Statistics Explained

Population statistics at regional level



Data extracted in March 2021.

Planned article update: 7 October 2022.

Highlights

As of 1 January 2020, Chemnitz (Germany) had the highest median age (52.0 years) in the EU; five other German regions were present in the top 10 list of EU regions with the highest median ages.

Aside from the EU’s outermost regions, the eastern Romanian region of Vaslui had the highest fertility rate in the EU, with an average of 2.98 live births per woman in 2019.

Source: Eurostat (demo_r_find2) and (demo_find)

Demographic developments in the European Union (EU) are far from uniform, with considerable variations both between and within individual EU Member States. One factor that is often key to explaining these divergences is the mobility of young people, reflecting — among other issues — their search for education and/or job opportunities. The increased mobility of younger generations can result in profound changes to demographic structures in particular geographic areas, with some regions thriving due to an inflow of younger more-qualified generations, whereas others lag behind. Changes such as these can result in considerable differences in demographic structures, for example resulting in:

  • major urban areas which are often characterised by relatively youthful populations, large numbers of people living alone, high costs of living, diverse educational opportunities and buoyant labour markets;
  • towns and cities in former industrial heartlands that have been left behind economically, characterised by relatively high levels of unemployment, poverty and social exclusion;
  • commuter belts/suburban areas which are often inhabited by families;
  • coastal and countryside locations, some of which may be viewed as retirement locations for relatively affluent pensioners;
  • other rural and remote regions which may exhibit declining population numbers and a relatively elderly population structure, while being characterised by narrow labour market opportunities and relatively poor access to a wide range of services.

Full article

Regional populations

On 1 January 2020 there were 447 million persons living in the EU; this was 873 thousand more than on 1 January 2019. Most people in the EU live in relatively densely-populated cities, towns and suburbs, while the vast majority of the EU’s land area is more sparsely-populated. There are 240 NUTS level 2 regions and 1 169 NUTS level 3 regions across the EU from which a detailed typology for analysing demographic developments can be established. Note that some of the differences covered below reflect the criteria used to determine administrative boundaries that are used to delineate each region.

As of 1 January 2020, there were 51 NUTS level 2 regions in the EU that had at least 2.5 million people (as shown by the three largest circles in Map 1). This information relates to the ‘usual resident population’ (in other words, those people living in each region for at least the last 12 months). These most populous regions in the EU included the capital regions of Germany, Greece, Spain, France, Croatia, Italy, the Netherlands, Poland and Portugal. At the upper end of the distribution, there were just two regions with at least 10.0 million people, the French capital region (Île-de-France; 12.3 million) and Lombardia (10.0 million) in the north of Italy.

Regions with fewer than one million people as of 1 January 2020 (shown by the smallest circles in Map 1) were often rural, remote or peripheral regions. Among these, the least populous NUTS level 2 regions with less than 250 000 persons included the two Spanish Ciudades Autónomas de Ceuta y Melilla, the mountainous Italian region of Valle d’Aosta/Vallée d’Aoste, and four island regions — Ionia Nisia, Voreio Aigaio (both Greece), Região Autónoma dos Açores (Portugal) and Åland (Finland). The lowest population count (just under 30 000 persons) was in Åland.

Most capital regions are projected to see their populations grow during the next three decades

Populations change in a dynamic fashion over time, as a function of births, deaths and migratory flows; this is true for regional as well as national populations. The EU is undergoing a period of progressive ageing of its population with low fertility rates contributing to the growing share of the elderly in the total population. This on-going process of demographic ageing has a number of socioeconomic impacts: for example, there will probably be a sizeable reduction in the number and share of working-age persons which may result in considerable challenges for public expenditure on pensions, healthcare and long-term care costs.

EUROPOP2019 is the latest set of population projections released by Eurostat. It provides ‘what-if’ scenarios that may be used to trace projected population developments (based on various assumptions that are held constant over time). According to the baseline projection, the EU’s population will fall by 6.1 million persons during the next three decades (equivalent to an overall fall of 1.4 %).

Map 1 shows projected changes in populations for NUTS level 2 regions between 1 January 2020 and 1 January 2050. In the vast majority of EU Member States, capital regions have some of the highest positive projected rates of change, suggesting that they will (continue to) exert a considerable pull on both international and inter-regional migrants.

There are 19 regions across the EU where the population is projected to increase by at least 15.0 % during the next three decades (as shown by the darkest shade of orange in Map 1). Particularly high projected growth — more than 25.0 % — was observed in regions as far afield as Mayotte and Guyane (France), Voreio Aigaio (Greece), Illes Balears (Spain), Malta, Eastern and Midland (Ireland) and Stockholm (Sweden).

Regional populations are projected to increase between 1 January 2020 and 1 January 2050 across many densely-populated, predominantly urban regions of the EU. Looking in more detail at population developments within individual EU Member States, every region of Denmark, Ireland, Luxembourg, Malta and Sweden is projected to experience an increase in population numbers during the period under consideration. By contrast, population levels are projected to fall across many eastern regions of the EU and in the Baltic Member States. This pattern is particularly apparent in Bulgaria, Estonia, Croatia, Latvia, Lithuania and Romania, where every region is projected to see its population fall. A similar pattern is foreseen in Poland, Slovenia and Slovakia, as every region — except for the capital region — is projected to experience a decline in population numbers.

Map 1: Population on 1 January 2020 and projected population change 1 January 2020-2050
(by NUTS 2 regions)
Source: Eurostat (demo_r_pjangroup), (proj_19rp3), (demo_pjan) and (proj_19np)

Population density provides an average measure for the number of persons living per square kilometre (km²) of land area. Most regions are characterised by a broad range of different land uses beyond residential developments (for example, agriculture, forests, factories, offices and retail space, transport infrastructure, unused and abandoned areas). Therefore, even within individual regions there can be wide-ranging differences in population density.

In 2019, the population density of the EU was 109.0 persons per km². In general, there were quite low levels of population density across much of the EU, although these were interspersed by pockets of more densely-populated regions. As of 1 January 2020, the 30 most populous NUTS level 3 regions accounted for 16.3 % of the EU’s total population, whereas their combined share of the EU’s total area was just 3.8 %.

On average, there were almost 21 000 persons living in every square kilometre of Paris …

The highest population density in the EU was recorded in the French capital region, Paris, where there were, on average, almost 21 000 persons per km² in 2019. As noted above, the administrative boundaries used to delineate each region can have a considerable influence on these results. For example, the French capital region is constrained by the périphérique (a Parisian ring road) and hence its area is strictly confined to the centre of Paris, in contrast to most urban regions which include both a city centre and its surrounding (less densely-populated) suburban areas. That said, population density was also very high in the three regions bordering directly onto the French capital (Hauts-de-Seine, Seine-Saint-Denis and Val-de-Marne), with much lower values for the next concentric ring of regions around the capital (Essonne, Yvelines and Seine-et-Marne).

The second highest level of population density in 2019 was recorded in the Greek capital region, Kentrikos Tomeas Athinon (10 446 persons per km²), followed by Hauts-de-Seine, which covers some of the inner suburbs to the west of Paris (9 457 persons per km²). The top five most densely-populated regions in the EU was completed by the Romanian and Belgian capital regions, Bucureşti (7 933 persons per km²) and Arr. de Bruxelles-Capitale/Arr. van Brussel-Hoofdstad (7 527 persons per km²).

Most of the other regions with very high levels of population density were characterised as urban regions containing some of the EU’s largest cities (including most of the remaining capitals) or regions that were located adjacent to these (in other words, areas of suburban sprawl around some of the EU’s main cities and conurbations — for example, the Ruhrgebiet in Germany or Randstad in the Netherlands).

The lowest level of population among EU capital regions was recorded in Vilniaus apskritis (Lithuania), at 86.6 persons per km², which was below the average population density for the whole of the EU. Cyprus had a population density of 95.7 persons per km² and was the only other capital region to record a level of population density below the EU average.

… in contrast to large expanses of uninhabited areas in northern Europe

At the other end of the range there remain large expanses of the EU where relatively few people are living. Nowhere was this more apparent than in Lappi — the northernmost region of Finland — which had the lowest population density in the EU, at 1.9 persons per km² in 2019. The second and third lowest population densities in the EU were recorded in neighbouring Sweden, in the northernmost region of Norrbottens län and the central region of Jämtlands län.

Map 2: Population density, 2019
(persons per km², by NUTS 3 regions)
Source: Eurostat (demo_r_d3dens)

Population structure

As noted above, regional population projections suggest that demographic ageing will continue across the EU as a result of persistently low fertility rates and extended longevity. The social and economic consequences of this process are likely to have profound implications both nationally and regionally, for example, impacting the capacity of governments to raise tax revenue, or provide adequate pensions and healthcare services. These challenges are likely to be more intensely felt in those regions from which younger (and working-age) people relocate.

That said, the elderly have been most impacted by the COVID-19 pandemic in terms of morbidity and mortality (see the article on health for more details). As a result, regions characterised by high shares of elderly populations are more likely to have witnessed rapid changes in their population structures during the pandemic.

Some of the highest median ages in the EU were recorded in regions in Germany, Spain and Italy …

The median age is an indicator that may be used to analyse population ageing. It gives an idea of the pace at which the EU’s population structure is changing. The median age of the EU population was 38.4 years in 2001 (the first reference year for which information is available). Over a period of 19 years, the median age in the EU increased by more than five years, to stand at 43.9 years by 2020.

In 2020, 6 out of the 10 NUTS level 2 regions in the EU with the highest median ages were situated in (predominantly eastern) Germany: Chemnitz, Sachsen-Anhalt, Brandenburg, Mecklenburg-Vorpommern, Thüringen and Saarland. These regions were often characterised by relatively low levels of disposable income and relatively high unemployment rates (when compared with other regions in Germany). It is therefore likely that their high median ages reflect, at least to some degree, younger people having moved — for example to regions with larger and more affluent cities in Germany, or further afield (for example, in neighbouring countries such as Austria) — in search of higher wages and/or better job opportunities.

The median age of the population was also relatively high in a number of Spanish and Italian regions that were characterised by relatively low fertility rates and rural depopulation (in part reflecting a range of push factors that encourage younger people to leave their region). This pattern was most evident for the neighbouring regions of Principado de Asturias and Castilla y León in north-west Spain and two northern regions of Italy — Liguria and Friuli-Venezia Giulia. In these two Italian regions, population ageing was enhanced as their coastlines provided popular retirement destinations (thereby pulling in additional old people).

… while some of the lowest median ages were recorded in and around capital cities

Capital regions often exert a considerable pull on international and inter-regional migrants, as they tend to provide a wide range of educational and employment opportunities. This process can lead to a shift in population structures, with younger people accounting for a growing share of the total population in capital regions; over time, this pattern may self-propagate, insofar as populations with younger age structures are more likely to have relatively high birth rates.

In 2020, 5 out of the 10 NUTS level 2 regions in the EU with the lowest median ages were capital regions, those of Belgium, Ireland, France, Cyprus and Sweden. Among these, the lowest median age was recorded in Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (35.9 years). The other five regions with the lowest median ages were outermost regions and autonomous regions/cities. Two of these had particularly low median ages (reflecting their high fertility rates): the French régions ultrapériphériques of Mayotte (17.7 years) and Guyane (26.1 years).

Figure 1: Median age of population, 2020
(years, by NUTS 2 regions)
Source: Eurostat (demo_r_pjanind2) and (demo_pjanind)

There were 75 regions across the EU with old-age dependency ratios of at least 50.0 %

An alternative indicator for measuring the gradual ageing of the EU’s population is the old-age dependency ratio. It is calculated as the number of elderly people (aged 65 years or more) compared with the number of working-age people (defined here as those aged 20-64 years). In 2001, the EU’s old-age dependency ratio was 25.9 %. In other words, there were slightly fewer than four adults of working age for every person aged 65 years or more. The old-age dependency ratio had risen to 34.8 % by 1 January 2020 (when there were slightly fewer than three adults of working age for every person aged 65 years or more), while the ratio is projected to reach 56.7 % by 2050 (by when there will be fewer than two working-age adults for each elderly person).

As of 1 January 2020, there were 75 NUTS level 3 regions across the EU which reported an old-age dependency ratio of at least 50.0 %; in other words, regions where there were fewer than two working-age adults for each person aged 65 years or more. These 75 regions were predominantly characterised as rural, mountainous or relatively remote, where it is likely that younger people have left the region in which they grew up so they could continue their studies or look for alternative and perhaps more varied work. Some of the highest old-age dependency ratios were concentrated in (eastern) Germany, Greece, Spain, France, Italy, Portugal and Finland.

The mountainous, central Greek region of Evrytania had the highest old-age dependency ratio on 1 January 2020, at 78.3 %. It was followed by the north-western Belgian region of Arr. Veurne (64.6 %) and the German region of Suhl, Kreisfreie Stadt (61.3 %). At the other end of the scale, the lowest old-age dependency ratios in the EU were often recorded in outermost regions, for example, the French régions ultrapériphériques of Mayotte and Guyane or the Spanish region of Fuerteventura (part of Canarias).

During the next three decades, old-age dependency ratios are projected to increase in all but one region of the EU

EUROPOP2019 data can be used to provide an idea of how the EU’s population structure is projected to change in the coming years. As noted above, there were 75 regions across the EU (out of a total of 1 169 NUTS level 3 regions) with an old-age dependency ratio of at least 50.0 % on 1 January 2020. Over the next three decades, old-age dependency ratios are projected to increase in all but one of these 1 169 regions [1] and by 1 January 2050 the projections indicate that there will be 974 regions where the old-age dependency ratio has risen to at least 50.0 %. While an ageing population has traditionally been seen as a concern — based upon the assumption that older people have to be economically supported by those of working age — this view is evolving. As people live healthier and longer lives, they may (choose or be able to) work later in life, thereby increasing economic activity at older ages.

Map 3: Old-age dependency ratio, 1 January 2020
(%,people aged ≥ 65 years / people aged 20-64 years, by NUTS 3 regions)
Source: Eurostat (demo_r_pjanind3) and (demo_pjanind)

Fertility

EU regions with relatively high levels of fertility are protected, to some degree, from the impact of population ageing. One factor which may explain the relatively low levels of fertility in the EU is the growing proportion of women giving birth later in life. This may be linked, among other factors, to: higher female participation rates in further education and/or more women choosing to establish a career before starting a family; lower levels of job security (for example, in the gig economy); the increasing cost of raising children and of housing; and a decline in the number of traditional family units (less people getting married and more people getting divorced). In 2019, there were 4.17 million live births across the EU, while the median age of women at childbirth was 31.4 years.

The vast majority of regions in the EU had a total fertility rate that was below the natural replacement rate

The total fertility rate is defined as the mean number of children who would be born to a woman during her lifetime, if she were to spend her childbearing years conforming to the age-specific fertility rates of a given year. In 2019, the EU’s total fertility rate was 1.53 live births per woman, which was considerably below the natural replacement rate — the average number of live births per woman required to keep the population size constant in the absence of migration in developed world economies — of 2.1 children per woman. The regional distribution of this indicator was somewhat skewed insofar as there were 479 NUTS level 3 regions where the total fertility rate was below the EU average (as shown by the blue shades in Map 4), while there were 690 regions where the rate was as high as the EU average or higher (as shown by the orange shades). Across most of the EU Member States, predominantly urban regions (which tend to have a higher proportion of young people) generally recorded higher fertility rates than predominantly rural, remote and sparsely-populated regions.

Of the 1 169 NUTS level 3 regions for which data are available, there were only 14 where the total fertility rate was at least 2.1 live births per woman. These included all of the French régions ultrapériphériques except for Martinique, three other French regions situated around the French capital — Seine-Saint-Denis, Val-d’Oise and Essonne — and five regions in Romania. The highest fertility rates were recorded in two of the EU’s outermost regions, Mayotte (4.56 live births per woman) and Guyane (3.72 live births per woman). Aside from these, the highest fertility rate in the EU was recorded in the eastern Romanian region of Vaslui (2.98 live births per woman). By contrast, some of the lowest fertility rates were recorded in southern regions of the EU, principally across Greece, Spain, Italy and Portugal, where there were 16 regions that registered a total fertility rate of less than 1.00 live births per woman in 2019. The lowest fertility rate in the EU was recorded in the central Greek region of Fokida (0.63 live births per woman).

The total fertility rate is projected to rise in approximately three quarters of all regions

According to the assumptions used within EUROPOP2019, the EU’s total fertility rate will gradually rise during the next three decades to stand at 1.62 by 2050 (compared with 1.53 in 2019); note that a different methodology is used for computing these projections. The latest projections indicate that this pattern of rising fertility rates between 2019 and 2050 will be repeated in approximately three quarters of the NUTS level 3 regions in the EU (905 out of 1 169). However, total fertility rates will generally rise at a modest pace: the latest assumptions reveal only 26 regions with rates increasing by at least 0.25 between 2019 and 2050. By contrast, there are just seven regions where the latest assumptions are for fertility rates to fall by at least 0.25 between 2019 and 2050.

Map 4: Total fertility rate, 2019
(live births per woman, by NUTS 3 regions)
Source: Eurostat (demo_r_find3) and (demo_find)

There has been a gradual increase across the EU in the age at which mothers give birth

In 2000, slightly more than one in seven live births in the EU were childbirths from women aged 35 years or more. By 2019, this share had risen to more than one in four (25.9 %). The median age of women at childbirth across the EU was 31.4 years in 2019 (see Figure 2), ranging from a high of 34.6 years in Galicia (north-west Spain) down to a low of 27.2 years in Severozapaden (north-west Bulgaria).

Looking in more detail within individual EU Member States, the pattern of delayed childbirth was often quite pronounced in capital regions. This was particularly the case in eastern Member States, as the median age of women at childbirth in the capital regions of Romania, Hungary and Slovakia was 2.2 to 2.3 years above their respective national average. A similar pattern, although less marked, was repeated in most of the remaining multi-regional Member States; the only exceptions were Ireland (where the latest data for the capital region and the national average were identical) and Croatia (where the national average for the median age of women at childbirth was 0.1 years higher than that for the capital region).

Figure 2: Median age of mothers at childbirth, 2019
(years, by NUTS 2 regions)
Source: Eurostat (demo_r_find2) and (demo_find)

Life expectancy

Life expectancy at birth is the average number of years a newborn would live if subjected throughout his/her life to current mortality conditions. During the last two centuries, life expectancy in the EU rose at a relatively consistent pace (with a few exceptional periods, such as in periods of war). This increased longevity can be attributed to a range of factors including significant advances in medical treatment and care, changes in living and environmental conditions, changes in working conditions/occupations, as well as lifestyle changes. This pattern of rising life expectancy in the EU has, in recent years, shown signs of change. Indeed, there was a slight fall in life expectancy between 2014 and 2015 and no change between 2016 and 2017 (note however that these reductions may be linked to breaks in series). Provisional estimates for 2020 are available for nearly all of the EU Member States and these indicate a fall in life expectancy within the EU, related at least in part to the COVID-19 pandemic.

When averaged over the most recent three years for which data are available, life expectancy in the EU had increased to 81.1 years by 2017-2019. Map 5 shows regional life expectancy at birth for NUTS level 2 regions during the same period. The regional distribution around the EU average was somewhat skewed, insofar as there were 93 regions with life expectancy below 81.1 years, while there were 147 that had a life expectancy of 81.1 years or more. There are a range of potential drivers that may impact on inter-regional differences in life expectancy, including:

  • proximity to healthcare services — capital regions tend to have a greater number and variety of healthcare facilities compared with rural regions;
  • the prosperity of a region — life expectancy is generally higher in regions characterised by a higher standard of living and lower in regions characterised by poverty and social deprivation;
  • lifestyle and cultural differences — for example, the type of work that predominates in a region, the typical diet of a region, or the incidence of smoking and alcohol consumption;
  • climatic conditions — people living in warm, temperate and relatively dry climates tend to live longer lives than those living in regions that experience more extreme weather conditions.

The above may explain, at least to some degree, why some of the highest regional life expectancies in 2017-2019 were concentrated in France, Spain and Italy. These three EU Member States accounted for 27 of the 29 regions in the EU that had a life expectancy at birth of at least 83.5 years (as shown by the darkest shade of orange in Map 5); the other two regions were Ipeiros (north-west Greece) and Åland (an autonomous island region of Finland). Severozapaden in north-west Bulgaria recorded, by some margin, the lowest level of life expectancy, at 73.6 years. This was 0.8 years lower than in the four regions with the next lowest levels of life expectancy: two more Bulgarian regions — Severen tsentralen and Yugoiztochen; Észak-Magyarország (northern Hungary); and Nord-Est (north-east Romania).

Map 5: Life expectancy at birth, 2017-2019
(years, by NUTS 2 regions)
Source: Eurostat (demo_r_mlifexp) and (demo_mlexpec)

A girl born in the Spanish capital region during the period 2017-2019 could expect to live 87.9 years

By 2017-2019, life expectancy at birth in the EU stood at 83.8 years for women and 78.3 years for men. During this period, the Spanish capital region of Comunidad de Madrid had the highest level of life expectancy at birth both for women (an average of 87.9 years) and for men (82.6 years). The highest life expectancies for women were concentrated in regions of Spain, whereas the highest life expectancies for men were principally recorded in central and northern Italy.

The EU gender gap for life expectancy at birth was 5.5 years in favour of women in 2017-2019. Female life expectancy was consistently higher than male life expectancy across every region of the EU. Some of the largest gender gaps were recorded in the Baltic Member States and several Polish regions, while the difference in life expectancy between the sexes was much narrower in Dutch regions and in the French outermost region of Mayotte. Vidurio ir vakaru Lietuvos regionas — the Lithuanian capital region — had the highest gender gap for life expectancy at birth (9.8 years difference), while the lowest gap was recorded in Mayotte (1.3 years).

Figure 3: Life expectancy at birth by sex, 2017-2019
(years, by NUTS 2 regions)
Source: Eurostat (demo_r_mlifexp) and (demo_mlexpec)

Source data for figures and maps

Data sources

Regional demographic statistics

Eurostat collects a wide range of regional demographic statistics: these include data on population numbers and various demographic events which influence the population’s size, structure and specific characteristics. Regional demographic statistics may be used for a wide range of planning, monitoring and evaluating actions, for example, to:

  • analyse population ageing and its effects on sustainability and welfare;
  • evaluate the economic impact of demographic change;
  • calculate ratios relative to the size of the population — such as regional GDP per person — which may be used, for example, to allocate structural funds to economically less advantaged regions.

Regional demographic data include statistics that provide a count for the usual resident population, representing the number of persons living in a given area on 1 January of the year in question (or, in some cases, the 31 December of the previous year), as well as the number of live births and the number of deaths during the previous year.

Regional demographic data and indicators are presented at different levels of the NUTS classification (for EFTA and candidate countries the data are compiled according to agreed statistical regions that have been coded in a way that resembles NUTS):

NUTS level 2

  • population by sex, age and region of residence;
  • live births by mother’s age, mother’s year of birth and mother’s region of residence;
  • deaths by sex, age, year of birth and region of residence;
  • life table including life expectancy at a given exact age;
  • infant mortality and infant mortality rates.

NUTS level 3

  • population by sex, five-year age group and region of residence;
  • live births by five-year age group of the mothers and region of residence;
  • deaths by sex, five-year age group and region of residence;
  • demographic balance and crude rates (population change, natural change, net migration including statistical adjustment, crude birth and death rates, crude rates of population change);
  • population structure indicators (shares of various population age groups, dependency ratios and median ages);
  • fertility indicators (total fertility rate, mean age of woman at childbirth and median age of woman at childbirth);
  • population density.

All the indicators are also compiled for more aggregated levels of the NUTS classification. In other words, data compiled for NUTS level 3 regions will also be available for NUTS level 2 and NUTS level 1 (as well as at the country level).

Regional demographic data are collected in accordance with Article 3 of Regulation (EU) No 1260/2013 of the European Parliament and of the Council of 20 November 2013 on European demographic statistics and the measures/conditions laid out in Commission Implementing Regulation (EU) No 205/2014 of 4 March 2014.

Regional demographic data have been collected according to this legal basis since reference year 2013. Prior to 2013, regional demographic data were provided by national statistical authorities on a voluntary basis.

Population projections

EUROPOP2019 refers to the latest set of population projections established by Eurostat for all EU Member States and EFTA countries. The time horizon spans from the year 2019 (also called the base year of the projections) to 2100. The approach used is that of deterministic projections, or ‘what-if’ population projections, based on assumptions formulated on a future course of fertility, mortality and migration.

Given their unpredictability, it is common for population projections to neglect exogenous events, for example, the possibility of a war or an economic shock. That said, in recent years there have been a number of significant events that have taken place, each of which has impacted on demographic dynamics, at least in the short run and in some parts of the EU. Examples of such events include the global financial and economic crisis, the refugee crisis, Brexit (the United Kingdom leaving the EU) and the COVID-19 pandemic.

The EUROPOP2019 projections are based on a scenario of convergence that is central to many EU policies. This main assumption is that socioeconomic differences between EU Member States are expected to fade out in the very long term, as countries move closer together from a demographic perspective in terms of fertility, mortality and international migration.

Eurostat’s population projections are made for NUTS level 3 regions and include the following information:

  • projected population on 1 January by age and sex;
  • assumptions on future age-specific fertility rates, probabilities of dying and net migration levels by age and sex;
  • projected number of deaths by age and sex;
  • projected life expectancy by age and sex;
  • total numbers of projected live births and deaths, projected population structure indicators (shares of broad population age groups, age dependency ratios and median ages).

Although they are hypothetical in nature, population projections are designed to help the public, statisticians and policymakers understand population dynamics. The usual projection period spans over several decades, sometimes up to a century. Therefore, they contribute to informed debates on demographic and societal changes which are likely to affect our everyday lives in the coming years. For example, projections such as these may be used to analyse the long-run economic and fiscal implications of the EU’s ageing population.

Indicator definitions

Population

The population, of a given area (region or country), is the total number of persons that are usually resident in that area. This count is generally compiled on 31 December each year, and published as 1 January of the next year.

The average population for a calendar year is calculated as the arithmetic mean of the population on 1 January for two consecutive years. This measure is used in the calculation of demographic indicators, such as crude rates per 1 000 persons, and for some other indicators calculated relative to population size.

Population density

Population density is the number of persons per square kilometre (km²). For the calculation of population density, the land-area concept (which excludes inland water bodies like lakes or rivers) should be used wherever available.

Median age

The median age is the age that divides a population that has been ranked by age into two equal sized groups.

Old-age dependency ratio

The old-age dependency ratio is the ratio of the number of elderly people at an age when they are generally economically inactive, compared with the number of people of working age. A number of different age classes may be used for these two population cohorts. Within this publication, the old age-dependency ratio is defined as the ratio of the number of persons aged 65 years and over compared with the number aged 20-64 years.

Fertility

Fertility is the ability to conceive (become pregnant) and give birth to children. The total fertility rate is defined as the mean number of children who would be born to a woman during her lifetime, if she were to spend her childbearing years conforming to the age-specific fertility rates that have been measured in a given year.

The median age of women at childbirth is the age that divides the population of mothers ranked on their age at childbirth into two equal sized groups, meaning half of the mothers are younger than the median age and half are older.

Life expectancy

Life expectancy, at a certain age, is the mean additional number of years that a person of that age can expect to live, if subjected throughout the rest of his or her life to the current mortality conditions (age-specific probabilities of dying). Life expectancy at birth is the mean number of years a newborn child can expect to live if subjected throughout his or her life to the current mortality conditions. Life expectancy is normally calculated separately for all age levels, as well as for males, females and the total population.

Context

Demography

While the COVID-19 pandemic has radically impacted how people in the EU live, study, work and enjoy their leisure time, demographic changes are likely to shape socioeconomic developments across the EU over a long period of time. Such changes may drive a range of policy developments, in particular within the fields of employment and social policy, health, free movement, asylum and migration. Indeed, statistics on population change and population structures are increasingly used to support policymaking in these and other areas.

Prolonged life expectancy may be viewed as a considerable achievement of progress and economic development. However, when coupled with historically low fertility rates, it has led to a considerable change in the EU’s age structure, with a growing share of elderly persons in the population. These developments may pose a range of societal challenges, with a higher proportion of individuals that are traditionally considered as unproductive (those aged 65 years or over) acting as a break on economic growth. The growing number of very old persons also has an impact on the sustainability of welfare systems and may require a wide range of new services to be provided in order to cater for the specific demands of an increasingly large part of the population that is frail.

The European Parliament passed a resolution in November 2011 on Demographic change and its consequences for the future cohesion policy of the EU (2010/2157(INI)) which underlined that regional demographic developments should be statistically measured and stressed that demographic change should be considered as a cross-cutting objective in future cohesion policy.

Building on this, the European Commission adopted a Report on the impact of demographic change on 17 June 2020. It presented information on the drivers of long-term demographic change and its impacts. It also highlighted the links between demographic structures and the impact of the COVID-19 pandemic, with the oldest generations being particularly affected by the crisis in health terms. As parts of the EU appear to be cautiously emerging from the worst of the COVID-19 pandemic, it is apparent that the impact of demographic change continues to be of utmost importance at a socioeconomic level, for health and long-term care, and much more besides.

On 27 January 2021, the European Commission launched a wide-ranging debate on the impact of an ageing population. A Green Paper titled Fostering solidarity and responsibility between generations (COM(2021) 50 final) sought to initiate a discussion on the challenges and opportunities that may be associated with an ageing society and how to anticipate and respond to the socioeconomic impacts of the EU’s ageing population. Among other issues, this discussed:

  • healthy and active ageing and lifelong learning;
  • improving labour market performance;
  • modernising social protection systems and fighting old-age poverty;
  • improving the resilience of our health and care systems;
  • fostering intergenerational solidarity and responsibility.

Based on Eurostat’s latest round of population projections (EUROPOP2019), the Economic Policy Committee (EPC) published The 2021 Ageing Report which seeks to estimate the economic and budgetary impact of an ageing population across the EU Member States through until 2070.

Direct access to

Other articles
Tables
Database
Dedicated section
Publications
Methodology
Visualisations




Regional demographic statistics (t_reg_dem)
Population (regional level) (t_demopreg)
Population on 1 January by NUTS 2 region (tgs00096)
Population density by NUTS 2 region (tgs00024)
Fertility (regional level) (t_demofreg)
Total fertility rate by NUTS 2 region (tgs00100)


Regional demographic statistics (reg_dem)
Population and area (reg_dempoar)
Fertility (reg_demfer)
Mortality (reg_demmor)
Population (national level) (demo_pop)
Population (regional level) (demopreg)
Fertility (national level) (demo_fer)
Fertility (regional level) (demofreg)
Mortality (national level) (demo_mor)
Mortality (regional level) (demomreg)
EUROPOP2019 - Population projections at national level (2019-2100) (proj_19n)
EUROPOP2019 - Population projections at regional level (2019-2100) (proj_19r)


Manuals and further methodological information

Metadata

Maps can be explored interactively using Eurostat’s Statistical Atlas (see user manual).

This article forms part of Eurostat’s annual flagship publication, the Eurostat regional yearbook.

Notes

  1. The only exception is Harz, the westernmost region of Sachsen-Anhalt (Germany).