health and health-related behaviours of the Lesbian, Gay and Bisexual (LGB) population in England. These are analysed by age, sex and ethnicity. The data are based on a representative sample of adults, aged 16 and over, who participated in the Health Survey for England from 2011–2018. 2% of adults surveyed in 2011-2018 identified as lesbian, gay or bisexual (LGB) The Health Survey for England series was designed to monitor trends in the health, and health related behaviours, of adults and children in England.

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Race Disparity Unit (2025). Persistent low income [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/pay-and-income/low-income/latest

Persistent low income

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11 scholarly articles cite this dataset (View in Google Scholar)
csv(81 KB), csv(302 KB)Available download formats
Dataset updated
Sep 17, 2025
Dataset authored and provided by
Race Disparity Unit
License

Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically

Area covered
United Kingdom
Description

Between 2019 and 2023, people living in households in the Asian and ‘Other’ ethnic groups were most likely to be in persistent low income before and after housing costs

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