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.

Russia is the largest country in Europe, and also the largest in the world, its total size amounting to 17 million square kilometers (km2). It should be noted, however, that over three quarters of Russia is located in Asia, and the Ural mountains are often viewed as the meeting point of the two continents in Russia; nonetheless, European Russia is still significantly larger than any other European country. Ukraine, the second largest country on the continent, is only 603,000 km2, making it about 28 times smaller than its eastern neighbor, or seven times smaller than the European part of Russia. France is the third largest country in Europe, but the largest in the European Union. The Vatican City, often referred to as the Holy Sea, is both the smallest country in Europe and in the world, at just one km2. Population Russia is also the most populous country in Europe. It has around 144 million inhabitants across the country; in this case, around three quarters of the population live in the European part, which still gives it the largest population in Europe. Despite having the largest population, Russia is a very sparsely populated country due to its size and the harsh winters. Germany is the second most populous country in Europe, with 83 million inhabitants, while the Vatican has the smallest population. Worldwide, India and China are the most populous countries, with approximately 1.4 billion inhabitants each. Cities Moscow in Russia is ranked as the most populous city in Europe with around 13 million inhabitants, although figures vary, due to differences in the methodologies used by countries and sources. Some statistics include Istanbul in Turkey* as the largest city in Europe with its 15 million inhabitants, bit it has been excluded here as most of the country and parts of the city is located in Asia. Worldwide, Tokyo is the most populous city, with Jakarta the second largest and Delhi the third.

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 2023 based on 47 countries was 51.06 percent. The highest value was in Moldova: 53.98 percent and the lowest value was in Malta: 48.11 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

In 2025, Moscow was the largest city in Europe with an estimated urban agglomeration of 12.74 million people. The French capital, Paris, was the second largest city in 2025 at 11.35 million, followed by the capitals of the United Kingdom and Spain, with London at 9.84 million and Madrid at 6.81 million people. Istanbul, which would otherwise be the largest city in Europe in 2025, is excluded as it is only partially in Europe, with a sizeable part of its population living in Asia. Europe’s population is almost 750 million Since 1950, the population of Europe has increased by approximately 200 million people, increasing from 550 million to 750 million in these seventy years. Before the turn of the millennium, Europe was the second-most populated continent, before it was overtaken by Africa, which saw its population increase from 228 million in 1950 to 817 million by 2000. Asia has consistently had the largest population of the world’s continents and was estimated to have a population of 4.6 billion. Europe’s largest countries Including its territory in Asia, Russia is by far the largest country in the world, with a territory of around 17 million square kilometers, almost double that of the next largest country, Canada. Within Europe, Russia also has the continent's largest population at 145 million, followed by Germany at 83 million and the United Kingdom at almost 68 million. By contrast, Europe is also home to various micro-states such as San Marino, which has a population of just 30 thousand.

Eurostat’s annual data collections on population are structured as follows:

POPSTAT Population statistics data collection: The most in-depth annual national and regional demographic and migration data collection. The data relate to populations, births, deaths, immigrants, emigrants, marriages and divorces, and is broken down into several categories (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EU) No 862/2007).

URESPOP Usually resident population: Usually resident population for the purpose of the qualified majority voting.
Formore specific information, please see the metadata on Usually resident population (Article 4 of Regulation (EU) No 1260/2013).

Member States send population data to Eurostat data as on of 31 December for the reference year under http://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32013R1260&from=EN" target="_blank">Regulation 1260/2013 on European demographic statistics. The data are conventionally published by Eurostat as population on 1 January of the following year (reference year + 1).

The aim is to collect annual mandatory and voluntary demographic data from the national statistical institutes. Mandatory data are those defined by the legislation listed under ‘6.1. Institutional mandate — legal acts and other agreements’.

The completeness of the demographic data collected on a voluntary basis depends on the availability and completeness of information provided by the national statistical institutes.

For more information on mandatory/voluntary data collection, see 6.1. Institutional mandate — legal acts and other agreements.

The following statistics are available.

Population on 1 January by sex and by:

• single age and educational attainment / marital status / broad group of citizenship / broad group of country of birth;
• five-year age group and citizenship / country of birth;
• citizenship and broad group of country of birth / country of birth and broad group of citizenship;
• broad age group and NUTS 3 (under regional data population folder);
• single age and NUTS 2 (under regional data population folder);
• five-year age group and NUTS 2 / NUTS 3 (under regional data population folder).

Population structure statistics: median age of population, proportion of population by various age groups, old age dependency ratio.

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).

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

Eurostat’s annual data collections on population are structured as follows:

POPSTAT Population statistics data collection: The most in-depth annual national and regional demographic and migration data collection. The data relate to populations, births, deaths, immigrants, emigrants, marriages and divorces, and is broken down into several categories (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EU) No 862/2007).

URESPOP Usually resident population: Usually resident population for the purpose of the qualified majority voting.
Formore specific information, please see the metadata on Usually resident population (Article 4 of Regulation (EU) No 1260/2013).

Member States send population data to Eurostat data as on of 31 December for the reference year under http://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32013R1260&from=EN" target="_blank">Regulation 1260/2013 on European demographic statistics. The data are conventionally published by Eurostat as population on 1 January of the following year (reference year + 1).

The aim is to collect annual mandatory and voluntary demographic data from the national statistical institutes. Mandatory data are those defined by the legislation listed under ‘6.1. Institutional mandate — legal acts and other agreements’.

The completeness of the demographic data collected on a voluntary basis depends on the availability and completeness of information provided by the national statistical institutes.

For more information on mandatory/voluntary data collection, see 6.1. Institutional mandate — legal acts and other agreements.

The following statistics are available.

Population on 1 January by sex and by:

• single age and educational attainment / marital status / broad group of citizenship / broad group of country of birth;
• five-year age group and citizenship / country of birth;
• citizenship and broad group of country of birth / country of birth and broad group of citizenship;
• broad age group and NUTS 3 (under regional data population folder);
• single age and NUTS 2 (under regional data population folder);
• five-year age group and NUTS 2 / NUTS 3 (under regional data population folder).

Population structure statistics: median age of population, proportion of population by various age groups, old age dependency ratio.

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Longitudinal data is limited to income information and a limited set of critical qualitative, non-monetary variables of deprivation, aimed at identifying the incidence and dynamic processes of persistence of poverty and social exclusion among subgroups in the population. The longitudinal component is also more limited in sample size compared to the primary, cross-sectional component. Furthermore, for any given set of individuals, microlevel changes are followed up only for a limited duration, such as a period of four years. For both the cross-sectional and longitudinal components, all household and personal data are linkable. Furthermore, modules providing updated information in the field of social exclusion is included starting from 2005.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

This is the 4th release of 2009 Longitudinal Dataset, as published by Eurostat in March 2013.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Documentation.

Mode of data collection

Mixed

Abstract

In 2007, the EU-SILC instrument covered all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The sixth revision of the 2007 Cross-Sectional User Database is documented here.

Geographic coverage

National

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Documentation.

Mode of data collection

Mixed

This dataset shows different breakdowns of London's resident population by their country of birth. Data used comes from ONS' Annual Population Survey (APS).

The APS has a sample of around 320,000 people in the UK (around 28,000 in London). As such all figures must be treated with some caution. 95% confidence interval levels are provided.

Numbers have been rounded to the nearest thousand and figures for smaller populations have been suppressed.

Four files are available for download:

• Country of Birth - Borough: Shows country of birth estimates in their broad groups such as European Union, South East Asia, North Africa, etc. broken down to borough level.
• Detailed Country of Birth - London: Shows country of birth estimates for specific countries such as France, Bangladesh, Nigeria, etc. available for London as a whole
• Demography Update 09-2015: A GLA Demography report that uses APS data to analyse the trends in London for the period 2004 to 2014. A supporting data file is also provided.
• Country of Birth Borough 2004-2016 Analysis Tool: A tool produced by GLA Demography that allows users to explore different breakdowns of country of birth data.

An accompanying Tableau visualisation tool has also been produced which maps data from 2004 to 2015.

Nationality data can be found here: https://data.london.gov.uk/dataset/nationality

Nationality refers to that stated by the respondent during the interview. Country of birth is the country in which they were born. It is possible that an individual’s nationality may change, but the respondent’s country of birth cannot change. This means that country of birth gives a more robust estimate of change over time.

In 2025, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth.

BackgroundSocioeconomic inequalities in alcohol-related mortality have been documented in several European countries, but it is unknown whether the magnitude of these inequalities differs between countries and whether these inequalities increase or decrease over time.Methods and FindingsWe collected and harmonized data on mortality from four alcohol-related causes (alcoholic psychosis, dependence, and abuse; alcoholic cardiomyopathy; alcoholic liver cirrhosis; and accidental poisoning by alcohol) by age, sex, education level, and occupational class in 20 European populations from 17 different countries, both for a recent period and for previous points in time, using data from mortality registers. Mortality was age-standardized using the European Standard Population, and measures for both relative and absolute inequality between low and high socioeconomic groups (as measured by educational level and occupational class) were calculated.Rates of alcohol-related mortality are higher in lower educational and occupational groups in all countries. Both relative and absolute inequalities are largest in Eastern Europe, and Finland and Denmark also have very large absolute inequalities in alcohol-related mortality. For example, for educational inequality among Finnish men, the relative index of inequality is 3.6 (95% CI 3.3–4.0) and the slope index of inequality is 112.5 (95% CI 106.2–118.8) deaths per 100,000 person-years. Over time, the relative inequality in alcohol-related mortality has increased in many countries, but the main change is a strong rise of absolute inequality in several countries in Eastern Europe (Hungary, Lithuania, Estonia) and Northern Europe (Finland, Denmark) because of a rapid rise in alcohol-related mortality in lower socioeconomic groups. In some of these countries, alcohol-related causes now account for 10% or more of the socioeconomic inequality in total mortality.Because our study relies on routinely collected underlying causes of death, it is likely that our results underestimate the true extent of the problem.ConclusionsAlcohol-related conditions play an important role in generating inequalities in total mortality in many European countries. Countering increases in alcohol-related mortality in lower socioeconomic groups is essential for reducing inequalities in mortality. Studies of why such increases have not occurred in countries like France, Switzerland, Spain, and Italy can help in developing evidence-based policies in other European countries.

Harmonized data file as the basis for comparative analysis of quality of life in the Candidate Countries and the European Union member states, based on seven different data sets, one Eurobarometer survey covering 13 Candidate Countries with an identical set of variables conducted in April 2002, the other six Standard Eurobarometer of different subjects and fielded in different years, each with another set of questions identical with the CC Eurobarometer. Selected aggregate indicators of quality of life ... describing the social situation in the EU15 and Candidate Countries. The countries are tentatively grouped according to affinities following a families of nations logic. The indicators were drawn from various sources, mainly provided by supranational organisations. They are grouped into six categories and recorded in the technical report (page 12 ff.): (1) economy and employment; (2) health; (3) population and family; (4) inequality and social problems; (5) modernisation; (6) political system. Most indicators refer to the year 2000. Deviations from this rule are explained in the list of indicators, together with definitions, coding, and sources. The indicators are added to the harmonized EB data file for all 28 countries in order to provide an opportunity for multi-level analysis. Selected comprehensive indicators and relevant indices have been defined and constructed for quality of life and subjective well-being as well as for poverty and deprivation measures. The CC-Eurobarometer contains several questions on the perceived income situation of a household and on the availability or lack of certain consumer goods. It also provides information on the perception of social integration and general acceptance. (Source: Alber, Jens; Böhnke, Petra; Delhey, Jan; Fliegner, Florian; Gauckler, Britta; Habich, Roland; Keck, Wolfgang; Kohler, Ulrich; Nauenburg, Ricarda; Schiller, Sabine: Quality of Life in the European Union and the Candidate Countries. Technical Report. Results of data inspection, establishing a harmonized data file, recoding procedure and preparation of analysis. Hand-out for the first researchers’ meeting, Brussels, 4-5 March 2003.). Multi-stage, random (probability) sampling. The sampling is based on a random selection of sampling points after stratification by the distribution of the national, resident population in terms of metropolitan, urban and rural areas, i.e. proportional to the population size (for a total coverage of the country) und to the population density. These primary sampling units (PSU) are selected from each of the administrative regions in every country. In the second stage, a cluster of addresses is selected from each sampled PSU. Addresses are chosen systematically using standard random route procedures, beginning with an initial address selected at random. In each household, one respondent is selected by a random procedure, such as the first birthday method.

The European Union Statistics on Income and Living Conditions (EU-SILC) collects timely and comparable multidimensional microdata on income, poverty, social exclusion and living conditions.

The EU-SILC collection is a key instrument for providing information required by the European Semester (_[1]) and the European Pillar of Social Rights, and the main source of data for microsimulation purposes and flash estimates of income distribution and poverty rates.

AROPE remains crucial to monitor European social policies, especially to monitor the EU 2030 target on poverty and social exclusion. For more information, please consult EU social indicators.

The EU-SILC instrument provides two types of data:

• Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions.
• Longitudinal data pertaining to individual-level changes over time, observed periodically over four‐or more year rotation scheme (Annex III (2) of 2019/1700).

EU-SILC collects:

• annual variables,
• three-yearly modules,
• six-yearly modules,
• ad-hoc new policy needs modules,
• optional variables.

The variables collected are grouped by topic and detailed topic and transmitted to Eurostat in four main files (D-File, H-File, R-File and P-file).

The domain ‘Income and Living Conditions’ covers the following topics: persons at risk of poverty or social exclusion, income inequality, income distribution and monetary poverty, living conditions, material deprivation, and EU-SILC ad-hoc modules, which are structured into collections of indicators on specific topics.

In 2023, in addition to annual data, in EU-SILC were collected: the three yearly module on labour market and housing, the six yearly module on intergenerational transmission of advantages and disadvantages, housing difficulties, and the ad hoc subject on households energy efficiency.

Starting from 2021 onwards, the EU quality reports use the structure of the Single Integrated Metadata Structure (SIMS).

_{([1]) The European Semester is the European Union’s framework for the coordination and surveillance of economic and social policies.}

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

The statistic depicts France's real gross domestic product (GDP) growth rate from 2020 to 2024, with projections up until 2030. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. Real GDP is adjusted for price changes and is therefore regarded as a key indicator for economic growth. In 2024, France's real GDP grew by about 1.07 percent compared to the previous year. Unemployment in France France has one of the largest economies in the world and is the second largest economy in the European Union, behind Germany, with whom France often partnered in order to support the structure of the European Union. France is also the fourth most populated country in Europe and has maintained slow population growth since the mid 2000s. Despite being not only a European but also a global economic power, France struggled with maintaining a low unemployment rate and experienced a significant increase in unemployment after the 2008 crash, just like many other prominent industrial countries. However, unlike these other nations, unemployment continued to rise well into the 2010s, while the employment situations in neighboring and international countries improved almost every year. The lack of working opportunities is related to the Eurozone crisis that primarily affected southern European countries, such as Spain, Portugal and Italy.

The statistic shows the total population of Poland from 2020 to 2024, with projections up until 2030. In 2024, the total population of Poland amounted to around 36.62 million inhabitants. Population and economy of Poland Poland is the sixth most populated country in the EU, and the ninth most populated one in Europe. After experiencing a minor decline in population from the mid to late 2000s, Poland’s populace has gradually risen annually. Based on current trends, it is estimated that Poland will suffer a population decrease of roughly 4 million in 2050, an estimate that is highly plausible due to the ongoing financial crisis in Europe. A reason for the country’s slow but certain growth in population could be its economic upturn that has seen momentous improvements over the past decade. Due to industrialization during Russian-ruled Congress Poland as well as the Great Depression, Poland suffered from high amounts of unemployment. However, demand for jobs dramatically increased during the mid 21st century, causing unemployment to plummet. Interestingly, Poland is one of the few countries that reported an unemployment rate which was lower than during the years prior to the global financial crisis. A further indication of economic upturn is evident in the country’s gross domestic product, which is primarily an indicator of economic strength and production in a country. Poland’s GDP trend coincides with its unemployment rate, having doubled in value and maintained a higher GDP compared to the years prior to the financial crisis of 2008.

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