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.

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

Unequal impact of COVID-19: BAME disproportionality This slide pack covers the latest PHE and ONS data, national and local, showing diagnosis and death rates by deprivation, underlying conditions and ethnicity (note: these analyses did not account for the effect of occupation, co-morbidities or obesity).

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

Unequal impact of COVID-19: BAME disproportionality Camden Demographics of Shielded Population by location age ethnicity deprivation gender GPs and reason for shielding.

First annual update of the set of headline indicators recommended in the Equally Well report of the ministerial task force on health inequalities. Source agency: Scottish Government Designation: Official Statistics not designated as National Statistics Language: English Alternative title: Long-Term Monitoring of Health Inequalities

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.

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.

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 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.

Unequal impact of COVID-19: BAME disproportionality Further analyses of death registration data and 2011 census data .

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. Healthy life expectancy at birth – male Healthy life expectancy at birth – female Children born with low birth weight School readiness among children Excess weight in children at age 10-11 (year 6) Excess mortality in adults with serious mental illness Suicide Mortality caused by Particulate Matter (PM2.5) Employment Feeling of belonging to a community (provisional) HIV late diagnosis People diagnosed with TB Adults walking or cycling for two periods of ten minutes each day Smoking

Healthy life expectancy at birth by groupings of LSOAs into national deciles of area deprivation.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Inequality in Healthy Life Expectancy at birth by national deciles of area deprivation: England

This slide deck includes a short briefing which summarises key findings from the full analysis ‘Health inequality:’ Closing the life expectancy gap over time?’ for both Camden and Islington.

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.

This publication signposts to a range of information relating to a range of Public Health Statistics on Alcohol, Drug Misuse, Obesity, Physical Activity, Diet and Smoking. The publication is broken down by data source and within that the domains as follows: Part 1: Hospital Admissions - sourced from the Office for Health Improvement and Disparities (OHID). Part 2: Mortality - sourced from the Office for Health Improvement and Disparities (OHID). Part 3: Prescriptions - sourced from the NHS Business Services Authority (NHS BSA). Part 4: Affordability and Expenditure - sourced from the Office for Health Improvement and Disparities (OHID). Part 5: Other Data Sources.