57 datasets found
  1. Estimates of the population for the UK, England, Wales, Scotland, and...

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Oct 8, 2024
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    Office for National Statistics (2024). Estimates of the population for the UK, England, Wales, Scotland, and Northern Ireland [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Oct 8, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Ireland, England, United Kingdom
    Description

    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).

  2. o

    Geonames - All Cities with a population > 1000

    • public.opendatasoft.com
    • data.smartidf.services
    • +2more
    csv, excel, geojson +1
    Updated Mar 10, 2024
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    (2024). Geonames - All Cities with a population > 1000 [Dataset]. https://public.opendatasoft.com/explore/dataset/geonames-all-cities-with-a-population-1000/
    Explore at:
    csv, json, geojson, excelAvailable download formats
    Dataset updated
    Mar 10, 2024
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

  3. Understanding towns in England and Wales: population and demography

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Feb 24, 2021
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    Office for National Statistics (2021). Understanding towns in England and Wales: population and demography [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/understandingtownsinenglandandwalespopulationanddemography
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Feb 24, 2021
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Wales, England
    Description

    Towns in England and Wales: towns list, cities list, classification and population data.

  4. s

    Output Area (2001) to Major Towns and Cities (December 2015) Best Fit Lookup...

    • geoportal.statistics.gov.uk
    Updated Oct 24, 2018
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    Office for National Statistics (2018). Output Area (2001) to Major Towns and Cities (December 2015) Best Fit Lookup in EW [Dataset]. https://geoportal.statistics.gov.uk/datasets/output-area-2001-to-major-towns-and-cities-december-2015-best-fit-lookup-in-ew/about
    Explore at:
    Dataset updated
    Oct 24, 2018
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A CSV file containing the best fit lookup between 2011 Output Areas (OA) and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data. (File Size 6.5MB).Field Names – OA01CD, OA01CDOLD, TCITY15CD, TCITY15NM

    Field Types – Text, Text, Text, Text

    Field Lengths – 9, 10, 9, 25REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/OA01_TCITY15_EW_LU_a0e2581567bc425ba62da183b51ead0f/FeatureServer

    For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about

  5. a

    Output Area (2011) to Major Towns and Cities (December 2015) Best Fit Lookup...

    • hub.arcgis.com
    • geoportal.statistics.gov.uk
    Updated Jul 23, 2022
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    Office for National Statistics (2022). Output Area (2011) to Major Towns and Cities (December 2015) Best Fit Lookup in EW [Dataset]. https://hub.arcgis.com/datasets/710f510c52a84ae8a0ab0be104a4b021
    Explore at:
    Dataset updated
    Jul 23, 2022
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A best fit lookup between 2011 Output Areas (OA) and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data. (File Size - 4 MB). REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/OA11_TCITY15_EW_LU_65267a69bf06490d81a4ee1458747f48/FeatureServer

    For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about

  6. e

    Bradford Council populations

    • data.europa.eu
    • cloud.csiss.gmu.edu
    html, pdf
    Updated Sep 25, 2021
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    City of Bradford Metropolitan District Council (2021). Bradford Council populations [Dataset]. https://data.europa.eu/data/datasets/bradford-council-populations
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    pdf, htmlAvailable download formats
    Dataset updated
    Sep 25, 2021
    Dataset authored and provided by
    City of Bradford Metropolitan District Council
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Bradford
    Description

    The latest population figures produced by the Office for National Statistics (ONS) on 28 June 2018 show that an estimated 534,800 people live in Bradford District – an increase of 2,300 people (0.4%) since the previous year.

    Bradford District is the fifth largest metropolitan district (in terms of population) in England, after Birmingham, Leeds, Sheffield and Manchester although the District’s population growth is lower than other major cities.

    The increase in the District’s population is largely due to “natural change”- there have been around 3,300 more births than deaths, although this has been balanced by a larger number of people leaving Bradford to live in other parts of the UK than coming to live here and a lower number of international migrants. In 2016/17 the net internal migration was -2,700 and the net international migration was 1,700.

    A large proportion of Bradford’s population is dominated by the younger age groups. More than one-quarter (29%) of the District’s population is aged less than 20 and nearly seven in ten people are aged less than 50. Bradford has the highest percentage of the under 16 population in England after the London Borough of Barking and Dagenham, Slough Borough Council and Luton Borough Council.

    The population of Bradford is ethnically diverse. The largest proportion of the district’s population (63.9%) identifies themselves as White British. The district has the largest proportion of people of Pakistani ethnic origin (20.3%) in England.

    The largest religious group in Bradford is Christian (45.9% of the population). Nearly one quarter of the population (24.7%) are Muslim. Just over one fifth of the district’s population (20.7%) stated that they had no religion.

    There are 216,813 households in the Bradford district. Most households own their own home (29.3% outright and 35.7% with a mortgage). The percentage of privately rented households is 18.1%. 29.6% of households were single person households.

    Information from the Annual Population Survey in December 2017 found that Bradford has 228,100 people aged 16-64 in employment. At 68% this is significantly lower than the national rate (74.9%). 91,100 (around 1 in 3 people) aged 16-64, are not in work. The claimant count rate is 2.9% which is higher than the regional and national averages.

    Skill levels are improving with 26.5% of 16 to 74 year olds educated to degree level. 18% of the district’s employed residents work in retail/wholesale. The percentage of people working in manufacturing has continued to decrease from 13.4% in 2009 to 11.9% in 2016. This is still higher than the average for Great Britain (8.1%).

  7. Major Towns and Cities (December 2015) Boundaries

    • cloud.csiss.gmu.edu
    • data.europa.eu
    • +1more
    csv, esri rest +6
    Updated Dec 25, 2019
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    Office for National Statistics (2019). Major Towns and Cities (December 2015) Boundaries [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/major-towns-and-cities-december-2015-boundaries5
    Explore at:
    kml, html, wfs, csv, wms, zip, geojson, esri restAvailable download formats
    Dataset updated
    Dec 25, 2019
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    This file contains the digital vector boundaries for Major Towns and Cities in England and Wales in 2015. The Major Towns and Cities (TCITY) statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data. 112 TCITY are included in the dataset. The TCITY boundaries are generalised and created using an automated approach based on a 50m grid squares.


    Contains both Ordnance Survey and ONS Intellectual Property Rights.

    Download File Size - 3 MB



  8. Data from: Towns and cities, characteristics of built-up areas, England and...

    • ons.gov.uk
    xlsx
    Updated Aug 2, 2023
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    Office for National Statistics (2023). Towns and cities, characteristics of built-up areas, England and Wales: Census 2021 [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/housing/datasets/townsandcitiescharacteristicsofbuiltupareasenglandandwalescensus2021
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Aug 2, 2023
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    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.

  9. a

    Workplace Zone (2011) to Major Towns and Cities (December 2015) Best Fit...

    • hub.arcgis.com
    • geoportal.statistics.gov.uk
    • +1more
    Updated Jul 23, 2022
    + more versions
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    Office for National Statistics (2022). Workplace Zone (2011) to Major Towns and Cities (December 2015) Best Fit Lookup in EW [Dataset]. https://hub.arcgis.com/datasets/41655bf542e949c0bea9cff5653205fe
    Explore at:
    Dataset updated
    Jul 23, 2022
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A best fit lookup between 2011 Workplace Zones (WZ) and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales. The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-up Areas geography that was created for the release of 2011 Census data (File Size 1.3MB).REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/WZ11_TCITY15_EW_LU_a7a1a2f6feb24aac800596276d82f5ad/FeatureServer

    For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about

  10. f

    Travel time to cities and ports in the year 2015

    • figshare.com
    tiff
    Updated May 30, 2023
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    Andy Nelson (2023). Travel time to cities and ports in the year 2015 [Dataset]. http://doi.org/10.6084/m9.figshare.7638134.v4
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    tiffAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    figshare
    Authors
    Andy Nelson
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The dataset and the validation are fully described in a Nature Scientific Data Descriptor https://www.nature.com/articles/s41597-019-0265-5

    If you want to use this dataset in an interactive environment, then use this link https://mybinder.org/v2/gh/GeographerAtLarge/TravelTime/HEAD

    The following text is a summary of the information in the above Data Descriptor.

    The dataset is a suite of global travel-time accessibility indicators for the year 2015, at approximately one-kilometre spatial resolution for the entire globe. The indicators show an estimated (and validated), land-based travel time to the nearest city and nearest port for a range of city and port sizes.

    The datasets are in GeoTIFF format and are suitable for use in Geographic Information Systems and statistical packages for mapping access to cities and ports and for spatial and statistical analysis of the inequalities in access by different segments of the population.

    These maps represent a unique global representation of physical access to essential services offered by cities and ports.

    The datasets travel_time_to_cities_x.tif (where x has values from 1 to 12) The value of each pixel is the estimated travel time in minutes to the nearest urban area in 2015. There are 12 data layers based on different sets of urban areas, defined by their population in year 2015 (see PDF report).

    travel_time_to_ports_x (x ranges from 1 to 5)

    The value of each pixel is the estimated travel time to the nearest port in 2015. There are 5 data layers based on different port sizes.

    Format Raster Dataset, GeoTIFF, LZW compressed Unit Minutes

    Data type Byte (16 bit Unsigned Integer)

    No data value 65535

    Flags None

    Spatial resolution 30 arc seconds

    Spatial extent

    Upper left -180, 85

    Lower left -180, -60 Upper right 180, 85 Lower right 180, -60 Spatial Reference System (SRS) EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)

    Temporal resolution 2015

    Temporal extent Updates may follow for future years, but these are dependent on the availability of updated inputs on travel times and city locations and populations.

    Methodology Travel time to the nearest city or port was estimated using an accumulated cost function (accCost) in the gdistance R package (van Etten, 2018). This function requires two input datasets: (i) a set of locations to estimate travel time to and (ii) a transition matrix that represents the cost or time to travel across a surface.

    The set of locations were based on populated urban areas in the 2016 version of the Joint Research Centre’s Global Human Settlement Layers (GHSL) datasets (Pesaresi and Freire, 2016) that represent low density (LDC) urban clusters and high density (HDC) urban areas (https://ghsl.jrc.ec.europa.eu/datasets.php). These urban areas were represented by points, spaced at 1km distance around the perimeter of each urban area.

    Marine ports were extracted from the 26th edition of the World Port Index (NGA, 2017) which contains the location and physical characteristics of approximately 3,700 major ports and terminals. Ports are represented as single points

    The transition matrix was based on the friction surface (https://map.ox.ac.uk/research-project/accessibility_to_cities) from the 2015 global accessibility map (Weiss et al, 2018).

    Code The R code used to generate the 12 travel time maps is included in the zip file that can be downloaded with these data layers. The processing zones are also available.

    Validation The underlying friction surface was validated by comparing travel times between 47,893 pairs of locations against journey times from a Google API. Our estimated journey times were generally shorter than those from the Google API. Across the tiles, the median journey time from our estimates was 88 minutes within an interquartile range of 48 to 143 minutes while the median journey time estimated by the Google API was 106 minutes within an interquartile range of 61 to 167 minutes. Across all tiles, the differences were skewed to the left and our travel time estimates were shorter than those reported by the Google API in 72% of the tiles. The median difference was −13.7 minutes within an interquartile range of −35.5 to 2.0 minutes while the absolute difference was 30 minutes or less for 60% of the tiles and 60 minutes or less for 80% of the tiles. The median percentage difference was −16.9% within an interquartile range of −30.6% to 2.7% while the absolute percentage difference was 20% or less in 43% of the tiles and 40% or less in 80% of the tiles.

    This process and results are included in the validation zip file.

    Usage Notes The accessibility layers can be visualised and analysed in many Geographic Information Systems or remote sensing software such as QGIS, GRASS, ENVI, ERDAS or ArcMap, and also by statistical and modelling packages such as R or MATLAB. They can also be used in cloud-based tools for geospatial analysis such as Google Earth Engine.

    The nine layers represent travel times to human settlements of different population ranges. Two or more layers can be combined into one layer by recording the minimum pixel value across the layers. For example, a map of travel time to the nearest settlement of 5,000 to 50,000 people could be generated by taking the minimum of the three layers that represent the travel time to settlements with populations between 5,000 and 10,000, 10,000 and 20,000 and, 20,000 and 50,000 people.

    The accessibility layers also permit user-defined hierarchies that go beyond computing the minimum pixel value across layers. A user-defined complete hierarchy can be generated when the union of all categories adds up to the global population, and the intersection of any two categories is empty. Everything else is up to the user in terms of logical consistency with the problem at hand.

    The accessibility layers are relative measures of the ease of access from a given location to the nearest target. While the validation demonstrates that they do correspond to typical journey times, they cannot be taken to represent actual travel times. Errors in the friction surface will be accumulated as part of the accumulative cost function and it is likely that locations that are further away from targets will have greater a divergence from a plausible travel time than those that are closer to the targets. Care should be taken when referring to travel time to the larger cities when the locations of interest are extremely remote, although they will still be plausible representations of relative accessibility. Furthermore, a key assumption of the model is that all journeys will use the fastest mode of transport and take the shortest path.

  11. s

    LSOA (2001) to Major Towns and Cities (December 2015) Best Fit Lookup in EW

    • geoportal.statistics.gov.uk
    • open-geography-portalx-ons.hub.arcgis.com
    Updated Dec 13, 2017
    + more versions
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    Office for National Statistics (2017). LSOA (2001) to Major Towns and Cities (December 2015) Best Fit Lookup in EW [Dataset]. https://geoportal.statistics.gov.uk/datasets/lsoa-2001-to-major-towns-and-cities-december-2015-best-fit-lookup-in-ew/about
    Explore at:
    Dataset updated
    Dec 13, 2017
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A best fit lookup between 2001 Lower layer Super Output Areas (LSOA) and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data (File Size 1.5MB). For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about

    REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/LSOA01_TCITY15_EW_LU_3ce58949f68241f4892dc8d1d23a1bfd/FeatureServer

  12. e

    Focus on London - Population and Migration

    • data.europa.eu
    • data.wu.ac.at
    unknown
    Updated Oct 18, 2021
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    GLA Intelligence Unit (2021). Focus on London - Population and Migration [Dataset]. https://data.europa.eu/88u/dataset/focus-on-london-population-and-migration-1
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    unknownAvailable download formats
    Dataset updated
    Oct 18, 2021
    Dataset authored and provided by
    GLA Intelligence Unit
    Area covered
    London
    Description

    This report was released in September 2010. However, recent demographic data is available on the datastore - you may find other datasets on the Datastore useful such as: GLA Population Projections, National Insurance Number Registrations of Overseas Nationals, Births by Birthplace of Mother, Births and Fertility Rates, Office for National Statistics (ONS) Population Estimates

    FOCUSONLONDON2010:POPULATIONANDMIGRATION

    London is the United Kingdom’s only city region. Its population of 7.75 million is 12.5 per cent of the UK population living on just 0.6 per cent of the land area. London’s average population density is over 4,900 persons per square kilometre, this is ten times that of the second most densely populated region.

    Between 2001 and 2009 London’s population grew by over 430 thousand, more than any other region, accounting for over 16 per cent of the UK increase.

    This report discusses in detail the population of London including Population Age Structure, Fertility and Mortality, Internal Migration, International Migration, Population Turnover and Churn, and Demographic Projections.

    Population and Migration report is the first release of the Focus on London 2010-12 series. Reports on themes such as Income, Poverty, Labour Market, Skills, Health, and Housing are also available.

    PRESENTATION:

    To access an interactive presentation about population changes in London click the link to see it on Prezi.com

    FACTS:

    • Top five boroughs for babies born per 10,000 population in 2008-09:
    • 1. Newham – 244.4
    • 2. Barking and Dagenham – 209.3
    • 3. Hackney – 205.7
    • 4. Waltham Forest – 202.7
    • 5. Greenwich – 196.2
    • ...
    • 32. Havering – 116.8
    • 33. City of London – 47.0
    • In 2009, Barnet overtook Croydon as the most populous London borough. Prior to this Croydon had been the largest since 1966
    • Population per hectare of land used for Domestic building and gardens is highest in Tower Hamlets
    • In 2008-09, natural change (births minus deaths) led to 78,000 more Londoners compared with only 8,000 due to migration. read more about this or click play on the chart below to reveal how regional components of populations change have altered over time.
  13. l

    Census 21 - Main Language MSOA

    • data.leicester.gov.uk
    csv, excel, geojson +1
    Updated Aug 22, 2023
    + more versions
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    (2023). Census 21 - Main Language MSOA [Dataset]. https://data.leicester.gov.uk/explore/dataset/census-21-main-language-msoa/
    Explore at:
    json, geojson, excel, csvAvailable download formats
    Dataset updated
    Aug 22, 2023
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for the MSOAs of Leicester and compare this with Leicester overall statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsMain languageThis dataset provides Census 2021 estimates that classify usual residents in England and Wales by their main language. The estimates are as at Census Day, 21 March 2021.Main language is a person's first or preferred language. They may speak other languages as well. A main language is provided only for residents age 3 and above. Residents age below 3 years will appear as ‘Does not apply’. Please note that some organisations exclude those below 3 years when calculating percentages for this variable.This dataset contains information for the MSOAs of Leicester City.

  14. England and Wales Census 2021 - TS024: Main language (detailed)

    • statistics.ukdataservice.ac.uk
    xlsx
    Updated Feb 10, 2023
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    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service. (2023). England and Wales Census 2021 - TS024: Main language (detailed) [Dataset]. https://statistics.ukdataservice.ac.uk/dataset/england-and-wales-census-2021-ts024-main-language-detailed
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    xlsxAvailable download formats
    Dataset updated
    Feb 10, 2023
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Northern Ireland Statistics and Research Agency
    Office for National Statisticshttp://www.ons.gov.uk/
    Authors
    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service.
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    Wales, England
    Description

    This dataset provides Census 2021 estimates that classify usual residents in England and Wales by their main language. The estimates are as at Census Day, 21 March 2021.

    Main language (detailed) (95 categories)

    A person's first or preferred language.

    This shows a detailed breakdown of the responses given in the write-in option "Other, write in".

    Area type

    Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

    For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

    Lower Tier Local Authorities

    Lower tier local authorities provide a range of local services. In England there are 309 lower tier local authorities. These are made up of non-metropolitan districts (181), unitary authorities (59), metropolitan districts (36) and London boroughs (33, including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities. Of these local authority types, only non-metropolitan districts are not additionally classified as upper tier local authorities.

  15. a

    Cancer (in persons of all ages): England

    • hub.arcgis.com
    • data.catchmentbasedapproach.org
    Updated Apr 6, 2021
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    The Rivers Trust (2021). Cancer (in persons of all ages): England [Dataset]. https://hub.arcgis.com/datasets/c5c07229db684a65822fdc9a29388b0b
    Explore at:
    Dataset updated
    Apr 6, 2021
    Dataset authored and provided by
    The Rivers Trust
    Area covered
    Description

    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.

  16. a

    Levels of obesity, inactivity and associated illnesses (England): Summary

    • hub.arcgis.com
    • data.catchmentbasedapproach.org
    • +1more
    Updated Apr 20, 2021
    + more versions
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    The Rivers Trust (2021). Levels of obesity, inactivity and associated illnesses (England): Summary [Dataset]. https://hub.arcgis.com/maps/theriverstrust::levels-of-obesity-inactivity-and-associated-illnesses-england-summary
    Explore at:
    Dataset updated
    Apr 20, 2021
    Dataset authored and provided by
    The Rivers Trust
    Area covered
    Description

    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

  17. England and Wales Census 2021 - Ethnic group by highest level qualification

    • statistics.ukdataservice.ac.uk
    xlsx
    Updated Mar 15, 2023
    + more versions
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    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service. (2023). England and Wales Census 2021 - Ethnic group by highest level qualification [Dataset]. https://statistics.ukdataservice.ac.uk/dataset/england-and-wales-census-2021-ethnic-group-by-highest-level-qualification
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Mar 15, 2023
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Northern Ireland Statistics and Research Agency
    Office for National Statisticshttp://www.ons.gov.uk/
    Authors
    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service.
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England, Wales
    Description

    This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.

    The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

    Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

    "Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

    This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

    These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

    For quality information in general, please read more from here.

    Ethnic Group (19 tick-box level)

    These are the 19 ethnic group used in this dataset:

    • Asian, Asian British or Asian Welsh
      • Bangladeshi
      • Chinese
      • Indian
      • Pakistani
      • Other Asian
    • Black, Black British, Black Welsh, Caribbean or African
      • African
      • Caribbean
      • Other Black
    • Mixed or Multiple ethnic groups
      • White and Asian
      • White and Black African
      • White and Black Caribbean
      • Other Mixed or Multiple ethnic groups
    • White
      • English, Welsh, Scottish, Northern Irish or British
      • Gypsy or Irish Traveller
      • Irish
      • Roma
      • Other White
    • Other ethnic group
      • Arab
      • Any other ethnic group

    No qualifications

    No qualifications

    Level 1

    Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

    Level 2

    5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

    Apprenticeship

    Apprenticeship

    Level 3

    2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

    Level 4 +

    Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

    Other

    Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

  18. a

    MSOA (2011) to Major Towns and Cities (December 2015) Best Fit Lookup in EW

    • open-geography-portalx-ons.hub.arcgis.com
    • geoportal.statistics.gov.uk
    Updated Dec 13, 2017
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    Office for National Statistics (2017). MSOA (2011) to Major Towns and Cities (December 2015) Best Fit Lookup in EW [Dataset]. https://open-geography-portalx-ons.hub.arcgis.com/datasets/msoa-2011-to-major-towns-and-cities-december-2015-best-fit-lookup-in-ew
    Explore at:
    Dataset updated
    Dec 13, 2017
    Dataset authored and provided by
    Office for National Statistics
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    A best fit lookup between Middle Layer Super Output Areas (MSOA) as at December 2011, and Major Towns and Cities (TCITY) as at December 2015 in England and Wales. The TCITY statistical geography provides a precise definition of the major towns and cities in England and Wales The geography has been developed specifically for the production and analysis of statistics, and is based on the Built-Up Areas geography that was created for the release of 2011 Census data (File Size 297KB).REST URL of Feature Access Service – https://services1.arcgis.com/ESMARspQHYMw9BZ9/arcgis/rest/services/MSOA11_TCITY15_EW_LU_e9458a2654ac404c961d645c86978493/FeatureServer

    For more information and an overview of best-fitting follow this link - https://geoportal.statistics.gov.uk/datasets/f0aac7ccbfd04cda9eb03e353c613faa/about

  19. Standard Area Measurements for 2021 Statistical Geographies (March 2021) in...

    • geoportal.statistics.gov.uk
    Updated Aug 16, 2022
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    Office for National Statistics (2022). Standard Area Measurements for 2021 Statistical Geographies (March 2021) in EW (V2) [Dataset]. https://geoportal.statistics.gov.uk/datasets/a488cb8fc9a74accb63cb52961e456ef
    Explore at:
    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences

    Area covered
    Description

    This zip file contains the Standard Area Measurements (SAM) for the 2021 Statistical Areas in England and Wales as at Census Day (21 March 2021). This includes the Output Areas (OA), Lower layer Super Output Areas (LSOA), Middle layer Super Output Areas (MSOA), the Lower-Tier Local Authorities (LTLA) including the Unitary Authorities (E06 and W06), Non-metropolitan Districts (E07), Metropolitan Districts (E08) and London Boroughs (E09), the Upper-Tier Local Authorities (UTLA) including the Unitary Authorities (E06 and W06), Counties (E10), Metropolitan Districts (E08) and London Boroughs (E09), the Regions including the country of Wales, Countries and National. All measurements provided are ‘flat’ as they do not take into account variations in relief e.g. mountains and valleys. Measurements are given in hectares (10,000 square metres) to 2 decimal places and square kilometres to 4 decimal places. Four types of measurements are included: total extent (AREAEHECT), area to mean high water (coastline) (AREACHECT), area of inland water (AREAIHECT) and area to mean high water excluding area of inland water (land area) (AREALHECT). The Eurostat-recommended approach is to use the ‘land area’ measurement to compile population density figures.This V2 is because the user guide name was too long.PLEASE NOTE:There is an extremely small OA with the code E00187556 and measures 400 centimetres squared. This is because all the population and household points are centred around a very small space and to make sure it was in threshold it was manually changed to make it within threshold.Click the Download button to download the files

  20. England and Wales Census 2021 - Religion by highest qualification level

    • statistics.ukdataservice.ac.uk
    xlsx
    Updated Mar 24, 2023
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    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service. (2023). England and Wales Census 2021 - Religion by highest qualification level [Dataset]. https://statistics.ukdataservice.ac.uk/dataset/england-and-wales-census-2021-religion-by-highest-qualification-level
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Mar 24, 2023
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    Office for National Statisticshttp://www.ons.gov.uk/
    Northern Ireland Statistics and Research Agency
    Authors
    Office for National Statistics; National Records of Scotland; Northern Ireland Statistics and Research Agency; UK Data Service.
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England, Wales
    Description

    Census 2021 data on religion by highest qualification level, by sex, by age, England and Wales combined. This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

    The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it.
    This question was voluntary and the variable includes people who answered the question, including “No religion”, alongside those who chose not to answer this question.

    Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

    This dataset shows population counts for usual residents aged 16 years and over. Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

    These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

    Quality notes can be found here

    Quality information about Education can be found here

    Religion

    The 8 ‘tickbox’ religious groups are as follows:

    • Buddhist
    • Christian
    • Hindu
    • Jewish
    • Muslim
    • No religion
    • Sikh
    • Other religion

    No qualifications

    No qualifications

    Level 1

    Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

    Level 2

    5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

    Apprenticeship

    Apprenticeship

    Level 3

    2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

    Level 4 +

    Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

    Other

    Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

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Office for National Statistics (2024). Estimates of the population for the UK, England, Wales, Scotland, and Northern Ireland [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland
Organization logo

Estimates of the population for the UK, England, Wales, Scotland, and Northern Ireland

Explore at:
xlsxAvailable download formats
Dataset updated
Oct 8, 2024
Dataset provided by
Office for National Statisticshttp://www.ons.gov.uk/
License

Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically

Area covered
Ireland, England, United Kingdom
Description

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).

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