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 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.

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.

As of 2023, the population density in London was by far the highest number of people per square km in the UK, at 5,690. Of the other regions and countries which constitute the United Kingdom, North West England was the next most densely populated area at 533 people per square kilometer. Scotland, by contrast, is the most sparsely populated country or region in the United Kingdom, with only 70 people per square kilometer. UK population over 67 million According to the official mid-year population estimate, the population of the United Kingdom was just almost 67.6 million in 2022. Most of the population lived in England, where an estimated 57.1 million people resided, followed by Scotland at 5.44 million, Wales at 3.13 million and finally Northern Ireland at just over 1.9 million. Within England, the South East was the region with the highest population at almost 9.38 million, followed by the London region at around 8.8 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 494 billion British pounds, almost a quarter of UK GDP overall. In terms of GDP per capita, Londoners had a GDP per head of 56,431 pounds, compared with an average of 33,224 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 33.2 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.

UK residents by broad country of birth and citizenship groups, broken down by UK country, local authority, unitary authority, metropolitan and London boroughs, and counties. Estimates from the Annual Population Survey.

United Kingdom UK: Population Density: People per Square Km data was reported at 272.898 Person/sq km in 2017. This records an increase from the previous number of 271.134 Person/sq km for 2016. United Kingdom UK: Population Density: People per Square Km data is updated yearly, averaging 235.922 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 272.898 Person/sq km in 2017 and a record low of 218.245 Person/sq km in 1961. United Kingdom UK: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted average;

Abstract copyright UK Data Service and data collection copyright owner.

The aims of this project were to:

• understand the demographic changes that United Kingdom local ethnic populations are presently experiencing and are likely to experience in the remainder of the 21st century
• understand the impact that international migration is having on the size and ethnic composition of UK local populations
• understand the role that differences in fertility between the UK's ethnic groups plays in shaping current and future trends
• understand the role that mortality differences between ethnic groups is playing in the changing demography of the UK's local populations
• understand how the ethnic diversity of UK local populations is changing and likely to change in the future
• deliver the projections as a resource for use by social science in the UK
• build capacity in the analysis of demographic change through the development of young and middle career researchers
• tap into the best practice internationally to benefit the UK social science community.

To achieve the project aims, the objectives were to:

• build projections of the populations of ethnic groups for UK local areas
• use the population projection model to explore alternative futures.

The project built a model for projecting the ethnic group populations of UK Local Authorities (LAs), which handles 352 LAs, 16 ethnic groups, 102 ages and 2 sexes. To drive the projections, estimates of the components of ethnic change were prepared for 2001-7. A new method produced UK estimates of ethnic life expectancy, ranging from 82 years for Chinese women to 77 for Pakistani. A future 2% decline in mortality per annum was assumed. Ethnic fertility estimates showed that only Indians, Pakistanis and Bangladeshis had total fertility rates above replacement. Small declines in fertility were forecast. New estimates of the local distribution of immigration were made, using administrative data, because of concerns about official figures. The ethnicity of both immigrants and emigrants for local areas was projected. Estimates were constructed of the ethnic group probabilities for internal in- and out-migration for LAs using 2001 Census data. These probabilities were assumed constant in the future, as migration was stable between 2001 and 2008. Five projections were produced. Two benchmark projections, using constant inputs from 2001-2, forecast the UK population would be 62 and 56 million in 2051.The official projection reports 77 million. The Trend projection, aligned to ONS assumptions projected 78 million for 2051. Using revised assumptions 80 million was projected in a fourth projection. When the model for emigration was changed the projected population was only 71 million. All projections showed ageing and dispersion of ethnic minorities. By 2051 the UK will have a larger, more diverse and integrated population.

For further information about the project, see documentation and the What happens when international migrants settle? Ethnic group population trends and projections for UK local areas under alternative scenarios ESRC award page.


Main Topics:

For full details of the individual files (and topics covered) within the study, see documentation files '6777_list_of_files.xlsx' and '6777_fileinformation.pdf' in the Documentation table below.

Users should note that this study is very large - c.8GB. Multiple files have been created for download, according to the type of compilation - benchef, bencher, trendef, uptapef and uptaper (see 6777_fileinformation.pdf for details). To obtain all files contained within the study, users should download all zip files.

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.

Middlesbrough’s current population was estimated to be 140,398 in 2016 by the Office of National Statistics (Mid-year population estimates 2016). With a total area of 5,387 hectares, Middlesbrough is the smallest and second most densely-populated local authority area in the north east. Significant changes in the population demographics of Middlesbrough since the 2001 Census highlight an increasingly diverse and ageing population in the town.Age[1]Middlesbrough has a younger population than both the national and regional averages, however there has been significant growth in the ageing population since Census 2001.20.58% of Middlesbrough’s resident population are Children and Young People aged 0 to 15 years. This is higher than the England rate of 19.05% and the north east rate of 17.74%.63.56% are ‘working age’ between 16 and 64 years. This is higher than both the England rate of 63.07% and the north east rate of 63.01%.15.90% are ‘older people’ aged over 65 years. This is lower than both the England rate of 17.88% and the north east rate of 19.25%.Gender [2]50.85% of Middlesbrough’s population were estimated to be female. This is in line with both the England rate of 50.60% and the north east rate of 50.92%49.15% of Middlesbrough’s population were estimated to be male. This is in line with the England rate of 49.40% and the north east rate of 49.08%.Women in Middlesbrough live longer than men, with 17.62% of women are aged over 65 years. This is lower than both the England rate of 19.75% and the north east rate of 21.43%The gender breakdown of Council employment figures is 70.57% women and 29.42% men. This is not reflective of the wider labour market figures of 47% and 53% respectively[3] though it is broadly comparable with the employment levels in other local authorities.[4]Sexual Orientation[5]Office for National Statistics has estimated that 94.6% of Middlesbrough’s population identify as heterosexual or straight, with 1.2% identifying as gay or lesbian, 0.4% identify as bisexual, as a result of the Annual Population Survey 2016. This is higher than the north east region and England.Ethnic Diversity[6]Middlesbrough is the most ethnically diverse local authority area in the Tees Valley, with a British Minority Ethnic population of 11.7% identified at Census 2011, an increase of 86% since 2001 and which is projected to grow further.88.18% of Middlesbrough’s resident population were classed as White (with various sub-groups) this was lower than the north east rate of 93.63% but higher than the England rate of 79.75%. Middlesbrough is the second most ethnically diverse local authority in the north east, behind Newcastle upon Tyne with 81.92% classed as White.7.78% were classed as Asian/Asian British (with sub-groups), this is higher than the north east rate of 2.87% but slightly lower albeit in lien with the England rate of 7.82%. Again, Middlesbrough is only behind Newcastle upon Tyne on this measure (9.67%), however has the highest percentage in the Tees Valley.1.71% of the population were identified as Mixed/Multiple ethnic groups (with sub-groups), this was higher than the north east rate of 0.86% but slower than the national rate of 2.25%. Middlesbrough had the highest percentage of this group in the north east.1.25% of the population were identified as Black/Africa/Caribbean/Black British, this was higher than the north east rate of 0.51% but lower than the England rate of 3.48%. Middlesbrough is only behind Newcastle upon Tyne on this measure (1.84%), however has the highest percentage in the Tees Valley.1.08% of the population were identified as Other Ethnic Group, this was higher than both the England rate of 1.03% and the north east rate of 0.43%. Middlesbrough is only behind Newcastle upon Tyne with 1.46%, however has the highest percentage in the Tees Valley.8.2% of Middlesbrough’s total population were born outside of the UK as at census 2011, this was lower than the England rate of 8.21% but almost double the north east rate of 4.95%. Middlesbrough has the highest percentage of residents born outside of the UK in the Tees Valley, however it is second behind Newcastle upon Tyne in the north east.15.74% of Asylum seekers in the north east were reported to be resident in Middlesbrough in the period October to December 2017 (Q4). Newcastle upon Tyne has the highest rate with 23.66%, followed by Stockton-on-Tees with 19.73%, this places Middlesbrough third in the north east and second in the Tees Valley.ONS reports a rise in the number of Non-British nationals per 1,000 of the resident population, with 51.1 in 2011 and 72.5 in 2015. This is higher than the north east with 27.7 rising to 34.3 and lower than England at 83.5 rising to 93.2Gender Identity[7]The Gender Identity Research & Education Society (GIRES) estimates that about 1% of the British population are gender nonconforming to some degree. The numbers of Trans boys and Trans girls are about equal. The number of people seeking treatment is growing every year.Based on GIRES estimate, around 1,400 members of Middlesbrough’s population could be gender nonconforming, however this is an estimate.Whilst there is a requirement for data on gender identity, there are currently no means for recording it. The Office for National Statistics is currently considering the addition of a question on Gender Identity for the 2021 Census, however at this time it is under consultation as to how it will be added and worded to best suit this group of the population.Religion and Belief71.59% of Middlesbrough’s resident population were identified as having religion in the 2011 census. This is higher than both England with 68.09% and the north east with 70.52%22.25% of the population were identified as having no religion, this was lower than both England with 24.74% and the north east with 23.40%.6.16% of the population did not state their religion, this was lower than England with 7.18%, but higher than the north east with 6.08%.63.23% of the population were identified as Christian, this was higher than England with 59.38% but lower than the north east with 67.52%.7.05% of the population were identified as Muslim, this was higher than both England with 5.02% and the north east with 1.80%. Middlesbrough has the highest Muslim population in the north east and the Tees Valley.The remaining proportion of the population were identified as Buddhist, Hindu, Jewish, Sikh and ‘Other religion’ each accounting for less than 1% of the population. This trend is seen in the England and north east averages.

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.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of cancer (in persons of all ages). Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.ANALYSIS METHODOLOGYThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to cancer (in persons of all ages).This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.The percentage of each MSOA’s population (all ages) with cancer was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of registered patients that have that illness The estimated percentage of each MSOA’s population with cancer was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with cancer, within the relevant age range.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have cancerB) the NUMBER of people within that MSOA who are estimated to have cancerAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA that are estimated to have cancer, compared to other MSOAs. In other words, those are areas where it’s estimated a large number of people suffer from cancer, and where those people make up a large percentage of the population, indicating there is a real issue with cancer within the population and the investment of resources to address that issue could have the greatest benefits.LIMITATIONS1. GP data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children (see the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset), we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of populations that are registered with each GP practice or who live within each MSOA. Populations might be concentrated in certain areas of a GP practice’s catchment area or MSOA and relatively sparse in other areas. Therefore, the dataset should be used to identify general areas where there are high levels of cancer, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of cancer.TO BE VIEWED IN COMBINATION WITH:This dataset should be viewed alongside the following datasets, which highlight areas of missing data and potential outliers in the data:Health and wellbeing statistics (GP-level, England): Missing data and potential outliersLevels of obesity, inactivity and associated illnesses (England): Missing dataDOWNLOADING THIS DATATo access this data on your desktop GIS, download the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset.DATA SOURCESThis dataset was produced using:Quality and Outcomes Framework data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.GP Catchment Outlines. Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Data was cleaned by Ribble Rivers Trust before use.MSOA boundaries: © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021.Population data: Mid-2019 (June 30) Population Estimates for Middle Layer Super Output Areas in England and Wales. © Office for National Statistics licensed under the Open Government Licence v3.0. © Crown Copyright 2020.COPYRIGHT NOTICEThe reproduction of this data must be accompanied by the following statement:© Ribble Rivers Trust 2021. Analysis carried out using data that is: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital; © Office for National Statistics licensed under the Open Government Licence v3.0. Contains OS data © Crown copyright and database right 2021. © Crown Copyright 2020.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

Land area and population density figures for 2001 to 2041 for wards and boroughs. Ward data begins in 2011.

Population figure included are GLA estimate (2012 projections) and 2011 Census.

GLA figures are based on GLA population projections 2012 round (SHLAA) Standard Fertility. Select which year you require from the drop-down box in the spreadsheet.

Inland area takes account of water line. Areas with large bodies of water will have a smaller inland area than total area since some of the area will be water.
Land area figures are taken from Ordnance Survey boundaries using MapInfo.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of hypertension (in persons of all ages). Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.ANALYSIS METHODOLOGYThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to hypertension (in persons of all ages).This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.The percentage of each MSOA’s population (all ages) with hypertension was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of registered patients that have that illness The estimated percentage of each MSOA’s population with hypertension was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with hypertension , within the relevant age range.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have hypertension B) the NUMBER of people within that MSOA who are estimated to have hypertension An average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA that are estimated to have hypertension , compared to other MSOAs. In other words, those are areas where it’s estimated a large number of people suffer from hypertension, and where those people make up a large percentage of the population, indicating there is a real issue with hypertension within the population and the investment of resources to address that issue could have the greatest benefits.LIMITATIONS1. GP data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Health and wellbeing statistics (GP-level, England): Missing data and potential outliers’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children (see the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset), we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of populations that are registered with each GP practice or who live within each MSOA. Populations might be concentrated in certain areas of a GP practice’s catchment area or MSOA and relatively sparse in other areas. Therefore, the dataset should be used to identify general areas where there are high levels of hypertension, rather than interpreting the boundaries between areas as ‘hard’ boundaries that mark definite divisions between areas with differing levels of hypertension .TO BE VIEWED IN COMBINATION WITH:This dataset should be viewed alongside the following datasets, which highlight areas of missing data and potential outliers in the data:Health and wellbeing statistics (GP-level, England): Missing data and potential outliersLevels of obesity, inactivity and associated illnesses (England): Missing dataDOWNLOADING THIS DATATo access this data on your desktop GIS, download the ‘Levels of obesity, inactivity and associated illnesses: Summary (England)’ dataset.DATA SOURCESThis dataset was produced using:Quality and Outcomes Framework data: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.GP Catchment Outlines. Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Data was cleaned by Ribble Rivers Trust before use.COPYRIGHT NOTICEThe reproduction of this data must be accompanied by the following statement:© Ribble Rivers Trust 2021. Analysis carried out using data that is: Copyright © 2020, Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

(File Size - 5 KB). The 2011 rural-urban classification (RUC) of counties in England is based on the 2011 RUC of Output Areas (OA) published in August 2013, and allows users to create a rural/urban view of county level products. The classification was produced by the University of Sheffield and was sponsored by a cross-Government working group comprising Department for Environment, Food and Rural Affairs, Department of the Communities and Local Government and Office for National Statistics.

SUMMARYThis analysis, designed and executed by Ribble Rivers Trust, identifies areas across England with the greatest levels of obesity, inactivity and inactivity/obesity-related illnesses. Please read the below information to gain a full understanding of what the data shows and how it should be interpreted.The analysis incorporates data relating to the following:Obesity/inactivity-related illnesses (asthma, cancer, chronic kidney disease, coronary heart disease, depression, diabetes mellitus, hypertension, stroke and transient ischaemic attack)Excess weight in children and obesity in adults (combined)Inactivity in children and adults (combined)The analysis was designed with the intention that this dataset could be used to identify locations where investment could encourage greater levels of activity. In particular, it is hoped the dataset will be used to identify locations where the creation or improvement of accessible green/blue spaces and public engagement programmes could encourage greater levels of outdoor activity within the target population, and reduce the health issues associated with obesity and inactivity.ANALYSIS METHODOLOGY1. Obesity/inactivity-related illnessesThe analysis was carried out using Quality and Outcomes Framework (QOF) data, derived from NHS Digital, relating to:- Asthma (in persons of all ages)- Cancer (in persons of all ages)- Chronic kidney disease (in adults aged 18+)- Coronary heart disease (in persons of all ages)- Depression (in adults aged 18+)- Diabetes mellitus (in persons aged 17+)- Hypertension (in persons of all ages)- Stroke and transient ischaemic attack (in persons of all ages)This information was recorded at the GP practice level. However, GP catchment areas are not mutually exclusive: they overlap, with some areas covered by 30+ GP practices. Therefore, to increase the clarity and usability of the data, the GP-level statistics were converted into statistics based on Middle Layer Super Output Area (MSOA) census boundaries.For each of the above illnesses, the percentage of each MSOA’s population with that illness was estimated. This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of patients registered with each GP that have that illness The estimated percentage of each MSOA’s population with each illness was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of people in each MSOA with each illness, within the relevant age range.For each illness, each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have that illnessB) the NUMBER of people within that MSOA who are estimated to have that illnessAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA predicted to have that illness, compared to other MSOAs. In other words, those are areas where a large number of people are predicted to suffer from an illness, and where those people make up a large percentage of the population, indicating there is a real issue with that illness within the population and the investment of resources to address that issue could have the greatest benefits.The scores for each of the 8 illnesses were added together then converted to a relative score between 1 – 0 (1 = worst, 0 = best), to give an overall score for each MSOA: a score close to 1 would indicate that an area has high predicted levels of all obesity/inactivity-related illnesses, and these are areas where the local population could benefit the most from interventions to address those illnesses. A score close to 0 would indicate very low predicted levels of obesity/inactivity-related illnesses and therefore interventions might not be required.2. Excess weight in children and obesity in adults (combined)For each MSOA, the number and percentage of children in Reception and Year 6 with excess weight was combined with population data (up to age 17) to estimate the total number of children with excess weight.The first part of the analysis detailed in section 1 was used to estimate the number of adults with obesity in each MSOA, based on GP-level statistics.The percentage of each MSOA’s adult population (aged 18+) with obesity was estimated, using GP-level data (see section 1 above). This was achieved by calculating a weighted average based on:The percentage of the MSOA area that was covered by each GP practice’s catchment areaOf the GPs that covered part of that MSOA: the percentage of adult patients registered with each GP that are obeseThe estimated percentage of each MSOA’s adult population with obesity was then combined with Office for National Statistics Mid-Year Population Estimates (2019) data for MSOAs, to estimate the number of adults in each MSOA with obesity.The estimated number of children with excess weight and adults with obesity were combined with population data, to give the total number and percentage of the population with excess weight.Each MSOA was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that MSOA who are estimated to have excess weight/obesityB) the NUMBER of people within that MSOA who are estimated to have excess weight/obesityAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the MSOA predicted to have excess weight/obesity, compared to other MSOAs. In other words, those are areas where a large number of people are predicted to suffer from excess weight/obesity, and where those people make up a large percentage of the population, indicating there is a real issue with that excess weight/obesity within the population and the investment of resources to address that issue could have the greatest benefits.3. Inactivity in children and adultsFor each administrative district, the number of children and adults who are inactive was combined with population data to estimate the total number and percentage of the population that are inactive.Each district was assigned a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the PERCENTAGE of the population within that district who are estimated to be inactiveB) the NUMBER of people within that district who are estimated to be inactiveAn average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of the population in the district predicted to be inactive, compared to other districts. In other words, those are areas where a large number of people are predicted to be inactive, and where those people make up a large percentage of the population, indicating there is a real issue with that inactivity within the population and the investment of resources to address that issue could have the greatest benefits.Summary datasetAn average of the scores calculated in sections 1-3 was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer the score to 1, the greater the number and percentage of people suffering from obesity, inactivity and associated illnesses. I.e. these are areas where there are a large number of people (both children and adults) who are obese, inactive and suffer from obesity/inactivity-related illnesses, and where those people make up a large percentage of the local population. These are the locations where interventions could have the greatest health and wellbeing benefits for the local population.LIMITATIONS1. For data recorded at the GP practice level, data for the financial year 1st April 2018 – 31st March 2019 was used in preference to data for the financial year 1st April 2019 – 31st March 2020, as the onset of the COVID19 pandemic during the latter year could have affected the reporting of medical statistics by GPs. However, for 53 GPs (out of 7670) that did not submit data in 2018/19, data from 2019/20 was used instead. Note also that some GPs (997 out of 7670) did not submit data in either year. This dataset should be viewed in conjunction with the ‘Levels of obesity, inactivity and associated illnesses: Summary (England). Areas with data missing’ dataset, to determine areas where data from 2019/20 was used, where one or more GPs did not submit data in either year, or where there were large discrepancies between the 2018/19 and 2019/20 data (differences in statistics that were > mean +/- 1 St.Dev.), which suggests erroneous data in one of those years (it was not feasible for this study to investigate this further), and thus where data should be interpreted with caution. Note also that there are some rural areas (with little or no population) that do not officially fall into any GP catchment area (although this will not affect the results of this analysis if there are no people living in those areas).2. Although all of the obesity/inactivity-related illnesses listed can be caused or exacerbated by inactivity and obesity, it was not possible to distinguish from the data the cause of the illnesses in patients: obesity and inactivity are highly unlikely to be the cause of all cases of each illness. By combining the data with data relating to levels of obesity and inactivity in adults and children, we can identify where obesity/inactivity could be a contributing factor, and where interventions to reduce obesity and increase activity could be most beneficial for the health of the local population.3. It was not feasible to incorporate ultra-fine-scale geographic distribution of

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

The LSOA atlas provides a summary of demographic and related data for each Lower Super Output Area in Greater London. The average population of an LSOA in London in 2010 was 1,722 compared with 8,346 for an MSOA and 13,078 for a ward.

The profiles are designed to provide an overview of the population in these small areas by combining a range of data on the population, diversity, households, health, housing, crime, benefits, land use, deprivation, schools, and employment.

Due to significant population change in some areas, not all 2011 LSOA boundaries are the same as previous LSOA boundaries that had been used from 2001. A lot of data is still only available using the 2001 boundaries therefore two Atlases have been created - one using the current LSOA boundaries (2011) and one using the previous boundaries (2001).

If you need to find an LSOA and you know the postcode of the area, the ONS NESS search page has a tool for this.

The LSOA Atlas is available as an XLS as well as being presented using InstantAtlas mapping software. This is a useful tool for displaying a large amount of data for numerous geographies, in one place (requires HTML 5).

CURRENT LSOA BOUNDARIES (2011)

NOTE: There is comparatively less data for the new boundaries compared with the old boundaries

Excel

Instant Atlas

PREVIOUS LSOA BOUNDARIES (2001)

Excel

Instant Atlas

For 2011 Census data used in the 2001 Boundaries Atlas: For simplicity, where two or more areas have been merged, the figures for these areas have been divided by the number of LSOAs that used to make that area up. Therefore, these data are not official ONS statisitcs, but presented here as indicative to display trends.

NB. It is currently not possible to export the map as a picture due to a software issue with the Google Maps background. We advise you to print screen to copy an image to the clipboard.

IMPORTANT: Due to the large amount of data and areas, the LSOA Atlas may take up to a minute to fully load. Once loaded, the report will work more efficiently by using the filter tool and selecting one borough at a time. Displaying every LSOA in London will slow down the data reload.

Tips:

1. - Select a new indicator from the Data box on the left. Select the theme, then indicator and then year to show the data.

2. - To view data just for one borough, use the filter tool.

3. - The legend settings can be altered by clicking on the pencil icon next to the LSOA tick box within the map legend.

4. - The areas can be ranked in order by clicking at the top of the indicator column of the data table.

Beware of large file size for 2001 Boundary Atlas (58MB) alternatively download Zip file (21MB).

Themes included in the atlases are Census 2011 population, Mid-year Estimates by age, Population Density, Households, Household Composition, Ethnic Group, Language, Religion, Country of Birth, Tenure, Number of dwellings, Vacant Dwellings, Dwellings by Council Tax Band, Crime (numbers), Crime (rates), Economic Activity, Qualifications, House Prices, Workplace employment numbers, Claimant Count, Employment and Support Allowance, Benefits claimants, State Pension, Pension Credit, Incapacity Benefit/ SDA, Disability Living Allowance, Income Support, Financial vulnerability, Health and Disability, Land use, Air Emissions, Energy consumption, Car or Van access, Accessibility by Public Transport/walk, Road Casualties, Child Benefit, Child Poverty, Lone Parent Families, Out-of-Work families, Fuel Poverty, Free School Meals, Pupil Absence, Early Years Foundation Stage, Key Stage 1, Key Stage 2, GCSE, Level 3 (e.g A/AS level), The Indices of Deprivation 2010, Economic Deprivation Index, and The IMD 2010 Underlying Indicators.

The London boroughs are: City of London, Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Camden, Croydon, Ealing, Enfield, Greenwich, Hackney, Hammersmith and Fulham, Haringey, Harrow, Havering, Hillingdon, Hounslow, Islington, Kensington and Chelsea, Kingston upon Thames, Lambeth, Lewisham, Merton, Newham, Redbridge, Richmond upon Thames, Southwark, Sutton, Tower Hamlets, Waltham Forest, Wandsworth, Westminster.

These profiles were created using the most up to date information available at the time of collection (Spring 2014).

You may also be interested in MSOA Atlas and Ward Atlas.

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.

Abstract

The Labour Force Survey (LFS) is a study of the employment circumstances of the UK population. It is the largest household study in the UK and provides the official measures of employment and unemployment.The first Labour Force Survey (LFS) in the United Kingdom was conducted in 1973, under the terms of a Regulation derived from the Treaty of Rome. The provision of information for the Statistical Office of the European Communities (SOEC) continued to be one of the reasons for carrying out the survey on an annual basis. SOEC co-ordinated information from labour force surveys in the member states in order to assist the EC in such matters as the allocation of the Social Fund. The survey was carried out biennially from 1973 to 1983 and was increasingly used by UK government departments to obtain information which would assist in the framing of social and economic policy. By 1983 it was being used by the Employment Department (now the Department for Work and Pensions) to obtain information which was not available from other sources or was only available for Census years. From 1984 the survey was carried out annually, and since that time the LFS has consisted of two elements:

• a quarterly survey conducted in Great Britain throughout the year, in which each sampled address was called on five times at quarterly intervals, and which yielded about 15,000 responding households in every quarter;
• a 'boost' survey in the spring quarter (March-May), which produced interviews at over 44,000 households in Great Britain and over 4,000 households in Northern Ireland.

Users should note that only the data from the spring quarter and the 'boost' survey were included in the annual datasets for public release, and that only data from 1975-1991 are available from the UK Data Archive. The depositor recommends only considered use of data for 1975 and 1977 (SNs 1757 and 1758), as the concepts behind the definitions of economic activity changed and are not comparable with later years. Also the survey methodology was being developed at the time and so the estimates may not be reliable enough to use.

During 1991 the survey was developed, so that from spring 1992 the data were made available quarterly, with a quarterly sample size approximately equivalent to that of the previous annual data. The Quarterly Labour Force Survey series therefore superseded the annual LFS series, and is held at the Data Archive under GN 33246.

The study is being conducted by the Office for National Statistics (ONS), the government's largest producer of statistics. They compile independent information about the UK's society and economy which provides evidence for policy and decision making, and for directing resources to where they are needed most. The ten-yearly census, measures of inflation, the National Accounts, and population and migration statistics are some of our highest-profile outputs.

Geographic coverage

The whole country.

Analysis unit

• Individuals
• Families/households

Universe

• Households
• All persons normally resident in private households in the United Kingdom

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified multi-stage sample; for further details see annual reports. Until 1983 two sampling frames were used; in England, Northern Ireland and Wales, the Valuation Roll provided the basis for a sample which, in England and Wales, included all 69 metropolitan districts, and a two-stage selection from among the remaining non-metropolitan districts. In Northern Ireland wards were the primary sampling units. In Scotland, the Address File (i.e. post codes) was used as the basis for a stratified sample.From 1983 the Postoffice Address File has been used instead of the Valuation Roll in England and Wales. In 1984 sample rotation was introduced along with a panel element, the quarterly survey, which uses a two-stage clustered sample design.

The sample comprises about 90,000 addresses drawn at random from the rating lists in 190 different areas of England and Wales With such a large sample, it Will happen by chance that a small number of addresses which were selected at random for the 1979 survey Will come up again In addition 2,000 addresses in 8 of the areas selected in 1979 have been deliberately re-selected again this time (me Interviewers who get these addresses In their work w,ll receive a special letter to take with them.)

The sample is drawn from the "small users" sub-file of the Postcode Address File (PAF), which is a list of all addresses (delivery points) to which mail is delivered, prepared by the Post OffIce and held on computer. "Small users" are delivery points that receive less than 25 afiicles of mail a day and include all but a small proportion of private households. The PAF is updated regularly by the Post Office but, as mentioned in Chapter 1, there was an interruption in the supply of updates in the period leading up to the 1988 msurvey. As a result one third of the sample was drawn from the PAF as at March 1986 and two thirds from the sample as at September 1986. Although the PAF includes newly built properties ahead of their actual occupation, the 1988 sample does seem to have been light in the most recently built properties. The 1990 sample was drawn from the PAF and should include most newly built houses.

Sampling deviation

One of the limitations of the LFS is that the sample design provides no guarantee of adequate coverage of any industry, as the survey is not industrially stratified. The LFS coverage also omits communal establishments, except NHS housing, students in halls of residence and at boarding schools. Members of the armed forces are only included if they live in private accommodation. Also, workers under 16 are not covered. As in previous years, the sample for the boost survey was drawn in a single stage in the most densely populated areas, in two stages elsewhere. The areas where the sample was drawn in a single stage were:

(I) local authority districts in the metropolitan counties and Greater London; (II) districts which, based on the 1981 Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

All questions in the specification are laid out using the same format. Some questions (for instance USUWRKM) have a main group routed to them, but subsets of this group are asked variations of the question. In such cases the main routing is at the foot of the question as usual, and the subsets are listed separately above it, with the individual aspect of the routing indented slightly from the left of the page.

Cleaning operations

Information Technology Centres provides one-year training and practical work experience course in the use of computers and word processors and other aspects of information technology (eg teletex, editing, computer maintenance).

Response rate

The response rate achieved averaged between 83 percent. The method of calculating response rates is the following: The response rate indicates how many interviews were achieved as a proportion of those eligible for the survey. The formula used is as follows: RR = (FR + PR)/(FR + PR + OR + CR + RHQ + NC + RRI*) where RR = response rate, FR = full response, PR = partial response, OR = outright refusal, CR = circumstantial refusal, RHQ = refusal to HQ, NC = non contact, RRI = refusal to re-interview, *applies to waves two to five only.

Sampling error estimates

As with any sample survey, the results of the Labour Force Survey are subject to sampling errors. In addition, the results of any sample survey are affected by non-sampling errors, i.e. the whole variety of errors other then those due to sampling.

Data appraisal

Day of birth and date of birth variables have been removed from the annual LFS datasets, in the same way that they have been removed from the quarterly LFS datasets from 1992 onwards, as this information is now considered to be disclosive. The variable AGEDFE (age at proceeding 31 August) has been added to all annual datasets.

The median age of the population in London was 35.9 years in 2023, the lowest median age among regions of the United Kingdom. By contrast, South West England had a median age of 43.9, the highest in the UK.