The population of the United Kingdom in 2024 was estimated to be approximately 69.3 million, with over 9.6 million people living in South East England. London had the next highest population, at almost 9.1 million people, followed by the North West England at 7.7 million. With the UK's population generally concentrated in England, most English regions have larger populations than the constituent countries of Scotland, Wales, and Northern Ireland, which had populations of 5.5 million, 3.2 million, and 1.9 million respectively. English counties and cities The United Kingdom is a patchwork of various regional units, within England the largest of these are the regions shown here, which show how London, along with the rest of South East England had around 18 million people living there in this year. The next significant regional units in England are the 47 metropolitan and ceremonial counties. After London, the metropolitan counties of the West Midlands, Greater Manchester, and West Yorkshire were the biggest of these counties, due to covering the large urban areas of Birmingham, Manchester, and Leeds respectively. Regional divisions in Scotland, Wales and Northern Ireland The smaller countries that comprise the United Kingdom each have different local subdivisions. Within Scotland these are called council areas, whereas in Wales the main regional units are called unitary authorities. Scotland's largest Council Area by population is that of Glasgow City at over 650,000, while in Wales, it was the Cardiff Unitary Authority at around 384,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of approxiamtely 352,000.

London was by far the largest urban agglomeration in the United Kingdom in 2025, with an estimated population of *** million people, more than three times as large as Manchester, the UK’s second-biggest urban agglomeration. The agglomerations of Birmingham and Leeds / Bradford had the third and fourth-largest populations, respectively, while the biggest city in Scotland, Glasgow, was the fifth largest. Largest cities in Europe Two cities in Europe had larger urban areas than London, with Istanbul having a population of around **** million and the Russian capital Moscow having a population of over **** million. The city of Paris, located just over 200 miles away from London, was the second-largest city in Europe, with a population of more than **** million people. Paris was followed by London in terms of population size, and then by the Spanish cities of Madrid and Barcelona, at *** million and *** million people, respectively. The Italian capital, Rome, was the next largest city at *** million, followed by Berlin at *** million. London’s population growth Throughout the 1980s, the population of London fluctuated from a high of **** million people in 1981 to a low of **** million inhabitants in 1988. During the 1990s, the population of London increased once again, growing from ****million at the start of the decade to **** million by 1999. London's population has continued to grow since the turn of the century, and despite declining between 2019 and 2021, it reached *** million people in 2023 and is forecast to reach almost *** million by 2047.

In 2024, the population of the United Kingdom reached 69.3 million, compared with 68.5 million in 2023. The UK population has more than doubled since 1871 when just under 31.5 million lived in the UK and has grown by around 10.4 million since the start of the twenty-first century. For most of the twentieth century, the UK population steadily increased, with two noticeable drops in population occurring during World War One (1914-1918) and in World War Two (1939-1945). Demographic trends in postwar Britain After World War Two, Britain and many other countries in the Western world experienced a 'baby boom,' with a postwar peak of 1.02 million live births in 1947. Although the number of births fell between 1948 and 1955, they increased again between the mid-1950s and mid-1960s, with more than one million people born in 1964. Since 1964, however, the UK birth rate has fallen from 18.8 births per 1,000 people to a low of just 10.2 in 2020. As a result, the UK population has gotten significantly older, with the country's median age increasing from 37.9 years in 2001 to 40.7 years in 2022. What are the most populated areas of the UK? The vast majority of people in the UK live in England, which had a population of 58.6 million people in 2024. By comparison, Scotland, Wales, and Northern Ireland had populations of 5.5 million, 3.2 million, and 1.9 million, respectively. Within England, South East England had the largest population, at over 9.6 million, followed by the UK's vast capital city of London, at almost 9.1 million. London is far larger than any other UK city in terms of urban agglomeration, with just four other cities; Manchester, Birmingham, Leeds, and Glasgow, boasting populations that exceed one million people.

Leeds West, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

Leeds 100, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

This graph presents the population density of the ten leading business cities in the United Kingdom (UK) in 2014. London has a significant lead in the ranking as there are 1078 more people per km² than in Bristol. Leeds, at *** people per km², is the least densely populated city on the list.

Directly Age Standardised Mortality Rates (DASR) per 100,000. Age standardised rates compensate for differing age structures by weighting them to meet the European Standard Population (2013). Rates can then be compared for different areas, or even across area types. Attention should be given to upper and lower 95% confidence intervals as a quick method of determining whether rates could overlap or are significantly different. Wide confidence intervals are indicative of small numbers in the numerator or of very skewed age structures. Rates of course cannot be summed, and because they are age standardised cannot be reverse engineered back to counts without knowing the age of every patient in the data. Source is ONS deaths extract, GP registered populations.

By 2047 the population of London is expected to reach 9.97 million people, an increase of almost 699,500 when compared with 2025. While there has been quite a steep rise in its population in recent years, London’s population growth was relatively stagnant throughout the 1980s and even decreased slightly towards the end of that decade. After peaking at 8.89 million in 2019, the population of London has fallen slightly, to 8.8 million by 2021. UK population forecast Like London, the population of the United Kingdom is forecast to continue to grow well into the middle of the century. By 2046, the population of the UK is estimated to be over 76.3 million people, an increase of over 20 million people when compared with the population figures for 1976. Additionally, the average age of the population is predicted to increase from 39.5 years in 2020 to 44.5 years by the mid-2040s, and continue to increase towards the end of the century. London looms large In the UK, London is by far the largest urban agglomeration in the country, dwarfing the UK's next largest cities of Birmingham, Manchester, and Leeds. London also has a dominant economic position in the UK, with the city accounting for around a quarter of the total GDP in the country. The UK capital also has a far higher GDP per head than the rest of the county, at over ****** pounds in 2023, compared with the UK average of ****** pounds.

Leeds 105, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

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%).

This graph presents the graduate population of the ten leading business cities in the United Kingdom (UK) in 2016. London and Leeds had a significant lead in the ranking, as **% of both populations are graduates, compared to ****% in Edinburgh, Oxford and York.

The aims of this project were to:

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

To achieve the project aims, the objectives were to:

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

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

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

The 2001 Area Classification of output areas is used to group together geographic areas according to key characteristics common to the population in that grouping. These groupings are called clusters, and are derived using 2001 population census data. This is a new classification produced using the same principles but a different statistical methodology from that used to produce the other area classifications.

This data package presents the data for the 24,140 Census Output Areas in Greater London but data for the UK is also available (see Download URL below).

For further guidance, advice and to see case studies using the 2001 OAC data, visit the OAC User Groups website: http://areaclassification.org.uk/

If you have any queries about or problems accessing any of the data please let Leeds University know: E-mail comments or queries to d.vickers@sheffield.ac.uk or visit their website.

*Please note that the Output Area cluster names (e.g. 'City Living') are not a national statistic and endorsed by ONS, these have been created and added by the University of Leeds to add further meaning to the classification.

Leeds 018, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

IMPORTANT: This deposit contains a range of supplementary material related to the deposit of the SIPHER Synthetic Population for Individuals, 2019-2021 (https://doi.org/10.5255/UKDA-SN-9277-1). See the shared readme file for a detailed description describing this deposit. Please note that this deposit does not contain the SIPHER Synthetic Population dataset, or any other Understanding Society survey datasets.

The lack of a centralised and comprehensive register-based system in Great Britain limits opportunities for studying the interaction of aspects such as health, employment, benefit payments, or housing quality at the level of individuals and households. At the same time, the data that exist, is typically strictly controlled and only available in safe haven environments under a “create-and-destroy” model. In particular when testing policy options via simulation models where results are required swiftly, these limitations can present major hurdles to coproduction and collaborative work connecting researchers, policymakers, and key stakeholders. In some cases, survey data can provide a suitable alternative to the lack of readily available administrative data. However, survey data does typically not allow for a small-area perspective. Although special license area-level linkages of survey data can offer more detailed spatial information, the data’s coverage and statistical power might be too low for meaningful analysis.

Through a linkage with the UK Household Longitudinal Study (Understanding Society, SN 6614, wave k), the SIPHER Synthetic Population allows for the creation of a survey-based full-scale synthetic population for all of Great Britain. By drawing on data reflecting “real” survey respondents, the dataset represents over 50 million synthetic (i.e. “not real”) individuals. As a digital twin of the adult population in Great Britain, the SIPHER Synthetic population provides a novel source of microdata for understanding “status quo” and modelling “what if” scenarios (e.g., via static/dynamic microsimulation model), as well as other exploratory analyses where a granular geographical resolution is required

As the SIPHER Synthetic Population is the outcome of a statistical creation process, all results obtained from this dataset should always be treated as “model output” - including basic descriptive statistics. Here, the SIPHER Synthetic Population should not replace the underlying Understanding Society survey data for standard statistical analyses (e.g., standard regression analysis, longitudinal multi-wave analysis). Please see the respective User Guide provided for this dataset for further information on creation and validation.

This research was conducted as part of the Systems Science in Public Health and Health Economics Research - SIPHER Consortium and we thank the whole team for valuable input and discussions that have informed this work.

THE PROBLEM: There is strong evidence that the social and economic conditions in which we grow, live, work and age determine our health to a much larger degree than lifestyle choices. These social determinants of health, such as income, good quality homes, education, or work, are not distributed equally in society, which leads to health inequalities. However, we know very little about how specific policies influence the social conditions to prevent ill health and reduce health inequalities. Also, most social determinants of health are the responsibility of policy sectors other than health, which means policymakers need to promote health in ALL their policies if they are to have a big impact on health. SIPHER will provide new scientific evidence and methods to support such a shift from health policy to healthy public policy.

OUR POLICY FOCUS: We are working with four policy partner organisations at local, regional, and national level to tackle their above-average chronic disease burden and persistent health inequalities: Sheffield City Council, Greater Manchester Combined Authority, the Scottish Government and Public Health Scotland. We will focus on three jointly agreed policy priorities for good health: - Inclusive Economies - Public Mental Health - Providing affordable, good quality housing

OUR COMPLEX SYSTEMS SCIENCE APPROACH: Each of the above policy areas is a complex political system with many competing priorities, where policy choices in one sector (e.g., housing) can have large unintended effects in others (e.g., poverty). There is often no correct solution because compromises between different outcomes require value judgements. This means that to assess the true benefits and costs of a policy in relation to health, policy effects and their interdependencies need to be assessed across a wide range of possible outcomes. However, no policymaker has knowledge of the whole system and future economic and political developments are uncertain. Ongoing monitoring of expected and unexpected effects of policies and other system changes is crucial so failing policies can be revised or dropped. We are using systems modelling, which has been developed to understand and make projections of what might happen in complex systems given different plausible assumptions about future developments. Our models are underpinned by the best available data and prior research in each policy area. Our new evidence about likely policy effects across a wide range of outcomes will help policy partners decide between alternative policies, depending on how important different outcomes are to them (e.g., improving health or economic growth). We are developing a decision support tool that can visualise the forecasts, identify policies that achieve the desired balance between competing outcomes and update recommendations when new information emerges. Whilst new to public health policy, these methods are well-established in engineering and climate science.

We are: 1. Developing an in-depth understanding of policy processes and evidence needs using a novel combination of qualitative methods including interviews, system mapping, ethnographic research, and documentary analysis. 2. Developing and applying iterative literature search and review strategies suitable for supporting complex systems research. 3. Building a secure data infrastructure, creating synthetic populations with relevant attributes for policy experiments, and developing a system monitoring function to inform adaptive policymaking. 4. Modelling the dynamics and feedback effects of higher-order causal processes, e.g., the relationships between unemployment, poverty, and mortality. 5. Modelling the impacts of events and policy change on the characteristics of individuals and households, showing how policy impacts differ across geographic areas and societal groups. 6. Providing insight into how people value different policy outcomes, and translate the multiplicity of outcomes that arise from a whole-systems perspective into two common well-being measures needed for economic evaluation. 7. Using distributed, robust multi-objective optimization to develop a cross-sector decision support tool that identifies strategies that perform well across key policy outcomes and for different assumptions about future developments. 8. Assessing SIPHER’s scientific contribution through monitoring of real-world impact and seeking regular multi-perspective feedback from scientists, topic experts and community representatives.

SIPHER's MAIN OUTCOME: We will provide policymakers with a new methodology that allows them to estimate the health-related costs and benefits of policies that are implemented outside the health sector. This will be useful to our partners, and others, who want to assess how scarce public sector resources can be spent to maximise the health and wellbeing benefits from all their activities.

Leeds 067, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

For odds ratio comparisons, the baseline level is indicated.

The Adult Psychiatric Morbidity Survey (APMS) series provides data on the prevalence of both treated and untreated psychiatric disorder in the English adult population (aged 16 and over). This survey is the fourth in a series and was conducted by NatCen Social Research, in collaboration with the University of Leicester, for NHS Digital. The previous surveys were conducted in 1993 (16-64 year olds) and 2000 (16-74 year olds) by the Office for National Statistics, which covered England, Scotland and Wales. The 2007 Survey included people aged over 16 and covered England only. The survey used a robust stratified, multi-stage probability sample of households and assesses psychiatric disorder to actual diagnostic criteria for several disorders. The report features chapters on: common mental disorders, mental health treatment and service use, post-traumatic stress disorder, psychotic disorder, autism, personality disorder, attention-deficit/hyperactivity disorder, bipolar disorder, alcohol, drugs, suicidal thoughts, suicide attempts and self-harm, and comorbidity. All the APMS surveys have used largely consistent methods. They have been designed so that the survey samples can be combined. This is particularly useful for examination of low prevalence population groups and disorders. For example, in the APMS 2014 survey report, analyses of psychotic disorder (Chapter 5) and autism (Chapter 6) have been run using the 2007 and 2014 samples combined. Due to the larger sample size, we consider estimates based on the combined sample to be the more robust. Further notes on the Autism chapter can be found with that chapter and in the 'Additional notes on autism' document below. NHS Digital carried out a consultation exercise to obtain feedback from users on the APMS publication and statistics. The consultation will inform the design, content and reporting of any future survey. The consultation closed 30 December 2016, findings will be made available by April 2017. You can access the results of consultation when available in the Related Links below. A correction has been made to this publication in September 2017. This correction applies to all statistics relating to people receiving medication for a mental health condition and more widely to people accessing mental health treatment. This correction increases the proportion of adults (aged 16-74) with a common mental disorder accessing mental health treatment in 2014 from 37 per cent to 39 per cent. Overall the proportion of all people receiving mental health treatment in 2014 increases from 12 per cent to 13 per cent. Logistic regression models used in chapter 3 have not been corrected due to the change not being large enough to change the findings of this analysis. A further correction has been made to this publication in February 2018. This correction applies to statistics for Asian/Asian British men and all adults in Table 10.5 - Harmful and dependent drinking in the past year (observed and age-standardised), by ethnic group and sex. Statistics for the number of respondents with an AUDIT score of 16 or over previously incorrectly included only those with an AUDIT score between 16 and 19. This has now been corrected to include respondents with an AUDIT score of 20 or more. NHS Digital apologies for any inconvenience caused.

Leeds 057, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.

Leeds 068, Leeds demographics statistics broken down by ethnicity, religion, age, birthplace and much more. View full insights for the local and surrounding households.