In 2022, the gross domestic product per capita in London was 57,338 British pounds, compared with 33,593 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 36,425 pounds per capita. By contrast, North East England had the lowest GDP per capita among UK regions, at 24,172 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.

This dataset is published as Open DataScottish Index of Multiple Deprivation, Small Area Population Estimates, and Child Poverty The Scottish Index of Multiple Deprivation 2020 is the Scottish Government’s official tool for identifying those places in Scotland suffering from deprivation. It incorporates several different aspects of deprivation (employment, income, health, education, skills and training, geographic access, crime and housing), combining them into a single index.The 2020 Index provides a relative ranking for small areas in Scotland, defined by the Scottish Neighbourhood Statistics (SNS) Data Zone 2011 geography, from 1 (most deprived) to 6,976 (least deprived). By identifying small areas where there are concentrations of multiple deprivation, the SIMD can be used to target policies and resources at the places with greatest need. The SIMD also provides a rank for each data zone within each of the seven domains, and therefore it is possible to look at individual aspects of deprivation for each area, as well as the overall level of deprivation.National Records of Scotland Small Area Population Estimates (2021)Child Poverty by Datazone (2022/23)

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.

Summary measures at ward level of the Indices of Deprivation (ID) 2007.

NOTE: The ward summary for ID2010 can be found on the ID2010 page.

The Government's Indices of Deprivation are produced for small areas across England. Summary measures of the Index of Multiple Deprivation (IMD) are published for local authorities. This dataset gives GLA calculations giving, as far as possible, comparable summary measures for wards in London. It also includes GLA calculations giving the two supplementary indices at ward level.

The purpose is to replicate, as far as possible, the local authority level measures published by CLG and gives alternative and additional measures, including a ward level version of the Income Deprivation Affecting Children Index (IDACI) and the Income Deprivation Affecting Older People Index (IDAOPI). The scores and ranks within London are given, with a rank of 1 denoting the most deprived out of a total of 628 wards in London, with the City of London grouped into four areas, only the first ward of which is named.

The ward level summary measures replicating those at LA level produced here are:
-Average of SOA Scores
-Average of SOA Ranks
-Extent
-The Income Scale
-The Employment Scale

The LA level Concentration measure cannot be sensibly reproduced at ward level, since it is based on ten per cent of the area’s population, which is in most cases less than a single SOA. Instead, a summary measure Highest ranked SOA in ward has been included.

Additionally, this Briefing includes the total number of SOAs in each ward and gives a count of how many SOAs are included among the more deprived areas in England. Four such counts are given – the five per cent most deprived, ten per cent, 20 per cent and 50 per cent, or above average.

In 2018 Turkey had the largest disparity between it's richest and poorest small regions in Europe, in terms of GDP per capita. The richest small regions in Turkey are estimated to have 3.5 times the GDP per capita of poor regions, with Hungary and the United Kingdom also displaying significant regional disparities.

This shows fuel poor households as a proportion of all households in the geographical area (modelled) using the Low Income Low Energy Efficiency (LILEE) measure. Since 2021 (2019 data) the LILEE indicator considers a household to be fuel poor if: it is living in a property with an energy efficiency rating of band D, E, F or G as determined by the most up-to-date Fuel Poverty Energy Efficiency Rating (FPEER) methodologyits disposable income (income after housing costs (AHC) and energy needs) would be below the poverty line. The Government is interested in the amount of energy people need to consume to have a warm, well-lit home, with hot water for everyday use, and the running of appliances. Therefore, fuel poverty is measured based on required energy bills rather than actual spending. This ensures that those households who have low energy bills simply because they actively limit their use of energy at home, Fuel poverty statistics are based on data from the English Housing Survey (EHS). Estimates of fuel poverty at the regional level are taken from the main fuel poverty statistics. Estimates at the sub-regional level should only be used to look at general trends and identify areas of particularly high or low fuel poverty. They should not be used to identify trends over time.Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Out of all OECD countries, Cost Rica had the highest poverty rate as of 2022, at over 20 percent. The country with the second highest poverty rate was the United States, with 18 percent. On the other end of the scale, Czechia had the lowest poverty rate at 6.4 percent, followed by Denmark.

The significance of the OECD

The OECD, or the Organisation for Economic Co-operation and Development, was founded in 1948 and is made up of 38 member countries. It seeks to improve the economic and social well-being of countries and their populations. The OECD looks at issues that impact people’s everyday lives and proposes policies that can help to improve the quality of life.

Poverty in the United States

In 2022, there were nearly 38 million people living below the poverty line in the U.S.. About one fourth of the Native American population lived in poverty in 2022, the most out of any ethnicity. In addition, the rate was higher among young women than young men. It is clear that poverty in the United States is a complex, multi-faceted issue that affects millions of people and is even more complex to solve.

This dataset contains the main ranking for the Index of Multiple Deprivation, 2007. This dataset puts the 32,482 LSOAs into a rank order based on their 2007 IMD score. A rank of 1 is the most deprived.

The English Indices of Deprivation provide a relative measure of deprivation at small area level across England. Areas are ranked from least deprived to most deprived on seven different dimensions of deprivation and an overall composite measure of multiple deprivation. Most of the data underlying the 2007 indices are for the year 2005.

The indices have been constructed by the Social Disadvantage Research Centre at the University of Oxford for the Department for Communities and Local Government. All figures can only be reproduced if the source (Department for Communities and Local Government, Indices of Deprivation 2007) is fully acknowledged.

The domains used in the Indices of Deprivation 2007 are: income deprivation; employment deprivation; health deprivation and disability; education deprivation; crime deprivation; barriers to housing and services deprivation; and living environment deprivation. Each of these domains has its own scores and ranks, allowing users to focus on specific aspects of deprivation.

Because the indices give a relative measure, they can tell you if one area is more deprived than another but not by how much. For example, if an area has a rank of 40 it is not half as deprived as a place with a rank of 20.

The Index of Multiple Deprivation was constructed by combining scores from the seven domains. When comparing areas, a higher deprivation score indicates a higher proportion of people living there who are classed as deprived. But as for ranks, deprivation scores can only tell you if one area is more deprived than another, but not by how much.

This dataset was created from a spreadsheet provided by the Department of Communities and Local Government, which can be downloaded here.

The method for calculating the IMD score and underlying indicators is detailed in the Guidance document.

The data is represented here as Linked Data, using the Data Cube ontology.

Abstract

The Born in Bradford study is tracking the health and wellbeing of over 13,500 children, and their parents born at Bradford Royal Infirmary between March 2007 and December 2010.

Documentation

Born in Bradford is a prospective pregnancy and birth cohort established to examine how genetic, nutritional, environmental, behavioral and social factors affect health and development during childhood, and subsequently adult life, in a deprived multi-ethnic population. It was developed in close consultation with local communities, clinicians and policy makers with commitment from the outset to undertake research that would both inform interventions to improve health in the city and generate robust science relevant to similar communities in the UK and across the world. Between 2007 and 2011 information on a wide range of characteristics were collected from 12,453 women (and 3,356 partners) who experienced 13,778 pregnancies and delivered 13,818 live births.

Source

Notes

Data Presentation: Born in Bradford Data

Born in Bradford Data Dictionary

Born in Bradford has a number of unique strengths: a) Composition. Half of all the families recruited are living in the UK’s most deprived wards, and 45% are of Pakistani origin. Half of Pakistani-origin mothers and fathers were born outside the UK and over half are related to their partner. This combination enhances the opportunity to study the interplay of deprivation, ethnicity, migration and cultural characteristics and their relationship to social, economic and health outcomes research relevant to many communities across the world.

b) Rich characterization. Detailed information has been collected from parents about demographic, economic, lifestyle, cultural, medical and health factors. Pregnancy oral glucose tolerance tests (OGTT), have been completed in 85% of the cohort and in combination with repeat fetal ultrasound data and subsequent follow-up growth and adiposity (repeat skinfolds, weight and height from birth to current age) will enable BiB uniquely to explore ethnic differences in body composition trajectories through infancy and childhood.

c) Genetic and biomarker data. Maternal, neonatal and follow-up child blood samples have provided biomarker measures of adiposity and immunity, together with stored samples, for which funding has been secured, to assess targeted NMR metabolites in maternal pregnancy fasting samples, cord-blood and infant samples taken at 12-24 months. Genome wide data is available for 9000+ mothers and 8000+ children and funding has been secured for DNA methylation of 1000 mother-child pairs. Our BiB biobank contains 200,000 stored samples.

d) System-wide coverage. The study has successfully linked primary and secondary care, radiology, laboratory and local authority data. This successful data linkage to routine health and education data will allow life-time follow up of clinical outcomes for BiB children and their parents, and educational attainment for children.

e) Community involvement. Close links with members of the public and particularly with cohort members allow the co-production of research in terms of the identification of research questions, monitoring the demands research makes on participants and discussion of the implementation of findings. The study has strong community roots and city-wide support.

Full details of the cohort and related publications can be found on the website

Patient characteristics Children born in the city of Bradford Claims years: 2007-2011 12,453 women with 13,776 pregnancies and 3,448 of their partners Cord blood samples have been obtained and stored and DNA extraction on 10,000 mother\offspring pairs. Sex: Adults: 12,453 women, 3,448 males

Application

If you are interested in working with these data, the application packet, with examples, can be found here: Born in Bradford Application Packet

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by long-term health problems or disabilities, sex, age and level of deprivation. The estimates are as at Census Day, 21 March 2021. Age-standardisation allows for comparisons between populations that may contain proportions of different ages.

This aggregate-level dataset links poor relief data recorded on 1 January 1891 with several variables from corresponding 1891 census data, all at the level of the registration district (RD). Specifically, the numbers of men and women receiving indoor and outdoor relief in the ‘non-able-bodied’ category (taken as a proxy of the numbers of older-age men and women on relief) are accompanied with a series of socio-economic variables calculated from census data on the population aged 60 years and over (our definition of ‘old age’). Thus, the dataset fulfils two objectives: 1. To start reconciling poor relief data from the House of Commons Parliamentary Papers archive with transcribed Integrated Census Microdata (I-CeM) available at the UK Data Service (UKDS). 2. To capture geographical variations in the proportion of older-age men and women on poor relief as well as in several household, occupational and migratory compositions recorded in the census, consulting data from 1891 as a pilot study in anticipation of an extended project covering all censuses from 1851-1911.The study of old age in history has generally had a narrow focus on welfare needs. Specific studies of the extreme poverty, or pauperism, of older people in late nineteenth-century London by Victorian contemporary Charles Booth (1840-1916) have remained remarkably influential for historical research on old age (Booth, 1894; Boyer and Schmidle, 2009). Old age is also examined through institutional care, particularly workhouse accommodation (Lievers, 2009; Ritch, 2014), while the subgroup of the elderly population that were not poor has been underexplored. However, my PhD thesis shows that pauperism was not a universal experience of old age between 1851 and 1911. Using transcribed census data for five selected counties in England and Wales, I find that pauperism was contingent upon many socio-economic factors recorded in census datasets, such as the occupational structure of older people, their living arrangements and their capacity to voluntarily retire from work based on their savings, land and capital. I find that, in some districts of the northern counties of Cheshire and the Yorkshire West Riding, the proportion of men described in the census as 'retired' and the proportion of women 'living on their own means' was greater than the respective proportions of men and women on welfare. For elderly men in particular, there were regional differences in agrarian work, where those in northern England are more likely to run smallholding 'family farms' whereas, in southern England, elderly men generally participate as agricultural labourers. I find that these differences play an important part in the likelihood of becoming pauperised, and adds to the idea of a north-south divide in old age pauperism (King, 2000). Furthermore, pauperism was predicated on the events and circumstances of people throughout their life histories and approaching their old age. My fellowship will enable me to expand upon these findings through limited additional research that stresses an examination of the experiences of all older people in England and Wales. Old age has to be assessed more widely in relation to regional and geographical characteristics. In this way, we refine Booth's London-centric focus on the relationship between poverty and old age. My fellowship will achieve these objectives by systematically tracing the diversity of old age experiences. A pilot study will link welfare data recorded on 1 January 1891 from the House of Commons Parliamentary Papers archive with the socio-economic indicators contained in the 1891 census conducted on 5 April, all incorporated at the level of c. 650 registration districts in England and Wales. I will also visit record offices to extract data on the names of older people recorded as receiving welfare in materials related to the New Poor Law, thereby expanding on the PhD's examination of the life histories of older people. With the key findings from my PhD presented above, I will spend my time addressing a wider audience on my research. As I will argue in blogs and webinars addressed to Age UK, the International Longevity Centre UK and History and Policy, a monolithic narrative of old age as associated with welfare dependency and gradual decline has been constructed since Booth's research in the late nineteenth century. This narrative has remained fixed through the growth of our ageing population, and the development of both old age pensions and the modern welfare state. My research alternatively uses historical censuses that reveal the economic productivity of older people in a manner that is not satisfactorily captured in present day discourse. I will also receive training on how to address my PhD to local schools, through the presentation of maps that present variations in the proportions of older people receiving welfare, and in the application of transcribed census data. Data on the numbers of 'non-able-bodied' men and women receiving outdoor and indoor relief on 1 January 1891 (taken as a proxy for the numbers in old age receiving welfare on this date) by Poor Law Union (648) are then converted to the numbers by corresponding Registration District (630). They are linked with several socio-economic variables involving the numbers of men and women aged 60 years and over in the 1891 census. Further information on this is in the User Guide.

This statistic displays the proportion of individuals with fair and poor eyesight in England in 2013, by gender and region. Of survey respondents, 12 percent of men and 11 percent of women living in the North East of England had fair or poor eyesight.

The English Indices of Deprivation 2010 provide a relative measure of deprivation at small area level across England. Areas are ranked from least deprived to most deprived on seven different dimensions of deprivation and an overall composite measure of multiple deprivation. Most of the data underlying the 2010 Indices are for the year 2008. The domains used in the Indices of Deprivation 2010 are: income deprivation; employment deprivation; health deprivation and disability; education deprivation; crime deprivation; barriers to housing and services deprivation; and living environment deprivation. Each of these domains has its own scores and ranks, allowing users to focus on specific aspects of deprivation. In addition, two supplementary indices measure income deprivation amongst children - the Income Deprivation Affecting Children Index (IDACI) - and older people - the Income Deprivation Affecting Older People Index (IDAOPI).This data was then combined with the LSOA boundaries in ArcGIS. The first data column is the Index of Multiple Deprivation Score. The second data column is the Rank of the Index of Multiple Deprivation Score. The LSOA with a rank of 1 is the most deprived, and 32482 the least deprived, on this overall measure. The IMD 2010 was constructed by combining the seven transformed domain scores, using the following weights: * Income (22.5%) * Employment (22.5%) * Health and Disability (13.5%) * Education, Skills and Training (13.5%) * Barriers to Housing and Services (9.3%) * Crime (9.3%) * Living Environment (9.3%) The the seven domain indices are each presented in separate tables available from the DCLG website. Data sourced from Data.gov.uk: http://data.gov.uk/dataset/index-of-multiple-deprivation and LSOA data from ONS Geoportal: https://geoportal.statistics.gov.uk/geoportal/catalog/main/home.page (the dataset date in this case refers to the date the data was uploaded). GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2013-12-06 and migrated to Edinburgh DataShare on 2017-02-22.

This dataset contains a range of measures which form the Indices of Deprivation 2015 at LSOA level. The boundaries used have been generalised by 50 metres (point remove) for web display. This dataset has been curated mainly for education/teaching purposes. The Index of Multiple Deprivation ranks every small area in England from 1 (most deprived area) to 32,844 (least deprived area). It is common to describe how relatively deprived a small area is by saying whether it falls among the most deprived 10 per cent, 20 per cent or 30 per cent of small areas in England (although there is no definitive cut-off at which an area is described as ‘deprived’). To help with this, deprivation ‘deciles’ are published alongside ranks. This dataset has been published to show the show the IMD Ranks and Deciles for each LSOA for Education purposes. The Indices of Deprivation 2015 provide a set of relative measures of deprivation for small areas (Lower-layer Super Output Areas*) across England, based on seven domains of deprivation. The domains were combined using the following weights to produce the overall Index of Multiple Deprivation (IMD):Income Deprivation (22.5%) Employment Deprivation (22.5%) Education, Skills and Training Deprivation (13.5%) Health Deprivation and Disability (13.5%) Crime (9.3%) Barriers to Housing and Services (9.3%) Living Environment Deprivation (9.3%). Please refer to this web page from Department for Communities and Local Government for more information on the dataset.

In the 3 years to March 2021, black households were most likely out of all ethnic groups to have a weekly income of under £600.

This dataset contains a summary measure of the Indices of Deprivation 2010 Barriers to housing and services domain at local authority district level. It puts the 326 Local Authority Districts into a rank order based the population weighted average rank of all LSOAs in the LAD. A rank of 1 is the most deprived.

The English Indices of Deprivation provide a relative measure of deprivation at small area level across England. Areas are ranked from least deprived to most deprived on seven different dimensions of deprivation and an overall composite measure of multiple deprivation. Most of the data underlying the 2010 indices are for the year 2008.

The Indices are designed for small areas, but one way of summarising relative deprivation at local authority level is by calculating the average rank of the LSOAs within it.

For the IMD and each domain, the summary measure is calculated by averaging all of the LSOA ranks in each local authority district. For the purpose of calculation, LSOAs are ranked such that the most deprived LSOA is given the rank of 32,482. The LSOA ranks are population weighted within a local authority district to take account of the fact that LSOA size can vary. (For simplicity in summarising the domains, the same total population size is used for all domains.) Finally the LADs are ranked according to the average rank of the LSOAs, from 1 to 326 where 1 is the most deprived.

The ‘Rank of average rank’ summary measure of for local authorities is also published for the IMD at: http://www.communities.gov.uk/documents/statistics/xls/1871689.xls.

This dataset contains a summary measure of the Indices of Deprivation 2010 Income domain at local authority district level. It puts the 326 Local Authority Districts into a rank order based the population weighted average rank of all LSOAs in the LAD. A rank of 1 is the most deprived.

The English Indices of Deprivation provide a relative measure of deprivation at small area level across England. Areas are ranked from least deprived to most deprived on seven different dimensions of deprivation and an overall composite measure of multiple deprivation. Most of the data underlying the 2010 indices are for the year 2008.

The Indices are designed for small areas, but one way of summarising relative deprivation at local authority level is by calculating the average rank of the LSOAs within it.

For the IMD and each domain, the summary measure is calculated by averaging all of the LSOA ranks in each local authority district. For the purpose of calculation, LSOAs are ranked such that the most deprived LSOA is given the rank of 32,482. The LSOA ranks are population weighted within a local authority district to take account of the fact that LSOA size can vary. (For simplicity in summarising the domains, the same total population size is used for all domains.) Finally the LADs are ranked according to the average rank of the LSOAs, from 1 to 326 where 1 is the most deprived.

The ‘Rank of average rank’ summary measure of for local authorities is also published for the IMD at: http://www.communities.gov.uk/documents/statistics/xls/1871689.xls.

About the indices of deprivationThe English indices of deprivation measure relative deprivation in small areas in England. The index of multiple deprivation is the most widely used of these indices.The updated index of multiple deprivation (IMD) was published by the Department of Communities and Local Government (CLG) on 30 September 2015.The IMD brings together data covering seven different aspects or ‘domains’ of deprivation into a weighted overall index for each Lower-layer Super Output Area (LSOA) in England. The scores are then used to rank the LSOAs nationally and to calculate an IMD score for each local authority area. Local authorities are then ranked by their IMD score. The IMD presents a ranking of relative deprivation between and within local authorities in England. It is not a measure of affluence in an area, nor an absolute measure of how much more or less deprived an area is compared to another.The domains used in calculating the index are: Income; Employment; Education, Skills and Training; Health Deprivation and Disability; Crime; Barriers to Housing and Services; Living Environment. There are also two supplementary domains - Income Deprivation Affecting Children Index (IDACI) and Income Deprivation Affecting Older People (IDAOPI).LSOAs are a geographical unit which has an average of 1,500 residents and 650 households. They were developed following the 2001 census, through the aggregation of smaller census output areas, to create areas with a reasonably compact shape and which were socially similar (assessed through housing type). Around one percent of LSOAs were changed following the 2011 Census in order to maintain the characteristics described above. There are now 32,844 LSOAs in England. Leicester now has 192 LSOAs.Leicester IMDLeicester is ranked 21st most deprived in IMD 2015 out of 326 local authorities, compared with 25th in the 2010 Index.Leicester is ranked within the 10% most deprived local authorities in EnglandCompared to England, Leicester has almost double the population living in the two fifths (40%) most deprived LSOA’s in the country. 76% of Leicester’s population, compared with only 40% of England’s, live in the 40% most deprived LSOAs in the country.A full report on deprivation in Leicester can be found on the Leicester City Council website here: https://www.leicester.gov.uk/your-council/policies-plans-and-strategies/health-and-social-care/data-reports-information/

With a Gross Domestic Product of over 4.18 trillion Euros, the German economy was by far the largest in Europe in 2023. The similar-sized economies of the United Kingdom and France were the second and third largest economies in Europe during this year, followed by Italy and Spain. The smallest economy in this statistic is that of the small Balkan nation of Montenegro, which had a GDP of 5.7 billion Euros. In this year, the combined GDP of the 27 member states that compose the European Union amounted to approximately 17.1 trillion Euros. The big five Germany’s economy has consistently had the largest economy in Europe since 1980, even before the reunification of West and East Germany. The United Kingdom, by contrast, has had mixed fortunes during the same time period and had a smaller economy than Italy in the late 1980s. The UK also suffered more than the other major economies during the recession of the late 2000s, meaning the French economy was the second largest on the continent for some time afterward. The Spanish economy was continually the fifth-largest in Europe in this 38-year period, and from 2004 onwards, has been worth more than one trillion Euros. The smallest GDP, the highest economic growth in Europe Despite having the smallerst GDP of Europe, Montenegro emerged as the fastest growing economy in the continent, achieving an impressive annual growth rate of 4.5 percent, surpassing Turkey's growth rate of 4 percent. Overall,this Balkan nation has shown a remarkable economic recovery since the 2010 financial crisis, with its GDP projected to grow by 28.71 percent between 2024 and 2029. Contributing to this positive trend are successful tourism seasons in recent years, along with increased private consumption and rising imports. Europe's economic stagnation Malta, Albania, Iceland, and Croatia were among the countries reporting some of the highest growth rates this year. However, Europe's overall performance reflected a general slowdown in growth compared to the trend seen in 2021, during the post-pandemic recovery. Estonia experienced the sharpest negative growth in 2023, with its economy shrinking by 2.3% compared to 2022, primarily due to the negative impact of sanctions placed on its large neighbor, Russia. Other nations, including Sweden, Germany, and Finland, also recorded slight negative growth.