Living conditions statistics at regional level

Data extracted in May 2025.

Planned article update: September 2026.

Highlights

In 2024, Guyane (France), Calabria, Campania (both Italy), Ciudad de Melilla and Ciudad de Ceuta (both Spain), the at risk of poverty or social exclusion rate was more than twice as high as the EU average of 21.0%.

In 2024, 7.9% of people in the EU lived in a household with very low work intensity: the lowest shares among EU regions were in the capital regions of Bucureşti-Ilfov in Romania (0.6%), Bratislavský kraj in Slovakia (0.8%) and Warszawski stołeczny in Poland (1.1%).

Source: Eurostat (ilc_peps11n) and (ilc_peps01n)

By global standards, most people living in the European Union (EU) enjoy relatively high standards of living. This reflects the EU’s high income/wealth levels and its network of established social protection systems that provide a safety net for many less fortunate people. Nevertheless, 93.3 million people in the EU – or 21.0% of the population – were at risk of poverty or social exclusion in 2024. Among EU regions (NUTS level 2), the French outermost region of Guyane recorded the highest rate, at 59.5%. It was the only region in the EU where more than half of the population faced the risk of poverty or social exclusion. The next highest rate was observed in the southern Italian region of Calabria, at 48.8% (see the infographic above for more information).

Sociodemographic characteristics like age, educational attainment, sex and country of birth / citizenship can influence an individual’s living conditions. Wider societal developments, such as the impact of globalisation, coupled with unexpected shocks – for example, the global financial and economic crisis, the COVID-19 crisis, the impact of Russia’s war of aggression against Ukraine or the cost-of-living crisis – can also have a considerable influence. In some cases, these events can rapidly undo more gradual, long-term reductions in inequality.

Since late 2021, there has been a considerable increase in the cost of living in the EU. Some of the most rapid increases in prices were experienced for goods like energy and food. Price increases for these goods often disproportionately impact the poorest individuals in society, as they tend to allocate a larger proportion of their disposable income to such ‘essential goods’. The EU’s annual inflation rate rose from 0.7% in 2020 to 9.2% by 2022, before falling back to 6.4% in 2023 and then 2.6% in 2024.

People at risk of poverty or social exclusion

Absolute poverty is a lack of basic human needs, for example, food, shelter, water, sanitation facilities, health or education; in other words, a situation where a household’s income is insufficient to afford the basic necessities of life. By contrast, relative poverty concerns a situation where a household’s income is below a certain percentage of the median household income of the country where they live.

More about the data: at risk of poverty or social exclusion

The indicator for people at risk of poverty or social exclusion is based on measures of relative poverty, severe material and social deprivation, and quasi-joblessness. The number/rate of people at risk of poverty or social exclusion combines these criteria to cover people who are in at least 1 of the following situations:

at risk of poverty – people with an equivalised disposable income (after social transfers) below the at-risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income
facing severe material and social deprivation – people unable to afford at least 7 out of 13 deprivation items (6 related to the individual and 7 related to the household) that are considered desirable, or even necessary, to lead an adequate quality of life
living in a household with very low work intensity – where adults aged 18 to 64 years (excluding students aged 18 to 24 years and retired people under the age of 65 years) worked for 20% or less of their combined potential working time during the previous 12 months.

Intersections for the at risk of poverty or social exclusion rate
(million, EU, 2024)
Source: Eurostat (ilc_pees01n)

For EU statistics on income and living conditions (EU-SILC):

the reference period for statistics on income generally refers to the calendar year before the year in which the survey took place
data for the Finnish regions of Länsi-Suomi and Åland are aggregated (the same value is shown for both regions)
due to changes in regional boundaries, data are only available for reference year 2024 (not any earlier years) for Utrecht, Zuid-Holland (both the Netherlands), Centro, Grande Lisboa, Península de Setúbal, Alentejo and Oeste e Vale do Tejo (all Portugal)
there is no information for Mayotte in France
an earlier reference year is sometimes used for individual regions/countries (see specific footnotes under each map/figure for more information).

On 4 March 2021, the European Commission set out its ambition for a stronger social EU to focus on education, skills and jobs, paving the way for a fair, inclusive and resilient socioeconomic recovery from the COVID-19 crisis, while fighting discrimination, tackling poverty and alleviating the risk of exclusion for vulnerable groups.

The European Pillar of Social Rights Action Plan outlines a set of commitments from policymakers and provides 3 key targets for monitoring progress; 1 of which is to reduce, between 2019 and 2030, the number of people in the EU at risk of poverty or social exclusion by at least 15 million people (of which, at least 5 million should be children).

More than 1 in 5 of the EU’s population was at risk of poverty or social exclusion in 2024

Map 1 shows the regional distribution of people at risk of poverty or social exclusion across NUTS level 2 regions. In 2024, the regional distribution of this indicator was somewhat skewed, as less than 40% of all EU regions (93 out of the 243 for which data are available) recorded at risk of poverty or social exclusion rates that were higher than the EU average, 4 regions had the same rate, while 146 regions had rates that were lower.

In 2024, there were 25 NUTS level 2 regions where at least 33.0% of the population was at risk of poverty or social exclusion (these regions are shown in the darkest shade of blue in Map 1). The highest risks were principally observed in southern, eastern and outermost regions of the EU:

the 25 regions were concentrated in Greece (5 regions), Bulgaria, Spain, Italy (4 regions each), as well as Romania and the outermost regions of France (3 regions each)
this group also included 2 predominantly urban regions in western EU countries – the capital region of Belgium (Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest) and Bremen in Germany.

In 2024, there were 5 NUTS level 2 regions across the EU that reported at risk of poverty or social exclusion rates that was more than double the EU average (21.0%). All 5 were located either in the EU’s southern countries or its outermost regions, where social and economic challenges tend to be more pronounced.

The highest rate was in Guyane (France), where 59.5% of the population was at risk.
In southern Italy, Calabria had a rate of 48.8%, while the neighbouring region of Campania also had a relatively high rate, at 43.5%.
The Spanish autonomous cities of Melilla (44.5%) and Ceuta (42.2%) completed this group.

At the other end of the distribution, there were 26 NUTS level 2 regions where less than 12.5% of the population was at risk of poverty or social exclusion in 2024 (these regions are shown in a light yellow shade in Map 1). This group included:

7 regions from northern and central Italy, including Provincia Autonoma di Bolzano/Bozen (6.6%), which had the lowest at risk of poverty or social exclusion rate in the EU
6 out of the 8 regions of Czechia, including Jihozápad (8.8%), which had the 3rd lowest rate in the EU
3 regions from Vlaams Gewest in northern Belgium
3 regions from Austria
2 regions from Poland, including the capital region Warszawski stołeczny
the capital regions of Croatia, Romania, Slovenia and Slovakia; the last of these, Bratislavský kraj, had the 2nd lowest rate in the EU (8.6%)
the north-western Hungarian region of Közép-Dunántúl.

In 2024, people living in the capital regions of eastern EU countries generally faced a lower risk of poverty or social exclusion compared with those living elsewhere. For example, in Romania, the national at risk of poverty or social exclusion rate (27.9%) was 2.3 times as high as the rate recorded in the capital region of Bucureşti-Ilfov (12.0%). A similar pattern was observed in Slovakia, Croatia, Poland, Hungary and Bulgaria, where the national rate was at least 50% higher than in the capital region. This pattern was also present – although generally less pronounced – in several other EU countries: Lithuania, Slovenia, Spain, Portugal, Greece, Sweden, Finland, Ireland, Denmark and France.

By contrast, the situation was reversed in several EU countries. In Belgium, the rate recorded in the capital region was more than double the national average, while in Austria it was 1.7 times as high. The capital regions of 4 more EU countries – Italy, Czechia, the Netherlands and Germany – also recorded somewhat higher risks of poverty or social exclusion compared with their respective national averages.

Map 1: People at risk of poverty or social exclusion
Source: Eurostat (ilc_peps11n) and (ilc_peps01n)

Figure 1 highlights the NUTS level 2 regions with the highest and lowest at risk of poverty or social exclusion rates in 2024. It also presents information on the regions that recorded the biggest increases and decreases in their rates between 2022 and 2024. Across the EU, the at risk of poverty or social exclusion rate fell 0.6 percentage points from 21.6% to 21.0%. Looking more closely at the 236 regions for which data are available, the at risk of poverty or social exclusion rate fell in 134 regions, remained unchanged in 2 regions and increased in 100 regions.

There were 3 NUTS level 2 regions where the risk of poverty or social exclusion increased by a considerable margin between 2022 and 2024. The French outermost region of Guyane recorded the largest increase, up 10.3 percentage points (from 49.2% to 59.5%). The other 2 regions with notable increases were Trier (Germany) and Ionia Nisia (Greece), where rates rose by 10.0 and 9.6 points, respectively. There were 6 more regions across the EU that reported increases of at least 5.0 points:

Rheinhessen-Pfalz in Germany – a neighbouring region to Trier (up 6.5 points)
Dytiki Makedonia and Voreio Aigaio in Greece (up 6.5 points and 5.4 points, respectively)
Calabria in Italy (up 6.0 points)
Dél-Alföld in Hungary (up 5.3 points)
Nordjylland in Denmark (up 5.2 points).

The regions with the largest falls in their at risk of poverty or social exclusion rates were all located in eastern or southern EU countries. The Italian regions of Liguria, Abruzzo and Molise experienced the biggest declines, as their rates fell between 2022 and 2024 by 10.5, 10.2 and 9.7 percentage points, respectively. There were 8 more regions across the EU that reported decreases of at least 7.0 percentage points:

6 of the 8 Romanian regions – the exceptions being Nord-Vest and Nord-Est (where rates also fell, although at a more modest pace) – with the largest fall in Sud-Vest Oltenia (down 9.6 points)
the Portuguese regions of Região Autónoma da Madeira (down 7.3 points) and Algarve (down 7.0 points).

Figure 1: People at risk of poverty or social exclusion
Source: Eurostat (ilc_peps11n) and (ilc_peps01n)

People at risk of poverty

In 2024, 72.1 million people in the EU were at risk of poverty (after social transfers), representing 16.2% of the population. Some of the highest regional rates for people at risk of poverty were concentrated in southern, eastern and Baltic countries. By contrast, some of the lowest rates were recorded in a cluster of regions stretching from central/northern Italy through Austria and into southern Germany, Hungary, Czechia and Poland. Another cluster of regions with low rates was found in northern Belgium and the Netherlands. Several capital regions also recorded relatively low rates.

More about the data: at-risk-of-poverty rate

The at-risk-of-poverty rate (after social transfers) is 1 of 3 criteria used to identify people who are at risk of poverty or social exclusion. It provides information on the share of the population with a level of income that is below a threshold set relative to the median income.

The at-risk-of-poverty rate identifies the proportion of the population who live in a household with an annual equivalised disposable income that is below 60% of the national median. While the threshold is the same for all EU countries in percentage terms (60%), it varies in monetary terms as median incomes differ – sometimes considerably – between countries.

Map 2 shows the at-risk-of-poverty rate for NUTS level 2 regions. In 2024, the regional distribution of this rate was relatively skewed: there were 95 regions that recorded a rate equal to or above the EU average of 16.2%, while the remaining 148 regions had lower than average rates.

In 2024, the French outermost region of Guyane reported the highest at-risk-of-poverty rate

The French outermost region of Guyane (53.3%), the autonomous Spanish cities of Melilla (41.4%) and Ceuta (34.6%), and the southern Italian regions of Calabria (37.2%), Campania (35.5%) and Sicilia (35.3%) recorded the highest at-risk-of-poverty rates among NUTS level 2 regions. These were the only regions across the EU where more than 1 in 3 of the population was at risk of poverty in 2024. An additional 25 regions had at-risk-of-poverty rates covering between a quarter and a third of their populations. These 31 regions with the highest at risk of poverty rates are shown in the darkest shade of blue in Map 2.

… while the lowest rate was recorded in the Romanian capital region of Bucureşti-Ilfov

By contrast, at the other end of the distribution, there were 27 NUTS level 2 regions where the at-risk-of-poverty rate was below 10.0% in 2024 (as shown by the lightest shade of yellow). Many of these regions were predominantly urban regions (including capitals) or regions with lower unemployment rates, higher standards of living and/or in countries characterised by strong social protection systems. This group of 27 included:

5 regions each from Belgium, Czechia and Italy
2 regions each from Hungary, Austria and Poland
the capital region from Croatia, Romania, Slovakia and Finland
a single region from each of Denmark and Spain.

These 27 regions with a relatively low risk of poverty in 2024 included 7 capital regions, all but 1 from eastern EU countries: Bucureşti-Ilfov in Romania (3.7%), Bratislavský kraj in Slovakia (7.0%), Praha in Czechia (7.5%), Warszawski stołeczny in Poland (8.0%), Budapest in Hungary (9.5%) and Grad Zagreb in Croatia (9.7%); the 7th was Helsinki-Uusimaa in Finland (9.4%).

The Romanian capital region of Bucureşti-Ilfov had, by far, the lowest at-risk-of-poverty rate (3.7% in 2024), while rates below 7.0% were also observed in:

the northern Italian regions of Provincia Autonoma di Bolzano/Bozen and Provincia Autonoma di Trento
the northern Belgian regions of Prov. Oost-Vlaanderen, Prov. Vlaams-Brabant and Prov. West-Vlaanderen
Burgenland in eastern Austria.

Across several EU countries – for example, Romania, Italy, France and Belgium – there was a considerable degree of inter-regional variation for at-risk-of-poverty rates.

In Romania, the at-risk-of-poverty rate in Sud-Vest Oltenia was 8.1 times as high as in the capital region of Bucureşti-Ilfov.
In Italy, the rate in the southern region of Calabria was 6.3 times as high as in the northern region of Provincia Autonoma di Bolzano/Bozen.
In France, the rate in the outermost region of Guyane was 5.0 times as high as in the western region of Bretagne.
In Belgium, the rate in the capital region of Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest was 4.6 times as high as in Prov. Oost-Vlaanderen.

Map 2: At-risk-of-poverty rate
Source: Eurostat (ilc_li41) and (ilc_li02)

In 2024, the redistributive impact of social transfers reduced the risk of monetary poverty across the EU from 24.7% to 16.2%

More about the data: social transfers

The at-risk-of-poverty rate before social transfers measures a hypothetical situation where social transfers are absent; pensions, such as old-age and survivors’ (widows’ and widowers’) benefits, are counted as income (before social transfers) and not as social transfers.

It is possible to assess the impact and redistributive effects of welfare policies by comparing at-risk-of-poverty rates before and after social transfers. Such transfers cover assistance that is given by central, state or local institutional units and include, among other types of transfers, unemployment benefits, sickness and invalidity benefits, housing allowances, social assistance and tax rebates.

Figure 2 illustrates how the redistributive impact of social transfers reduces the risk of monetary poverty, reflecting, among other factors, historical, political, economic and cultural influences. In 2024, the EU’s at-risk-of-poverty rate before social transfers was 24.7%; this was 8.5 percentage points lower, at 16.2%, after social transfers.

Figure 2 is split into 2 parts: the left-hand side presents the EU regions with the highest and lowest at-risk-of-poverty rates before social transfers and the right-hand side presents similar information after social transfers. In 2024, there were 2 NUTS level 2 regions where more than half of the population was at risk of poverty before social transfers:

the French outermost region of Guyane (64.3%)
the southern Italian region of Campania (52.8%).

The other 9 regions in the EU where, in 2024, more than 40.0% of the population was at risk of poverty before social transfers were:

2 more outermost regions in France – La Réunion and Guadeloupe
3 more regions in southern Italy – Calabria, Sicilia and Puglia
the Spanish regions of Ciudad de Melilla and Ciudad de Ceuta
the capital region of Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest (Belgium)
Bremen (Germany).

At the lower end of the distribution, there were 2 NUTS level 2 regions where, in 2024, less than 10.0% of the population faced the risk of monetary poverty before social transfers:

the Romanian capital region of Bucureşti-Ilfov (5.8%)
the northern Italian region of Provincia Autonoma di Bolzano/Bozen (7.1%).

Relatively low at-risk-of-poverty rates before social transfers were also recorded in several other capital regions in eastern EU countries:

Bratislavský kraj in Slovakia (10.2%)
Praha in Czechia (11.4%)
Budapest in Hungary (12.1%)
Grad Zagreb in Croatia (12.3%).

The right-hand side of Figure 2 shows the regions with the highest and lowest at-risk-of-poverty rates after social transfers. Taking account of the redistributive impact of social transfers, Guyane was the only region in the EU where more than half of the population continued to be at risk of monetary poverty in 2024, while Ciudad de Melilla was the only other region where this risk affected more than 40.0% of the population. There were 6 other regions where the at-risk-of-poverty rate after social transfers was more than twice as high as the EU average, namely:

Calabria, Campania and Sicilia (Italy)
Ciudad de Ceuta (Spain)
Guadeloupe and La Réunion (France).

Across many regions in western and northern EU countries, it was common for social transfers to markedly reduce the risk of poverty. In 2024, this risk was reduced by at least 8.5 percentage points – the EU average – in:

every region of Belgium, Denmark, Ireland and Finland
24 of the 26 regions of France (the exceptions being the eastern regions of Franche-Comté and Alsace)
6 of the 8 regions of Sweden (the exceptions being the capital region of Stockholm and Mellersta Norrland)
a similar pattern was also observed in Estonia.

In some cases, the redistributive impact of social transfers was considerable. In 2024, the at-risk-of-poverty rate was reduced by at least 14.0 percentage points in:

several regions of Belgium – Prov. Hainaut (where the at-risk-of-poverty rate was 20.5 points lower after social transfers, the largest reduction recorded among EU regions), Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest (18.3 points lower), Prov. Luxembourg (14.8 points lower) and Prov. Liège (14.0 points lower)
the southern Italian regions of Campania (17.3 points lower) and Abruzzo (17.0 points lower)
the French outermost region of La Réunion (15.9 points lower)
the German region of Bremen (15.3 points lower)
the Irish region of Southern (15.2 points lower)
the Danish regions of Nordjylland (14.6 points lower) and Midtjylland (14.0 points lower).

In addition to the 11 regions mentioned above, a further 104 NUTS level 2 regions across the EU recorded a fall of at least an 8.5 percentage point fall in their at-risk-of-poverty rates due to social transfers – matching or exceeding the average reduction observed across the whole of the EU.

At the other end of the scale, there were 31 NUTS level 2 regions in the EU where the redistributive impact of social transfers reduced the at-risk-of-poverty rate by less than 5.0 percentage points in 2024. These regions were principally concentrated in Greece, northern and central Italy, Portugal, Romania and Spain. In other countries, this group included the capital regions of Hungary, Croatia, Slovakia, Czechia and Lithuania.

Figure 2: At-risk-of-poverty rate before and after social transfers
Source: Eurostat (ilc_li10_r), (ilc_li41), (ilc_li10) and (ilc_li02)

Severe material and social deprivation, and economic strain

The severe material and social deprivation rate measures the share of people whose living conditions are severely constrained by an enforced lack of items that are necessary and desirable to lead an adequate life. It reflects enforced inability to afford basic goods, services or social activities – such as a meal with protein, adequate heating, or spending social time with family and/or friends.

The EU’s severe material and social deprivation rate rose during the cost-of-living crisis, peaking at 6.8% in 2023. A year later, it fell 0.4 percentage points, returning to a level that was similar to that recorded before the crisis. In 2024, there were 27.5 million people across the EU that were facing severe material and social deprivation; this was equivalent to 6.4% of the total population.

More about the data: severe material and social deprivation

The severe material and social deprivation rate is 1 of 3 criteria used to identify people at risk of poverty or social exclusion. It is defined as the share of people who are unable to afford at least 7 out of 13 items (6 related to the individual and 7 related to the household) that are considered desirable – or even necessary – to lead an adequate quality of life

List of items related to the individual

having an internet connection
replacing worn-out clothes by some new ones
having 2 pairs of properly fitting shoes (including a pair of all-weather shoes)
spending a small amount of money each week on themselves
having regular leisure activities
getting together with friends/family for a drink/meal at least once a month

List of items related to the household

capacity to face unexpected expenses
capacity to afford paying for 1-week annual holiday away from home
capacity to being confronted with payment arrears (on mortgage or rental payments, utility bills, hire purchase instalments or other loan payments)
capacity to afford a meal with meat, chicken, fish (or vegetarian equivalent) every 2nd day
ability to keep home adequately warm
have access to a car/van for personal use
replacing worn-out furniture

In 2024, the highest severe material and social deprivation rates were recorded in the south-eastern corner of the EU, peaking in Ionia Nisia (Greece) and Sud-Est (Romania), where more than 1 in 4 of the population faced such deprivation

Map 3 shows the regional distribution of severe material and social deprivation rates. In 2024, the highest rates among NUTS level 2 regions were concentrated Greece, Romania, Bulgaria, the outermost regions of France and Hungary. The lowest rates were observed in northern and central Italy, Slovenia, Austria, Croatia, the Netherlands, Poland and northern Sweden. Of the 243 regions for which data are available, 150 had rates below the EU average of 6.4%, 3 had the same rate, and 90 recorded higher than average rates.

In 2024, Ionia Nisia in Greece (28.0%) and Sud-Est in Romania (26.4%) recorded the highest severe material and social deprivation rates. These were the only EU regions where more than 1 in 4 of the population was affected by the enforced inability to afford basic goods, services or social activities. There were 6 other regions in the EU where more than 20.0% of the population faced severe material and social deprivation:

Calabria in Italy (24.9%)
Yugoiztochen (22.7%), Yuzhen tsentralen (22.1%) and Severen tsentralen (21.6%) in Bulgaria
Anatoliki Makedonia, Thraki in Greece (21.4%)
Sud-Muntenia in Romania (20.3%).

At the other end of the distribution, every region of Czechia, Denmark, Ireland, Croatia, the Netherlands, Poland, Slovenia, Finland and Sweden had a severe material and social deprivation rate that was below the EU average of 6.4% in 2024; this was also the case in Estonia, Cyprus, Latvia, Luxembourg and Malta.

In 2024, there were 6 regions in the EU with severe material and social deprivation rates that were less than 1.0%:

the northern Italian regions of Provincia Autonoma di Bolzano/Bozen and Provincia Autonoma di Trento recorded the lowest rates in the EU (both 0.1%)
the Slovenian capital region of Zahodna Slovenija (0.7%)
the Polish region of Mazowiecki regionalny (0.9%)
2 more Italian regions – Marche and Valle d’Aosta/Vallée d’Aoste (both 0.9%).

Map 3: Severe material and social deprivation rate
Source: Eurostat (ilc_mdsd18) and (ilc_mdsd11)

Figure 3 highlights the NUTS level 2 regions that recorded the biggest increases and decreases in their severe material and social deprivation rates between 2022 and 2024. Across the EU, this rate fell from 6.7% to 6.4% – a decrease of 0.3 percentage points. Looking more closely at the 236 regions for which data are available, the severe material and social deprivation rate fell in 131 regions during the period under consideration, remained unchanged in 5 regions and increased in 100 regions.

There were 2 NUTS level 2 regions that recorded double-digit increases in their severe material and social deprivation rates between 2022 and 2024. The biggest increase was in the southern Italian region of Calabria, up 13.1 percentage points (from 11.8% to 24.9%). There was also a marked increase in Ionia Nisia (Greece), where the rate increased 11.0 points (from 17.0% to 28.0%). Anatoliki Makedonia, Thraki (also Greece) was the only other region in the EU to record an increase of more than 4.5 points, with its rate up 8.9 points (from 12.5% to 21.4%).

There were 10 NUTS level 2 regions that recorded a fall of more than 5.0 percentage points for their severe material and social deprivation rate between 2022 and 2024. This group included 7 out of the 8 regions in Romania (the exception being Nord-Vest), 2 regions from Greece and a single region from Spain. The Romanian regions of Sud-Vest Oltenia and Sud-Muntenia and the Greek region of Dytiki Elláda experienced the biggest declines, as their rates fell by 10.8, 8.5 and 8.3 percentage points, respectively.

Figure 3: Severe material and social deprivation rate
Source: Eurostat (ilc_mdsd18) and (ilc_mdsd11)

Economic strain has gained renewed attention in light of the ongoing cost-of-living crisis. Rising inflation, surging energy prices and challenges around housing affordability have placed considerable pressure on household budgets, particularly among vulnerable groups. Indicators of economic strain can reveal growing disparities in financial resilience, which may be used to understand where support is most needed to address economic insecurity.

The cost-of-living crisis reflects prices increasing at a faster pace than wages, such that purchasing power falls. The surge in prices of food and energy, as well as other goods and services, may be attributed, at least in part, to Russia’s military aggression against Ukraine. For example, concerns over supply shortages, along with international sanctions placed on Russian energy exports, led to an increase in the price of energy products, while prices for foodstuffs and fertilisers also rose strongly. Another contributing factor to rising inflation was a post-pandemic surge in demand.

More about the data: economic strain

Economic strain refers to a set of indicators that measure self-perceived financial difficulties of households. This concept is covered by a group of indicators collected as part of the EU-SILC survey, designed to capture material hardship and/or financial stress.

While economic strain is not generally used as a headline indicator within EU policy development, it does play a key role in understanding living conditions and poverty (beyond income-based measures). Various measures of economic strain are included in composite indicators such as the severe material and social deprivation rate. Some of the most common measures include, whether households:

can keep their home adequately warm
can afford a meal with meat, chicken, fish (or vegetarian equivalent) every 2nd day
can afford unexpected financial expenses
have arrears on mortgage/rent, utility bills, hire purchase instalments or other loan payments.

The data presented in the 4 maps below relate to the share of the population affected by each measure of economic strain. The data are shown as indices, relative to the EU average (that is set equal to 100.0); higher values indicate that people living in a particular region have greater difficulty affording the specific goods and/or services.

In Kentriki Elláda (Greece) and Sur (Spain), more than 1 in 5 people were unable to keep their home adequately warm in 2024

Map 4A highlights the share of the population living in households that are struggling to keep their homes adequately warm. In 2024, this issue affected 9.2% of the EU population. Among NUTS level 1 regions, the highest incidence was observed in Kentriki Elláda (Greece), where 21.2% of people lived in households struggling to keep their homes adequately warm. This was more than 11 times as high as the share recorded in the Polish region of Makroregion województwo mazowieckie (1.9%). In comparison with the EU average, a notably higher share of people in regions of Bulgaria, Greece and Spain lived in households unable to keep their homes adequately warm, with regional shares sometimes more than twice as high as the EU average. By contrast, many regions across the Nordic EU countries and Poland, reported significantly lower levels, with shares that were often less than half the EU average; this was also the case in Estonia, Luxembourg, Austria and Slovenia.

In 2024, more than 1 in 5 people in the Romanian region of Macroregiunea Unu were unable to afford a meal with protein (meat, chicken, fish or vegetarian equivalent) every 2nd day

Map 4B depicts the share of people who could not afford a meal containing protein every 2nd day; this economic strain impacted 8.5% of the EU population in 2024. The highest share across NUTS level 1 regions was recorded in the Romanian region of Macroregiunea Unu (22.9%), which was almost 20 times as high as in Cyprus, where the lowest share was recorded (1.2%). The share of people who could not afford a meal containing protein every 2nd day was more than twice as high as the EU average in:

both Bulgarian regions
Saarland (Germany)
Alföld és Észak (Hungary)
Macroregiunea Unu (Romania)
Slovakia.

In Bremen (Germany) and Severna i Yugoiztochna Bulgaria (Bulgaria), more than half of the population was unable to face unexpected financial expenses in 2024

Map 4C shows the proportion of people who were unable to manage unexpected financial costs; across the EU, 30.0% of the population was affected by this economic strain in 2024. Among NUTS level 1 regions, the lowest share was recorded in the northern Belgian region of Vlaams Gewest (13.2%). Relatively low shares – less than half the EU average – were also observed in 3 out of the 4 regions of the Netherlands (with the exception of West-Nederland).

At the other end of the scale, more than half of the population was unable to manage unexpected financial costs in 2024 in the northern German region of Bremen (52.4%) and in Severna i Yugoiztochna Bulgaria (51.5%). Relatively high shares – of at least 40.0% – were also recorded in Yugozapadna i Yuzhna tsentralna Bulgaria, 3 out of 4 Greek regions (excluding the capital region of Attiki), the Spanish regions of Sur and Canarias, the French outermost regions, the Italian regions of Sud and Isole, the Baltic countries of Latvia and Lithuania, and the Romanian regions of Macroregiunea Doi and Macroregiunea Patru.

In all 4 Greek regions, more than 40% of the population had arrears on mortgage, rent, utility bills or hire purchase payments in 2024

Map 4D focuses on the share of individuals falling behind on payments for mortgages, rent, utilities or hire purchase agreements. In 2024, these issues affected 9.2% of the EU population. The highest regional shares (among NUTS level 1 regions) were recorded in Greece, with more than 40% of the population falling behind on payments in all 4 regions. The highest share was recorded in Kentriki Elláda, at 45.8%. The share of people who were in arrears on mortgage, rent, utility bills or hire purchase payments was more than twice as high as the EU average in every region of Greece, the Bulgarian region of Severna i Yugoiztochna Bulgaria, the French outermost regions and the Romanian region of Macroregiunea Doi.

By contrast, Noord-Nederland (2.1%) had the lowest share of people falling behind on payments for mortgages, rent, utilities or hire purchase agreements in 2024. There were several other regions across the EU where the share of people in arrears was less than half the EU average: Vlaams Gewest (Belgium), Czechia, Sachsen (Germany), Nord-Est, Nord-Ovest and Centro (Italy), 2 more Dutch regions (Oost-Nederland and Zuid-Nederland), and 5 out of the 7 regions in Poland (the exceptions being Makroregion południowy and Makroregion południowo-zachodni).

Map 4: Economic strain
(indices relative to EU average = 100.0, by NUTS 1 regions, 2024)
Source: Eurostat (ilc_mdes01_r), (ilc_mdes03_r), (ilc_mdes04_r), (ilc_mdes05_r), (ilc_mdes01), (ilc_mdes03), (ilc_mdes04) and (ilc_mdes05)

People living in a household with very low work intensity

In 2024, there were 26.2 million people (aged 0 to 64 years) across the EU living in a household with very low work intensity, representing 7.9% of this subpopulation. In 2021, the share had been 9.0%. It declined relatively sharply in 2022 (by 0.7 percentage points), followed by smaller decreases in 2023 (0.3 points) and 2024 (a further 0.1 points).

More about the data: very low work intensity

The share of people living in a household with very low work intensity is 1 of the 3 criteria used to identify people at risk of poverty or social exclusion. Working-age adults with low work intensity are defined as people aged 18 to 64 years (excluding students aged 18 to 24 years and retired people under the age of 65 years) who worked for 20% or less of their combined potential working time during the previous 12 months. Households composed only of children, of students younger than 25 years and/or of people aged 65 years or more are excluded from the calculation of this indicator.

In 2024, low work intensity was concentrated in clusters of regions across western EU countries and southern Italy

Of the 243 NUTS level 2 regions for which data are available, there were 104 regions that had shares of people living in households with very low work intensity that were higher than the EU average (7.9%), while there were 139 that had lower than average shares. Map 5 highlights those regions across the EU with a relatively high share of people living in households with very low work intensity in 2024 (as shown by the darkest shade of blue). There were 26 such regions, each with a share of at least 12.5%:

7 (predominantly urban) regions in Germany
6 regions in France (4 of which were the outermost regions)
4 regions in Belgium – the capital Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest and 3 in Région wallonne
4 regions in Italy, located either in the south or on islands
the 2 autonomous Spanish cities of Melilla and Ceuta
Austria’s capital region, Wien
Dytiki Makedonia in Greece
Severozapaden in Bulgaria.

By contrast, there were 27 regions across the EU where fewer than 3.5% of people were living in households with very low work intensity in 2024 (as shown by the lightest shade of yellow in Map 5). These 27 regions were widely dispersed across 12 different EU countries, including Poland (5 predominantly western regions), Italy (4 northern regions), Hungary (3 western regions), Austria (3 western regions) and Romania (3 eastern regions).

Map 5: People living in households with very low work intensity
Source: Eurostat (ilc_lvhl21n) and (ilc_lvhl11n)

Figure 4 is split into 2 parts: the left-hand side presents information for the NUTS level 2 regions with the highest and lowest shares of people living in a household with very low work intensity in 2024; the right-hand side presents the biggest increases and decreases in these shares between 2022 and 2024. In 2024, the French outermost region of Guyane (35.4%) had, by far, the highest share. The next highest shares – where more than 1 in 5, but less than 1 in 4 people were living in a household with very low work intensity – were observed in:

Campania in Italy (24.4%)
the French outermost regions of Guadeloupe (23.5%) and La Réunion (21.9%)
Bremen in Germany (22.9%)
the autonomous Spanish region of Ciudad de Ceuta (21.9%)
the Belgian regions of Prov. Hainaut (20.5%) and Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest (20.3%).

At the lower end of the distribution, there were 8 NUTS level 2 regions where, in 2024, the share of people living in a household with very low work intensity was less than 2.0%. The Romanian capital region of Bucureşti-Ilfov (0.6%) and the Slovak capital region of Bratislavský kraj (0.8%) had the lowest shares and were the only regions in the EU where fewer than 1.0% of people were living in a household with very low work intensity. The 3rd lowest share was also recorded in a capital region of an eastern EU country, Warszawski stołeczny in Poland (1.1%). The other 5 regions with shares below 2.0% included:

Provincia Autonoma di Bolzano/Bozen in Italy (1.3%)
the western Austrian regions of Salzburg (1.4%) and Tirol (1.6%)
Közép-Dunántúl in Hungary (1.7%)
Sud-Muntenia in Romania (1.9%).

The right-hand side of Figure 4 shows the regions that experienced the biggest increases and decreases in their share of people living in a household with very low work intensity between 2022 and 2024. Across the EU, there was a 0.4 percentage points decrease in this share. During the same period, the share of people living in a household with very low work intensity fell in almost 2 out of 3 (150 out of 236) NUTS level 2 regions for which data are available, while there was an increase in 86 regions.

The Spanish autonomous city of Melilla recorded the largest decrease in its share of people living in a household with very low work intensity, down 8.0 percentage points between 2022 and 2024. Marked reductions were also observed in 3 Italian regions – Calabria (down 7.4 points), Abruzzo (down 6.9 points) and Liguria (down 6.7 points) – as well as in Spain’s other autonomous city, Ceuta (down 6.2 points). No other region in the EU reported a decrease that was greater than 4.5 points.

Among the 86 regions that reported a rising share of people living in a household with very low work intensity between 2022 and 2024, the highest increases were recorded in the western German region of Trier (up 8.1 percentage points) and the French outermost region of Guyane (up 7.3 points). Relatively large increases – ranging from 4.3 to 5.8 points – were also observed in Yugoiztochen (Bulgaria), Burgenland (Austria) and Bremen (Germany).

Figure 4: People living in households with very low work intensity
Source: Eurostat (ilc_lvhl21n) and (ilc_lvhl11n)

Income distribution

Gross domestic product (GDP) per inhabitant has traditionally been used to assess regional divergence/convergence in overall living standards. However, this commonly used measure fails to account for income paid/received across borders. It also fails to capture the distribution of income within a population and thereby does little to reflect economic inequalities. Alternative/broader measures can help provide a more comprehensive and nuanced understanding of economic and societal developments.

The unequal distribution of income and wealth has gained prominence in political and socioeconomic discourse since the global financial and economic crisis and, more recently, during the cost-of-living-crisis. This inequality not only reflects a wider concentration of wealth among a small privileged group – raising concerns about social cohesion, fairness, and long-term economic stability – but also highlights persistent disparities between regions, particularly those considered to have been ‘left behind’.

More about the data: income inequality

The income quintile share ratio (S80/S20) measures the inequality of income distribution. It is calculated as the ratio between the share of income received by the 20% of the population with the highest income (the top quintile) and the share of income received by the 20% of the population with the lowest income (the bottom quintile). High values for this ratio suggest that there are considerable disparities in the distribution of income between upper and lower income groups.

The reference period for income statistics refers to the calendar year before the year in which the survey took place. Income statistics for Belgium and Serbia refer to NUTS level 1 regions, while there are only national data available for France and Türkiye.

In 2024, the EU’s income quintile share ratio was 4.7 – in other words, the combined income received by the 20% of people with the highest incomes was 4.7 times as high as the combined income received by the 20% with the lowest incomes.

Across the EU, the Slovak capital region of Bratislavský kraj had the lowest income quintile share ratio, at 2.5 in 2024

Map 6 shows the regional distribution of the income quintile share ratio. In 2024, this distribution was skewed: 148 out of the 210 regions for which data are available had ratios below the EU average, 8 regions had the same ratio, while 54 regions reported income disparities above the EU average. The highest income disparities were recorded in the Spanish autonomous cities and parts of Bulgaria and Italy, while the most equitable distributions of income were observed in parts of Czechia, Slovakia and the Netherlands.

At the top end of the distribution, there were 4 NUTS level 2 regions where the income quintile share ratio was at least 7.5 in 2024 (as shown by the darkest shade of blue in Map 6). The Spanish regions of Ciudad de Melilla had the highest income quintile share ratio, at 9.7. The other 3 regions – the Bulgarian capital region of Yugozapaden, the Spanish region of Ciudad de Ceuta and the southern Italian region of Calabria – each had a ratio of 7.6.

At the other end of the distribution, the share of income held by the highest earning 20% of the population in 2024 in Bratislavský kraj – the Slovak capital region – was 2.5 times as high as that held by the lowest earning 20%. This was the lowest income quintile share ratio among NUTS level 2 regions. There were 4 other regions across the EU with ratios below 3.0 (as shown by the lightest shade of yellow in Map 6):

Drenthe and Zeeland in the Netherlands (2.6 and 2.8, respectively)
Západné Slovensko in Slovakia (2.8)
Jihozápad in Czechia (2.9).

In many multi-regional EU countries, income distribution in the capital region differed significantly from that in the rest of the country. In 2024, capital regions often recorded the highest income quintile share ratios, as seen in Belgium, Bulgaria, Czechia, Denmark, Ireland, Hungary, the Netherlands, Austria, Poland, Finland and Sweden. For instance, the ratios in the Belgian and Austrian capitals – Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest and Wien – were 1.4 times as high as their respective national averages. By contrast, the pattern was reversed in Germany, Croatia, Lithuania, Romania and Slovakia, where national averages exceeded the ratios recorded in each capital region. For example, income quintile share ratios for Romania and Slovakia were 1.3 times as high as those in Bucureşti-Ilfov and Bratislavský kraj, respectively.

Map 6: Income quintile share ratio (S80/S20)
Source: Eurostat (ilc_di11_r) and (ilc_di11)

Criminal justice

More about the data: crime and criminal justice statistics

The statistics presented in this section are based on official figures for police-recorded offences (criminal acts), classified according to the International Classification of Crime for Statistical Purposes (ICCS).

The number of police-recorded crimes varies considerably across the EU: this may reflect, among other factors, different rates for reporting crimes to the police (especially for minor offences), different laws in each EU country and different police practices for recording crimes.

The data shown in this section are based on crime rates, the number of police-recorded crimes per 100 000 inhabitants for NUTS level 2 regions. These rates were subsequently converted into indices to show deviations from the national average in each country (with the national average = 100).

Domestic burglary is defined as breaking in and stealing, in other words, getting unauthorised access to a dwelling for theft or intent of theft (with or without forcing locks, doors, windows, and so on).

Theft is defined as taking property unlawfully – without violence, force, threat, coercion or deception – with the intent to keep it permanently without consent. Theft of motorised land vehicles includes stealing cars, motorcycles, buses, coaches, lorries, trucks, bulldozers and so on.

Intentional homicide is defined as killing a human being wilfully and illegally; in other words, the intent was to cause death or serious injury, but not necessarily that it was planned beforehand. This is a wider concept than murder, for which also planning and other criteria are considered. Intentional homicide statistics:

include murder, deadly assault, assassination, terrorism, femicide, infanticide, voluntary manslaughter, extrajudicial killings and illegal killing by police or military
exclude attempted homicide, justifiable self-defence, assisted suicide, euthanasia and abortion.

Special care should be taken when analysing the statistics presented below, as there may be very low counts of intentional homicides in some regions. Counts can vary considerably over time, especially in jurisdictions with small populations, whereby a small increase/decrease in the number of homicides may lead to a relatively large change in crime rates.

You can find more information about how crimes are classified across EU regions in the metadata.

Table 1 highlights the region within each country with the highest incidence of domestic burglaries, motor vehicle thefts and intentional homicides in 2023. Note these figures are normalised, using incidence rates per 100 000 inhabitants to enable more relevant comparisons between regions of different population sizes; these rates were subsequently converted to indices so that each region may be compared with its national average. As such, cross-country comparisons should not be made.

In Belgium, Czechia, Lithuania and Slovenia, capital regions – Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest, Praha, Sostinės regionas and Zahodna Slovenija – consistently recorded the highest incidence rate for all 3 crimes.
Midtjylland (Denmark), Provence-Alpes-Côte d’Azur (France), Algarve (Portugal) and Bucureşti-Ilfov (Romania) recorded the highest incidence rates for domestic burglaries and for motor vehicle thefts.
In Spain, Ciudad de Ceuta recorded the highest incidence rate for motor vehicle thefts and for intentional homicides. A similar situation was observed in Italy, as the highest incidence rate for motor vehicle thefts was in Campania which also had the joint highest rate – with Calabria – for intentional homicides.
In Slovakia, Východné Slovensko recorded the highest incidence rate for domestic burglaries and for intentional homicides.
In all of the remaining multi-regional EU countries, different regions recorded the highest incidence rates for each of the 3 crimes covered in this section.

Capital and coastal regions have some of the highest incidence rates for domestic burglaries

Based on the latest information available, there were an estimated 703 500 police-recorded domestic burglaries across the EU in 2023 (including 2021 data for Luxembourg and excluding Ireland, Cyprus and Hungary). Within several EU countries, the capital region – specifically those of Belgium, Czechia, Croatia, Lithuania, Austria, Romania and Slovenia – recorded the highest incidence of domestic burglaries.

In relative terms (compared with national averages), the highest incidence of domestic burglaries was recorded in Bremen (Germany), where burglaries were 2.8 times as likely as the national average. Relatively high indices – more than twice as high as the national average – were also observed in Wien (the Austrian capital region; 2.2 times) and Algarve (southern Portugal; 2.1 times).

In 2023, there was a relatively high incidence of motor vehicle thefts in the capital regions of Romania, Poland and Germany

In 2023, police recorded 477 300 motor vehicle thefts across the EU (including 2022 data for Ireland, 2021 data for Germany, and excluding Cyprus and Hungary). There were 12 multi-regional EU countries where the capital region recorded the highest incidence of motor vehicle theft, namely, Belgium, Czechia, Germany, Ireland, Greece, Lithuania, the Netherlands, Poland, Romania, Slovenia, Slovakia and Finland.

In relative terms, the highest incidence rates of motor vehicle theft in 2023 were recorded in:

Romania, where police in the capital region of Bucureşti-Ilfov were 5.6 times as likely to record an offence as was the situation for the national average
Poland, where police in the capital region of Warszawski stołeczny were 4.3 times as likely to record an offence as was the situation for the national average
Germany, where police in the capital region of Berlin were 4.1 times as likely to record an offence as was the situation for the national average.

In 2023, there was a very high incidence of intentional homicide in French outermost regions

In 2023, there were 3 930 police-recorded intentional homicides within the EU, marking an increase of 1.5% compared with 2022. Most EU countries had a relatively narrow range of inter-regional variation for incidence rates of intentional homicides. There were 6 multi-regional EU countries where the capital region recorded the highest incidence of intentional homicide – namely, Belgium, Czechia, Denmark, Lithuania, Hungary and Slovenia. By contrast, the capital regions of Bulgaria, Spain, France, Italy, Slovakia and Finland recorded rates that were below their respective national averages.

However, there were a few outliers with much higher incidence rates, including several of the outermost regions of France and the autonomous Spanish city of Ceuta. In relative terms, the French outermost region of Guyane had the highest incidence of intentional homicide in 2023, at 16.1 times the French national average. The 2nd and 3rd highest rates in France were also recorded in outermost regions: Guadeloupe (7.3 times the national average) and Martinique (4.7 times). In Spain, the highest incidence rate for intentional homicide was recorded in Ciudad de Ceuta (8.6 times the national average).

Table 1: Police-recorded offences
Source: Eurostat (crim_gen_reg) and (crim_off_cat)

Source data for figures and maps

Download Excel file

Data sources

EU statistics on income and living conditions (EU-SILC) cover objective and subjective aspects of income, poverty, social exclusion, housing conditions, labour, education and health. They are presented in monetary and non-monetary terms for households and for individuals.

As of reference year 2021, EU-SILC data have a new legislative basis – Regulation (EU) No 2019/1700 of the European Parliament and of the Council of 10 October 2019 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples.

The reference population for the EU-SILC data collection is all private households and their current members residing in the territory of an EU country; people living in collective households and in institutions are generally excluded. The data presented for the EU aggregate are population-weighted averages of national data.

Indicator definitions

People at risk of poverty or social exclusion

The number of people at risk of poverty or social exclusion corresponds to the number of people who are at risk of poverty and/or facing severe material and social deprivation and/or living in a household with a very low work intensity. As well as being expressed as an absolute number, this indicator can also be compiled as a rate for the total population.

In 2021, the calculation of the number/rate of people at risk of poverty or social exclusion was modified to reflect new EU targets introduced within the European Pillar of Social Rights Action Plan. The number of people who are at risk of poverty or social exclusion in the EU should fall by at least 15 million by 2030 (compared with 2019), with children accounting for at least a third of the overall fall. This new EU target on poverty and social exclusion redefined 2 of the components used to calculate the risk of poverty or social exclusion, extending the measure of:

deprivation by introducing a new indicator for severe material and social deprivation
quasi-joblessness among people living in households with very low work intensity through the inclusion of adults aged 60 to 64 years (who were previously omitted).

At-risk-of-poverty rate

Equivalised disposable income is the total income of a household (after tax and other deductions) that is available for spending or saving, divided by the number of household members (having been converted into equalised adults). Household members are ‘equalised’ or made ‘equivalent’ by weighting each person according to their age, using the so-called modified OECD equivalence scale (a weight of 1.0 to the 1st adult; 0.5 to the 2nd and each subsequent person aged 14 years or more; 0.3 to each child aged under 14 years).

The at-risk-of-poverty threshold is set at 60% of the national median equivalised disposable income after social transfers. Pensions, such as old-age and survivors’ (widows’/widowers’) benefits, are counted as income before social transfers and not as social transfers. A comparison of rates before and after social transfers gives some idea as to the impact of social transfers in terms of alleviating the risk of poverty.

The at-risk-of-poverty rate after social transfers is 1 of 3 components used to monitor progress towards the EU’s revised 2030 target on poverty and social exclusion. This relative measure does not provide an indication of wealth or poverty directly, rather it measures the share of people facing low incomes in comparison with other residents in the same country/region; this does not necessarily imply a low standard of living.

Severe material and social deprivation rate

The severe material and social deprivation rate is an indicator in EU-SILC that expresses an inability to afford some items considered by most people to be desirable or even necessary to lead an adequate life. It is defined as the share of the population who could not afford at least 7 out of 13 deprivation items. The indicator distinguishes between individuals who cannot afford a certain good or service and those who do not have this good or service for another reason, for example, because they do not want or do not need it.

The severe material and social deprivation rate is 1 of 3 components used to monitor progress towards the EU’s revised 2030 target on poverty and social exclusion.

People living in a household with very low work intensity

The share of people living in a household with very low work intensity is defined as the share of working-age adults aged 18 to 64 years (excluding students aged 18 to 24 years and retired people who are younger than 65 years) who worked for 20% or less of their combined potential working time during the previous 12 months. Households composed only of children, of students younger than 25 years and/or of people aged 65 years or more are excluded from the calculation of this indicator.

The share of people living in a household with very low work intensity is 1 of 3 components used to monitor progress towards the EU’s revised 2030 target on poverty and social exclusion.

Income quintile share ratio (S80/S20)

The income quintile share ratio (S80/S20) is a measure of the inequality of income distribution. It is calculated as the ratio of the combined income received by the 20% of the population with the highest incomes (the top quintile) to that received by the 20% of the population with the lowest incomes (the bottom quintile). All incomes relate to equivalised disposable incomes (see the definition of the ‘at-risk-of-poverty rate’ above for an explanation).

Crimes recorded by the police

Crime statistics are based on official figures for police-recorded offences (criminal acts), classified according to the International classification of crime for statistical purposes (ICCS). The ICCS provides a framework for the systematic production and comparison of statistical data across different criminal justice institutions and jurisdictions.

EU statistics on crime and criminal justice include administrative data at 4 different stages of the criminal justice system: the police and other law enforcement agencies, public prosecutors, law courts and prisons. Data from the police are thought to provide the broadest measure of crime, as they include all recorded offences (whether or not they lead to prosecution). That said, these administrative data likely under-report the total amount of crime for most offences.

For a crime to be reflected in official crime statistics, a chain of decisions needs to be successfully taken by the victim and police. These include recognition by the victim that a criminal offence has occurred, a decision to notify the relevant authorities and the recording of the event in official police records. If a victim is not aware that a crime has occurred, does not report it or is failed by the police in recording it, then that crime will not be reflected in official crime statistics. Police-recorded crime statistics may suffer from an additional weakness, insofar as there may be a lack of interest in pursuing minor infractions and petty offences which means that crimes such as these are not recorded accurately. By contrast, reporting rates are likely to be more robust for crimes such as the theft or burglary, as victims generally require a police record to support related insurance claims.

Comparisons of police-recorded crimes in absolute numbers between different jurisdictions are challenging, due to the different criminal laws and different criminal justice systems in EU countries. Furthermore, Eurostat recommends the use of crime rates that are based on a count of the number of police-recorded crimes normalised by the population and expressed per 100 000 inhabitants. Regional crime rates are subsequently indexed to show deviations from national averages (set = 100). This facilitates analyses of territorial differences, such as those between predominantly rural and predominantly urban regions.

Context

European pillar of social rights The EU operates an open method of coordination for social protection and social inclusion. This aims to promote social cohesion and equality through adequate, accessible and financially sustainable social protection systems and social inclusion policies. As such, the EU provides a framework for national strategy development, as well as the opportunity to discuss and learn from best practices and to coordinate policies between EU countries in areas such as building a fairer and more inclusive EU, social protection and social inclusion, and pensions.

At the start of March 2021, the European Commission outlined its ambition for an EU that focuses on education, skills and jobs for the future and targets a fair, inclusive and resilient socioeconomic recovery. The European Pillar of Social Rights Action Plan outlines a range of actions designed to promote social rights through the active involvement of social partners and civil society. It also proposes employment, skills and social protection headline targets for the EU: 1 of these relates specifically to living conditions, namely that the number of people at risk of poverty or social exclusion should decrease by at least 15 million people (of which, at least 5 million should be children) between 2019 and 2030.

The Action Plan highlights how the principles of the social pillar might be implemented, with the aim of building a stronger social Europe by 2030 through:

more and better jobs – creating job opportunities in the non-financial economy, making work standards fit for the future of work, improving occupational safety and health standards, increasing labour mobility
skills and equality – investing in skills and education to unlock new opportunities for all, building a Union of Equality
social protection and inclusion – living in dignity, fostering social inclusion and combatting poverty, promoting health and ensuring care, improving social protection.

The Action Plan also announced a number of initiatives to support the implementation of these principles. In the area of poverty and social exclusion, initiatives include the Council Recommendation establishing a European Child Guarantee, a Council Recommendation on minimum income ensuring active inclusion, the European platform to combat homelessness, a report on Access to essential services and guidance on the use of distributional impact assessments and a Pact for European Social Dialogue.

At a conference in La Hulpe (Belgium), EU institutions, social partners and civil society representatives renewed their commitment to a strong and resilient social Europe. In a Declaration on the Future of the European Pillar of Social Rights, the European Commission and other signatories pledged to continue implementing the European Pillar of Social Rights and further strengthen employment and social dimensions amidst demographic shifts, and digital and green transitions. They also agreed to review and update the Action Plan in 2025, introducing new initiatives to achieve the 2030 targets for employment, skills and poverty reduction. The forthcoming Action Plan is anticipated to address several key areas:

equal opportunities and access to the labour market
fair working conditions
social protection and inclusion
governance.

Criminal justice

In accordance with EU treaties, the areas of freedom, security and justice are shared competences between the EU and the EU countries. In the area of substantive criminal law, EU competence is limited to establishing minimum rules concerning the definition of criminal offences and sanctions in the areas of particularly serious crime with a cross-border dimension.

To combat crime efficiently, the criminal justice authorities of EU countries seek to work together. In developing a common European area of justice, national law enforcers and judiciaries aim to be able to trust and rely on each other. This is intended to increase people’s confidence in the fairness of proceedings, knowing that their rights are protected when they have to appear in court in another country, or if they fall victim to a crime.

On 24 June 2020, the European Commission adopted its first-ever EU Strategy on victims’ rights (2020–25) (COM(2020) 258 final). Its main objective is to ensure that all victims of crime, no matter where in the EU or in what circumstances the crime took place, can fully exercise their rights. The strategy presents 5 key priorities:

effective communication with victims and a safe environment for victims to report crime
improving support and protection to the most vulnerable victims
facilitating victims’ access to compensation
strengthening cooperation and coordination among all relevant actors
strengthening the international dimension of victims’ rights.

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

You can explore the maps interactively using Eurostat’s Statistical Atlas.

Explore further

Database

Income and living conditions (ilc), see

Persons at risk of poverty or social exclusion (EU 2030 target) (ilc_pe)

Inequality (ilc_iei)

Income distribution and monetary poverty (ilc_ip)

Living conditions (ilc_lv)

Material deprivation (ilc_md)

Regional statistics by NUTS classification (reg), see

Regional poverty and social exclusion statistics (reg_ilc)

Regional crime statistics (reg_crim)

Crime and criminal justice (crim), see

Police-recorded offences (crim_off)

Thematic section

Publications

News articles

Paper and PDF publications

Analytic report on subjective well-being
Eurostat regional yearbook – 2025 edition
Key figures on European living conditions – 2024 edition
Monitoring social inclusion in Europe – 2017 edition
Sustainable development in the European Union: monitoring report on progress towards the SDGs in an EU context – 2025 edition
Sustainable development in the European Union – Overview of progress towards the SDGs in an EU context – 2025 edition
Crime and criminal justice – publications

Online publications

Selected datasets

Income and living conditions – selected datasets (t_ilc), see

Persons at risk of poverty or social exclusion (EU 2030 target) (t_ilc_pe)

Income distribution and monetary poverty (t_ilc_ip)

Living conditions (t_ilc_lv)

Material deprivation (t_ilc_md)

Regional statistics (t_reg), see

Regional poverty and social exclusion statistics (t_reg_ilc)

Methodology

Manuals and further methodological information

Metadata

Crime and criminal justice (ESMS metadata file – crim_gen_reg)
Income and living conditions (SIMS metadata file – ilc_sieusilc)

External links

Legislation

Detailed list of legislative information on EU-SILC provisions for survey design, survey characteristics, data transmission and modules
Regulation (EU) No 2019/1700 – establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples – repealing legislation on EU-SILC (as of 01 January 2021)

Visualisation

Eurostat statistical atlas (Chapter 5)