Population statistics at regional level

Data extracted in March 2016. Most recent data: Further Eurostat information, Main tables and Database. Planned article update: September 2017.

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

Map 1: Life expectancy at birth, by NUTS 2 regions, 2014 (1)
(years)
Source: Eurostat (demo_r_mlifexp) and (demo_mlexpec)
Figure 1: Gender gap for life expectancy at birth, by NUTS 2 regions, 2014 (1)
(difference in years between the life expectancy of women and men)
Source: Eurostat (demo_r_mlifexp) and (demo_mlexpec)
Figure 2: Distribution of the total population by broad age groups, selected NUTS 3 regions, 1 January 2015 (1)
(%)
Source: Eurostat (demo_r_pjangrp3) and (demo_pjangroup)
Map 2: Share in the total population of the working age population (aged 20–64), by NUTS 3 regions, 1 January 2015 (1)
(%)
Source: Eurostat (demo_r_pjangrp3) and (demo_pjangroup)
Map 3: Crude rate of total population change, by NUTS 3 regions, 2014 (1)
(per 1 000 inhabitants)
Source: Eurostat (demo_r_gind3) and (demo_gind)
Map 4: Crude rate of net migration (plus statistical adjustment), by NUTS 3 regions, 2014 (1)
(per 1 000 inhabitants)
Source: Eurostat (demo_r_gind3) and (demo_gind)
Figure 3: Crude birth rate, by NUTS 2 regions, 2014 (1)
(number of live births per 1 000 inhabitants)
Source: Eurostat (demo_r_gind3) and (demo_gind)
Figure 4: Total fertility rate, by NUTS 2 regions, 2014 (1)
(average number of live births per woman)
Source: Eurostat (demo_r_frate2)
Map 5: Total fertility rate, by NUTS 3 regions, 2014 (1)
(average number of live births per woman)
Source: Eurostat (demo_r_frate3) and (demo_find)
Figure 5: Crude death rate, by NUTS 2 regions, 2014 (1)
(number of deaths per 1 000 inhabitants)
Source: Eurostat (demo_r_gind3) and (demo_gind)

This article is part of a set of statistical articles based on the Eurostat regional yearbook publication. It describes regional demographic patterns across the European Union (EU).

Statistics on regional demography are one of the few areas where detailed NUTS level 3 information is collected and published for each of the EU Member States. At the time of writing, the latest information is available for vital demographic events (live births and deaths) and a range of demographic indicators generally through to the end of 2014, with data on the size and structure of the population available for 1 January 2015.

An analysis of the overall population by degree of urbanisation is available in the introduction to the Eurostat regional yearbook. A regional analysis of population projections through to 2050 is presented in a separate article.

Main statistical findings

Life expectancy

Over the last 50 years, life expectancy at birth has increased by about 10 years on average across the EU, due in large part to improved socio-economic and environmental conditions and better medical treatment and care. Map 1 presents life expectancy at birth for NUTS 2 regions in 2014.

On average, a European born in 2014 could expect to live 80.9 years

Map 1 shows that life expectancy at birth averaged 80.9 years across the EU-28 in 2014. There were 45 level 2 regions where life expectancy at birth was 83.0 years or more; these were spread across just seven of the EU Member States, as well as Switzerland: there were 16 Italian regions, 11 Spanish regions, eight French regions, two British regions, one region each from Austria, Greece and Finland, as well as five Swiss regions. The highest life expectancy in 2014 (across level 2 regions) was recorded in the Spanish capital region of the Comunidad de Madrid, at 84.9 years.

At the other end of the range, there were 58 level 2 regions with an average life expectancy of less than 78.0 years (as shown by the lightest shade of orange in Map 1) and these were predominantly regions in eastern EU Member States — Bulgaria, the Czech Republic, Croatia, Hungary, Poland, Romania and Slovakia — as well as Turkey. The three Baltic Member States (each being a single region at this level of detail), the two Portuguese regiões autónomas da Madeira and dos Açores were the only other regions in the EU-28 to record life expectancy below 78.0 years, as did Montenegro, the former Yugoslav Republic of Macedonia (each being a single region at this level of detail) and Serbia (national data). The lowest life expectancy at birth in 2014 (across level 2 regions) was 73.0 years, recorded in the Bulgarian region of Severozapaden, which was the poorest region in the EU-28 (based on gross domestic product (GDP) per inhabitant in purchasing power standards (PPS)). As such, the difference in life expectancy between Severozapaden and the Comunidad de Madrid was 11.9 years.

It is important to note that while Map 1 presents information for the whole population, there remain considerable differences in life expectancy between men and women — despite evidence showing that this disparity between the sexes has been closing gradually in most EU Member States. The gender gap in the EU-28 was 5.5 years, as the life expectancy of women born in 2014 was 83.6 years, while that for men was 78.1 years. Figure 1 illustrates the gender gap across level 2 regions. The range from highest to lowest gender gap was relatively narrow within each country, with the exceptions often caused by a single outlier, such as the relatively low gaps for Åland in Finland, Bratislavský kraj in Slovakia and Praha in the Czech Republic.

Population structure and demographic ageing

There were 508.5 million inhabitants living in the EU-28 at the start of 2015. Across the whole of the EU-28, younger persons (0–19) accounted for 20.9 % of the total population as of 1 January 2015, while people of working age (20–64) accounted for three fifths (60.2 %) of the total (more information on this subgroup may be found in an article on the labour market), leaving some 18.9 % of the population as elderly persons (aged 65 and above). Note that these age classes used for an analysis of the structure of the EU-28 population have been adapted (compared with previous editions of the Eurostat regional yearbook) to reflect the age group used for the Europe 2020 target relating to the employment rate (20–64 years).

Looking in more detail at the broad age group of the working age population, 12.2 % of the population was aged 20–34 (this age group is used for some indicators in an article on education and training), 28.6 % was aged 35–54, and 12.8 % of the population was aged 55–64.

Demographic structures within individual EU Member States often show irregular patterns, which have the potential to impact on regional competitiveness and cohesion. Sometimes these divides are quite apparent, such as in Germany (where there is often a contrast between regions in the east and west), France (north-east and south-west), Italy (north and south) and Turkey (east and west). These differences may be attributed to a wide range of factors including: climatic, landscape, historical, political, social and economic developments.

Overseas and urban regions tended to have younger populations …

Figure 2 presents information on the 10 NUTS level 3 regions in the EU with the highest shares of younger persons (aged less than 20), the 10 NUTS level 3 regions in the EU with the highest shares of working-age persons (aged 20–64) disaggregated to show those aged 20–34 (including people who might still be in education), 35–54 (including people who are in the process of raising a family) and 55–64 (including people who might have moved into retirement), and; the 10 NUTS level 3 regions in the EU with the highest shares of elderly persons (aged 65 and above); the data are for 1 January 2015.

Those NUTS level 3 regions in the EU with the highest shares of young persons were generally located in those Member States which recorded the highest birth and fertility rates (see Map 5 for fertility rates), thereby boosting the relative importance of younger persons in their total populations. This was particularly the case in several Irish and French regions, for example, the French overseas regions of Guyane and La Réunion or suburban regions around Paris. Age structures of largely urban regions may display a higher proportion of young and working age persons as a result of a ‘pull effect’ associated with increased employment opportunities attracting both internal migrants (from different regions of the same country) and international migrants (from other Member States and non-member countries).

... while the relative importance of working age people was particularly high in some capital city regions …

Most of the top 10 NUTS level 3 regions in the EU with the highest shares of their populations being of working age were capital city regions, six of them in Inner London (the United Kingdom), and one each in Denmark (Byen København) and Romania (Bucureşti). The two remaining regions in the top 10 were Spanish island regions — Eivissa, Formentera (in the Balearic islands) and Fuerteventura (in the Canary islands) — these had relatively low shares of people aged 20–34 (compared with the capital city regions in the list), perhaps due to young people completing their studies on the Spanish mainland, but higher shares of people aged 35–54 and 55–64.

A comprehensive analysis of the share of working age people is provided for level 3 regions in Map 2. Across the 1 482 regions shown (national data for Albania and Serbia), there were 306 where the working age population reached or exceeded 62 %, among which 61 where this share reached or exceeded 65 %. Many of these regions were in capital or other large cities, mainly in Germany, Poland, Romania, Slovakia and the United Kingdom, but including also Sofia (stolitsa) in Bulgaria and Oslo in Norway. Other regions with relatively high shares included three of the eight statistical regions in the former Yugoslav Republic of Macedonia.

... and the relative importance of elderly persons has grown in most EU regions

Most regions in the EU have witnessed the relative share of their elderly populations becoming progressively larger as a result of a significant and continuous increase in life expectancy and the entry into retirement of the post-World War II baby-boom generation. Those regions with the highest shares of elderly persons are often identified as being rural, relatively remote and sparsely populated areas, where a low share of working age persons may, at least in part, be linked to a lack of employment and education opportunities, thereby motivating younger generations to leave in search of work or to pursue further studies.

The elderly accounted for a particularly high share of the total population in several rural and remote regions of Greece, Spain, France and Portugal, as well as a number of regions in eastern Germany. Elderly persons accounted for more than one third (33.7 %) of the total population in the central, inland Greek region of Evrytania as of 1 January 2015 — the highest share in the EU. Ourense in the north-west of Spain was the only other NUTS level 3 region in the EU where elderly persons accounted for upwards of 30 % of the total population, and was one of three Spanish regions among the 10 regions in the EU with the highest shares (28.5 % or higher) of elderly persons in their respective populations.

Population change

The EU-28’s population increased each and every year between 1 January 1960 and 1 January 2015, with overall growth of 101.7 million inhabitants, equivalent to an annualised increase of 0.4 %. Historically, population growth in the EU has largely reflected developments in natural population change (the total number of births minus the total number of deaths), as opposed to migratory patterns. A closer examination shows that natural population growth for an aggregate composed of the EU-28 Member States peaked in 1964, when 3.6 million more births than deaths were recorded. Thereafter, birth rates fell progressively and life expectancy increased gradually, resulting in a slowdown of the natural rate of population growth. By 2003, natural population growth for the EU-28 Member States was almost balanced, as the number of births exceeded the number of deaths by less than 100 000. Subsequently, the birth rate and natural population growth increased again somewhat in several EU Member States, although this pattern was generally reversed with the onset of the financial and economic crisis: between 2008 and 2013, as natural population change fell from an increase of 578 thousand to an increase of 82 thousand, although this rebounded to 191 thousand in 2014.

Tower Hamlets in eastern London and Ilfov — which surrounds the Romanian capital — recorded the highest population growth during 2014

Map 3 presents the crude rate of total population change in 2014: these changes result from the combined effects of natural change and net migration between 1 January 2014 and 1 January 2015. The population of the EU-28 rose by 1.3 million during this period, equivalent to 2.5 per 1 000 inhabitants. Among the 1 341 NUTS 3 regions for which data are shown in Map 3 (no data available for Mayotte, France), there were more regions in the EU reporting an increase in their number of inhabitants (806 regions) than those where the population declined (530 regions); there were five regions where the population remained unchanged.

The darkest shade of blue shows the 238 NUTS level 3 regions where the population grew, on average, by at least 8.0 per 1 000 inhabitants during 2014; among these there were 32 regions where population growth was at least 15.0 per 1 000 inhabitants. The highest growth was recorded for Tower Hamlets in London (33.0 per 1 000 inhabitants), followed by Ilfov (30.6 per 1 000 inhabitants), a region which surrounds the Romanian capital of Bucharest. A total of 13 of these 32 regions with the highest crude rates of population growth were in the United Kingdom, with four in Outer London and six in Inner London; nine regions were in Germany, none of which were in the capital city, Berlin, although the list did include Potsdam, Kreisfreie Stadt in neighbouring Brandenburg. Five more regions were in the capital city regions of Denmark, Ireland, Luxembourg, Austria and Sweden. The remaining regions included a second region in Austria (Innsbruck), the French overseas region of Guyane, two Spanish island regions (Fuerteventura and Eivissa, Formentera), as well as Ilfov.

Many regions with declining populations were in eastern and southern Member States

There were 17 NUTS level 3 regions where the population fell in 2014 by more than 15.0 per 1 000 inhabitants. These regions were mainly in Bulgaria (seven regions), Croatia (three regions) and Portugal (two regions), with one region each in Germany, Greece, Latvia, Lithuania and Romania. The biggest reduction in population among the NUTS level 3 regions (24.9 per 1 000 inhabitants) was registered in the Greek region of Kentrikos Tomeas Athinon, while Vidin in Bulgaria was the only other region to report that its population had declined by at least 20.0 per 1 000 inhabitants.

More broadly, looking at the 268 NUTS level 3 regions in the EU where the population fell by more than 4.0 per 1 000 inhabitants during 2014 (the darkest shade of orange in Map 3), these were mainly concentrated in several areas: the Baltic Member States; an arc in south-eastern Europe, starting in Croatia and moving through Hungary, Romania, Bulgaria and down into Greece; several regions on the Iberian peninsula; and many eastern German regions. Several other countries had a few regions where the population fell by more 4.0 per 1 000 inhabitants, including 22 regions that were spread across most of Italy.

Among the EFTA and candidate country regions, the highest variation in population growth was recorded across Turkish regions

During 2014, it was generally more common to observe population growth across the level 3 regions of the EFTA and candidate countries (national data for Albania and Serbia), as shown in Map 3, with a positive development registered in 115 regions, while only 25 regions recorded a decline in their number of inhabitants. Among the EFTA countries, the population grew in every region. In relative terms, the fastest population growth was recorded in Oslo (the capital of Norway) and in Freiburg (western Switzerland).

In the candidate countries there was a more mixed picture, with the population declining in Albania and Serbia (national data), half of the eight regions from the former Yugoslav Republic of Macedonia, and 19 Turkish regions, the majority of which were in central and north-eastern Turkey. Declining population numbers in these regions of Turkey could be contrasted with very high population growth rates in other parts of the country. Indeed, Turkey displayed the highest degree of variation in population change between level 3 regions, with the crude rate of population growth ranging from a low of -39.3 per 1 000 inhabitants in Çankiri (close to the capital of Ankara) to a high of 63.8 per 1 000 inhabitants in Bayburt (in the north-east). The considerable differences in population developments across Turkish regions can often be attributed to internal migratory patterns, with a general flow of migrants from eastern to western regions.

Since 1985 there has consistently been a net inflow of migrants to the EU-28 Member States

Overall population change results from the interaction of two components: natural population change and net migration plus statistical adjustment (hereafter simply referred to as net migration). These components can combine to reinforce population growth or population decline or they may cancel each other out to some extent when moving in opposite directions.

Historically, migratory patterns were relatively balanced during the 1960s and by 1970 there was a net outflow of 707 028 persons from the EU-28 Member States to other destinations around the globe; this was the highest number of net emigrants during the whole of the period 1961–2014. The next time there was a net outflow of migrants leaving the EU-28 Member States was between 1982 and 1984 (a recessionary period); thereafter, there were consistently more immigrants arriving in than emigrants leaving. From 1988 onwards, positive net migration exceeded half a million people each year, with the exceptions of 1991 and 1997, with net migration exceeding one million persons in 10 of the 27 years during the period 1988–2014. Net migration for the EU-28 Member States reached 1.8 million persons in 2003, after which the scale of population increases due to net migration slowed to a low of 712 000 persons in 2011. In 2013, net migration jumped to 1.7 million and remained above one million in 2014.

Net inward migration particularly high in many regions of Germany

Map 4 presents the crude rate of net migration for 2014, which averaged 2.2 per 1 000 inhabitants across the EU-28. There is a similarity between Maps 3 and 4, emphasising the close relationship between migratory patterns and overall population change, a development which was enhanced by the rate of natural population change being nearly balanced in many regions of the EU.

In 2014, the net inflow of migrants (from other regions of the same Member State, from other EU regions, or from non-member countries) was particularly concentrated across many parts of Germany. Among the 19 regions with net migration of 15.0 per 1 000 inhabitants or more, 12 were in Germany. Extending this to the 217 regions with net migration of at least 8.0 per 1 000 inhabitants (the darkest shade of blue in Map 4), the number of German regions increased to 147; while the United Kingdom (26 regions), France (11 regions), Austria (10 regions) and Sweden (9 regions) were also common destinations for migrants.

The highest net influx of migrants was registered in Ilfov in Romania, where the crude rate of net migration was 29.8 per 1 000 inhabitants. The next four highest rates of net migration were recorded in German regions — Landshut, Kreisfreie Stadt; Suhl, Kreisfreie Stadt; Leipzig, Kreisfreie Stadt; Gießen, Landkreis — where rates were between 21.8 and 23.9 per 1 000 inhabitants. Tower Hamlets in London was the only other NUTS 3 region with a crude rate of net migration above 20.0 per 1 000 inhabitants, with Luxembourg (19.9) and Frankfurt am Main, Kreisfreie Stadt (19.2) just below this level.

All four regions that compose the Greek capital experienced net emigration in 2014

There were 430 NUTS level 3 regions in the EU-28 where net migration in 2014 was negative (in other words, where more people left a region than arrived in it) and in 117 of these the crude rate was below -4.0 per 1 000 inhabitants. These were spread across Slovenia, Croatia, Hungary, Romania, Bulgaria, Greece and Cyprus (one region at this level of detail) in eastern and southern Europe, as well as the Baltic Member States in northern Europe, several regions on the Iberian peninsula, the Île de France and the neighbouring region of Champagne-Ardenne in France, and much of Ireland, as well as a handful of regions elsewhere. In amongst these regions were eight capital city regions, including all four regions that compose the Greek capital of Athens, one of the Inner London regions, Paris, Bucureşti and Cyprus. The biggest negative crude rates of net migration were recorded in the Irish Border region and one of the Greek capital regions, Kentrikos Tomeas Athinon, where the rate of net migration fell to -21.1 per 1 000 inhabitants.

SPOTLIGHT ON THE REGIONS

Border, Ireland

Dkit1 1024x768.jpg

The NUTS level 3 region in the EU with the lowest crude rate of net migration was Border in Ireland; in 2014, it had a crude rate of net migration (the difference between the immigration and emigration rate) of -21.1 per 1 000 inhabitants.

©: Scollonp

For the EFTA and candidate countries there were contrasting patterns in relation to net migratory patterns in 2014 (only national data available for Albania and Serbia). Nowhere was this more true than in Turkey, as there were 22 level 3 regions which recorded double-digit negative rates of net migration, with the lowest rate of -43.3 per 1 000 inhabitants in Çankiri (to the north-east of Ankara). By contrast, there were 11 Turkish level 3 regions where double-digit positive rates were recorded, peaking at 54.1 per 1 000 inhabitants in Bayburt (north-east Turkey). Otherwise, net migration was positive in each of the EFTA level 3 regions, peaking at 14.6 per 1 000 inhabitants in the western Swiss region of Freiburg.

Birth and fertility rates

Women in the EU are having fewer children, contributing to a slowdown of natural growth and even to negative natural change (more deaths than births): see an article on population projections for an overview of how demographic developments are projected to impact on the population of the EU’s regions.

This section presents information on regional crude birth rates (the ratio of the number of births to the average population, expressed per 1 000 inhabitants) and fertility rates (the mean number of children born per woman). The EU-28 crude birth rate was 10.1 births per 1 000 inhabitants in 2014. Across the EU Member States, the crude birth rate peaked at 14.6 births per 1 000 inhabitants in Ireland and was also relatively high in France (12.4 births), the United Kingdom (12.0 births) and Sweden (11.9 births). At the other end of the range, the crude birth rate was 10.0 births per 1 000 inhabitants or lower across much of eastern Europe (Bulgaria, Croatia, Hungary, Poland and Romania), southern Europe (Greece, Spain, Italy, Malta and Portugal), as well as in Germany and Austria.

Some of the highest crude birth rates in the EU were recorded in the capital regions of Belgium, Ireland, France and the United Kingdom

Figure 3 shows crude birth rates for NUTS level 2 regions in 2014. In all of the multi-regional EU Member States and non-member countries shown, the crude birth rate was above the national average in the capital city region. Some Member States reported very homogeneous regional crude birth rates, for example in the Czech Republic, Poland and Hungary. Others were more heterogeneous, often because of just one or a few regions with particularly high rates: in Belgium, the capital city Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest was the only region with a crude birth rate above the national average, while the outlying regions of Ciudad Autónoma de Melilla and Ciudad Autónoma de Ceuta in Spain, and Guyane and La Réunion in France reported rates that were notably higher than those recorded in any of the other regions in these Member States. In fact, the three highest crude birth rates among the EU’s regions were registered in Guyane, Ciudad Autónoma de Melilla and La Réunion, followed by three capital city regions: Inner London - East, Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest and Île de France, all of which had rates of 15.0 births per 1 000 inhabitants or higher, as did Outer London - West and North West.

The five lowest crude birth rates (less than 7.0 births per 1 000 inhabitants in 2014) were concentrated in southern Member States, two each in Italy and Portugal and one in Spain. The lowest rate was recorded in north-western Spain in the Principado de Asturias (6.3 births per 1 000 inhabitants).

Across the level 2 regions of the EFTA countries, crude birth rates were generally within the range of 10.0–15.0 births per 1 000 inhabitants in 2014. The only exceptions were Hedmark og Oppland (south-eastern Norway) and three regions from Switzerland — Espace Mittelland, Ostschweiz and Ticino — in all four of these the crude birth rate was below 10.0 births per 1 000 inhabitants.

By contrast, crude birth rates were within the range of 10.0–15.0 births per 1 000 inhabitants in the candidate countries (national data for Albania and Serbia), with the exception of 14 level 2 regions in Turkey where the crude birth rate was higher. The rate peaked at a value of 30.8 births per 1 000 inhabitants in the southern Turkish region of Şanliurfa, Diyarbakir.

Fertility rates fell in the first decade of the 21st century

The total fertility rate was decreasing in the EU-28 at the start of the century. In 2001 and 2002, it was 1.46 live births per woman, but it recovered, climbing to 1.62 by 2010, before dipping again to 1.54 by 2013 and recovering to 1.58 in 2014. In developed parts of the world, a total fertility rate of 2.10 live births per woman is considered to be the natural replacement rate, in other words, the level at which the size of the population would remain stable, in the long-run, if there were no inward or outward migration.

The highest fertility rate across the EU Member States in 2014 was recorded in France (2.01 live births per woman), followed by Ireland (1.94), Sweden (1.88) and the United Kingdom (1.81). Fertility rates were often higher in those Member States where the family as a unit was relatively weak (a low proportion of people being married and a high proportion of births outside marriage), couple instability relatively common (relatively high divorce rates), and women’s labour market participation was high. Fertility rates were 1.50 live births per woman or lower in 13 of the EU Member States; the lowest rate was recorded in Portugal (1.23 live births per woman).

Differences in regional fertility may be linked to a range of factors, among others: the socio-economic structure of the population (for example, educational attainment, occupational status, income or age); place of residence (for example, the availability of infrastructure, childcare facilities, or the housing market); or cultural factors (for example, religious beliefs and customs, attitudes to giving birth outside of marriage, or attitudes to contraception). The distribution of fertility rates is shown in Figure 4 for level 2 regions: like Figure 3 it appears very homogeneous, as most regions within the same EU Member State rarely displayed rates that were far from their national average in 2014. The exceptions to this rule again included the outlying Spanish region of the Ciudad Autónoma de Melilla, and the French overseas regions of Guyane, La Réunion, Guadeloupe and Martinique; these were the only NUTS level 2 regions in 2014 to record total fertility rates that were above the natural replacement rate of 2.10.

An analysis for EFTA countries confirms that fertility rates for level 2 regions were consistently below the natural replacement rate. The same was true in the candidate countries (national data for Albania and Serbia), except in Turkey. There was a rough divide in Turkey between western regions (with relatively low fertility rates) and eastern regions (with much higher rates): for example, the lowest fertility rate (1.59 live births per woman) was registered for Zonguldak, Karabük, Bartin on the Black Sea coast, while the highest rate was recorded for Şanliurfa, Diyarbakir (3.91 live births per woman) — this region also recorded the highest crude birth rate in Turkey (see above).

Highest fertility rates mainly in French and British regions

Map 5 provides a more detailed analysis of the same indicator, showing the fertility rate for NUTS 3 regions. The French overseas region of Guyane and the Spanish outlying territory of Ciudad Autónoma de Melilla reported the highest rates in 2014, with 3.50 and 2.70 live births per woman respectively. These were followed by Seine-Saint-Denis (near to the French capital) and another French overseas region, La Réunion. A total of 34 NUTS level 3 regions recorded fertility rates in excess of 2.10, with more than half of these (20 in total) in France and more than a quarter (9) in the United Kingdom. A similar picture can be seen for the 186 NUTS level 3 regions with a fertility rate of 1.90 or higher (the darkest shade of orange in Map 5), as just over three quarters of these regions were in France or the United Kingdom, while this set of regions also included six of the eight Irish regions and 10 of the 21 Swedish regions.

SPOTLIGHT ON THE REGIONS

Douro, Portugal

1280px-Douro.jpg

A fertility rate of 2.10 live births per woman is considered to be the natural replacement rate in developed world countries; in other words, the level at which the size of the population would remain stable, in the long-run, if there were no inward or outward migration. Fertility rates across EU regions are generally much lower: for example, Douro was one of four NUTS level 3 regions in Portugal to record a fertility rate less than 1.0 live births per woman in 2014.

©: Aires Almeida

By contrast, the lowest fertility rates (below 1.35) were mainly found in Germany as well as eastern and southern Member States, in particular in Cyprus (one region at this level of detail), Portugal (22 out of 25 regions), Spain (37 out of 59 regions), Slovakia (five out of eight regions) and Poland (42 out of 72 regions), and to a lesser extent in Greece and Italy.

In 2014, none of the level 3 regions in the EFTA countries reported a fertility rate above 2.10, however four Norwegian regions, one Swiss region and one Icelandic region each reporting fertility rates that were above 1.90, with Landsbyggð in Iceland reporting the highest rate (2.03).

Among the candidate countries (national data for Albania and Serbia), three of the eight regions in the former Yugoslav Republic of Macedonia reported fertility rates below 1.35 in 2014. By contrast, in Turkey there were 29 regions where the fertility rate exceeded 2.10, and a further 13 regions with a rate of 1.90 or higher. The two highest rates in 2014 were recorded in the western Turkish regions of Şanliurfa (4.52) and Sirnak (4.22). There was a sharp contrast between these relatively high fertility rates and those recorded in most of the western Turkish regions, where fertility rates were generally in the range of 1.5–1.9 live births per woman (more in line with the rates recorded across the EU).

Death rates

There were 4.94 million deaths across the whole of the EU-28 in 2014, which was 1.1 % fewer than in 2013. The EU-28’s crude death rate was 9.7 deaths per 1 000 inhabitants in 2014, ranging from 15.1 in Bulgaria, 14.3 in Latvia and 13.7 in Lithuania, to less than 8.0 deaths per 1 000 inhabitants in Malta, Luxembourg, Ireland and Cyprus.

The crude death rate generally reflects the population structure (elderly persons are more likely to die) as well as the likelihood of catching/contracting a specific illness/disease or dying from an external cause; note that regional statistics on some causes of deaths — from diseases of the circulatory system and from cancer — is provided in an article on health.

Figure 5 displays how death rates varied among level 2 regions. This can be compared with Figure 3 which shows a similar analysis for the crude birth rate and it can be seen that, in general, the crude death rate varied more across regions than the crude birth rate. The Czech Republic reported the most homogeneous death rates among its regions, while there was a much wider degree of dispersion in Spain, France and the United Kingdom; death rates in the Turkish regions were also relatively heterogeneous. In nearly all multi-region Member States, the crude death rate of the capital city region was below the national average, with Croatia, Poland and Slovenia the only exceptions to this rule; this was also the case in Switzerland.

In 2014, four Bulgarian regions recorded the highest crude death rates in the EU, ranging from 14.5 to 19.8 deaths per 1 000 inhabitants. The highest crude death rate was recorded in the northern region of Severozapaden, which also recorded the lowest level of life expectancy. The lowest crude death rate was in the French overseas region of Guyane, with a rate of 3.1 deaths per 1 000 inhabitants; an equally low death rate was reported for the Turkish region of Mardin, Batman, Sirnak, Siirt. Other EU regions with low death rates included Inner London - East (4.3) and Inner London - West (4.7). Several other capital city regions had low crude death rates, for example those in France, Ireland, Spain, Luxembourg (one region at this level of detail), Sweden and Finland.

Infant mortality

Significant gains in life expectancy across the EU in recent years have not only been due to people living increasingly long lives, but may also be attributed to a reduction in infant mortality rates. Around 19 100 children died before reaching one year of age in the EU-28 in 2014. This was equivalent to an infant mortality rate of 3.7 deaths per 1 000 live births, compared with a rate of 5.3 a decade earlier and 32.8 half a century earlier.

Figure 6 shows the range in infant mortality rates among NUTS level 2 regions in 2014. EU Member States with particularly heterogeneous regional infant mortality rates included Slovakia, Finland, France and Austria; the relatively high heterogeneity in Finland was due to the particular situation in the island region of Åland where no child aged less than one year died (thus, the infant mortality rate was 0.0). Among the EU regions, the lowest rate, apart from that in Åland, was 0.7 in the western Austrian region of Vorarlberg. By contrast, rates of at least 10.0 deaths per 1 000 live births were recorded in three regions in eastern Europe: Sud-Est (Romania), Yugoiztochen (Bulgaria) and Východné Slovensko (Slovakia). Five of the Member States with more than one region reported an infant mortality rate for their capital city region that was above the national average: Croatia, Portugal, Spain, the Netherlands and Austria; this was also the situation in Norway.

In the EFTA countries, infant mortality rates in Iceland, Liechtenstein and all seven level 2 regions in Norway were below the EU-28 average. On average, Switzerland recorded slightly higher infant mortality rates, although the Région lémanique, Espace Mittelland and Ticino also recorded rates that were below the EU-28 average.

Higher infant mortality rates were recorded in the candidate countries (national data for Albania and Serbia), ranging from 4.9 deaths per 1 000 live births in Montenegro (a single region at this level of detail) to 11.1 deaths per 1 000 live births in Turkey. There was a wide range in regional infant mortality rates in Turkey, from a low of 7.0 deaths per 1 000 live births in the capital city region of Ankara, to a high of 16.9 deaths per 1 000 live births in the southern region of Gaziantep, Adiyaman, Kilis.

Data sources and availability

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. This data may be used for a wide range of planning, monitoring and evaluating actions across a number of important socio-economic policy areas, for example, to:

  • analyse population ageing and its effects on sustainability and welfare;
  • evaluate the economic impact of demographic change;
  • calculate per inhabitant ratios and indicators — such as regional gross domestic product per capita, which may be used to allocate structural funds to economically less advantaged regions;
  • develop and monitor immigration and asylum systems.

The legal basis for the collection of population statistics is provided by European Parliament and Council Regulation (EU) No 1260/2013 on European demographic statistics and by its implementing Regulation (EU) No 205/2014. European Parliament and Council Regulation (EC) No 862/2007 legislates for the collection of Community statistics on migration and international protection, together with implementing Regulation (EU) No 351/2010.

For more information: please refer to the dedicated section on population projections on Eurostat's website.

Statistics on population change and the structure of population are increasingly used to support policymaking and to provide the opportunity to monitor demographic behaviour within a political, economic, social or cultural context. The European Parliament passed a resolution on ‘Demographic change and its consequences for the future of the EU’s cohesion policy’ (2013/C 153 E/02) which underlined that demographic developments in the regions should be statistically measured and stressed that demographic change should be considered as a cross-cutting objective in future cohesion policy.

NUTS

The data presented in this article are based exclusively on the 2013 version of NUTS.

Indicator definitions

Life expectancy at birth is the mean number of years that a new born child can expect to live if subjected throughout his or her life to current mortality conditions.

Population change is the difference in the size of a population between the end and the beginning of a period (for example, one calendar year). A positive population change is referred to as population growth, while a negative population change is referred to as population decline. Population change consists of two components.

  • Natural change which is calculated as the difference between the number of live births and the number of deaths. Positive natural change, also known as natural increase, occurs when live births outnumber deaths. Negative natural change, also known as natural decrease, occurs when live births are less numerous than deaths.
  • Net migration plus statistical adjustment, which is calculated as the difference between the total change in the population and natural change; the statistics on net migration are therefore affected by all the statistical inaccuracies in the two components of this equation, especially population change. Net migration plus statistical adjustment may cover, besides the difference between inward and outward migration, other changes observed in the population figures between 1 January for two consecutive years which cannot be attributed to births, deaths, immigration or emigration.

Crude rates of change are calculated for total population change, natural population change and net migration plus statistical adjustment. In all cases, the level of change during the year is compared with the average population of the area in question in the same year and the resulting ratio is expressed per 1 000 inhabitants.

Crude rates of vital demographic events (births and deaths) are defined as the ratio of the number of demographic events to the average population of the region in the same year, again expressed per 1 000 inhabitants.

The total fertility rate is defined as the average number of children that would be born to a woman during her lifetime if she were to pass through her childbearing years conforming to the age-specific fertility rates that have been measured in a given year.

The infant mortality rate is defined as the ratio of the number of infant (children aged less than one year) deaths to the number of live births of the region in the same year, it is expressed per 1 000 live births.

Context

Demographic changes in the EU are likely be of considerable importance in the coming decades as the vast majority of models concerning future population trends suggest that the EU’s population will continue to age, due to consistently low fertility levels and extended longevity.

Although migration plays an important role in the population dynamics of EU Member States, it is unlikely that migration alone will reverse the ongoing trend of population ageing experienced in many parts of the EU.

The social and economic consequences associated with population ageing are likely to have profound implications across Europe, both nationally and regionally. For example, low fertility rates will lead to a reduction in the number of students in education, there will be fewer working age persons to support the remainder of the population, and a higher proportion of elderly persons (some of whom will require additional infrastructure, healthcare services and adapted housing). These structural demographic changes could impact on the capacity of governments to raise tax revenue, balance their own finances, or provide adequate pensions and healthcare services.

Those regions projected to face the greatest demographic challenges include peripheral, rural and post-industrial regions, where the population is likely to decline. The territorial dimension of demographic change is seen most notably through:

  • an east–west effect, whereby many of the Member States that have joined the EU since 2004 are still playing catch-up;
  • a north–south effect, whereby there are often considerable differences between Mediterranean regions and more temperate regions in the north and west of the EU;
  • an urban–rural split, with the majority of urban regions continuing to report population growth, while the number of persons resident in many rural areas is declining;
  • a capital region effect, as capitals and some of their surrounding regions (for example, around the EU’s two global metropolises of Paris and London) display a ‘pull effect’ associated with increased employment opportunities;
  • several examples of regional disparities at a national level, which have the potential to impact on regional competitiveness and cohesion, for example, in Germany and Turkey (between those regions in the east and the west), or in France, Italy and the United Kingdom (between regions in the north and those in the south).

Policy development

Concerned by future demographic developments, it is unsurprising that policymakers have addressed a range of issues. The European Commission adopted a Communication titled ‘The demographic future of Europe — from challenge to opportunity’ (COM(2006) 571 final), which highlighted five key policy responses:

  • promoting demographic renewal through better conditions for families and an improvement in the reconciliation of working and family life;
  • promoting employment, through more jobs and longer working lives of better quality;
  • a more productive and dynamic EU, raising productivity and economic performance through investing in education and research;
  • receiving and integrating migrants in the EU;
  • ensuring sustainable public finances to guarantee adequate pensions, social security, health and long-term care.

Europe 2020

Furthermore, most of the seven flagship initiatives of the Europe 2020 strategy also touch upon demographic challenges, and in particular demographic ageing. The innovation union flagship initiative provides an opportunity to bring together public and private actors at various territorial levels to tackle a variety of challenges, and in 2011 a European innovation partnership on active and healthy ageing was launched: its aim is to raise by two years the average healthy lifespan of Europeans by 2020. Another flagship initiative, the digital agenda, promotes digital literacy and accessibility for older members of society, while an EU agenda for new skills and jobs supports longer working lives through lifelong learning and the promotion of healthy and active ageing. Finally, the European platform against poverty and social exclusion addresses the adequacy and sustainability of social protection and pension systems and the need to ensure adequate income support in old age and access to healthcare systems.

Migration

In May 2015, the European Commission presented a European agenda on migration outlining immediate measures to respond to the influx of migrants and asylum seekers from across the Mediterranean, as well as providing a range of policy options for the longer-term management of migration into the EU. The agenda recognises that there is a need to respond to humanitarian challenges, but seeks to increase the number of returns among irregular migrants, while providing for the continued right to seek asylum.

The agenda sets out four levels of action for EU migration policy, namely:

  • a new policy on legal migration — maintaining the EU as an attractive destination for migrants, notably by reprioritising migrant integration policies, managing migration through dialogue and partnerships with non-member countries, and modernising the blue card scheme for highly educated persons from outside the EU;
  • reducing incentives for irregular migration — through a strengthening of the role of Frontex, especially in relation to migrant returns;
  • border management — helping to strengthen the capacity of non-member countries to manage their borders;
  • a strong common asylum policy — to ensure a full and coherent implementation of the common European asylum system.

The migrant crisis during much of 2015 and the first quarter of 2016 resulted in the European Commission announcing in March 2016 proposals for an emergency assistance instrument within the EU. The plan would allocate some EUR 700 million of aid (over a period of three years) to help avert a humanitarian crisis and to be able to deliver more rapidly food, shelter and healthcare, as required by refugees within the EU.

See also

Further Eurostat information

Data visualisation

Publications

Main tables

Regional demographic statistics (t_reg_dem)
Crude rates of population change by NUTS 2 region (tgs00099)
Population on 1 January by NUTS 2 region (tgs00096)

Database

Regional demographic statistics (reg_dem)
Population and area (reg_dempoar)
Fertility (reg_demfer)
Mortality (reg_demmor)
Regional data (demopreg)

Dedicated section

Methodology / Metadata

  • Population (ESMS metadata file — demo_pop_esms)

Source data for tables, figures and maps (MS Excel)

External links