Living conditions statistics at regional level

Data extracted in June 2024.

Planned article update: September 2025.

Highlights

In 2023, the share of the population at risk of poverty or social exclusion in Guyane, La Réunion (both France; 2022 data), Calabria, Campania (both Italy) and Sud-Est (Romania) was more than twice as high as the EU average of 21.4%.

The EU’s severe material and social deprivation rate was 6.8% in 2023: there was a considerable range across EU regions, from a low of 0.7% in Flevoland (the Netherlands) up to a high of 30.8% in Sud-Est (Romania).

Source: Eurostat (ilc_pees01n)

By global standards, most people living in the European Union (EU) are relatively prosperous. 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. That said, 94.6 million people in the EU (21.4% of the population) were at risk of poverty or social exclusion in 2023 (see the infographic above for more information).

Sociodemographic characteristics like age, educational attainment, sex and country of birth / citizenship can play an important role in shaping 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 ware of aggression against Ukraine, or the cost-of-living crisis – can also have a considerable impact. In some cases, these events can rapidly undo long-term decreases in inequality, thereby reinforcing or exacerbating patterns of inequality and exclusion.

Since late 2021, there has been a considerable increase in the cost of living across much of the EU. Some of the most rapid increases in prices were experienced for goods like energy and food. Price increases for these goods generally had a greater impact on 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 accelerated from 0.7% in 2020 to 9.2% by 2022, before falling back to 6.4% in 2023. This surge in prices could be attributed, at least in part, to Russia’s war of aggression against Ukraine. For example, the price of energy products increased because of concerns over supply shortages (with international sanctions placed on Russian energy exports), while prices for foodstuffs and fertilisers also rose strongly. Another contributing factor to rising inflation was a post-pandemic surge in demand.

Full article

People at risk of poverty or social exclusion

Absolute poverty is the 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/share of people at risk of poverty or social exclusion (see the infographic at the start of this chapter) 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 working-age adults (aged 18–64, excluding students aged 18–24 and those who are retired) worked for 20% or less of their combined potential working time during the previous 12 months.

For the data based on 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)
there is no information for Mayotte in France
an earlier reference year is sometimes used for individual EU 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; one of the targets 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).

In 2023, more than 1 in 5 (21.4%) of the EU’s population was at risk of poverty or social exclusion

Map 1 shows the regional distribution of people at risk of poverty or social exclusion across NUTS level 2 regions. In 2023, the regional distribution of this indicator was somewhat skewed, as close to 40% of all EU regions (101 out of the 241 for which data are available) recorded shares of people at risk of poverty or social exclusion that were higher than the EU average.

The highest risks of poverty or social exclusion were typically observed in southern, eastern and outermost regions of the EU. At the top end of the distribution, there were 19 NUTS level 2 regions that recorded shares of at least 35.0% in 2023; they are shown by the darkest shade of blue in Map 1. These 19 regions were concentrated in Bulgaria, Spain, Italy, Romania (3 regions each) and the outermost regions of France (4 regions; 2022 data); this group was completed by 2 regions from western Greece and the Belgian capital region.

In 2023, Guyane in France (49.5%; 2022 data) and Calabria in southern Italy (48.6%) had the highest regional shares of people at risk of poverty or social exclusion. They were followed by Sud-Est in Romania (45.3%), Campania in southern Italy (44.4%) and La Réunion in France (43.2%; 2022 data). These were the only regions in the EU where the share of people at risk of poverty or social exclusion was more than twice as high as the EU average (21.4%).

At the other end of the distribution, there were 5 NUTS level 2 regions where less 10.0% of the population was at risk of poverty or social exclusion in 2023; they are shown in a yellow shade in Map 1. This group included

2 regions from northern Italy – Provincia Autonoma di Bolzano/Bozen (5.8%; the lowest regional share in the EU) and Emilia-Romagna (7.4%)
2 regions from Czechia(2022 data) – Střední Čechy (8.7%) which surrounds the capital region of Praha (8.9%)
the Polish capital region of Warszawski stołeczny (8.9%).

In 2023, people living in the capital regions of eastern EU countries were generally less likely to be at risk of poverty or social exclusion than their counterparts living in the remainder of the country. For example, the proportion of people at risk of poverty or social exclusion across Romania (32.0%) was 2.6 times as high as the share recorded in its capital region of Bucureşti-Ilfov (12.3%). A similar pattern was observed in Poland and in Croatia. In the former, the share of people at risk of poverty or social exclusion was 16.3%, which was 1.8 times as high as the share recorded in Warszawski stołeczny (8.9%). More than 20.7% of the population in Croatia was at risk of poverty or social exclusion, which was 1.7 times as high as the share recorded in Grad Zagreb (11.9%). This pattern was repeated, although to a lesser extent, in the other eastern EU countries.

By contrast, the situation was reversed in several western EU countries. In Germany, Ireland, France and the Netherlands, the risk of poverty or social exclusion was somewhat higher in capital regions (than the national average); this was also the case in Italy. The difference was more marked in Belgium and Austria, where the share of people at risk of poverty or social exclusion in the capital regions of Région De Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (37.6%) and Wien (29.5%) was considerably higher than their respective national average (18.6% and 17.7%).

Figure 1 identifies the NUTS level 2 regions that had the biggest changes in their respective shares of people at risk of poverty or social exclusion between 2022 and 2023. There was a modest reduction across the EU, as the share fell 0.2 percentage points from 21.6% to 21.4%. Among the 203 regions for which data are available (at the time of the data extraction, there was no information for 2023 for Czechia, France and Slovakia), the share of people at risk of poverty or social exclusion rose in 88 regions between 2022 and 2023, remained unchanged in 8 regions, and fell in 107 regions.

There were 7 NUTS level 2 regions where the risk of poverty or social exclusion increased by at least 5.0 percentage points between 2022 and 2023. The highest increase was recorded in north-eastern Hungarian region of Észak-Magyarország, up 6.8 points (from 25.0% to 31.8%). The other regions with relatively high increases were

Calabria and Valle d’Aosta/Vallée d’Aoste in Italy (up 5.8 and 5.2 points)
Nordjylland in Denmark (up 5.6 points)
Świętokrzyskie in Poland (up 5.4 points)
Rheinhessen-Pfalz in Germany (up 5.0 points)
Burgenland in Austria (also up 5.0 points).

Most of the regions with the biggest falls in their respective shares of people at risk of poverty or social exclusion were in eastern and southern EU countries. Between 2022 and 2023, the biggest decrease in the share of people at risk of poverty or social exclusion was recorded in the southern Italian region of Molise, down 12.4 percentage points (from 37.2% to 24.8%). There were 6 other regions that reported falls of more than 5.0 points

Sterea Elláda in Greece (down 9.0 points)
the Romanian capital region of Bucureşti-Ilfov (down 6.9 points)
Abruzzo (down 6.7 points), Liguria (down 6.6 points) and Provincia Autonoma di Bolzano/Bozen (down 5.9 points) in Italy
the Irish region of Northern and Western (down 5.6 points).

Figure 1: People at risk of poverty or social exclusion, 2023
(by NUTS 2 regions)
Source: Eurostat (ilc_peps11n) and (ilc_peps01n)

People at risk of poverty

In 2023, there were 71.9 million people in the EU who were at risk of poverty (after social transfers); this was equivalent to 16.2% of the population. The highest regional shares of people at risk of poverty were principally recorded in southern, eastern and Baltic countries, while the lowest shares were concentrated in northern Belgium, southern Germany, northern Italy, western Czechia and western Hungary, as well as several capital regions.

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. This rate doesn’t directly measure poverty; instead, 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 national median incomes differ between countries.

Map 2 shows the at-risk-of-poverty rate for NUTS level 2 regions. In 2023, the regional distribution of this rate was relatively skewed: there were 89 regions (just over a third of the total) that recorded a rate equal to or above the EU average of 16.2%, while the remaining 152 regions had lower than average rates.

In 2023, the lowest at-risk-of-poverty rate was recorded in Romanian capital region of Bucureşti-Ilfov

The French outermost region of Guyane recorded the highest at-risk-of-poverty rate among NUTS level 2 regions, at 42.0% (2022 data). In 2023, the highest rates were observed in the southern Italian regions of Calabria (40.6%), Sicilia (38.0%) and Campania (36.1%). By contrast, at the other end of the distribution, there were 9 regions where the at-risk-of-poverty rate was no higher than 7.5%

the Czech and Romanian capital regions of Praha (6.9%) and Bucureşti-Ilfov (2.1%), the latter recording the lowest rate in the EU
the Hungarian regions of Nyugat-Dunántúl (7.3%) and Közép-Dunántúl (6.3%)
the Belgian regions of Prov. West-Vlaanderen (6.9%) and Prov. Oost-Vlaanderen (5.4%)
the Italian regions of Provincia Autonoma di Trento (7.5%), Emilia-Romagna (5.8%) and Provincia Autonoma di Bolzano/Bozen (3.9%).

There was considerable degree of inter-regional variation in at-risk-of-poverty rates for the different regions of Belgium, Italy and Romania

the rate in the Belgian capital Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest was 5.1 times as high as that recorded in Prov. Oost-Vlaanderen
the rate in the southern Italian region of Calabria was 10.4 times as high as that recorded in northern region of Provincia Autonoma di Bolzano/Bozen
the rate in Sud-Vest Oltenia was 14.9 times as high as that recorded in the Romanian capital region of Bucureşti-Ilfov.

In 2023, the risk of monetary poverty in the EU was reduced from 24.8% to 16.2% as a result of the redistributive impact of social transfers

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 shows the redistributive impact of social transfers and the extent to which they reduce the risk of monetary poverty, reflecting, among other influences, historical, political, economic and cultural factors. In 2023, the EU’s at-risk-of-poverty rate before social transfers was 24.8%. It was reduced by 8.6 percentage points to 16.2% after social transfers. Social transfers had a high impact on reducing the risk of poverty across many regions of Belgium, Denmark, Ireland, southern Italy and Poland.

Figure 2 is split into 2 parts: the left-hand side presents the regions in the EU with the highest and lowest at-risk-of-poverty rates before social transfers. Prior to social transfers, there were 4 NUTS level 2 regions that recorded considerably higher rates than in any other region of the EU, with upwards of 40.0% of their populations facing the risk of monetary poverty in 2023: the southern Italian regions of Calabria (51.9%), Campania (51.7%) and Sicilia (49.1%), and the Belgian capital Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (47.1%). At the lower end of the distribution, there were 3 EU regions where less than 10.0% of the population faced the risk of monetary poverty: the Romanian capital region of Bucureşti-Ilfov (4.8%), the northern Italian region of Provincia Autonoma di Bolzano/Bozen (8.2%) and the Slovak capital region of Bratislavský kraj (9.0%).

The right-hand side of Figure 2 shows the regions with the highest and lowest at-risk-of-poverty rates after social transfers. Having taken account of the redistributive impact of social transfers, only Calabria continued to report that more than 40.0% of its population was at risk of monetary poverty, while Sicilia and Campania were the only other regions in the EU where the risk of monetary poverty after social transfers was more than twice as high as the EU average (16.2%).

Social transfers played an important role in reducing the risk of poverty across several Belgian, Danish, Irish and Italian regions

the biggest reduction – in percentage point terms – was recorded in the Irish region of Northern and Western (where the at-risk-of-poverty rate fell by 19.8 points), while Southern (down 16.7 points) and the capital region of Eastern and Midland (down 15.0 points) also recorded considerable falls
large reductions were recorded in 2 out of the 3 NUTS level 1 regions of Belgium, as the redistributive impact of social transfers was considerable in Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (down 19.4 percentage points) and Région wallonne (down 15.8 points)
in 4 out of 5 Danish regions – the exception being the capital region of Hovedstaden – social transfers reduced the share of the population facing the risk of poverty by more than 10.0 percentage points, the biggest fall was recorded in Nordjylland (down 15.6 points)
there were 7 southern Italian regions where the redistributive impact of social transfers reduced the risk of monetary poverty by more than 10.0 percentage points, the biggest fall was recorded in Campania (down 15.6 points).

At the other end of the scale, there were 29 regions in the EU where the redistributive impact of social transfers resulted in the at-risk-of-poverty rate falling by no more than 5.0 percentage points in 2023. These 29 regions were principally concentrated in Greece, Croatia, northern Italy, Portugal (national data) and Romania.

Figure 2: At-risk-of-poverty rate before and after social transfers, 2023
(%, by NUTS 2 regions)
Source: Eurostat (ilc_li10_r), (ilc_li41), (ilc_li10) and (ilc_li02)

Severe material and social deprivation

The severe material and social deprivation rate provides information on people experiencing an enforced lack of items that are necessary and desirable to lead an adequate life (individuals who can’t afford a certain good, service or social activity). The 2024 edition of the Eurostat Regional Yearbook marks the 1st time that regional data have been published for this indicator.

In 2023, there were 29.3 million people across the EU that were facing severe material and social deprivation; this was equivalent to 6.8% of the total population. The severe material and social deprivation rate had previously stood at 6.3% in 2021 but increased by 0.4 percentage points in 2022 and by a further 0.1 points in 2023; these recent rises may be linked, at least in part, to the cost-of-living crisis.

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 him/herself
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

Sud-Est in Romania had the highest severe material and social deprivation rate among NUTS level 2 regions, at 30.8% in 2023

Figure 3 shows the regional distribution of severe material and social deprivation rates. Many of the highest regional rates were observed in the south-eastern corner of the EU, while the lowest rates tended to be concentrated in Czechia, northern/central Italy, the Netherlands, Austria and Poland.

In 2023, the highest regional share of people experiencing severe material and social deprivation was recorded in Sud-Est in Romania (30.8%). There were 8 other regions in the EU where more than 20.0% of the population faced severe material and social deprivation

Severen tsentralen (25.0%), Yuzhen tsentralen (23.9%) and Yugoiztochen (22.9%) in Bulgaria
Sud-Vest Oltenia (24.8%) and Sud-Muntenia (23.7%) in Romania
Észak-Magyarország (21.4%) in Hungary
Calabria (20.7%) in Italy
Dytiki Elláda (20.2%) in Greece.

At the other end of the distribution, every region in Czechia, Ireland, Croatia, Lithuania, the Netherlands, Poland, Slovenia, Finland and Sweden had a severe material and social deprivation rate that was less than the EU average of 6.8% in 2023; this was also the case in Estonia, Cyprus, Latvia, Luxembourg and Malta. There were 4 regions in the EU where the severe material and social deprivation rate was less than 1.0%

Flevoland (0.7%) in the Netherlands that had the lowest rate in the EU
Provincia Autonoma di Bolzano/Bozen (0.8%) and Emilia-Romagna (0.9%) in Italy
Mellersta Norrland (0.9%) in Sweden.

Figure 3: Severe material and social deprivation rate, 2023
(%, by NUTS 2 regions)
Source: Eurostat (ilc_mdsd18) and (ilc_mdsd11)

As noted above, the EU’s severe material and social deprivation rate was 0.1 percentage points higher in 2023 than in 2022, with the rate increasing in 122 out of the 215 regions for which data are available. By far the biggest increase was observed in the southern Italian region of Calabria (up 8.9 percentage points). The next highest increases were recorded in the Greek region of Dytiki Makedonia (up 4.8 points) and the Hungarian regions of Észak-Magyarország (up 4.5 points) and Dél-Dunántúl (up 4.1 points). There were 9 more regions across the EU where the severe material and social deprivation rate increased by at least 3.0 points between 2022 and 2023

5 that were principally located in northern and western Germany – Bremen, Münster, Rheinhessen-Pfalz, Saarland and Gießen
Nordjylland, the northernmost region of Denmark
the southern Spanish Región de Murcia
the Austrian capital region of Wien
the southern Italian region of Puglia.

The largest fall for the severe material and social deprivation rate between 2022 and 2023 was reported in the Greek region of Sterea Elláda, where the rate fell from 15.4% to 9.1% (down 6.3 percentage points). There were 4 other regions across the EU where the severe material and social deprivation rate fell by more than 4.0 points

3 regions located in Romania – Nord-Est, Bucureşti-Ilfov and Sud-Muntenia
the autonomous Spanish region of Ciudad de Melilla.

Figure 4: Severe material and social deprivation rate, 2023
(by NUTS 2 regions)
Source: Eurostat (ilc_mdsd18) and (ilc_mdsd11)

People living in a household with very low work intensity

In 2023, there were 26.5 million people (aged 0–64) in the EU living in a household with very low work intensity, this equated to 8.0% of this subpopulation. In 2021, the share of people living in a household with very low work intensity had been 9.0%: it fell at a relatively fast pace in 2022 (down 0.7 percentage points), with a more modest reduction in 2023 (down a further 0.3 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 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 18–64 (excluding students aged 18–24 and those who are retired) who worked for 20% or less of their combined potential working time during the previous 12 months. Households composed only of children, of students aged less than 25 and/or of people aged 65 or more are excluded from the calculation of this indicator.

Figure 5 shows there was a relatively high degree of regional variation for the share of people living in households with very low work intensity. Across multi-regional EU countries the difference between the highest and lowest shares – as measured in percentage point terms – peaked in France (at 20.3 points; 2022 data), while relatively large regional variations were also observed across Italy (18.9 points), Germany (18.2 points), Belgium (17.7 points) and Spain (15.5 points).

Figure 5: People living in a household with very low work intensity, 2023
(%, by NUTS 2 regions)
Source: Eurostat (ilc_lvhl21n) and (ilc_lvhl11n)

Guyane in France had the highest share of people living in a household with very low work intensity among NUTS level 2 regions, at 28.1%

Figure 6 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 2023, the highest share was recorded in the French outermost region of Guyane (28.1%; 2022 data), while there were 7 other regions across the EU with shares of more than 20.0%

the French outermost regions of La Réunion (23.1%; 2022 data) and Guadeloupe (22.6%; 2022 data)
Bremen (21.8%) in Germany
Prov. Hainaut (21.5%) in Belgium
Campania (21.2%) and Calabria (20.9%) in southern Italy
the autonomous Spanish region of Ciudad de Melilla (20.3%).

At the lower end of the distribution, there were 10 NUTS level 2 regions where the share of people living in a household with very low work intensity was no more than 2.5% in 2023. This group was concentrated in Austria (3 regions), Romania and Italy (both 2 regions), while it also included single regions from each of Slovakia, Hungary and Poland. The Romanian capital region of Bucureşti-Ilfov (0.7%) and the Austrian region of Salzburg (0.8%) had the lowest values and were the only regions in the EU where the share of people living in a household with very low work intensity was less than 1.0%.

The right-hand side of Figure 6 shows the regions that experienced the biggest and smallest changes in their share of people living in a household with very low work intensity between 2022 and 2023. Across the EU, this share fell 0.3 percentage points in 2023, with a fall reported in more than half (120 out of 215) of the NUTS level 2 regions for which data are available. The largest fall in the share of people living in a household with very low work intensity was recorded in the Spanish autonomous region of Ciudad de Ceuta (down 10.8 percentage points). It was followed, at some distance, by the Austrian regions of Vorarlberg (down 5.4 points) and Tirol (down 4.6 points), and the Dutch region of Groningen (also down 4.6 points).

Among the 92 NUTS level 2 regions that reported a rising share of people living in a household with very low work intensity between 2022 and 2023, the highest increases were recorded in the Romanian regions of Sud-Est (up 7.9 percentage points) and Vest (up 6.9 points), and the German regions of Sachsen-Anhalt (up 5.7 points) and Münster (up 4.3 points).

Figure 6: People living in a household with very low work intensity, 2023
(by NUTS 2 regions)
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 doesn’t account for income paid/received across borders. Nor does it capture the distribution of income within a population and thereby does little to reflect economic inequalities. Consequently, social scientists are increasingly using alternative/broader measures in their quest to gain a more comprehensive and nuanced understanding of economic and societal developments.

The unequal distribution of income/wealth has gained increasing importance in political and socioeconomic discourse since the global financial and economic crisis and, more recently, during the cost-of-living-crisis. It is also a key issue when examining regions that 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 statistics on income refers to the calendar year before the year in which the survey took place.

In 2023, 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.

In 2023, the southern Italian region of Calabria had the highest income quintile share ratio, at 8.5

Map 3 shows the regional distribution of the income quintile share ratio. In 2023, its regional distribution was skewed: 83 out of 124 regions for which data are available had a ratio that was below the EU average, while there were 3 regions that had the same ratio, and 38 regions that reported income disparities that were greater than the EU average.

At the top end of the distribution, there were 12 NUTS level 2 regions where the income quintile share ratio was at least 6.0 in 2023 (as shown by the darkest shade of blue in Map 3). The highest ratios were concentrated in Bulgaria, Italy, the northern EU countries and Romania, with a peak registered in the southern Italian region of Calabria (where the income of the top 20% of earners was 8.5 times as high as the income of the bottom 20% of earners). The next highest ratios were observed in the Romanian region of Sud-Vest Oltenia (7.4) and the Bulgarian capital region of Yugozapaden (7.0).

At the other end of the range, the distribution of income was most equitable for a group of regions that spanned several eastern EU countries, while relatively low ratios were also recorded across several regions in the Benelux and Nordic EU countries. In 2023, the lowest income quintile share ratio was recorded in the Slovak capital region of Bratislavský kraj, where the share of total income held by the highest earning 20% of the population was 2.7 times as high as the share held by the lowest earning 20% of the population.

Within multi-regional EU countries, the distribution of income often had a different pattern in the capital region when compared with the rest of each territory. In 2023, it was commonplace to find that the capital region had the highest income quintile share ratio. This was the case in Belgium (4.6; NUTS level 1), Bulgaria (7.0), Ireland (3.9), Lithuania (6.8), the Netherlands (4.3; NUTS level 1), Poland (5.0), Slovenia (3.4) and Finland (4.2). By contrast, this pattern was reversed in Romania and Slovakia, where the lowest income quintile share ratios were recorded in the capital regions of Bucureşti-Ilfov (3.8) and Bratislavský kraj (2.7).

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 data shown are based on crime rates: the number of police-recorded crimes per 100 000 inhabitants for NUTS level 2 regions. These rates were subsequently indexed to show deviations from the national average of each country (with the national average = 100).

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.

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).

More information about how crimes are classified across EU regions may be found in the metadata.

Based on the latest information available, there were an estimated 483 000 police-recorded domestic burglaries across the EU in 2022 (no information available for Ireland, France, Cyprus and Hungary; 2021 data for Luxembourg and Poland). The number of domestic burglaries in the EU declined between 2014 and 2021, before increasing in 2022.

Figure 7 shows the regional distribution of burglaries of private residential premises, as recorded by the police. There were considerable regional variations in most multi-regional EU countries: this was particularly the case across Germany and Greece, where the region with the highest incidence of burglaries had a crime rate that was more than 10 times as high as the region with the lowest incidence.

In 2022, capital regions recorded the highest incidence of burglaries of private residential premises in Belgium, Czechia, Croatia, Lithuania, Austria, Romania, Slovenia and Slovakia. By contrast, the lowest incidence of burglaries was usually recorded in a predominantly rural region. For those EU countries where the capital region didn’t have the highest incidence of burglaries, the highest rate was generally recorded in a predominantly urban region or a region known as a holiday destination. For example, the highest incidence

in Germany was recorded in Bremen (2.60 times as high as the national average; 2019 data)
in Spain was recorded in Comunitat Valenciana (1.58 times as high as the national average)
in France was recorded in Provence-Alpes-Côte d’Azur (1.47 times as high as the national average)
in Italy was recorded in Emilia-Romagna (1.43 times as high as the national average)
in the Netherlands was recorded in Utrecht (1.14 times as high as the national average)
in Portugal was recorded in Região Autónoma dos Açores (1.87 times as high as the national average).

Figure 7: Burglary of private residential premises recorded by the police, 2022
(national average = 100, by NUTS 2 regions)
Source: Eurostat (crim_gen_reg)

Figure 8 shows how crime rates for burglaries of private residential premises developed over the period 2012–22, with selected regional examples for the Netherlands, Austria and Portugal (that show the 3 NUTS level 2 regions with the largest falls in their crime rates). In both the Netherlands and Portugal there was a relatively steady decline in crime rates during the period under consideration, whereas rates initially rose in Austria, particularly in Salzburg, before following a downward trend.

Figure 8: Burglary of private residential premises recorded by the police, 2012–22
(2012 = 100, selected NUTS 2 regions)
Source: Eurostat (crim_gen_reg)

More about the data: statistics on theft

Theft is defined as taking property unlawfully – without violence, force, threat, coercion, or deception – with the intent to keep it permanently without consent

it includes car theft, bicycle theft, animal theft, shoplifting and pickpocketing
it excludes possession, receiving, handling, disposing, selling or trafficking stolen goods or money; using stolen parts for producing other goods; concealment of stolen goods; fraud, robbery, burglary, damage; intellectual property crimes, identity misuse.

Theft of motorised land vehicles includes stealing cars, motorcycles, buses, coaches, lorries, trucks, bulldozers, and so on.

More information about how crimes are classified across EU regions may be found in the metadata.

Police-recorded thefts across the EU numbered 5.09 million in 2022, which equates to an average of 1 140 thefts per 100 000 inhabitants. Only a partial set of data are available for the theft of motorised land vehicles, of which there were 309 730 in 2022 (this aggregate is based on 2021 data for Germany and excludes France, Cyprus and Hungary).

Figure 9 shows the regional distribution of thefts of motorised land vehicles as recorded by the police. It was relatively common for capital regions to record the highest incidence of theft for motorised land vehicles. For example, in the Polish capital region of Warszawski stołeczny, the crime rate was 84.0 thefts of motorised land vehicles per 100 000 inhabitants in 2022, which was more than 4 times as high as the national average (19.6 per 100 000 inhabitants). Where the capital region didn’t record the highest incidence, it was nevertheless common for the capital region to record a relatively high crime rate, for example

in Bulgaria, the eastern region of Severoiztochen had the joint highest rate with the capital region of Yugozapaden
in Spain, only Ciudad de Ceuta and Illes Balears had higher rates
in France, only Provence-Alpes-Côte d’Azur had a higher rate
in Italy, only Campania, Puglia and Sicilia had higher rates
in the Netherlands, only Limburg had a higher rate
in Finland, only Åland had a higher rate
in Sweden, only Norra Mellansverige and Västsverige had higher rates.

Among the EU countries, Wien in Austria and Área Metropolitana de Lisboa in Portugal were the only capital regions where crime rates for the theft of motorised land vehicles were below their respective national averages. In 2022, the highest rate in Austria was recorded in Tirol, while the highest rate in Portugal was recorded in Algarve.

In 2022, there were considerable variations in crime rates across the regions of Italy, Poland, Spain, Greece and Germany (2019 data), as the region with the highest incidence for the theft of motorised land vehicles had an index that was more than 10 times as high as the region with the lowest incidence. For example,

the southern Italian region of Campania had a rate that was 2.66 times as high as the national average, while the northern region of Provincia Autonoma di Trento had a rate that was approximately 10% of the national average
the Polish capital region of Warszawski stołeczny had a rate that was 4.29 times as high as the national average, while the relatively rural, south-eastern region of Podkarpackie had a rate that was approximately a 20% of the national average.

By contrast, there were relatively small inter-regional differences concerning the theft of motorised land vehicles in 2022 in Lithuania, Austria and the Nordic EU countries. For example, the central Swedish region of Norra Mellansverige had the highest rate (1.07 times as high as the national average), while the south-eastern region of Småland med öarna had the lowest rate (approximately 75% of the national average).

Figure 9: Theft of a motorised land vehicle recorded by the police, 2022
(national average = 100, by NUTS 2 regions)
Source: Eurostat (crim_gen_reg)

Figure 10 shows how crime rates for the theft of motorised land vehicles developed during the period 2012–22, with selected regional examples for Czechia, Slovakia and Finland (based on the NUTS level 2 regions with the largest falls in their crime rates). Across all 3 countries, there was a marked reduction in the incidence of thefts of motorised land vehicles: for example, crime rates in the 3 Czech regions had fallen in 2022 to less than 20% of their original level from 2012.

In Czechia and in Slovakia, the largest falls in the incidence of theft of motorised land vehicles during the period 2012–22 were observed in the capital regions of Praha and Bratislavský kraj. By contrast, there were 2 regions in Finland – Etelä-Suomi and Pohjois- ja Itä-Suomi – which recorded falls in their crime rates that were larger than those experienced in the capital region of Helsinki-Uusimaa (where developments over the last decade followed a fluctuating but nevertheless downward trend).

Figure 10: Theft of a motorised land vehicle recorded by the police, 2012–22
(2012 = 100, selected NUTS 2 regions)
Source: Eurostat (crim_gen_reg)

In 2022, there were 3 862 police-recorded intentional homicides across the EU; this figure marked an increase of 4.4% compared with a year before. Expressed in relation to its population, there were 0.86 intentional homicides per 100 000 inhabitants.

More about the data: statistics on intentional homicide

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 those jurisdictions with small populations, whereby a small increase/decrease in the number of homicides may lead to a relatively large change in crime rates.

Figure 11 shows the regional distribution of intentional homicides recorded by the police. In 2022, most EU countries were characterised by a relatively narrow range of inter-regional variations for crime rates concerning intentional homicides. A different pattern was observed in Spain and France, as the incidence of intentional homicide was substantially higher in the autonomous cities of Spain and most of the outermost regions of France (La Réunion was an exception). Most of these regions have relatively small populations, so an increase in the number of homicides would likely have a significant impact on their homicide rates per 100 000 inhabitants.

In 2022, the French outermost region of Guyane had the highest incidence of intentional homicide among NUTS level 2 regions, at 13.5 per 100 000 inhabitants. This was approximately twice as high as in any other region of the EU: the 2nd and 3rd highest rates were also recorded in French outermost regions, namely, Martinique (6.8 per 100 000 inhabitants) and Guadeloupe (6.6 per 100 000 inhabitants).

Within the multi-regional EU countries, the highest incidences of intentional homicide in 2022 were recorded in the capital regions of Belgium (joint highest with Prov. Hainaut), Czechia, Germany (2019 data), Ireland, Lithuania and Slovakia. By contrast, the capital regions of Bulgaria, Denmark, Greece, France, Italy, Poland, Romania and Slovenia recorded rates that were lower than their respective national averages.

Figure 11: Intentional homicide recorded by the police, 2022
(national average = 100, by NUTS 2 regions)
Source: Eurostat (crim_gen_reg)

Source data for figures and maps

Living conditions at regional level

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 share of the total population.

In 2021, the calculation of the number/share 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 low work intensity through the inclusion of adults aged 60–64 (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).

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 doesn’t 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 doesn’t 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 couldn’t afford at least 7 out of 13 deprivation items. The indicator distinguishes between individuals who can’t afford a certain good or service, and those who don’t have this good or service for another reason, for example, because they don’t want or don’t need it.

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 18–64, excluding students aged 18–24 and retired people) who worked for 20% or less of their combined potential working time during the previous 12 months. Households composed only of children, of students aged less than 25 and/or of people aged 65 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 above for an explanation).

Crimes recorded by the police

Crime statistics presented in this chapter 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 isn’t aware that a crime has occurred, doesn’t to report it or is failed by the police in recording it, then that crime won’t 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 aren’t recorded accurately. By contrast, reporting rates are likely to be more robust for crimes such as the theft of a car 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 allows comparisons to be made between regions from different countries and analyses of territorial differences, such as those between predominantly rural and predominantly urban regions.

Context

The COVID-19 crisis had a direct and indirect impact on vulnerable groups such as the elderly, young people, parents of pre-school and school age children (particularly single-parents), low-wage earners, women, migrants, people with disabilities, people with precarious work contracts and those living in areas with limited or no digital connectivity. Some of these groups faced a higher risk of income loss due to increasing unemployment and reduced possibilities for teleworking, while disruptions to services (especially for health and education) may also have exacerbated existing inequalities.

Aside from putting huge pressure on health care services, the pandemic also resulted in considerable demands for additional support from social and welfare services. There was an extensive political debate over how best to respond to the socioeconomic crisis. This reflected, among other issues, the balance between concerns over public finances and the need for further spending on healthcare, education and social protection.

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: one 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).

Under the heading of fostering social inclusion and combatting poverty, the EU plans actions to

break intergenerational cycles of disadvantage
review the adequacy and coverage of minimum income schemes
provide access to affordable housing through raising the quality of the existing housing stock
extend access to essential services, such as water, sanitation, healthcare, energy, transport, financial services and digital communications.

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 will be able to trust and rely on each other. This will 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.

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 (for example, measures against those seeking to circumvent EU sanctions against Russian and Belarussian individuals), as listed in Article 83(1) of the Treaty on the Functioning of the European Union.

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.