London was by far the largest urban agglomeration in the United Kingdom in 2023, with an estimated population of 9.65 million people, more than three times as large as Manchester, the UK’s second-biggest urban agglomeration. The agglomerations of Birmingham and Leeds / Bradford had the third and fourth-largest populations respectively, while the biggest city in Scotland, Glasgow, was the fifth largest. Largest cities in Europe Two cities in Europe had larger urban areas than London, with the Russian capital Moscow having a population of almost 12.7 million. The city of Paris, located just over 200 miles away from London, was the second-largest city in Europe, with a population of more than 11.2 million people. Paris was followed by London in terms of population-size, and then by the Spanish cities of Madrid and Barcelona, at 6.75 million and 5.68 million people respectively. Russia's second-biggest city; St. Petersburg had a population of 5.56 million, followed by Rome at 4.3 million, and Berlin at 3.5 million. London’s population growth Throughout the 1980s, the population of London fluctuated from a high of 6.81 million people in 1981 to a low of 6.73 million inhabitants in 1988. During the 1990s, the population of London increased once again, growing from 6.8 million at the start of the decade to 7.15 million by 1999. London's population has continued to grow since the turn of the century, reaching a peak of 8.96 million people in 2019, and is forecast to reach 9.8 million by 2043.

National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

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.

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.

This statistic shows the ten largest cities in the United Kingdom in 2021. In 2021, around 8.78 million people lived in London, making it the largest city in the United Kingdom.

Population and household characteristics by built-up area (BUA) size classification and individual BUAs, England (excluding London) and Wales, Census 2021. Data are available at a country, BUA size classification and individual BUA level.

As of 2023, the population density in London was by far the highest number of people per square km in the UK, at *****. Of the other regions and countries which constitute the United Kingdom, North West England was the next most densely populated area at *** people per square kilometer. Scotland, by contrast, is the most sparsely populated country or region in the United Kingdom, with only ** people per square kilometer. Countries, regions, and cities According to the official mid-year population estimate, the population of the United Kingdom was just almost **** million in 2022. Most of the population lived in England, where an estimated **** million people resided, followed by Scotland at **** million, Wales at **** million and finally Northern Ireland at just over *** million. Within England, the South East was the region with the highest population at almost **** million, followed by the London region at around *** million. In terms of urban areas, Greater London is the largest city in the United Kingdom, followed by Greater Manchester and Birmingham in the North West and West Midlands regions of England. London calling London's huge size in relation to other UK cities is also reflected by its economic performance. In 2021, London's GDP was approximately *** billion British pounds, almost a quarter of UK GDP overall. In terms of GDP per capita, Londoners had a GDP per head of ****** pounds, compared with an average of ****** for the country as a whole. Productivity, expressed as by output per hour worked, was also far higher in London than the rest of the country. In 2021, London was around **** percent more productive than the rest of the country, with South East England the only other region where productivity was higher than the national average.

In 2023, the population of the United Kingdom reached 68.3 million, compared with 67.6 million in 2022. The UK population has more than doubled since 1871 when just under 31.5 million lived in the UK and has grown by around 8.2 million since the start of the twenty-first century. For most of the twentieth century, the UK population steadily increased, with two noticeable drops in population occurring during World War One (1914-1918) and in World War Two (1939-1945). Demographic trends in postwar Britain After World War Two, Britain and many other countries in the Western world experienced a 'baby boom,' with a postwar peak of 1.02 million live births in 1947. Although the number of births fell between 1948 and 1955, they increased again between the mid-1950s and mid-1960s, with more than one million people born in 1964. Since 1964, however, the UK birth rate has fallen from 18.8 births per 1,000 people to a low of just 10.2 in 2020. As a result, the UK population has gotten significantly older, with the country's median age increasing from 37.9 years in 2001 to 40.7 years in 2022. What are the most populated areas of the UK? The vast majority of people in the UK live in England, which had a population of 57.7 million people in 2023. By comparison, Scotland, Wales, and Northern Ireland had populations of 5.44 million, 3.13 million, and 1.9 million, respectively. Within England, South East England had the largest population, at over 9.38 million, followed by the UK's vast capital city of London, at 8.8 million. London is far larger than any other UK city in terms of urban agglomeration, with just four other cities; Manchester, Birmingham, Leeds, and Glasgow, boasting populations that exceed one million people.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..In 2016, changes were made to the languages and language categories presented in tables B16001, C16001, and B16002. For more information, see: 2016 Language Data User note..Geographical restrictions have been applied to Table B16001 - LANGUAGE SPOKEN AT HOME BY ABILITY TO SPEAK ENGLISH FOR THE POPULATION 5 YEARS AND OVER for the 5-year data estimates. These restrictions are in place to protect data privacy for the speakers of smaller languages. Geographic areas published for the 5-year B16001 table include: Nation (010), States (040), Metropolitan Statistical Area-Metropolitan Divisions (314), Combined Statistical Areas (330), Congressional Districts (500), and Public Use Microdata Sample Areas (PUMAs) (795). For more information on these geographical delineations, see the Metropolitan Statistical Area Reference Files. County and tract-level data are no longer available for table B16001; for specific language data for these smaller geographies, please use table C16001. Additional languages are also available in the Public Use Microdata Sample (PUMS), at the State and Public Use Microdata Sample Area (PUMA) levels of geography..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Cambridge was the fastest growing city in the United Kingdom between 2013 and 2023, with its population increasing by 17.3 percent. Exeter, Milton Keynes, and Peterborough also grew quite fast, with their populations increasing by 15.2 percent, 14.9 percent, and 14 percent, respectively. Largest UK urban areas When looking at cities defined by their urban agglomerations, as of 2023, London had approximately 9.65 million people living there, far larger than any other city in the United Kingdom. The urban agglomeration around the city of Birmingham had a population of approximately 2.67 million, while the urban areas around Manchester and Leeds had populations of 2.79 and 1.92 million respectively. London not only dominated other UK cities in terms of its population, but in its importance to the UK economy. In 2023, the gross domestic product of Greater London was approximately 569 billion British pounds, compared with 101 billion for Greater Manchester, and 85 billion in the West Midlands Metropolitan Area centered around Birmingham. UK population growth In 2023, the overall population of the United Kingdom was estimated to have reached approximately 68.3 million, compared with around 58.9 million in 2000. Since 1970, 2023 was also the year with the highest population growth rate, growing by 0.98 percent, and was at its lowest in 1982 when it shrank by 0.12 percent. Although the UK's birth rate has declined considerably in recent years, immigration to the UK has been high enough to drive population growth in the UK, which has had a positive net migration rate since 1994.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..For information on definitions of the OMB-defined racial classifications, see the "Race" and "Race Concepts" sections of the American Community Survey and Puerto Rico Community Survey 2019 Subject Definitions document at https://www2.census.gov/programs-surveys/acs/tech_docs/subject_definitions/2019_ACSSubjectDefinitions.pdf..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

In 2019, people from most ethnic minority groups were more likely than White British people to live in the most deprived neighbourhoods.

In 2020/21 there were approximately 696,000 Polish nationals living in the United Kingdom, the highest non-British population at this time. Indian and Irish were the joint second-largest nationalities at approximately 370,000 people.

This dataset provides data on a sample of 327 core cities within the EU-28, covered by the Cities Statistics database of the European Statistics Office (Eurostat), formerly known as “Urban Audit” (UA). It is organized in three spreadsheets containing, respectively, the following data: 1. List of the analyzed plans: Country / City, City population, Climate change mitigation strategy name (in national languages / in English), Year of adoption of the strategy/plan, Type of Mitigation Local Climate Plan (M-LCP), Integrated Mitigation and Adaptation Plan, Carbon neutrality, target year carbon neutrality, Global Covenant of Mayors for Climate and Energy (GCoM), Climate Alliance (CA), C40, CNCA (Carbon Neutral Cities Alliance) 2. GHG emission targets for UA cities with a plan, by country: Country / City with a plan, Type of M-LCP, CO2 emission target (% / baseline year / target year), GHG emission target (CO2eq) (% / baseline year / target year), Geographical location (Northern/Southern Europe) 3. Key data summary on the sample: Country, Total number (No.) of cities in the sample, M-LCPs by type, Total No. of M-LCP Cities without a plan, Cities with a plan, Integrated M&A LCPs, Total population, Population in our city sample, Population representativeness in the sample

Our networking project on the alignment of Sustainable Development Goals with local climate actions collected relevant data as follows: 1) We engaged with officials in selected cities in the UK and Japan. Data collected through interviews and meetings with such officials provided useful information. 2) An online survey was conducted to understand local authority engagement in the SDG and climate actions in the UK. The data collected and created through the above activities is made available through this collection for use in research purposes.

We are requesting the funding to develop social science research collaboration between De Montfort University (UK) and the Institute for Global Energy Strategies (Japan). We are proposing a series of networking and knowledge exchange activities on the timely theme of making climate planning more sustainable in cities in United Kingdom and Japan. The world is urbanising rapidly and more than 50% of the global population now lives in cities around the world. As the economic output is concentrated in cities, their contribution to climate change is significant and growing rapidly. While many cities have climate action plans and city administrations are seemingly well-positioned to align their climate change plans with other sustainable development concerns, little is known about the sustainability of city climate plans. Relatively little is known about the steps cities are taking to make climate plan sustainable. In fact, whether and to what extent cities are making links between their climate and sustainability objectives remains an open question.This proposal aims to fill this knowledge gap through this networking and knowledge exchange activity. This would help us in identifying and developing a larger action-oriented, multidisciplinary research programme on the integration between climate planning and the SDGs in cities. We are proposing the work in a number of distinct phases. In the networking phase, we will develop a list of cities that have already produced climate change plan. In the scoping phase, we aim to develop screening criteria to help identify the links and gaps between that climate plan and the SDGs. The screening criteria will be used to create a shortlist of cities in both countries to determine the status of integration of Sustainable Development Goals in climate action plans, identify the reasons for weak alignment and find ways of improving the linkage. This scoping exercise would consist of interviews and surveys with a manageable number of cities in both Japan and the United Kingdom. In the final phase, the research teams in both countries would develop a set of knowledge products and learning materials that would summarise the preliminary results of the networking and then scoping phase. The main outputs would consist of an introductory paper that outlines the objectives, key questions, scope, methods, and relevant literature on the themes covered in the project. This would then be complemented by two additional papers-one each for Japan and the United Kingdom-that lays out the main results for both of those countries. An additional paper would focus on some of the comparative insights from looking across the results of cities in the two countries. We plan to develop collaboration through two-way researcher exchanges, joint workshops, scoping studies in UK and Japanese cities, developing an online platform to share ideas and solicit inputs into a full research proposal around the integration of climate and SDG planning in the UK and Japan. Both the teams are well placed to undertake the work given their respective strengths in energy systems (for DMU) and climate policy (IGES) and their existing networks with the local city administrations as well as other stakeholders. The work is planned for 18 months and both the teams are committing significant financial resources in addition to the requested fund.

Table from the American Community Survey (ACS) B16003 of age by language spoken at home for the population 5 years and over in limited English-speaking households. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B16003Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

In 2016, it was estimated that Birmingham had the largest Muslim population of any local authority in England and Wales at approximately 280 thousand people. Newham and Tower Hamlets, both boroughs of London, had the second and third-largest Muslim populations at 135 and 128 thousand respectively.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).