According to a survey conducted in the United Kingdom (UK) in 2021, ** percent of people thought it is important that the government addresses health differences due to income, while a further ** percent thought it is important to address health differences due to geographical areas.

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 March 2023 update, data has been updated for deaths, hospital admissions and vaccinations. Data on inequalities in vaccination uptake within upper tier local authorities has been added to the tool for the first time. This replaces data for lower tier local authorities, published in December 2022, allowing the reporting of a wider range of inequality breakdowns within these areas.

Please send any questions or comments to PHA-OHID@dhsc.gov.uk

Rates of mortality involving cancers, cardiovascular diseases, chronic kidney disease, dementia, diabetes, and respiratory diseases, by Census 2021 variables. Experimental Statistics.

Health inequalities are the differences in health and wellbeing, risk or outcomes, between different groups of people. Tackling health inequalities requires knowledge about the factors affecting health. With input from key stakeholders we selected 12 indicators of health and the wider determinants of health which we will monitor over time. These indicators will improve our understanding of health inequalities.

Go to Tackling London’s Health Inequalities for more information on the HIS Health Inequalities Strategy and the Indicators.

Data and Resources

The most recent data for each indicator will be available for download below:

Overall measures of health inequality:

1. Slope Index of Inequality for Life Expectancy
2. Healthy Life Expectancy
3. Self-reported wellbeing:
   1. Happiness
   2. Life Satisfaction
   3. Worthwhileness
   4. Anxiety

More specific measures of health inequality:

1. School Readiness at age 5
2. Educational Achievement - Percentage of pupils achieving 5 or more GCSEs at grades A*-C (including English and Maths)
3. Antenatal late booking - Percentage of pregnant women booking after 12wks +6 days
4. Flu vaccination proportion of those >65 years and of those at risk
5. Vulnerable road user risk of fatality or serious injury
6. Homelessness
   1. Statutory homelessness
   2. Homelessness prevention
   3. Change in number of rough sleepers
7. Proportion of employees receiving lower income than the London Living Wage
8. Unemployment rates – model-based estimates; proportion of resident population
9. Childhood obesity - Proportion of children aged 4-5 classified as overweight or obese.

This release presents trends in estimates of mortality rates for males and females of working age in English regions and Wales, from 2001-03 to 2008-10, calculated using population denominators derived from the Labour Force Survey (LFS). The analysis is based on the seven class reduced National Statistics Socio-economic Classification (NS-SEC).

Source agency: Office for National Statistics

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Health Inequalities

Life expectancy (LE), healthy life expectancy (HLE), disability-free life expectancy (DFLE), Slope Index of Inequality (SII) and range by national deprivation deciles using the Index of Multiple Deprivation 2015 for data periods from 2011 to 2013 to 2015 to 2017, and the Index of Multiple Deprivation 2019 for data periods from 2016 to 2018 to 2018 to 2020: England, 2011 to 2013 to 2018 to 2020.

The Mayors Health Inequalities Strategy sets out his plans to tackle unfair differences in health to make London a healthier, fairer city. This dataset reports the 14 headline population health indicators that will be used to monitor London’s progress in reducing health inequalities over the next ten years. The themes of the indicators are listed below. The measures will monitor an identified inequality gap between defined populations. 1. Healthy life expectancy at birth – male 2. Healthy life expectancy at birth – female 3. Children born with low birth weight 4. School readiness among children 5. Excess weight in children at age 10-11 (year 6) 6. Excess mortality in adults with serious mental illness 7. Suicide 8. Mortality caused by Particulate Matter (PM2.5) 9. Employment 10. Feeling of belonging to a community (provisional) 11. HIV late diagnosis 12. People diagnosed with TB 13. Adults walking or cycling for two periods of ten minutes each day 14. Smoking

Creative Insights is a research project focused on exploring young people’s perspectives on health inequalities, particularly their ideas for potential solutions. In 2018, the project was conceived as a partnership between researchers at University of Glasgow’s MRC/CSO Social and Public Health Sciences Unit and CoSS, and community organisations Impact Arts in Glasgow and Leeds Playhouse that would involve dynamic face-to-face workshops with artists, young people and researchers working together to develop research and creative outputs with a message for policymakers. In practice, the onset of the pandemic switched the focus to delivering all aspects of the project online, including focus group discussions, workshop activities, and individual and collaborative art-making. As such, the data included in this collection comprises transcripts of Zoom recordings and the final artworks presented by each of the young participants. Focus group discussions focused on various themes relating to health inequalities and their potential solutions, with descriptions of prompts and activities detailed in the topic guides.

This is a monthly report on publicly funded community services for people of all ages using data from the Community Services Data Set (CSDS) reported in England for April 2025. It has been developed to help achieve better outcomes and provide data that will be used to commission services in a way that improves health, reduces inequalities, and supports service improvement and clinical quality. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. More information about experimental statistics can be found on the UK Statistics Authority website (linked at the bottom of this page). A provisional data file for May 2025 is now included in this publication. Please note this is intended as an early view until providers submit a refresh of their data, which will be published next month.

Life expectancy (LE), healthy life expectancy (HLE), disability-free life expectancy (DFLE), Slope Index of Inequality (SII) and range at birth and age 65 by national deprivation deciles (IMD 2015 and IMD 2019), England, 2011 to 2019.

Description

This data companion pack is a resource intended to frame and be read alongside the linked Evidence Review: Housing and Health Inequalities in London (available on the Institute of Health Equity website) .

The resource provides intelligence and context on the housing and health inequalities in London only, while the accompanying rapid review of evidence for interventions contains the recommendations for action.​

1. This pack is intended to provide a high-level overview of the best available data on housing in London and the key housing-related health inequalities issues faced by Londoners, in correlation with the IHE Evidence Review: Housing and Health Inequalities in London.​
2. This pack identifies how certain groups in the population are at greatest risk of housing-related health inequalities, as well as noting gaps in available data for particularly excluded groups.
3. The pack provides a platform for partnership work on housing-related health inequalities across London, including providing an overview of key issues, and identifying key gaps in intelligence that would help improve understanding of housing-related inequalities across the capital. ​

Audience

It will be useful for health leaders, analysts, officers, and policy makers from local and regional government, integrated care systems, and more, to address ​housing-related health inequalities by -

• Advocating for the need for action to address housing inequalities, given impacts on health and health inequalities ​
• Framing the context for the interventions highlighted in the linked rapid review of interventions​
• Engaging communities ​

​Development of this resource

The Institute of Health Equity (IHE), Greater London Authority (GLA) Health, GLA City Intelligence Unit, Office for Health Improvement and Disparities London (OHID), Association of Directors of Public Health London (ADPH), and NHSE have collaboratively produced this report, as part of the Building the Evidence (BTE) programme of work

• The sources of data available and topics included have been identified from existing published data, working in partnership through iterative discussion
• The resource is provided in PDF and PowerPoint format to support colleagues in their work to
• There is no current plan for periodic updates of this resource, though this will be discussed on completion of this programme of work

Other useful resources:

• The Integrated Care Systems (ICS) Housing Profile is a resource that aims to support people working in ICSs and ICBs to understand, and work jointly with partners to mitigate and tackle the key housing-related issues that drive poor health in London.

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. South East London Community Health (SELCoH) study is a follow up study of the community psychiatric and physical morbidity of adults, age 16 years and over from randomly selected households in the south London boroughs of Southwark and Lambeth. Participants were identified through use of the random household sampling as described and used for the Household Survey of the National Survey of Psychiatric morbidity (1). The sample is stratified across the two boroughs to ensure a similar sample size for each area. Individuals were eligible for participation providing they lived in a household in the catchment area. No further exclusion criteria applied. Recruitment for phase 1 (hereafter SELCoH-I), was done between 2008 and 2010, with the final data-set containing information on 1698 adults, aged between 16 and 90 years, from 1075 randomly selected households across two London boroughs. Further details on SELCoH’s organisation, sample and procedures may be found elsewhere (2). Most (94%) of the SELCoHI study participants agreed to be contacted for future studies. The second phase of SELCoH (hereafter SELCoH-II) is a coordinated follow up of participants that participated in the SELCoHI who have agreed to be followed up. This study is also shared with the study entitled, ‘An Health Disparities Study of Discrimination & Disparities in Health & Health Service Use in the UK and US (Health Disparities study) for which the UK sample is drawn from SELCoH I. Thus SELCoHII aimed to update the locally relevant prevalence estimates and to investigate the influence of deleterious experiences across different demographic groups. Recruitment of SELCoH study participants began by sending a letter describing the study. This was sent two weeks in advance of interviewers visiting a household. During each household visit, interviewers attempted contact with a resident. Where contact was achieved, potential participants were given study information, reminded that their continued engagement was voluntary and, where possible, scheduled for an in-home interview. A maximum of four contact attempts (inclusive of any messages and/or home visits) were permitted per eligible individual. Closely supervised, trained interviewers conducted face-to-face interviews with computer assisted interview schedules. The survey questionnaire collected information on the following topics: (1) demographics; (2) migration; (3) socioeconomic status (SES); (4) ethnic identity (5)work attitude and experience (6) psychosocial factors (e.g., social support); (7) neighbourhood characteristics; (8) social adversity; (9) health behaviours; (10) physical and mental health status; (11) treatment and health service use; (12) access to technology; (13) the experience of unfair treatment and discrimination; (14) coping methods; (15) wellbeing. Translators employed by the SLAM NHS Trust were used in interviews with non-English speaking adults upon request. Participants were able to end the interview at any time and compensated for their time. We also provided an option to do a telephone interview for participants who moved out of London. References 1. Jenkins R, Bebbington P, Brugha T, Farrell M, Gill B, Lewis G, Meltzer H, Petticrew M: The National Psychiatric Morbidity surveys of Great Britain-strategy and methods. Psychological Medicine 1997, 27(4): 765-774. 2. Hatch SL, Frissa S, Verdecchia M, Stewart R, Fear NT, Reichenberg A, Morgan C, Kankulu B, Clark J, Gazard B, Medcalf R, the SELCoH study team, Hotopf M: Identifying socio-demographic and socioeconomic determinants of health inequalities in a diverse London community: the South East London Community Health (SELCoH) study. BMC Public Health (2011) 11:861

Life expectancy (LE), healthy life expectancy (HLE), disability-free life expectancy (DFLE) by national deprivation deciles (IMD 2015 and IMD 2019), England: 2011 to 2019.

Life expectancy (LE), healthy life expectancy (HLE), disability-free life expectancy (DFLE), Slope Index of Inequality (SII) and range at birth and age 65 years by national deprivation deciles (WIMD 2014 and WIMD 2019), Wales, 2011 to 2019.

While London tends to have better health outcomes than the rest of the UK, stark ethnic and socioeconomic inequalities remain.

The Snapshot of Health Inequalities in London provides a high-level overview of major inequalities issues affecting Londoners with thematic packs on climate, children and young people, and the cost of living.

This is a resource intended to inform health and non-health specialists. It will inform action on health inequalities across all strategies, policies and programmes, supporting a health in all policies approach.

Webinar

‘Exploring the London Snapshot of Health Inequalities’ webinar presents the key findings followed by a panel discussion, covering five priority areas:

1. Child health equity
2. Cardiovascular health
3. Mental health
4. Poverty and economy
5. Climate and environment

Watch the webinar here.

Development of the resource

Greater London Authority (GLA) Health, GLA City Intelligence Unit, Office for Health Improvement and Disparities London (OHID), Association of Directors of Public Health London (ADPH), NHSE and Institute of Health Equity (IHE) have collaboratively produced this report.

The snapshot brings together published data. The topics and themes have been identified with partners through iterative discussion.

Originally published in 2022, this updated and expanded version was published in July 2024.

NHS-funded Community Services for children and young people aged 18 years or under using data from the new Children and Young People's Health Services (CYPHS) data set reported in England. The CYPHS is a patient-level dataset providing information relating to NHS-funded community services for children and young people aged 18 years or under. These services can include health centres, schools and mental health trusts. The data collected includes personal and demographic information, diagnoses including long-term conditions and childhood disabilities and care events plus screening activities.

It has been developed as part of the Maternity and Children's Data Set (MCDS) Project to achieve better outcomes of care for children and young people. It provides data that will be used to improve clinical quality and service efficiency, in a way that improves health and reduces inequalities.

These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. They are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. More information about experimental statistics can be found on the UK Statistics Authority website.

Annual age-standardised and age-specific mortality rates by indices of deprivation for England and Wales (Experimental Statistics).

Contemporary public health and healthcare are navigating a complex landscape marked by limited resources, conflicting individual and collective preferences, and the challenge of improving efficiency while maintaining quality. This scenario raises a multitude of ethical and moral questions, necessitating state intervention through stewardship and governance. Governments worldwide strive to enhance utility, value for money, and health equity, guided by principles of distributive and procedural justice. The moral underpinnings of public health activities, such as overall benefit, collective efficiency, distributive fairness, and harm prevention, are crucial in addressing global health resource challenges. These considerations encompass efficiency, equity, rights, and other ethical issues. The distribution of resources, whether based on noncorrelative or correlative principles, is a key aspect of justice in public health. Public health efforts are also focused on mitigating the adverse effects of socio-economic determinants on health outcomes and addressing health disparities. This is particularly vital for vulnerable, high-risk, and marginalized groups who face unique challenges like historic injustices, discrimination, and specific social or physical needs. The project at hand delves into the concepts outlined by Peragine, focusing on measuring individual opportunity sets, assessing inequality in opportunity distribution, and designing mechanisms to enhance 'opportunity equality'. A representative survey of Vienna's population (N=1411) explores various dimensions: Socio-demography: This module gathers data on gender, age, education, and migration background. Health: It assesses individual health status, chronic conditions, multimorbidity, and health-related behaviors. Socio-economic status: This includes occupation, net income, asset wealth, and other indicators of social or economic capital. Access to healthcare: Respondents provide insights into their experiences with healthcare access, including barriers and needs. Affordability of healthcare: Questions revolve around health-related expenditures and attitudes towards healthcare coverage and benefits. Provision of healthcare: This focuses on the quality and timeliness of medical interventions and healthcare services. Justice-Fairness attitudes: The survey captures attitudes towards social/distributive justice and fairness in socio-economic and health-related aspects. Preferences for health policy and redistribution: This module explores public vs. private health insurance preferences and allocation preferences for the public health budget. Solidarity & Reciprocity: Estimating solidarity through measures of social trust, cooperative behavior, sharing, helping, and expressions of solidarity. Overall, this comprehensive approach aims to address the intricate interplay of ethical, moral, and practical considerations in public health and healthcare, emphasizing the need for equitable and just solutions in a resource-constrained environment.