In 2023, the population of the United Kingdom reached 68.3 million, compared with 67.6 million in 2022. The UK population has more than doubled since 1871 when just under 31.5 million lived in the UK and has grown by around 8.2 million since the start of the twenty-first century. For most of the twentieth century, the UK population steadily increased, with two noticeable drops in population occurring during World War One (1914-1918) and in World War Two (1939-1945). Demographic trends in postwar Britain After World War Two, Britain and many other countries in the Western world experienced a 'baby boom,' with a postwar peak of 1.02 million live births in 1947. Although the number of births fell between 1948 and 1955, they increased again between the mid-1950s and mid-1960s, with more than one million people born in 1964. Since 1964, however, the UK birth rate has fallen from 18.8 births per 1,000 people to a low of just 10.2 in 2020. As a result, the UK population has gotten significantly older, with the country's median age increasing from 37.9 years in 2001 to 40.7 years in 2022. What are the most populated areas of the UK? The vast majority of people in the UK live in England, which had a population of 57.7 million people in 2023. By comparison, Scotland, Wales, and Northern Ireland had populations of 5.44 million, 3.13 million, and 1.9 million, respectively. Within England, South East England had the largest population, at over 9.38 million, followed by the UK's vast capital city of London, at 8.8 million. London is far larger than any other UK city in terms of urban agglomeration, with just four other cities; Manchester, Birmingham, Leeds, and Glasgow, boasting populations that exceed one million people.

The total population in the United Kingdom was estimated at 69.2 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides the latest reported value for - United Kingdom Population - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The population of England was estimated to have reached almost 57.7 million in 2023, compared with 53.9 million ten years earlier in 2013. Compared with 1971, the population of England has grown by over ten million.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

In 1938, the year before the outbreak of the Second world War, the countries with the largest populations were China, the Soviet Union, and the United States, although the United Kingdom had the largest overall population when it's colonies, dominions, and metropole are combined. Alongside France, these were the five Allied "Great Powers" that emerged victorious from the Second World War. The Axis Powers in the war were led by Germany and Japan in their respective theaters, and their smaller populations were decisive factors in their defeat. Manpower as a resource In the context of the Second World War, a country or territory's population played a vital role in its ability to wage war on such a large scale. Not only were armies able to call upon their people to fight in the war and replenish their forces, but war economies were also dependent on their workforce being able to meet the agricultural, manufacturing, and logistical demands of the war. For the Axis powers, invasions and the annexation of territories were often motivated by the fact that it granted access to valuable resources that would further their own war effort - millions of people living in occupied territories were then forced to gather these resources, or forcibly transported to work in manufacturing in other Axis territories. Similarly, colonial powers were able to use resources taken from their territories to supply their armies, however this often had devastating consequences for the regions from which food was redirected, contributing to numerous food shortages and famines across Africa, Asia, and Europe. Men from annexed or colonized territories were also used in the armies of the war's Great Powers, and in the Axis armies especially. This meant that soldiers often fought alongside their former-enemies. Aftermath The Second World War was the costliest in human history, resulting in the deaths of between 70 and 85 million people. Due to the turmoil and destruction of the war, accurate records for death tolls generally do not exist, therefore pre-war populations (in combination with other statistics), are used to estimate death tolls. The Soviet Union is believed to have lost the largest amount of people during the war, suffering approximately 24 million fatalities by 1945, followed by China at around 20 million people. The Soviet death toll is equal to approximately 14 percent of its pre-war population - the countries with the highest relative death tolls in the war are found in Eastern Europe, due to the intensity of the conflict and the systematic genocide committed in the region during the war.

Reconstitutions of families from historical parish register baptism, marriage and burial entries of individuals in 26 English parishes (Alcester, Aldenham, Ash, Austrey, Banbury, Birstall, Bottesford, Bridford, Colyton, Dawlish, Earsdon, Gainsborough, Gedling, Great Oakley, Hartland, Ipplepen, Lowestoft, March, Methley, Morchard Bishop, Odiham, Reigate, Shepshed, Southill, Terling and Willingham). These data formed the empirical basis for the population history of England presented in: EA Wrigley, RS Davies, JE Oeppen and RS Schofield: 'English Population History from Family Reconstitution: 1580-1837' (Cambridge University Press, 1997).

Using families reconstructed from baptism, burial and marriage records from Anglican parish registers as a national population sample to explore the demographic history of England. This included detailed studies of fertility, mortality and nuptiality, and refinements to previous estimates of population size and structure.

Abstract copyright UK Data Service and data collection copyright owner.

This collection represents the data used to reconstruct the pre-Census population history of England by Wrigley and Schofield, in restructured form. It consists of counts of parish register events from 404 English sample parishes. These data were originally used to estimate national totals of births, deaths and marriages. From these population growth rates were derived and hence the overall English population in each year between 1539 and 1836, but these data are also relevant for local studies of particular parishes or regions, and for studies of mortality variations and crises, which was the purpose for which this restructuring was undertaken. This data collection contains tab-delimited text files of monthly and annual historical counts of baptisms, marriages and burials from parish registers in 404 English parishes, with missing data interpolated, for varying coverage periods in each parish, including a core period of 1662 to 1811.

Volunteer local historians counted events from accessible parish registers with apparently good coverage, from a list distributed by Tony Wrigley at CAMPOP. Counts were recorded on paper pro formas. These were digitised many years ago by CAMPOP into the Population History of England database. Quality checking of count accuracy per volunteer was performed by Roger Schofield and inaccurate contributions discarded. In their current restructured form these files were derived by Gill Newton at CAMPOP from the Population History of England database.

Main Topics:

Population, baptisms, marriages, burials, mortality, nuptiality, fertility, historical demography.

The Census@Leicester datasets include socio-demographic data from the 2001, 2011, and 2021 Leicester censuses to enable the exploration of recent historical trends. It also includes data from the 2021 census for both Nottingham and Coventry to enable comparisons with other cities.

This online resource that can be used for teaching and research purposes by staff and students and to create a legacy for the Census@Leicester Project.

Abstract copyright UK Data Service and data collection copyright owner.

These data formed the basis of a reconstruction of English population history from the sixteenth to the nineteenth century, published as The population history of England, 1541-1871: a reconstruction (1981) by E.A. Wrigley and R.S. Schofield.
Main Topics:

The data comprise aggregated monthly totals of baptisms, marriages and burials for 404 English parishes from the sixteenth to the nineteenth century. For each parish monthly and annual totals are provided, along with monthly and annual totals by decade. There are also monthly seasonality indexes by half-century. Where defective data have been replaced with corrected frequencies, the original data have also been reproduced.

Summary information has also been provided about periods of epidemic mortality crisis in each parish, and the severity of the epidemic.

There is also information about the characteristics of each of the parishes included in the study. These characteristics include: the parish's location, altitude, population in 1811, main farming and soil types, occupational structure, proximity to towns, representation in Parliament, and indicators of poverty, religious activity and the provision of education.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

1. Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct population assessments by filling in missing values from surrogate species or other populations of the same species. Using these independent surrogate values concurrently with observed data neglects the life‐history trade‐offs that connect the different aspects of a population's demography. Consequently, this approach introduces biases that could ultimately lead to erroneous management decisions. 2. We use a Bayesian hierarchical framework to combine fragmented multi‐population data with established life‐history theory and reconstruct population‐specific demographic data across a substantial part of a species breeding range. We apply our analysis to a long‐lived colonial species, the black‐legged kittiwake Rissa tridactyla, that is classified as globally Vulnerable and is highly threatened by increasing anthropogenic pressures, including offshore renewable energy development. We then use a projection analysis to examine how the reconstructed demographic parameters may improve population assessments, compared to models that combine observed data with independent surrogate values. 3. Demographic parameters reconstructed using a hierarchical framework can be utilised in a range of population modelling approaches. They can also be used as reference estimates to assess whether independent surrogate values are likely to over or underestimate missing demographic parameters. We show that surrogate values from independent sources are often used to fill in missing parameters that have large potential demographic impact, and that resulting biases are driven in unpredictable directions thus precluding assessments from being consistently precautionary. 4. Synthesis and applications. Our study dramatically increases the spatial coverage of population‐specific demographic data for black‐legged kittiwakes. The reconstructed demographic parameters presented can also be used immediately to reduce uncertainty in the consenting process for offshore wind development in the United Kingdom and Ireland. More broadly, we show that the reconstruction approach used here provides a new avenue for improving evidence‐based management and policy action for animal and plant populations with fragmented and error prone demographic data. 22-Mar-2021

Methods JAGS code and data for the correlated model. The script was written using JAGS (v. 4.3.0) via the “jagsUI” library (v 1.5.1) for program R (v. 4.0.2). It runs a Bayesian hierarchical model (“correlated model”) to reconstruct mean rates of adult survival and fecundity for 68 populations of black-legged kittiwake breeding in the UK and Ireland. Input data supplied. See Table S1 in the Supplementary Information for additional details on data sources.

In 2021 the live birth rate of the United Kingdom fell to 10.4 births per 1,000 population, the lowest it had been during this time period. The UK's birth rate has been declining steadily since 2010 when the birth rate was 12.9 births per 1,000 population. After 1938, the year with the highest birth rate in the UK was 1947, when the crude birth rate was 21.2 births per 1,000 population. Under two children per mother in 2021 The most recent crude live birth rate for this statistic is based on the 694,685 births, that occurred in 2021 as well as the mid-year population estimate of 67 million for the United Kingdom. It has a close relation to the fertility rate which estimates the average number of children women are expected to have in their lifetime, which was 1.53 in this reporting year. Among the constituent countries of the UK, Northern Ireland had the highest birth rate at 11.6, followed by England at 10.5, Wales at 9.3, and Scotland at 8.7. International comparisons The UK is not alone in seeing its birth and fertility rates decline dramatically in recent decades. Across the globe, fertility rates have fallen noticeably since the 1960s, with the fertility rate for Asia, Europe, and the Americas being below two in 2021. As of this year, the global fertility rate was 2.31, and was by far the highest in Africa, which had a fertility rate of 4.12, although this too has fallen from a high of 6.72 in the late 1960s. A reduction in infant mortality, as well as better access to contraception, are factors that have typically influenced declining fertility rates recently.

This dataset contains information on life history variation and population dynamics in response to coloured environmental variation in the laboratory model system comprised of the moth Plodia interpunctella (Pyralidae; Hübner) and the parasitoid wasp Venturia canescens (Ichneumonidae; Gravenhorst). Data were collected from two complementary experiments investigating the effects of daily coloured temperature fluctuations on individual life history variation (single-generation life history experiment) and population dynamics (multi-generation microcosm experiment) in both species. In both experiments, the effects of three types of coloured noise were investigated and compared to constant temperature conditions: blue noise (characterized by rapid (negatively autocorrelated) fluctuations), red noise (characterized by slow (positively autocorrelated) fluctuations) and white noise (characterized by random fluctuations). The life history experiment lasted 56 days and the microcosm experiment lasted 310 days. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/ef7e47ae-bd28-4449-8587-8e5dda4ccfee

[This dataset is embargoed until December 1, 2020]. Data comprise monitoring records of a population of Gryllus campestris, a flightless, univoltine field cricket that lives in and around burrows excavated among the grass in a meadow in Asturias (North Spain). The area has an altitude range from around 60 to 270 metres above sea level. Data include basic traits, behavioural data, genotypes and pheromones. Data were collected from 2006 to 2016. Full details about this dataset can be found at https://doi.org/10.5285/42d9fc5d-f30e-46a9-9d09-50272f4538cb

The HMAP database (http://www.hull.ac.uk/hmap) is an open access facility that currently comprises time series of commercial catches covering the period 1611-2000. It is a growing resource and extends more that 240,000 records and more than 100 species. Data are mostly recovered from archives, tax records, custom records or surveys. The facility includes a web guide to the database (the Data Directory) and a web library of dataset downloads (the Data Library), while users can create customized datasets through the HMAP Portal, which is an interactive facility for searching the database. A significant proportion of these holdings are currently available through OBIS. HMAP is a distributed data contributor and the constituent datasets have been mapped to the OBIS schema using DiGIR since 2004.

The HMAP program (http://www.hmapcoml.org) is the historical component of the Census of Marine Life (CoML). It is a multidisciplinary, collaborative project which aims to enhance knowledge and understanding of how and why the diversity, distribution and abundance of marine life in the world's oceans changes over the long term. The HMAP program is currently composed of 9 datasets, 3 of which focus on trawl records from Southeast Australia, one on world whaling, 2 on Northwest Atlantic, and 3 on catch data from Norwegian and North and Baltic seas.

We obtained newly-generated genome-wide DNA methylation profiles from whole blood in 240 individuals from the TwinsUK cohort. DNA methylation levels were profiled at 38-86 years of age using the Infinium MethylationEPIC BeadChip.

Epigenetic mechanisms such as DNA methylation are key regulators of gene function. Epigenetic signals are malleable and can change in response to internal and external stimuli. The epigenome thereby provides a mechanism of interaction between the genome with the environment, and we hypothesize that early life stimuli and exposures over the life course leave an epigenetic mark. The proposal will explore DNA methylation in 4,024 samples from four British cohort studies (the MRC National Survey for Health and Development (NSHD) or 1946 birth cohort, the National Child Development Study (NCDS) or 1958 birth cohort, the 1970 British Cohort Study (BCS70), and the TwinsUK cohort (TwinsUK)) in order to identify epigenetic signatures of early life experience and exposure to social, environmental, and biological stimuli over the life course, linking findings to changes in physical and cognitive function during ageing. Each study captures a range of early life experiences, longitudinal health measures and lifestyle questionnaire data from adult life, DNA samples collected at single or multiple time-points, and in a sample subset, multiple genomic data for follow-up analyses. The primary research design is a prospective analysis of longitudinal data across 2,336 blood and 1,688 buccal samples from the four cohorts. The first aim of the research will be to establish whether biological, environmental, and social stimuli in early life and over the life course result in detectable differences in DNA methylation profiles in adults. We will consider whether there are epigenetic associations with a number of factors including biological, environmental and social factors in utero and in early childhood (e.g. birthweight, childhood growth, maternal smoking during pregnancy, nutrition, parental socioeconomic position), and in later life: (e.g. smoking, alcohol consumption, physical activity, diet, stressful events, adult socioeconomic position). The second aim is to assess whether there are differences between cohorts in DNA methylation patterns, comparing samples containing individuals born in different years (1946, 1958 and 1970), accounting for age, since these may reflect differences between cohorts in environmental and social influences in early life. Our third aim is to explore the role of epigenetics in healthy functional ageing by applying a two-fold approach. First, we will compare epigenetic signatures to longitudinal functional health trajectories throughout life across cohorts, across cell types (blood and buccal), and across different age categories. We will explore whether DNA methylation signatures of early life experiences can mediate functional ageing trajectories (such as cardiovascular, lung and cognitive function), and whether they can be reversed in response to social and environmental exposures in later life. Our fourth aim is to apply a new approach to estimate biological age, the epigenetic clock, to assess the rate of epigenetic ageing and relate it to early life stimuli and longitudinal biomedical, social, and environmental trajectories. Additional analyses in subsamples will include DNA methylation profiling at multiple time-points to estimate reversibility of DNA methylation, cross-tissue comparison across blood, buccal, and additional tissues, and gene expression analysis for functional interpretation. Replication will be pursued in 3,970 samples from four independent UK-population-based cohorts.

BackgroundThe ageing population poses a tremendous challenge in understanding the sources of inequalities in health. Though they appear to be far removed, childhood conditions are known to be inextricably linked with adult health, and in turn on health in later life. The long arm of childhood conditions hypothesis is often tested using recollection of childhood circumstances, but such subjective recall can yield potentially inaccurate or possibly biased inferences. We tested the long arm hypothesis on three outcomes in later life, arrayed from objective to subjective health, namely: gait speed, episodic memory and mental health.Methods and FindingsWe used the English Longitudinal Study of Ageing 2006 enriched with retrospective life history (N = 5,913). To deal with recall problems two solutions, covariate measurement and endogenous treatment models, were applied. Retrospective childhood material lack includes growing up without running hot or cold water, fixed bath, indoor lavatory and central heating. Adjustment is made for an extensive set of confounders including sex, age, adult health, wealth, education, occupation, social support, social connections, chronic conditions, smoking, drinking, and physical exercise. It is found that material poverty when growing up shows no association with health when growing old, assuming accurate recall. Once recall problems are controlled, we found that childhood material poverty changes inversely with later life health.ConclusionA poorer childhood goes with slower gait, poorer memory and more depression in later life. This result provides a further impetus to eliminate child poverty.

This dataset provides Census 2021 estimates for Employment history in Northern Ireland. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

The quality assurance report can be found here

In the combined Pakistani and Bangladeshi ethnic group in 2021, 16.2% of workers were self-employed, which is the highest percentage out of all ethnic groups.

Dataset information available at www.hull.ac.uk/hmap/

Population characteristics of UK Biobank sample used as outcome data.