Chart and table of population level and growth rate for the London, UK metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

The population of London was approximately 8.9 million in 2023, an increase of over two million people when compared with the early 1980s. Throughout the 1980s, the population of the United Kingdom's capital grew at a relatively slow rate, before accelerating to a much faster rate in the 1990s. London is by far the largest city / urban agglomeration in the United Kingdom, more than three times larger than the next largest cities of Manchester and Birmingham. London’s forecasted population is expected to continue growing at much the same pace it has been growing since the mid-1990s and reach almost 9.8 million by 2042. London boroughs As of 2022, the London borough with the highest population was Croydon, at approximately 392,224, followed by Barnet at 389,101. Overall, London is divided into 33 different boroughs, with London's historic center, the City of London having by far the smallest population, at just 10,847. Residents of the City of London, however, have the highest average median weekly earnings among all of London's boroughs, at 1,138 pounds per week, compared with just 588 pounds per week in Redbridge, the lowest average weekly earnings among London boroughs. While the overall unemployment rate for London was 4.3 percent in early 2023, this ranged from 6.8 percent in Brent, to just 2.3 percent in Kingston upon Thames.
Economic imbalance Aside from being the UK's largest city in terms of population, London is also undoubtedly the UK's cultural, political and economic center. As of 2021, the GDP of Greater London was approximately 496.4 billion British pounds, just over 23 percent of the UK's overall GDP. In the same year, GDP per person in London was 56,431 pounds compared with the UK average of 31,947 pounds. Additionally, productivity in London is far higher than the UK average. As measured by output per hour worked, London was 33.2 percent more productive than the rest of the UK.

There were 827,489 people living in London who were aged between 25 and 29 in 2023, the most of any group. The four largest age cohorts were all clustered between the ages of 25 and 44.

In 2023, Croydon had the largest population among London's 32 boroughs at 397,741, while Kensington and Chelsea had the smallest population, at 147,460.

The population of the United Kingdom in 2023 was estimated to be approximately 68.3 million in 2023, with almost 9.48 million people living in South East England. London had the next highest population, at over 8.9 million people, followed by the North West England at 7.6 million. With the UK's population generally concentrated in England, most English regions have larger populations than the constituent countries of Scotland, Wales, and Northern Ireland, which had populations of 5.5 million, 3.16 million, and 1.92 million respectively. English counties and cities The United Kingdom is a patchwork of various regional units, within England the largest of these are the regions shown here, which show how London, along with the rest of South East England had around 18 million people living there in this year. The next significant regional units in England are the 47 metropolitan and ceremonial counties. After London, the metropolitan counties of the West Midlands, Greater Manchester, and West Yorkshire were the biggest of these counties, due to covering the large urban areas of Birmingham, Manchester, and Leeds respectively. Regional divisions in Scotland, Wales and Northern Ireland The smaller countries that comprise the United Kingdom each have different local subdivisions. Within Scotland these are called council areas whereas in Wales the main regional units are called unitary authorities. Scotland's largest Council Area by population is that of Glasgow City at over 622,000, while in Wales, it was the Cardiff Unitary Authority at around 372,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of around 348,000.

The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.

For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.

Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022

APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.

APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Latest edition information

For the eighth edition (July 2023), the variable FDPCH16 was added to the study.

In 2023, almost nine million people lived in Greater London, making it the most populated ceremonial county in England. The West Midlands Metropolitan County, which contains the large city of Birmingham, was the second-largest county at 2.98 million inhabitants, followed by Greater Manchester and then West Yorkshire with populations of 2.95 million and 2.4 million, respectively. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with around 1.89 million people. A patchwork of regions England is just one of the four countries that compose the United Kingdom of Great Britain and Northern Ireland, with England, Scotland and Wales making up Great Britain. England is therefore not to be confused with Great Britain or the United Kingdom as a whole. Within England, the next subdivisions are the nine regions of England, containing various smaller units such as unitary authorities, metropolitan counties and non-metropolitan districts. The counties in this statistic, however, are based on the ceremonial counties of England as defined by the Lieutenancies Act of 1997. Regions of Scotland, Wales, and Northern Ireland Like England, the other countries of the United Kingdom have their own regional subdivisions, although with some different terminology. Scotland’s subdivisions are council areas, while Wales has unitary authorities, and Northern Ireland has local government districts. As of 2022, the most-populated Scottish council area was Glasgow City, with over 622,000 inhabitants. In Wales, Cardiff had the largest population among its unitary authorities, and in Northern Ireland, Belfast was the local government area with the most people living there.

The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.

For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.

Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022

APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.

APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Latest edition information

For the second edition (January 2024), a new version of the data file was deposited, with smoking variables added.

By 2043 the population of London is expected to reach 9.8 million people, an increase of 550,000 people when compared with 2025. While it has seen quite a steep rise in its population in recent years, London’s population was relatively stable throughout the 1980s and even decreased slightly towards the end of that decade. After peaking at 8.89 million in 2019, the population of London has fallen slightly, to 8.86 million by 2022. UK population forecast Like London, the population of the United Kingdom is forecast to continue to grow well into the middle of the century. By 2046, the population of the UK is estimated to be over 76.3 million people, an increase of over 20 million people when compared with the population figures for 1976. Additionally, the average age of the population is predicted to increase from 39.5 years in 2020 to 44.5 years by the mid-2040s, and continue to increase towards the end of the century. London looms large In the UK, London is by far the largest urban agglomeration in the country, dwarfing the UK's next largest cities of Birmingham, Manchester, and Leeds. London also has a dominant economic position in the UK, with the city accounting for around a quarter of the total GDP in the country. The UK capital also has a far higher GDP per head than the rest of the county, at 57,338 pounds, compared with 33,593 pounds.

Abstract copyright UK Data Service and data collection copyright owner.

The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.

For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.

Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022

APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.

APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.

End User Licence and Secure Access APS data
Users should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and...

These reports present information about people seen rough sleeping by outreach teams in London. Information in the report is derived from the Combined Homelessness and Information Network (CHAIN), a multi-agency database recording information about rough sleepers and the wider street population in London. CHAIN, which is commissioned and funded by the Greater London Authority (GLA) and managed by Homeless Link, represents the UK’s most detailed and comprehensive source of information about rough sleeping.

Services that record information on CHAIN include outreach teams, accommodation projects, day centres and specialist projects such as the GLA-commissioned No Second Night Out (NSNO). The system allows users to share information about work done with rough sleepers and about their needs, ensuring that they receive the most appropriate support and that efforts are not duplicated.

In these reports, people are counted as having been seen rough sleeping if they have been encountered by a commissioned outreach worker bedded down on the street, or in other open spaces or locations not designed for habitation, such as doorways, stairwells, parks or derelict buildings. The report does not include people from “hidden homeless” groups such as those “sofa surfing” or living in squats, unless they have also been seen bedded down in one of the settings outlined above.

Separate reports are produced for London as a whole and for individual boroughs, and these are published each quarter. There are also annual reports that contain aggregated information for all four quarters of the year.

As of January 2024, the PDF reports are accompanied by an OpenDocument Spreadsheet file providing the underlying data in an accessible aggregated tabular format. The file includes data at local authority level, and for London overall, including comparative data for previous periods. There is also an accompanying explanatory notes document, which provides important contextual information about the data.

A list of the organisations which have signed the CHAIN Data Protection Agreement and are able to access the CHAIN system is also available to download.

2023/24

• Quarterly and Annual Reports Schedule 2023/24
• Quarter 1 Reports
• Quarter 2 Reports
• Quarter 3 Reports

2022/23

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2021/22

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2020/21

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2019/20

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2018/19

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2017/18

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2016/17

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2015/16

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2014/15

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

Pre-2014/15

• For earlier reports please see the end of this page.

CHAIN data tables explanatory notes

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

Migration indicators from ONS and DWP.

The table below details the sources of the datasets available and the dates of their next update.

Migration Statistics Quarterly Report Statistical bulletins, ONS

26 November 2020

National Insurance numbers issued to overseas nationals, Stats-Xplore, DWP.

26 November 2020

Population Estimates for UK, England and Wales, Scotland and Northern Ireland, ONS

June 2021

Local area migration indicators suite, ONS.

TBA

Internal migration - Detailed estimates dataset by origin and destination local authorities, sex and single year of age, ONS.

June 2021

Population of the UK by country of birth and nationality, ONS.

November 2020

Short term international migration for England and Wales – accompanying data

Discontinued - latest available data for 2017

Abstract copyright UK Data Service and data collection copyright owner.The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.Occupation data for 2021 and 2022The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022APS Well-Being DatasetsFrom 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.APS disability variablesOver time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage. End User Licence and Secure Access APS dataUsers should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to: age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family nationality and country of origin geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district health: including main health problem, and current and past health problems education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from system variables: including week number when interview took place and number of households at address The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Latest edition informationFor the eighth edition (July 2023), the variable FDPCH16 was added to the study. Main Topics:Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS. Multi-stage stratified random sample Face-to-face interview Telephone interview 2020 ADULT EDUCATION AGE ANXIETY APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BONUS PAYMENTS BUSINESSES CARE OF DEPENDANTS CHRONIC ILLNESS COHABITATION COMMUTING CONDITIONS OF EMPLO... DEBILITATIVE ILLNESS DEGREES DISABILITIES Demography population ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EMPLOYEES EMPLOYER SPONSORED ... EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS FAMILIES FAMILY BENEFITS FIELDS OF STUDY FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER HAPPINESS HEADS OF HOUSEHOLD HEALTH HIGHER EDUCATION HOME OWNERSHIP HOURS OF WORK HOUSEHOLDS HOUSING HOUSING BENEFITS HOUSING TENURE INCOME INDUSTRIES JOB CHANGING JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS Labour and employment MANAGERS MARITAL STATUS NATIONAL IDENTITY NATIONALITY OCCUPATIONS OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE SECTOR PUBLIC SECTOR RECRUITMENT REDUNDANCY REDUNDANCY PAY RELIGIOUS AFFILIATION RENTED ACCOMMODATION RESIDENTIAL MOBILITY SELF EMPLOYED SICK LEAVE SICKNESS AND DISABI... SMOKING SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS STATE RETIREMENT PE... STUDENTS SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS TAX RELIEF TEMPORARY EMPLOYMENT TERMINATION OF SERVICE TIED HOUSING TOBACCO TRAINING TRAINING COURSES TRAVELLING TIME UNEMPLOYED UNEMPLOYMENT UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WELL BEING HEALTH WELSH LANGUAGE WORKING CONDITIONS WORKPLACE vital statistics an...

Census 2021 rounded population and household estimates for local authorities in England and Wales, by sex and five-year age group.

In 2020, the population of the United Kingdom was estimated to have grown by approximately 0.4 percent, with the population growing fastest in the South West and East Midlands, which reported growth rates of 0.6 percent in this year. By contrast, growth in Northern Ireland and Scotland was below the UK average, at just 0.1 percent and zero percent, respectively. Four countries of the UK Within the UK, South East England had the highest population of the regions that comprise the United Kingdom, at more than 9.37 million people. In terms of the four countries of the UK, England had by far the highest population at over 57.7 million people, compared with Scotland (5.5 million) Wales (3.13 million) and Northern Ireland (1.9 million people) which have comparatively smaller populations. Largest cities in the UK With 8.9 million people living there, London is one of the most heavily population regions of the UK, and by far the largest city. Other large cities in the UK include West Midlands urban area, centered around the city of Birmingham at 2.95 million people, along with Greater Manchester at 2.91 million, with these two cities generally considered as the main contenders for being the country's second-city.

The dataset consists of semi-structured interviews with governance stakeholders in London: representatives of London boroughs, the Greater London Authority, business organisations and non-governmental organisations. The interviews focused on: how the governance system in London works, how individual actors responded to the Covid-19 pandemic, how the pandemic influenced Londoners’ local socio-economic status, and how individual actors envision an ideal London governance.

This project responds to three global challenges: unequal urbanisation, growing complexity of the governance systems and a crisis of trust in democracy. More than half of the world population currently live in cities and this share is expected to increase. Modern urban areas are highly unequal, with vast shares of the population living in poverty and struggling to access city-services (Tonkiss 2018). The growing complexity of governance systems leads to an increased number of non-state actors who are not held democratically accountable and whose actions are difficult to control or regulate (Jervis 1997). Finally, along dropping trust in democratic governance, there is rising support for populism and growing acceptance for authoritarian practices (Foa and Mounk 2016). Due to the global impact and interconnected nature of these challenges, any social-scientific response to these problems cannot treat them separately. Existing interdisciplinary research tends to focus on solutions to some of these challenges, often without acknowledging its broader impact. For example, research on governing complex urban polities is focused on top-down and technocratic tools, which contributes to the deepening of the democratic crisis and further inequality (e.g. Kubler and Lefevre 2017). In turn, democratic and participatory solutions to urban inequality often rely on bottom-up communities and face-to-face decision-making, while ignoring the wider complexity of urban decision-making. Finally, research on the possibilities of democratic control over the complex governance ignores the questions of inequality it can produce. As a result, to respond to these three challenges, new, more integrated solutions are necessary.

I am applying for ESRC Fellowship to propose such an integrated solution. My project 'Coping with Complexity and Urban Inequality: Dilemmas of Democratic Mega-city Governance' investigates strategies of urban governance, in conditions of complexity, to realise democratic ideals and lead to more equal urban societies. It draws on my previous PhD research in political theory, complements it with an empirical case-study of constraints of democratic governance in London in order to produce a monograph. Big mega-cities, such as London, due to their global population share and projected continued growth will be vital actors in an integrated global response to the crisis of trust to democratic governance, managing the growing complexity of governance and to responding to consequences of unequal urbanisation. London is a critical case study, due to its inequalities, complex governance consisting of local, national and intra-national bodies and its democratic political system.

This project employs a cross-disciplinary, innovative research design that is rooted in applied political philosophy and qualitative case studies. Employment of applied political philosophy facilitates analysis of theoretical possibilities of democratic, equalising urban governance. Further, it facilitates re-shaping of the philosophical concepts according to the constraints of real-life circumstances (in London). Application of qualitative methods - a series of interviews with urban practitioners, urban NGO's, city council members, inhabitants' associations - provides information on constraints and opportunities for the development of democratic, equalising governance in London. This analysis constitutes a basis for policy-recommendation applicable beyond the specific case studies. Further, a planned workshop engages urban practitioners, urban NGO's, representatives of inhabitants' urban council and selected neighbourhood association. To identify solutions to given urban problems, the workshops will apply a management tool called Three Horizons' Framework (Sharpe 2016). Such mixed-methods research design combining political philosophy and qualitative methods provides a basis for philosophically informed urban policy and constitutes a methodological innovation.

Latest Edition Information
For the tenth edition (February 2020), the 2018 income weight variable has been added to the data.

The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS) (held at the UK Data Archive under GN 33246), all its associated LFS boosts and the APS boost. Thus, the APS combines results from five different sources: the LFS (waves 1 and 5); the English Local Labour Force Survey (LLFS), the Welsh Labour Force Survey (WLFS), the Scottish Labour Force Survey (SLFS) and the Annual Population Survey Boost Sample (APS(B) - however, this ceased to exist at the end of December 2005, so APS data from January 2006 onwards will contain all the above data apart from APS(B)). Users should note that the LLFS, WLFS, SLFS and APS(B) are not held separately at the Archive. For further detailed information about methodology, users should consult the Labour Force Survey User Guide, selected volumes of which have been included with the APS documentation for reference purposes (see 'Documentation' table below).

The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples such as the WLFS and SLFS, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.

New reweighting policy
Following the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.

End User Licence and Secure Access APS data
Users should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EU

These reports present information about people seen rough sleeping by outreach teams in London. Information in the report is derived from the Combined Homelessness and Information Network (CHAIN), a multi-agency database recording information about rough sleepers and the wider street population in London. CHAIN, which is commissioned and funded by the Greater London Authority (GLA) and managed by St Mungo’s, represents the UK’s most detailed and comprehensive source of information about rough sleeping.

Services that record information on CHAIN include outreach teams, accommodation projects, day centres and specialist projects such as the GLA-commissioned No Second Night Out (NSNO). The system allows users to share information about work done with rough sleepers and about their needs, ensuring that they receive the most appropriate support and that efforts are not duplicated.

In these reports, people are counted as having been seen rough sleeping if they have been encountered by a commissioned outreach worker bedded down on the street, or in other open spaces or locations not designed for habitation, such as doorways, stairwells, parks or derelict buildings. The report does not include people from “hidden homeless” groups such as those “sofa surfing” or living in squats, unless they have also been seen bedded down in one of the settings outlined above.

Separate reports are produced for London as a whole and for individual boroughs, and these are published each quarter. There are also annual reports that contain aggregated information for all four quarters of the year. The reports listed below cover the period from 1 April 2014 onwards. Earlier reports can be found on the St Mungo’s website.

2021/22

• Quarterly and Annual Reports Schedule 2021/22
• Quarter 1 Reports
• Quarter 2 Reports
• Quarter 3 Reports

2020/21

• Greater London Bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2019/20

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

2018/19

• Greater London bulletin
• Greater London full report
• Borough Annual Reports
• Quarterly Reports

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Abstract copyright UK Data Service and data collection copyright owner.

The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.

For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.

Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022

APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.

APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.

End User Licence and Secure Access APS data
Users should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and...

The LAEI 2016 has been superseded. Click here for the full list of releases.

Emissions estimates of key pollutants (NOx, PM10, PM2.5 and CO2) by source type are included for the base year 2016. Emissions for previous years 2010 and 2013 have also been recalculated, using the latest data sources (emission factors, activity data, ...) and methodology.

Emissions projected forward to 2020, 2025, and 2030 will be available soon.

The area covered by the LAEI includes Greater London (the 32 London boroughs and the City of London), as well as areas outside Greater London up to the M25 motorway.

These emissions have been used to estimate ground level concentrations of key pollutants NOx, NO2, PM10 and PM2.5 across Greater London for year 2016, using an atmospheric dispersion model. Air pollutant concentration maps and associated datasets are available for download.

Due to the size of the LAEI database, datasets have been zipped and need to be downloaded in several parts.

UPDATE 03/07/19 - The concentration maps and associated data (including population and school exposure data) have been reissued following a minor issue with the previous dataset. Please read the following note for further information: Updated LAEI 2016 Concentration Maps and Associated Data - July 2019 (.PDF - 146kB).

Documentation

• LAEI 2016 Methodology document (.PDF - 2.8MB)
• Regional Background Concentrations Update (.PDF - 646.3KB)

Supporting Information Key GIS geographies and road traffic flows and vehicle-kilometres for 2010, 2013 and 2016 for each vehicle type. Data are provided in Excel and GIS formats.

• Supporting Information - GIS geographies (.ZIP - 31.8MB)
• Supporting Information - Road Traffic Data - Excel (.ZIP - 211.9MB)
• Supporting Information - Road Traffic Data - GIS (.ZIP - 45.5MB)

Grid Emissions Summary This dataset includes emissions of NOx, PM10, PM2.5 and CO2in tonnes/year for 2010, 2013 and 2016 for each source category at a 1km grid square resolution, including summary tables for London boroughs and London zones (Central / Inner / Outer London). Data are provided in Excel and GIS formats.

• Emissions - Data - Excel Files (.ZIP - 20.9MB)
• Emissions - Data - GIS Files (.ZIP - 18.1MB)
• Emissions - Summary Dashboards (.ZIP - 41 KB)
• Emissions – Data – Excel files – Other pollutants (.ZIP - 4.7 MB)

Detailed Road Transport Road transport emissions in 2010, 2013 and 2016 by vehicle type and also by pollutant. This data is presented at link level for major roads and at grid level for minor roads and cold start emissions. Data are provided in Excel and GIS formats.

• Emissions - Detailed Road Transport - Major Roads - Excel (.ZIP - 340.2KB)
• Emissions - Detailed Road Transport - Minor Roads & Cold Start - Excel (.ZIP - 25.8KB)
• Emissions - Detailed Road Transport - GIS (.ZIP - 436.9KB)

Concentrations This dataset includes modelled 2016 ground level concentrations of annual mean NOx, NO2, PM10 and PM2.5 in µg/m3 (microgramme per cubic metre) at 20m grid resolution. For PM10, it also includes the number of daily means exceeding 50 µg/m3.Data are provided in Excel, GIS and PDF formats.

• Concentrations - Data - ASCII Files (.ZIP - 86.4MB)
• Concentrations - Data - Excel Files (.ZIP - 139.2MB)
• Concentrations - Maps - PDF Files (.ZIP - 10.9MB). Update 03/04/19 - Note that the map of PM 2.5 annual mean concentrations for 2016 has been added to the zip file.
• Concentrations - Data - GIS Files (.ZIP - 126.4MB). Includes GIS files in ESRI format to visualise the concentrations in a GIS software (ArcGIS).

Population Exposure This dataset includes estimations of the number of Londoners and number of schools in London exposed to an annual average NO2 concentration above the Air Quality Strategy objective of 40µg/m3, based on the modelled 2016 ground level concentrations. A comparison with previous 2013 concentrations modelled for the LAEI 2013 inventory is also provided.

• NO2 Population Exposure (.XLSX - 25KB)
• NO2 and PM2.5 School Exposure (.XLSX - 269KB)