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).

Interactive web application featuring Population Density within Southends local areas plus for comparison England and Wales districts. Created in November 2021. Population mid-year 2020 data and Standard Area Measurements (SAM) data sourced from ONS

The statistic depicts the median age of the population in the United Kingdom from 1950 to 2100*. The median age of a population is an index that divides the population into two equal groups: half of the population is older than the median age and the other half younger. In 2020, the median age of United Kingdom's population was 39.2 years. Population of the United Kingdom The United Kingdom (UK) includes Great Britain (England, Scotland and Wales) and Northern Ireland, and is a state located off the coast of continental Europe. The United Kingdom is a constitutional monarchy, which means the Queen acts as representative head of state, while laws and constitutional issues are discussed and passed by a parliament. The total UK population figures have been steadily increasing, albeit only slightly, over the last decade; in 2011, the population growth rate was lower than in the previous year for the first time in eight years. Like many other countries, the UK and its economy were severely affected by the economic crisis in 2009. Since then, the unemployment rate has doubled and is only recovering slowly. UK inhabitants tend to move to the cities to find work and better living conditions; urbanization in the United Kingdom has been on the rise. At the same time, population density in the United Kingdom has been increasing due to several factors, for example, the rising number of inhabitants and their life expectancy at birth, an increasing fertility rate, and a very low number of emigrants. In fact, the United Kingdom is now among the 20 countries with the highest life expectancy at birth worldwide. As can be seen above, the median age of UK residents has also been increasing significantly since the seventies; another indicator for a well-working economy and society.

The mid-year estimates refer to the population on 30 June of the reference year and are produced in line with the standard United Nations (UN) definition for population estimates. They are the official set of population estimates for the UK and its constituent countries, the regions and counties of England, and local authorities and their equivalents.

Mid-year (30 June) estimates of the usual resident population for electoral wards in England and Wales. Note: this page is no longer updated. Latest estimates, and all data for mid-2012 onwards, are available on the Nomis website.

According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.

11th January 2020 Change to vaccination data made available by UK gov - now just cumulative number of vaccines delivered are available for both first and second doses. For the devolved nations the cumulative totals are available for the dates from when given, however for the UK as a whole the total doses given is just on the last date of the index, regardless of when those vaccines were given.

4th January 2020 VACCINATION DATA ADDED - New and Cumulative First Dose Vaccination Data added to UK_National_Total_COVID_Dataset.csv and UK_Devolved_Nations_COVID_Dataset.csv

2nd December 2020:

NEW population, land area and population density data added in file NEW_Official_Population_Data_ONS_mid-2019.csv. This data is scraped from the Office for National Statistics and covers the UK, devolved UK nations, regions and local authorities (boroughs).

20th November 2020:

With European governments struggling with a 'second-wave' of rising cases, hospitalisations and deaths resulting from the SARS-CoV-2 virus (COVID-19), I wanted to make a comparative analysis between the data coming out of major European nations since the start of the pandemic.

I started by creating a Sweden COVID-19 dataset and now I'm looking at my own country, the United Kingdom.

The data comes from https://coronavirus.data.gov.uk/ and I used the Developer's Guide to scrape the data, so it was a fairly simple process. The notebook that scapes the data is public and can be found here. Further information about data collection methodologies and definitions can be found here.

The data includes the overall numbers for the UK as a whole, the numbers for each of the devolved UK nations (Eng, Sco, Wal & NI), English Regions and Upper Tier Local Authorities (UTLA) for all of the UK (what we call Boroughs). I have also included a small table with the populations of the 4 devolved UK nations, used to calculate the death rates per 100,000 population.

As I've said for before - I am not an Epidemiologist, Sociologist or even a Data Scientist. I am actually a Mechanical Engineer! The objective here is to improve my data science skills and maybe provide some useful data to the wider community.

Any questions, comments or suggestions are most welcome! I am open to requests and collaborations! Stay Safe!

This zip file contains the Standard Area Measurements (SAM) for the administrative areas in the United Kingdom as at 31 December 2020. This includes the wards, local authority districts, counties and regions in England and the countries. 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. 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.Couple of wards have updated ward codes - E05013830 Garforth & Swillington and E05013831 Temple Newsam. No changes in the Standard Area Measurements.Click the Download button to download the files

Mid-year (30 June) estimates of the usual resident population for Lower layer Super Output Areas (LSOAs) in England and Wales by single year of age and sex.

As of 2024, the population density in London was by far the highest number of people per square km in the UK, at *****. Of the other regions and countries which constitute the United Kingdom, North West England was the next most densely populated area at *** people per square kilometer. Scotland, by contrast, is the most sparsely populated country or region in the United Kingdom, with only ** people per square kilometer. Countries, regions, and cities In 2024, the population of the United Kingdom reached **** million. The majority of people in the UK live in England, which had a population of **** million that year, followed by Scotland at *** million, Wales at **** million and finally Northern Ireland at just over *** million. Within England, the South East was the region with the highest population at almost *** million, followed by London at just over *****million. In terms of cities, London is the largest urban agglomeration in the United Kingdom, followed by Manchester, and then Birmingham, although both these cities combined would still have a smaller population than the UK capital. London calling London's huge size in relation to other UK cities is also reflected by its economic performance. In 2023, London's GDP was over ****billion British pounds, around a quarter of UK's overall GDP. In terms of GDP per capita, Londoners had a GDP per head of ****** pounds, compared with an average of ****** for the country as a whole. Productivity, expressed as by output per hour worked, was also far higher in London than the rest of the country. In 2023, London was around *****percent more productive than the rest of the country, with South East England the only other region where productivity was higher than the national average.

This zip file contains the Standard Area Measurements (SAM) for the Health areas in England as at 1 April 2020 in CSV and XLSX format. This includes the Clinical Commissioning Groups (CCG), NHS England Regions (NHSER), Cancer Alliances (CAL) and Sustainability and Transformation Partnerships (STP). 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. 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.Click the Download button to download the file (293 KB)

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Equatorial Guinea data available from WorldPop here.

Mid-year (30 June) estimates of the usual resident population for health geographies in England and Wales.

In 2024, over 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 just over 3.03 million, closely followed by Greater Manchester at three million, and then West Yorkshire with a population of 2.4 million. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with just over 1.9 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 2024, the most-populated Scottish council area was Glasgow City, with over 650,000 inhabitants. In Wales, Cardiff had the largest population among its unitary authorities, and in Northern Ireland, Belfast was the local government area with the most people living there.

This zip file contains the Standard Area Measurements (SAM) for the parishes and non-civil parished areas in England and Wales as at 31 December 2020. 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. 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. Click the Download button to download the files

Abstract

1. A pioneering, quantitative study published in the Journal of Animal Ecology in 1966 on freshwater mussel populations in the River Thames, UK, continues to be cited extensively as evidence of the major contribution that mussels make to benthic biomass and ecosystem functioning in global river ecosystems.
2. Ecological alteration, as well as declines in freshwater mussel populations elsewhere, suggest that changes to mussel populations in the River Thames are likely to have occurred over the half century since this study.
3. We resurveyed the site reported in Negus (1966) and quantified the changes in mussel population density, species composition, growth patterns and productivity.
4. We found large declines in population density for all unionid species. The duck mussel Anodonta anatina decreased to 1.1% of 1964 density. The painter’s mussel Unio pictorum fell to 3.2% of 1964 density. The swollen river mussel Unio tumidus showed statistically non-significant declines. In contrast to 1964, in 2020 we found no living specimens of the depressed river mussel Pseudanodonta complanata (classified as Vulnerable by the IUCN Red List) but found new records of the invasive, non-native zebra mussel Dreissena polymorpha and Asian clam Corbicula fluminea. Additionally, we found strong decreases in size-at-age for all species, which now grow to 65-90% of maximum lengths in 1964. As a result of reduced density and size, estimated annual biomass production fell to 7.5% of 1964 levels.
5. Since mussels can be important to ecosystem functioning, providing key regulating and provisioning services, the declines we found imply substantial degradation of freshwater ecosystem services in the River Thames, one of the UK’s largest rivers. Our study also highlights the importance to conservationists and ecologists of updating and validating assumptions and data about wild populations, which in the present era of anthropogenic ecosystem alteration are undergoing significant and rapid changes. Regular population surveys of key species are essential to maintain an accurate picture of ecosystem health and to guide management.

Data collection

Sampling was conducted on 22 September 2020 in the River Thames adjacent to Wokingham Waterside Centre (51°27'35.7"N 0°56'34.3"W). The Thames is a 346km river with a densely populated catchment covering the southeast of England, comprising both tidal and non-tidal stretches and with 45 navigation locks and associated weirs. The study area was located in the non-tidal stretch, approximately 152km downstream of the source, and directly downstream of the city of Reading. Mean flow for the study area is 37.9 m3s-1 (data from the UK National River Flow Archive). By consulting maps published in Mann (1965) and Negus (1966) we were able to resurvey the identical locality to that surveyed in 1964, a 250m stretch of river varying in width from 50 to 65m.

Data collection

Sampling was designed to replicate as closely as possible the methods employed by Negus (1966). Consultation of the original paper was supplemented by in-person discussions with the original author. We sampled across four depth zones: 0-1m (n=32), 1-2m (n=32), 2-3m (n=14) and 3-4m (n=15), for a total of 93 samples, compared with a total of 24 samples conducted by Negus. We took equal numbers of replicates from each side of the river for each depth zone and allocating sampling effort proportionally to the different microhabitats present. Sampling in the 0-1m and 1-2m depth zones was conducted using randomly-placed 1m2 quadrats, with all live unionids within the quadrat area collected and transported to the lab for measurement. Sampling in the 2-3m and 3-4m zones was conducted by dredging (dredge width 45cm, mesh size 15mm) from a boat along replicate 20m-long upriver transects. Since dredge transects covered a greater area than the quadrats in shallower zones, we conducted fewer replicates for these deeper zones. The dredges used in 1964 and the present study were similar in design and conformed to the National Rivers Authority (1996) and Environment Agency (present) specifications, including a rectangular frame and angled blade to enable sampling from sediments including gravel, silt and mud. The dredges were also operated in a similar way, with samples collected by towing from a motor boat. The total area dredged was 580m2, compared with a total dredged sample area of 23.22m2 in 1964. All live mussels and all unionid shells were identified to species and recorded. For live unionids, we measured the length (longest anterior-to-posterior axis), height (dorsal-ventral axis) and width (left-right axis) using digital callipers. We additionally measured the length of each shell annulus (along its longest anterior-to-posterior axis). These are distinctive dark bands on the shell formed during periods of temporary growth cessation and have been confirmed to be annual (Rypel et al., 2008), including for populations in the Thames (Negus, 1966). They can therefore be used as a reliable measure of a mussel’s yearly growth (Aldridge, 1999).
We dissected a subset of 50 mussels, distributed across species, sampling depths and sizes, to measure shell wet mass and total wet mass separately in order to calculate an estimate of biomass production, following the method reported by Negus. To limit the extent of destructive sampling, we regressed wet mass on length and used this to interpolate total and shell wet mass for the remaining individuals. We report these equations for future reference in Table S1. Data for mussel populations in 1964 were obtained from Negus (Negus, 1966) and extracted from graphs using the software DataThief III (Tummers, 2006). Data used for comparison were those reported from ‘1964, unheated’ surveys. Additional surveys reported from 1963 and from heated effluents near the now-closed Earley Power Station offered less complete and less comparable data and were excluded. Water quality monitoring data were obtained from the Environment Agency for the River Thames at Caversham Weir monitoring point (sampling point ID: TH-PTHR0080), approximately 2km upstream of our sampling location. Data from 2000-present are publicly available (Environment Agency, 2021) and data for 1972 – 1999 were obtained via a Freedom of Information request. This study did not require ethical approval and no licences were required for the collection of mussels.

This file contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom as at August 2022 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. To download the zip file click the Download button. The NSPL relates both current and terminated postcodes to a range of current statutory geographies via ‘best-fit’ allocation from the 2021 Census Output Areas (national parks and Workplace Zones are exempt from ‘best-fit’ and use ‘exact-fit’ allocations) for England and Wales. Scotland and Northern Ireland has the 2011 Census Output AreasIt supports the production of area based statistics from postcoded data. The NSPL is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The NSPL is issued quarterly. (File size - 184 MB).

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

IntroductionEvidence for the effect of neighbourhood food environment (NFE) exposures on diet in the UK is mixed, potentially due to exposure misclassification. This study used the first national COVID-19 lockdown in England as an opportunity to isolate the independent effects of the NFE exposure on food and drink purchasing, and assessed whether these varied by region.MethodsTransaction-level purchasing data for food and drink items for at-home (1,221 households) and out-of-home consumption (171 individuals) were available from the GB Kantar Fast Moving Consumer Goods Panel for London and the North of England. The study period included 23rd March to 10th May 2020 (‘lockdown’), and the same period in 2019 for comparison. NFE exposures included food outlet density and proximity, and NFE composition within a 1 km network buffer around the home. Associations were estimated for both years separately, adjusted for individual and household characteristics, population density and area deprivation. Interaction terms between region and exposures were explored.ResultsThere were no consistent patterns of association between NFE exposures and food and drink purchasing in either time period. In 2019, there was some evidence for a 1.4% decrease in energy purchased from ultra-processed foods for each additional 500 m in the distance to the nearest OOH outlet (IR 0.986, 95% CI 0.977 to 0.995, p = 0.020). In 2020, there was some evidence for a 1.8% reduction in total take-home energy for each additional chain supermarket per km2 in the neighbourhood (IR 0.982, 95% CI 0.969, 0.995, p = 0.045). Region-specific effects were observed in 2019 only.DiscussionFindings suggest that the differences in exposure to the NFE may not explain differences in the patterns or healthiness of grocery purchasing. Observed pre-pandemic region-specific effects allude to the importance of geographical context when designing research and policy. Future research may assess associations for those who relied on their NFE during lockdown.

Understanding the size and spatial distribution of material stocks is crucial for sustainable resource management and climate change mitigation. This study presents high-resolution maps of buildings and mobility infrastructure stocks for the United Kingdom (UK) and the Republic of Ireland (IRL) at 10 m, combining satellite-based Earth observations, OpenStreetMaps, and material intensities research. Stocks in the UK and IRL amount to 19.8 Gigatons or 279 tons/cap, predominantly aggregate, concrete and bricks, as well as various metals and timber. Building stocks per capita are surprisingly similar across medium to high population density, with only the lowest population densities having substantially larger per capita stocks. Infrastructure stocks per capita decrease with higher population density. Interestingly, for a given building stock within an area, infrastructure stocks are substantially larger in IRL than in the UK. These maps can provide useful insights for sustainable urban planning and advancing a circular economy.

This dataset features a detailed map of material stocks in the United Kingdom and the Republic of Ireland on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.

Spatial extent
This dataset covers the whole British Isles. Due to processing reasons, the dataset is internally structured into the Island of Ireland, and the Island of Great Britain.

Temporal extent
The map is representative for ca. 2018.

Data format
The data are organized by nations. Within each nation, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.

Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).

Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.

• t at 10m x 10m
• kt at 100m x 100m
• Mt at 1km x 1km
• Gt at 10km x 10km

For each nation, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming.

Additionally, the grand total mass per nation is tabulated for each island in mass_grand_total_t_10m2.tif.csv. County code and the ID in this table can be related via zones_name_pop.csv.

Material layers
Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials).

Further information
For further information, please see the publication.
Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

Publication

D. Wiedenhofer, F. Schug, H. Gauch, M. Lanau, M. Drewniok, A. Baumgart, D. Virág, H. Watt, A. Cabrera Serrenho, D. Densley Tingley, H. Haberl, D. Frantz (2024): Mapping material stocks of buildings and mobility infrastructure in the United Kingdom and the Republic of Ireland. Resources, Conservation and Recycling 206, 107630. https://doi.org/10.1016/j.resconrec.2024.107630

Funding
This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

Acknowledgments
We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.