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.

Graph and download economic data for Income Inequality in New London County, CT (2020RATIO009011) from 2010 to 2021 about New London County, CT; Norwich; inequality; CT; income; and USA.

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

Income Inequality in New London County, CT was 12.68979 Ratio in January of 2021, according to the United States Federal Reserve. Historically, Income Inequality in New London County, CT reached a record high of 13.63894 in January of 2018 and a record low of 10.80520 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in New London County, CT - last updated from the United States Federal Reserve on November of 2025.

The Mayor has a role to play in leading, shaping and responding to changes in London through the work of the GLA group. Inclusive London: the Mayor's equality, diversity and inclusion strategy sets out how he will help address the inequalities, barriers and discrimination experienced by groups protected by the Equality Act 2010, as well as wider issues. These include poverty and socio-economic inequality, and the challenges and disadvantage facing groups like young people in care, care leavers, single parents, migrants and refugees. This report, the equality, diversity and inclusion evidence base for London, informs the strategy. It presents evidence on London's diverse population, as well as the inequalities experienced by Londoners in areas such as housing, education, employment, transport, crime, health, social integration, culture and sport.

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.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in London, KY, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 8,406, while the mean income for the highest quintile (20% of households with the highest income) is 144,994. This indicates that the top earners earn 17 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 249,623, which is 172.16% higher compared to the highest quintile, and 2969.58% higher compared to the lowest quintile.

https://i.neilsberg.com/ch/london-ky-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in London, KY (in 2022 inflation-adjusted dollars))">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for London median household income. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in London. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In London, the median income for all workers aged 15 years and older, regardless of work hours, was $50,110 for males and $31,360 for females.

These income figures highlight a substantial gender-based income gap in London. Women, regardless of work hours, earn 63 cents for each dollar earned by men. This significant gender pay gap, approximately 37%, underscores concerning gender-based income inequality in the city of London.

- Full-time workers, aged 15 years and older: In London, among full-time, year-round workers aged 15 years and older, males earned a median income of $70,750, while females earned $49,242, leading to a 30% gender pay gap among full-time workers. This illustrates that women earn 70 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in London.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for London median household income by race. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in London. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In London, the median income for all workers aged 15 years and older, regardless of work hours, was $37,598 for males and $21,979 for females.

These income figures highlight a substantial gender-based income gap in London. Women, regardless of work hours, earn 58 cents for each dollar earned by men. This significant gender pay gap, approximately 42%, underscores concerning gender-based income inequality in the city of London.

- Full-time workers, aged 15 years and older: In London, among full-time, year-round workers aged 15 years and older, males earned a median income of $53,839, while females earned $41,732, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in London.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for London median household income by race. You can refer the same here

The Greater London Authority (GLA) commissioned the University of Manchester to conduct a rapid evidence review to document and understand the impact of COVID-19 (in terms of both health and the broader impacts on existing social and economic inequalities) on those with protected characteristics, as well as those living in poorer, or more precarious, socioeconomic circumstances, paying particular attention to its effect in London. The report provides the outcomes of the review, as well as a series of recommendations, which are focused on identifying tractable policy solutions in order to prevent, or mitigate, the inequalities in relation to protected characteristics and socioeconomic position that result from the COVID-19 pandemic and policy responses to it. Also available to download below is a spreadsheet documenting the formalised literature review searches.

Ratio of household equivalised income of the top 10 per cent of households to the income of the bottom 10 per cent of households. Ratio calculated using weekly household income adjusted to take account of differences in numbers and ages of residents. This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more. This dataset is one of the Greater London Authority's measures of Economic Development strategy. Click here to find out more.

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.

Percentage of total wealth owned by households in each decile for London and Great Britain. Data extracted from the ONS Wealth and Assets Survey (WAS) microdata. This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

See article methods section for description of calculated variables.

FOCUSONLONDON2010:HEALTH:CHILDRENANDYOUNGPEOPLE

The health and wellbeing of London’s children and young people is fundamental to the health of the city. The recent Marmot Review of health inequalities noted that “What a child experiences during the early years lays down the foundation for the whole of their life.” The Mayor’s Health Inequality Strategy for London responds to this by challenging all partners in London to create “conditions that lead to better early years experiences”.

This chapter, authored by colleagues at the London Health Observatory, provides recent evidence on the health experience of children and young people in London. The report includes data about the Local Index of Child Wellbeing, infant mortality, breastfeeding, immunisation, injury, childhood obesity, physical activity, diet, smoking, alcohol consumption, drug use, teenage conceptions and sexual health. It reveals many areas of inequality within the city, but also highlights the ways in which London’s children are doing well.

REPORT:

Access the full report in PDF format

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PRESENTATION:

This interactive presentation about children’s health in London looks into some of the factors that may have an effect on the high childhood obesity figures in London.

Access the presentation at Prezi.com

CHART:

This interactive scatterplot allows users to observe the relationship between some of the health indicators in the report with a selection of other socio-economic data for each of London’s 32 boroughs.

Scatterplot

RANKINGS:

An informative regional rankings scorecard has been created showing where London sits in relation to the other English regions on a number of indicators contained within the report.

Rankings

DATA:

All the data contained within the health report and used to create the scatterplot and rankings scorecard can be accessed in this spreadsheet.

FACTS:

Some interesting facts from the report…

● Five boroughs with highest teenage conception rates in 2008:

1. Lambeth – 71.5
2. Lewisham – 68.7
3. Southwark – 68.0
4. Greenwich – 66.7
5. Hackney and City of London – 61.5

-31. Richmond upon Thames – 23.6

-32. Harrow – 23.1

● The percentage of London women who smoke during pregnancy was lower than all other English regions, and around half the England average - one in 13 women in London and one in 7 nationally in 2008/09.

Other interesting facts from the Datastore…

● Five boroughs with the highest rates for children in Year 6 at risk of obesity 2008/09:

1. Southwark – 26.7%
2. Tower Hamlets – 25.7%
3. Lambeth – 25.3%
4. Newham – 24.6%
5. Barking and Dagenham – 24.2%

-31. Bromley – 16.0%

-32. Richmond-upon-Thames – 11.7%

● London has always had the lowest levels of children immunised by their second birthday against Measles, Mumps and Rubella (MMR) compared with other regions (since regional data was first available in 1988/89).

Highest – 87 per cent (1995/96) Lowest – 70 per cent (2003/04) Now – 76 per cent (2008/09)

● Five boroughs with the highest rates of hospital admissions due to injury of children (0-17) 2008/09:

1. Hackney – 126.2
2. Tower Hamlets – 123.1
3. Hammersmith and Fulham – 117.7
4. Islington – 115.0
5. Waltham Forest – 112.5

-31. Richmond upon Thames – 63.4

-32. Kingston upon Thames – 40.2

Premature mortality exhibits strong spatial patterns in Great Britain. Local authorities that are located further North and West, that are more distant from its political centre London and that are more urban tend to have a higher premature mortality rate. Premature mortality also tends to cluster among geographically contiguous and proximate local authorities. We develop a novel analytical research design that relies on spatial pattern recognition to demonstrate that an empirical model that contains only socio-economic variables can eliminate these spatial patterns almost entirely. We demonstrate that socioeconomic factors across local authority districts explain 81 percent of variation in female and 86 percent of variation in male premature mortality in 2012–14. As our findings suggest, policy-makers cannot hope that health policies alone suffice to significantly reduce inequalities in health. Rather, it requires strong efforts to reduce the inequalities in socio-economic factors, or living conditions for short, in order to overcome the spatial disparities in health, of which premature mortality is a clear indication.

The attached file includes data and code used to analyse population scaling and house size in the ancient Near East.

In 2023, the gross domestic product per capita in London was 63,618 British pounds, compared with 37,135 pounds per capita for the United Kingdom as a whole. Apart from London, the only other region of the UK that had a greater GDP per capita than the UK average was South East England, at 38,004 pounds per capita. By contrast, North East England had the lowest GDP per capita among UK regions, at 26,347 pounds. Regional imbalance in the UK economy? London's overall GDP in 2022 was over 508 billion British pounds, which accounted for almost a quarter of the overall GDP of the United Kingdom. South East England had the second-largest regional economy in the country, with a GDP of almost 341.7 billion British pounds. Furthermore, these two regions were the only ones that had higher levels of productivity (as measured by output per hour worked) than the UK average. While recent governments have recognized regional inequality as a major challenge facing the country, it may take several years for any initiatives to bear fruit. The creation of regional metro mayors across England is one of the earliest attempts at giving regions and cities in particular more power over spending in their regions than they currently have. UK economy growth slow in late 2024 After ending 2023 with two quarters of negative growth, the UK economy grew at the reasonable rate of 0.8 percent and 0.4 percent in the first and second quarters of the year. This was, however, followed by zero growth in the third quarter, and by just 0.1 percent in the last quarter of the year. Other economic indicators, such as the inflation rate, fell within the expected range in 2024, but have started to rise again, with a rate of three percent recorded in January 2025. While unemployment has witnessed a slight uptick since 2022, it is still at quite low levels compared with previous years.

BackgroundNeglected tropical diseases (NTDs) are generally assumed to be concentrated in poor populations, but evidence on this remains scattered. We describe within-country socioeconomic inequalities in nine NTDs listed in the London Declaration for intensified control and/or elimination: lymphatic filariasis (LF), onchocerciasis, schistosomiasis, soil-transmitted helminthiasis (STH), trachoma, Chagas’ disease, human African trypanosomiasis (HAT), leprosy, and visceral leishmaniasis (VL).MethodologyWe conducted a systematic literature review, including publications between 2004–2013 found in Embase, Medline (OvidSP), Cochrane Central, Web of Science, Popline, Lilacs, and Scielo. We included publications in international peer-reviewed journals on studies concerning the top 20 countries in terms of the burden of the NTD under study.Principal findingsWe identified 5,516 publications, of which 93 met the inclusion criteria. Of these, 59 papers reported substantial and statistically significant socioeconomic inequalities in NTD distribution, with higher odds of infection or disease among poor and less-educated people compared with better-off groups. The findings were mixed in 23 studies, and 11 studies showed no substantial or statistically significant inequality. Most information was available for STH, VL, schistosomiasis, and, to a lesser extent, for trachoma. For the other NTDs, evidence on their socioeconomic distribution was scarce.The magnitude of inequality varied, but often, the odds of infection or disease were twice as high among socioeconomically disadvantaged groups compared with better-off strata. Inequalities often took the form of a gradient, with higher odds of infection or disease each step down the socioeconomic hierarchy. Notwithstanding these inequalities, the prevalence of some NTDs was sometimes also high among better-off groups in some highly endemic areas.ConclusionsWhile recent evidence on socioeconomic inequalities is scarce for most individual NTDs, for some, there is considerable evidence of substantially higher odds of infection or disease among socioeconomically disadvantaged groups. NTD control activities as proposed in the London Declaration, when set up in a way that they reach the most in need, will benefit the poorest populations in poor countries.

This project investigated UK secondary school students’ views of inequality and their sense of agency concerning their occupational prospects, using questionnaire and interview data. The data came from 78 students from three secondary schools in England between Year 7 and Year 13 who were aged between 12 and 19. The three schools were in areas with different socioeconomic characteristics – an affluent town in the London commuter belt (School A), a city in the east of England (School B) and a town to the east of London (School C). School A had a lower than national average free school meals (FSM) rate, whereas both School B and School C had a higher than national average FSM rate.

18 participants were from School A, 38 from School B and 22 from School C. While all 18 students in School A and all 22 students in School C participated in both the questionnaire and follow-up interview stages, in School B 37 participants filled in the questionnaire and, of these, 22 took part in the interviews. One student from School B who did not fill in a questionnaire took part in the interview, making the total interviews from School B 23. One student from School C did not want to have their interview audio-recorded; therefore, their interview transcript does not exist.

As a result, the dataset in total contains 77 questionnaires and 62 interview transcripts. The PDF files are questionnaire files and the word document files are interview transcripts. A file name (for both the pdf files and word document files) begins with ‘Y’ that is followed by a number which indicates a school year and this is followed by two letters that indicate a code for an individual participant, while the letter A, B or C immediately after a hyphen indicates School A, B or C respectively.