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).

This publication can be found in the NI prison service statistics section of the Department of Justice website.

This statistic illustrates the total housing stock per 1,000 population in Northern Ireland from 2008/2009 to 2019/2020. It can be seen that between the years of ******* and ******* the total housing stock per 1,000 population in Northern Ireland did not note a significant increase.

The Health Survey Northern Ireland (HSNI) was commissioned by the Department of Health in Northern Ireland and the Central Survey Unit (CSU) of the Northern Ireland Statistics and Research Agency (NISRA) carried out the survey on their behalf. This survey series has been running on a continuous basis since April 2010 with separate modules for different policy areas included in different financial years. It covers a range of health topics that are important to the lives of people in Northern Ireland. The HSNI replaces the previous Northern Ireland Health and Social Wellbeing Survey (available under SNs 4589, 4590 and 5710).

Adult BMI, height and weight measurements, accompanying demographic and derived variables, geography, and a BMI weighting variable, are available in separate datasets for each survey year.

Further information is available from the https://www.nisra.gov.uk/health-survey-northern-ireland" title="Northern Ireland Statistics and Research Agency">Northern Ireland Statistics and Research Agency and the https://www.health-ni.gov.uk/topics/doh-statistics-and-research/health-survey-northern-ireland" title="Department of Health (Northern Ireland)">Department of Health (Northern Ireland) survey webpages.

The Health Survey Northern Ireland, 2019-2020 provides a source of information on a wide range of health issues relevant to Northern Ireland. The information collected is pursuing the development of policies aimed at improving the health and well-being of the Northern Ireland population.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.


Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App.
The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively):

- Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
-Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
-Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
-Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020.
-Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019).

Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

The total population of Ireland was 5.42 million people in 2024. Between 1980 and 2024, the total population rose by 1.99 million people, though the increase followed an uneven trajectory rather than a consistent upward trend. The total population will steadily rise by 290,000 people over the period from 2024 to 2030, reflecting a clear upward trend.This indicator describes the total population in the country at hand. This total population of the country consists of all persons falling within the scope of the census.

These data were generated to compare different methods of estimating population density from marked and unmarked animal populations. We compare conventional live trapping with two more modern, non-invasive field methods of population estimation: genetic fingerprinting from hair-tube sampling and camera trapping for the European pine marten (Martes martes). We used arrays of camera traps, live traps, and hair tubes to collect the relevant data in the Ring of Gullion in Northern Ireland. We apply marked spatial capture-recapture models to the genetic and live trapping data where individuals were identifiable, and unmarked spatial capture-recapture (uSCR), distance sampling (CT-DS), and random encounter models (REM) to the camera trap data where individual ID was not possible. All five approaches produced plausible and relatively consistent point estimates (0.41 – 0.99 animals per km2), despite differences in precision, cost, and effort being apparent. In addition to the data, we provide novel code for running unmarked spatial capture-recapture (uSCR) and random encounter models (REM) to the camera trap data where individual ID was not possible. Methods All fieldwork was carried out in the Ring of Gullion, Northern Ireland, UK. Cameras Thirty Bushnell HD Trophy Cam 8MP camera traps (model number: 119577) with 8GB SD cards were deployed during June and July 2019. Thirty Bushnell HD Trophy Cam 8MP camera traps (model number: 119577) with 8GB SD cards were deployed during June and July 2019. At the end of the survey period, camera traps were checked and for each detection (the first image in a trigger sequence of an individual pine marten) distance to animal (m) and angle of detection (°) were measured in situ. Noninvasive genetic sampling Twenty hair tubes based on those developed by Mullins et al. (2010), were deployed across the study site between June and July 2019. Hair-tubes were checked weekly and sticky patches and bait were replaced on each visit. Hair samples were frozen at -20oC prior to DNA extraction. Microsatellite analysis to identify individual pine marten was carried out using up to 11 microsatellite markers. Each sample was analysed in duplicate and only samples giving identical results in the replicates were scored. Live traps Twelve Tomahawk 205 live cage traps were deployed along two perpendicular transects spaced approximately 400m apart. Trapping was conducted from August - October 2019 with daily trap checks. Trapped animals were anaesthetised with an intramuscular injection of ketamine (25mg per kg) and midazolam (0.2mg per kg) and scanned for a microchip. Statistical analyses Spatially explicit capture-recapture (SECR) models were used to estimate density for both live trapping and gNIS (Efford & Boulanger, 2019). Occasion lengths for live trapping were one day, whilst for gNIS were one week. For live trapping, we specified a single-use detector type, whilst for gNIS we specified a proximity-based detector type. Density was calculated from camera traps using REM (Rowcliffe et al. 2008), CT-DS (Howe et al. 2017) and uSCR (Chandler & Royle, 2013).

This dataset provides population estimates for the local authorities in Wales, the English regions and the UK countries for the period from 1991 onwards by sex and single year of age, together with some aggregated age groups. It should be noted that for mid-2020 there are some definitional changes (particularly affecting the migration components) compared with mid-2019 population estimates data and it is advised users read the Quality and Methodology Information section on the Office for National Statistics website. For Wales, England, and Northern Ireland, the mid-2021 population estimates are the first population estimates to be based on the 2021 censuses for these countries. For Scotland, the census was moved to 2022. The mid-2022 population estimates are the first population estimates to be based on the 2022 Census for Scotland. Internal migration estimates for mid-2023 have been produced using a different method to previous years, following a change to the variables available in the Higher Education Statistics Agency (HESA) data. This material is Crown Copyright and may be re-used (not including logos) free of charge in any format or medium, under the terms of the Open Government Licence.

The most popular sport or physical activity in Northern Ireland is walking for recreation. When it comes to specific types of sport, swimming, keepfit, jogging and cycling are the most practiced sports in Northern Ireland. Preferences appear to be rather similar between women and men, except that men tend to play more football and snooker or pool and women tend to do more keepfit and aerobics.

Sport participation stays constant in Northern Ireland   

The overall participation levels in sport in Northern Ireland stay constant. In 2019, approximately 56 percent of the population participated in some type of physical activity or sport, the same proportion throughout the past decade, only with minor fluctuations throughout. The most common barriers of participating are a lack of time available, a medical condition or simply being uninterested or untrained.

 Age groups  

The share of the population who participate in sports on a monthly basis is highest among 16 to 24 year olds and becomes lower as the age increases with 60 percent between 16 and 24 being physically active at least monthly and 20 percent of people 65 and over. The share of people who are physically active on every day of the week has significantly decreased in people 55 years and older over recent years.

Indicators included have been derived from the published 2019 mid-year population estimates for the UK, England, Wales, Scotland and Northern Ireland. These are the number of persons and percentage of the population aged 65 years and over, 85 years and over, 0 to 15 years, 16 to 64 years, 16 years to State Pension age, State Pension age and over, median age and the Old Age Dependency Ratio (the number of people of State Pension age per 1000 of those aged 16 years to below State Pension age).

This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which was published in July 2020. The tool enables users to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu.

Over the provided time period, the incident rate of cancer in Northern Ireland increased to 767.3 cases per 100,000 population in 2019. In 2020, the incidence fell to around 657 cases per 100,000, but the decline may have been caused by the COVID-19 pandemic affecting diagnosis rates. As a matter of fact, in 2021 this figure increased again, reaching 730.1 cases per 100,000 population. This statistic displays the incidence rate of cancer per 100,000 individuals in Northern Ireland from 2000 to 2021.

Both indicators included have been derived from the published 2019 mid-year population estimates for the UK, England, Wales, Scotland and Northern Ireland. These are sex ratios for people aged 65 years and over and 85 years and over. A sex ratio shows the number of males in the population for every 100 females.

This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which was published in July 2020. The tool enables users to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu.

Period life expectancy by age and sex for 1980 to 2023 for England, Wales (and combined), Scotland, Northern Ireland, Great Britain, and the UK. Each life table is based on population estimates, births and deaths for a single year.