In 2024, Russia had the largest population among European countries at ***** million people. The next largest countries in terms of their population size were Turkey at **** million, Germany at **** million, the United Kingdom at **** million, and France at **** million. Europe is also home to some of the world’s smallest countries, such as the microstates of Liechtenstein and San Marino, with populations of ****** and ****** respectively. Europe’s largest economies Germany was Europe’s largest economy in 2023, with a Gross Domestic Product of around *** trillion Euros, while the UK and France are the second and third largest economies, at *** trillion and *** trillion euros respectively. Prior to the mid-2000s, Europe’s fourth-largest economy, Italy, had an economy that was of a similar sized to France and the UK, before diverging growth patterns saw the UK and France become far larger economies than Italy. Moscow and Istanbul the megacities of Europe Two cities on the eastern borders of Europe were Europe’s largest in 2023. The Turkish city of Istanbul, with a population of 15.8 million, and the Russian capital, Moscow, with a population of 12.7 million. Istanbul is arguably the world’s most famous transcontinental city with territory in both Europe and Asia and has been an important center for commerce and culture for over 2,000 years. Paris was the third largest European city with a population of ** million, with London being the fourth largest at *** million.

This dataset provides values for POPULATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

In 2020, Germany remained the largest population in the European Union with over 83 million inhabitants. Most European countries have a larger female than male population. Only in Ireland, Luxembourg, Malta, Serbia, and Sweden constitute men the majority of inhabitants. Germany had the largest population of both genders in Europe, with 42.1 million women and 41 million men.

In 2024, Germany was the leading EU country in terms of population, with around 85 million inhabitants. In 2050, approximately 89.2 million people will live in Germany, according to the forecast. See the total EU population figures for more information. The global population The global population is rapidly increasing. Between 1990 and 2015, it increased by around 2 billion people. Furthermore, it is estimated that the global population will have increased by another 1 billion by 2030. Asia is the continent with the largest population, followed by Africa and Europe. In Asia,the two most populous nations worldwide are located, China and India. In 2014, the combined population in China and India alone amounted to more than 2.6 billion people. for comparison, the total population in the whole continent of Europe is at around 741 million people. As of 2014, about 60 percent of the global population was living in Asia, with only approximately 10 percent in Europe and even less in the United States. Europe is the continent with the second-highest life expectancy at birth in the world, only barely surpassed by Northern America. In 2013, the life expectancy at birth in Europe was around 78 years. Stable economies and developing and emerging markets in European countries provide for good living conditions. Seven of the top twenty countries in the world with the largest gross domestic product in 2015 are located in Europe.

The European countries which saw the greatest population growth in 2025 were Gibraltar, Kosovo and Iceland. Overall, Europe's population declined by 3.3 percent in 2025, with this varying by region from a 0.19 percent decline in northern Europe to 4.6 percent in southern Europe. All the countries which saw the largest declines in their population in 2025 were central and eastern European countries.

The average for 2024 based on 47 countries was 51.06 percent. The highest value was in Moldova: 53.99 percent and the lowest value was in Malta: 48.1 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

The population of Europe was estimated to be 745 million in 2024, an increase of around 4 million when compared with 2012. Over 35 years between 1950 and 1985, the population of Europe grew by approximately 157.8 million. But 35 years after 1985 it was estimated to have only increased by around 38.7 million. Since the 1960s, population growth in Europe has fallen quite significantly and was even negative during the mid-1990s. While population growth has increased slightly since the low of -0.07 percent in 1998, the growth rate for 2020 was just 0.04 percent. Which European country has the biggest population? As of 2024, the population of Russia was estimated to be approximately 144.8 million and was by far Europe's largest country in terms of population, with Turkey being the second-largest at over 87 million. While these two countries both have territory in Europe, however, they are both only partially in Europe, with the majority of their landmasses being in Asia. In terms of countries wholly located on the European continent, Germany had the highest population at 84.5 million, and was followed by the United Kingdom and France at 69.1 million and 66.5 million respectively. Characteristics of Europe's population There are approximately 384.6 million females in Europe, compared with 359.5 million males, a difference of around 25 million. In 1950, however, the male population has grown faster than the female one, with the male population growing by 104.7 million, and the female one by 93.6 million. As of 2024, the single year of age with the highest population was 37, at 10.6 million, while in the same year there were estimated to be around 136 thousand people aged 100 or over.

The average for 2024 based on 27 countries was 74.63 percent. The highest value was in Belgium: 98.22 percent and the lowest value was in Slovakia: 54.17 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

The average for 2024 based on 47 countries was 26.66 percent. The highest value was in Liechtenstein: 85.29 percent and the lowest value was in Gibraltar: 0 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

This statistic shows the total population of the European Union from 2010 to 2025. The population is based on data from the most recent census adjusted by the components of population change produced since the last census, or based on population registers. At the beginning of 2025, the total population of the European Union amounted to approximately 450.38 million inhabitants. See figures for the total population by continent here. The global population The global population is rapidly increasing. Between 1990 and 2015, the global population has increased by around 2 billion people, and it is estimated to have increased by another 1 billion people by 2030. Asia is the continent in the world with the largest population, followed by Africa and Europe. Asia has the two most populous nations in the world: China and India. In 2014, the combined population in China and India amounted to more than 2.6 billion people. The total population in Europe is around 741 million people. As of 2014, about 10.2 percent of the global population lived in Europe. Europe is the continent with the second highest life expectancy at birth in the world. Born in 2013, the average European was estimated to live for around 78 years. Stable economies as well as developing and emerging markets in Europe provide for good living conditions for foreign nationals; seven of the top twenty countries in the world with the largest gross domestic product in 2024 are located in Europe.

The average for 2023 based on 27 countries was 272670 refugees. The highest value was in Germany: 2593007 refugees and the lowest value was in Slovenia: 10525 refugees. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Have you ever wondered how the population landscape of our planet looks in 2025? This dataset brings together the latest population statistics for 233 countries and territories, carefully collected from Worldometers.info — one of the most trusted global data sources.

📊 It reveals how countries are growing, shrinking, and evolving demographically. From population density to fertility rate, from migration trends to urbanization, every number tells a story about humanity’s future.

🌆 You can explore which nations are rapidly expanding, which are aging, and how urban populations are transforming global living patterns. This dataset includes key metrics like yearly population change, net migration, land area, fertility rate, and each country’s share of the world population.

🧠 Ideal for data analysis, visualization, and machine learning, it can be used to study global trends, forecast population growth, or build engaging dashboards in Python, R, or Tableau. It’s also perfect for students and researchers exploring geography, demographics, or development studies.

📈 Whether you’re analyzing Asia’s population boom, Europe’s aging curve, or Africa’s youthful surge — this dataset gives you a complete view of the world’s demographic balance in 2025. 🌎 With 233 rows and 12 insightful columns, it’s ready for your next EDA, visualization, or predictive modeling project.

🚀 Dive in, explore the data, and uncover what the world looks like — one country at a time.

This graph displays the total population size of citizens aged from between 30 and 34 years old in Europe in 2018, by country. That year there were roughly **** million inhabitants of this age group in Germany, which was followed by the United Kingdom and France with approximately **** million and **** million inhabitants respectively.

It is estimated that Russia had the largest population among Central and Eastern European countries, with ***** million people in 2024. The following largest countries in terms of population size were Poland, with **** million, and Ukraine, with **** million.

In 2024, Italy was the European country with the oldest population, recording a median age of 48.7 years, closely ahead of Bulgaria and Portugal, with 47 years. In general, almost all European countries have a median age above 40 years old. Only Azerbaijan, Turkey, Armenia, and Kosovo had a median age below 35 years old. Kosovo was the youngest territory of the continent in terms of median age.

Each year Eurostat collects demographic data at regional level from EU, EFTA and Candidate countries as part of the Population Statistics data collection. POPSTAT is Eurostat’s main annual demographic data collection and aims to gather information on demography and migration at national and regional levels by various breakdowns (for the full overview see the Eurostat dedicated section). More specifically, POPSTAT collects data at regional levels on:

• population stocks;
• vital events (live births and deaths).

Each country must send the statistics for the reference year (T) to Eurostat by 31 December of the following calendar year (T+1). Eurostat then publishes the data in March of the calendar year after that (T+2).

Demographic data at regional level include statistics on the population at the end of the calendar year and on live births and deaths during that year, according to the official classification for statistics at regional level (NUTS - nomenclature of territorial units for statistics) in force in the year. These data are broken down by NUTS 2 and 3 levels for EU countries. For more information on the NUTS classification and its versions please refer to the Eurostat dedicated pages. For EFTA and Candidate countries the data are collected according to the agreed statistical regions that have been coded in a way that resembles NUTS.

The breakdown of demographic data collected at regional level varies depending on the NUTS/statistical region level. These breakdowns are summarised below, along with the link to the corresponding online table:

NUTS 2 level

• Population by sex, age and region of residence — demo_r_d2jan
• Population on 1 January by age group, sex and region of residence — demo_r_pjangroup
• Live births by mother's age, mother's year of birth and mother's region of residence — demo_r_fagec
• Deaths by sex, age, and region of residence — demo_r_magec

NUTS 3 level

• Population on 1 January by sex, age group and region of residence — demo_r_pjangrp3
• Population on 1 January by broad age group, sex and region of residence — demo_r_pjanaggr3
• Live births (total) by region of residence — demo_r_births
• Live births by five-year age group of the mothers and region of residence — demo_r_fagec3
• Deaths (total) by region of residence — demo_r_deaths
• Deaths by five-year age group, sex and region of residence — demo_r_magec3

This more detailed breakdown (by five-year age group) of the data collected at NUTS 3 level started with the reference year 2013 and is in accordance with the European laws on demographic statistics. In addition to the regional codes set out in the NUTS classification in force, these online tables include few additional codes that are meant to cover data on persons and events that cannot be allocated to any official NUTS region. These codes are denoted as CCX/CCXX/CCXXX (Not regionalised/Unknown level 1/2/3; CC stands for country code) and are available only for France, Hungary, North Macedonia and Albania, reflecting the raw data as transmitted to Eurostat.

For the reference years from 1990 to 2012 all countries sent to Eurostat all the data on a voluntary basis, therefore the completeness of the tables and the length of time series reflect the level of data received from the responsible National Statistical Institutes’ (NSIs) data provider. As a general remark, a lower data breakdown is available at NUTS 3 level as detailed:

• population data are broken down by sex and broad age groups (0-14, 15-64 and 65 or more). The data have this disaggregation since the reference year 2007 for all countries, and even longer for some — demo_r_pjanaggr3
• vital events (live births and deaths) data are available only as totals, without any further breakdown — demo_r_births and demo_r_deaths

Demographic indicators are calculated by Eurostat based on the above raw data using a common methodology for all countries and regions. The regional demographic indicators computed by NUTS level and the corresponding online tables are summarised below:

NUTS 2 level

• Population structure indicators by region of residence (shares of various population age groups, dependency ratios and median age) — demo_r_pjanind2
• Fertility indicators by region of residence — demo_r_find2
• Fertility rates by age and region of residence — demo_r_frate2
• Life table by age, sex and region of residence — demo_r_mlife
• Life expectancy by age, sex and region of residence — demo_r_mlifexp
• Infant mortality rates by region of residence — demo_r_minfind

NUTS 3 level

• Population change - Demographic balance and crude rates at regional level — demo_r_gind3
• Population density by region — demo_r_d3dens
• Population structure indicators by region of residence (shares of various population age groups, dependency ratios and median age) — demo_r_pjanind3
• Fertility indicators by region of residence (total fertility rate, mean age of woman at childbirth and median age of woman at childbirth) — demo_r_find3

Notes:

1) All the indicators are computed for all lower NUTS regions included in the tables (e.g. data included in a table at NUTS 3 level will include also the data for NUTS 2, 1 and country levels).

2) Demographic indicators computed by NUTS 2 and 3 levels are calculated using input data that have different age breakdown. Therefore, minor differences can be noted between the values corresponding to the same indicator of the same region classified as NUTS 2, 1 or country level.

3) Since the reference year 2015, Eurostat has stopped collecting data on area; therefore, the table 'Area by NUTS 3 region (demo_r_d3area)' includes data up to the year 2015 included.

4) Starting with the reference year 2016, the population density indicator is computed using the new data on area 'Area by NUTS 3 region (reg_area3).

In 2025, the population of Europe was estimated to be approximately 7.4 million, with the most common single year of age being 38, at over 10.6 million. By contrast, there were just 126,350 people aged 99 this year.

European countries are experiencing population decline and the tacit assumption in most analyses is that the decline may have detrimental welfare effects. In this paper we use a survey among the population in the Netherlands to discover whether population decline is always met with fear. A number of results stand out: population size preferences differ by geographic proximity: at a global level the majority of respondents favors a (global) population decline, but closer to home one supports a stationary population. Population decline is clearly not always met with fear: 31 percent would like the population to decline at the national level and they generally perceive decline to be accompanied by immaterial welfare gains (improvement environment) as well as material welfare losses (tax increases, economic stagnation). In addition to these driving forces it appears that the attitude towards immigrants is a very strong determinant at all geographical levels: immigrants seem to be a stronger fear factor than population decline.

Notes: na: data not available.Median value of all populations included in the analysis.*Economically inactive include unemployed (England/Wales and Finland is reference country for men and women respectively). Sweden is reference of countries with unemployed included in the active, both among men and women.M = men, W = women.Normal font style: reduction of mortality rate difference between low and high educated by 0–19 deaths per 100,000.Bold font style: reduction of mortality rate difference between low and high educated by 20–79 deaths per 100,000.Bold italic font style: reduction of mortality rate difference between low and high educated by at least 80 deaths per 100,000.Potential reduction of absolute educational inequalities in all-cause mortality between low and high educated (in deaths per 100,000 person-years), best practice scenario, by risk factor, country and sex.

Résumé

Le projet de recherche MAFE est une initiative de grande ampleur dont l'objectif est d'étudier les migrations entre l'Afrique subsaharienne et l'Europe. - Attention, la documentation des enquêtes MAFE est en langue anglaise. -

The MAFE project is a major research initiative focused on migration between Sub-Saharan Africa and Europe. It brings together ten European and African research centres working on international migration.

In the early XXIth Century, international migration from Sub-Saharan Africa to Europe has generated increasing public and policy attention. The flotilla of boats bringing would-be migrants to the Canary Islands, and attempts to reach Spanish territory in Ceuta and Mellila have drawn a rapid response from Europe in the form of new policy measures. Yet the scope, nature and likely development of Sub-Saharan African migration to Europe remained poorly understood, and, as a result, European polices may be ineffective. A major cause of this lack of understanding was the absence of comprehensive data on the causes of migration and circulation between Africa and Europe.

The MAFE project aimed at overcoming this lack of understanding by collecting unique data on the characteristics and behavior of migrants from Sub-Saharan countries to Europe. The key notion underpinning the project was that migration must not only be seen as a one-way flow from Africa to Europe. The argument was that return migration, circulation and transnational practices are significant and must be understood in order to design better migration policy.

The MAFE project focused on migration flows between Europe (Belgium, France, Italy, the Netherlands, Spain and the UK) and Senegal, the Democratic Republic of Congo and Ghana, which together accounted for over a quarter of all African migration to the EU at the time of the survey. In each of these "migration systems", the survey was designed to document four key areas: - Patterns of migration : *the socio-demographic characteristics of migrants, *the routes of migration from Africa to Europe, and *the patterns of return migration and circulation. - Determinants of migration: looking at departure, but also return and circulation and taking into account the whole set of possible destinations. - Migration and Development: MAFE documents some of the socio-economic changes driven by international migration, looking as often as possible at both ends of the Afro-European migration system, at the individual level. - Migrations and Families: the data collected by the MAFE project can be used to study all sorts of interactions between family formation and international migration. Although the survey was primarily designed to study international migration, it can also be used to study other phenomena, especially in Africa: domestic mobility, labor market participation, family formation, etc. Comparable data was collected in both 3 sending and 6 destination countries, i.e. in sub-Saharan Africa and in Europe. The data are longitudinal - including retrospective migration, education, work and family histories for individuals - and multi-level - (with data collected at the individual and household levels, in addition of macro-contextual data).

Please consult the official MAFE website for further details : https://mafeproject.site.ined.fr/en/

Geographic coverage

Six European countries and three African countries participated in the MAFE surveys. Data collection was carried out in both sending countries in Africa and destination countries in Europe, in order to constitute transnational samples. For MAFE DR Congo, data was collected in the Demogratic Republic of Congo (African part), and Belgium and United Kingdom (European part).

Analysis unit

Individual Household

Univers

DR CONGO Household: Households selected randomly from the updated list of households in the selected primary sampling units. Three strata were distinguished: households with return migrants, with migrants abroad, and without migrants. Individual: People aged 25-75, born in DR Congo. This lower age limit was set in order to obtain informative life histories. By not including respondents younger than 25, the resources were used more effectively. The place of birth criterion was used to exclude people who were born out of their country of origin in order to exclude second generation migrants in Europe and to increase the homogeneity of sample. All the return migrants and partners of migrants, and one randomly selected other eligible person. Return migrants were eligible if their first departure was above at 18 or over.

EUROPE In all the European countries, the surveys were conducted among males and females who were aged 25 and over at the time of the surveys, and who were 18 or over when they had left Africa for the first time for at least one year. Migrants from only DR Congo were interviewed.

Kind of data

survey data

Frequency of data collection

DR CONGO In DR Congo, the survey preparation started in March 2009. A pilot survey was organized in May-June 2009. The selection of the survey sites was done in June 2009, and the listing of the households in the selected sites started in June and ended in July 2009. Data collection started in early August, soon after the training of interviewers and the sampling of households. It lasted for about 4 months, until mid November. Like in Ghana, both the household and biographic surveys were conducted at the same time. Editing and coding was also done during the fieldwork and ended a few weeks after the fieldwork. Because of administrative problems with money transfer, data entry started a little bit later.

EUROPE In Belgium and United Kingdom, data collection was conducted in 2009-2010. Data collection lasted about five months in the UK and seven months in Belgium. Editing was done along data collection. Data entry was done between October and December 2009 in the UK, and between December 2009 and March 2010 in Belgium.

Sampling procedure

Probability: Stratified

  DR CONGO

A three-stage stratified random sample was used. At the first stage, primary sampling units (census district) were selected randomly with varying probabilities. At the second stage, households were selected randomly in each of the selected primary sampling units (PSUs). At the third stage, individuals were selected within the households. a) Selection of primary sampling units (first stage) For DR Congo, the target area was the city of Kinshasa. In this city, a sampling frame of primary sampling units was prepared. No recent census was available, so the sampling frame of the 2007 DHS was used to select neighbourhoods, and in each selected neighbourhoods, a sampling frame of streets was prepared. In DR Congo, a sample of 29 neighbourhoods (out of 324) was selected randomly with a probability proportional to size, and 3 streets were selected randomly with a probability proportional to size in each neighbourhood (87 sampling units). The sample was stratified at the first stage in DR Congo (3 strata). b) Selection of households (second stage) A listing operation was carried out in each of the selected survey sites to prepare the sampling frame of households. The listing consisted in enumerating all the households in the selected sites, and in identifying whether these households included migrants of not. In DR Congo and Ghana, three categories of households were distinguished (households with return migrants, with migrants abroad, and without migrants). 7 households were selected in each of the 3 strata (if less than 7 households were available in one or several strata, the remaining households were selected in the other stratum). The sampling rate was higher in strata of households with migrants, in order to get a sufficient sample of such households. c) Selection of individuals (third stage) In each of the selected households, one or several respondents were selected among the eligible people (people aged between 25 and 75, and born in the origin country). In DR Congo and Ghana, all the return migrants and partners of migrants currently abroad were selected. In addition, one other eligible member was randomly selected. A special tool had been designed so that the interviewers could randomly select the people during the fieldwork. Two types of questionnaires were used in the departure countries: the household questionnaire and the individual life history questionnaire. - The first questionnaire was used among a representative sample of households in the target region. - The second questionnaire was used among a sample of individuals in the selected households, targeting both return migrants and non-migrants. The household questionnaire was thus used as the sampling frame for the selection of individual respondents.

EUROPE The objective of the survey was to obtain a sample 'as representative as possible' of the African populations (Congolese, Ghanaian, Senegalese) in the destination countries (150 individuals per origin and destination country). The way the sample was constituted may vary across countries, but some common principles were respected: - The composition of the sample should be as close as possible to the population of (Congolese, Ghanaian, Senegalese) migrants in the country in terms of gender, geographic distribution, age, socio-economic category or occupation. - One exception: the sample should be gender balanced. Males and females should be equally represented in order to allow gender analyses. - Samples in origin and destination may be linked, but migrants with weak or no relationships at origin should not be excluded from the sample. - Both documented and