Energy poverty indicators dashboard

On this page, you may find EPAH indicators organised by topics for each European country. In this indicators collection, we use publicly available EU-wide datasets, so you may find that some data is unavailable for specific years or countries due to the timeline of data collection for such datasets, their geographical coverage or the update at the EU level of these statistics. However, this does not mean that the specific country does not have this or similar information to explore. You may like to visit national statistical databases to find more details on a particular topic.

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Arrears (mortgage or rent, utility bills or hire purchase)

At-risk-of-poverty rate

Cold stress days

Excess mortality during summer

Heat stress days

Population living in dwellings whose energy efficiency improved in the last 5 years

Population living in a dwelling not comfortably warm during winter

Population using or not public transport, by frequency

Population who cannot afford a personal car

Population living in private households by heating system used in the dwelling

Household final consumption expenditure by purpose

Household final consumption expenditure allocated to transport costs

Households unable to keep dwelling comfortably cool in the summer

Population that is Materially and Socially Deprived (MSD) and owns a car

Arrears on utility bills

Excess mortality during winter

At risk of poverty or social exclusion

Causes of death

Cooling degree days

Disposable annual household income

Dwellings with energy label A

Energy expenses by income quintile

Energy prices

Excess winter mortality/deaths

Final energy consumption in households by energy use

Final energy consumption in households by type of fuel

Heating degree days

High share of energy expenditure in income (2M)

Housing cost overburden rate

Inability to keep home adequately warm

Low absolute energy expenditure (M/2)

Population considering their dwelling as too dark

Population living in a dwelling equipped with air conditioning

Population living in a dwelling equipped with heating facilities

Population living in a dwelling with presence of leak, damp and rot

Population living in dwellings comfortably cool in summer time

Population living in dwellings comfortably warm in winter time

Population reporting a chronic disease

Population who cannot afford a regular use of public transport

No disaggregation

All causes of death excluding injury, poisoning and certain other consequences of external causes

Accidental poisoning by and exposure to noxious substances

Diseases of the circulatory system

Diseases of the respiratory system

Diseases of the skin and subcutaneous tissue

Mental and behavioural disorders

Tuberculosis

Total by NUTS region

Total

Above 60% of median equivalised income

Accommodation is provided free

Accommodation is rented at a reduced rate

Apartment or flat in a building with 10 or more dwellings

Apartment or flat in a building with less than 10 dwellings

Apartment house

Below 60% of median equivalised income

Densely populated

Detached house

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Income 7

Income 8

Income 9

Income 10

Income quintile 1

Income quintile 2

Income quintile 3

Income quintile 4

Income quintile 5

Intermediate populated

Intermediate urbanisation

One adult 65 years or over

Outright owner

Owner paying mortgage

Semi-detached or terraced house

Semi detached or terraced house

Single person with dependent children

Tenant/subtenant paying rent at market rate

Tenant/subtenant paying rent at reduced or free rate

Thinly populated

Two adults with three or more dependent children

Asthma

Chronic lower respiratory diseases (excluding asthma)

Coronary heart disease or angina pectoris

Heart attack or chronic consequences of heart attack

High blood lipids

High blood pressure

Stroke or chronic consequences of stroke

Cities

From 16 to 29 years

Females

From 16 to 64 years

65 years or over

First quintile

Second quintile

Third quintile

Fourth quintile

Fifth quintile

Household composed of one adult 65 years or over

Household composed of one adult with dependent children

Household composed of two adults with three or more dependent children

Males

Owner, no outstanding mortgage or housing loan

Owner, with mortgage or loan

Rural areas

Tenant, rent at market price

Tenant, rent at reduced price or free

Total

Towns and suburbs

Accommodation is provided free

Accommodation is rented at a reduced or free rate

Accommodation is rented at a reduced rate

Apartment or flat in a building with 10 or more dwellings

Apartment or flat in a building with less than 10 dwellings

Apartment house

Country averages

Country average

Densely populated

Detached house

Households with arrears on utility bills at least twice per year

Households with arrears on utility bills once per year

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Income 7

Income 8

Income 9

Income 10

Income quintile 1

Income quintile 2

Income quintile 3

Income quintile 4

Income quintile 5

Intermediate populated

Intermediate urbanisation

No disaggregation

Outright owner

Owner paying mortgage

Semi-detached or terraced house

Tenant/subtenant paying rent at market rate

Thinly populated

Urbanisation densely populated

From 16 to 29 years

Total by NUTS region

Total

Females

From 18 to 64 years

65 years or over

Above 60% of median equivalised income

Below 60% of median equivalised income

Males

Densely populated

Income decile 1

Income decile 2

Income decile 3

Income decile 4

Income decile 5

Income decile 6

Income decile 7

Income decile 8

Income decile 9

Income decile 10

Intermediate urbanisation

No disaggregation

Thinly populated

Total

From 16 to 29 years

From 16 to 64 years

65 years or over

Females

Above 60% of median equivalised income

Below 60% of median equivalised income

First quintile

Second quintile

Third quintile

Fourth quintile

Fifth quintile

Males

Not employed persons

Other persons outside the labour force (former name: inactive persons)

Retired persons

Unemployed persons

Energy expenses, income quintile 1

Energy expenses, income quintile 2

Energy expenses, income quintile 3

Energy expenses, income quintile 4

Energy expenses, income quintile 5

Cooking

Total

Lighting and electrical appliances

Space cooling

Space heating

Water heating

Other end use

Household electricity prices

Biomass prices

Coal prices

District heating prices

Fuel oil prices

Household natural gas prices

Densely populated

Income decile 1

Income decile 2

Income decile 3

Income decile 4

Income decile 5

Income decile 6

Income decile 7

Income decile 8

Income decile 9

Income decile 10

Intermediate urbanisation

No disaggregation

Thinly populated

Total

Less than 18 years

From 18 to 64 years

65 years or over

Above 60% of median equivalised income

Below 60% of median equivalised income

One adult 65 years or over

Females

Single person with dependent children

Males

Two adults with three or more dependent children

Ambient heat (heat pumps)

Biogases

Electricity

Total

Heat

Natural gas

Oil and petroleum products

Primary solid biofuels

Solar thermal

Solid fossil fuels, peat, peat products, oil shale and oil sands

Total

Females

Males

Arrears by NUTS region

Total

0-14 years

15-44 years

45-64 years

65-74 years

65+ years

75-84 years

85+ years

16 years or over

65 years or over

At risk of poverty or social exclusion

Cities

Female

From 16 to 29 years

From 16 to 44 years

From 16 to 64 years

From 25 to 34 years

From 35 to 44 years

From 45 to 64 years

Household with dependent children

Household without dependent children

Male

None

Not at risk of poverty or social exclusion

One adult

One adult 65 years or over

One adult with dependent children

One adult younger than 65 years

One single female

One single male

Rural areas

Serve

Some

Some or severe

Three or more adults

Three or more adults with dependent children

Total

Towns and suburbs

Two adults

Two adults with dependent children

Two adults with three or more dependent children

Two adults younger than 65 years

Two adults, at least one aged 65 years or over

Two or more adults with dependent children

Two or more adults without dependent children

16 years or over

65 years or over

At risk of poverty or social exclusion

Cities

Female

From 16 to 29 years

From 16 to 44 years

From 16 to 64 years

From 25 to 34 years

From 35 to 44 years

From 45 to 64 years

Household with dependent children

Household without dependent children

Male

None

Not at risk of poverty or social exclusion

One adult

One adult 65 years or over

One adult with dependent children

One adult younger than 65 years

One single female

One single male

Rural areas

Severe

Some

Some or severe

Three or more adults

Three or more adults with dependent children

Total

Towns and suburbs

Two adults

Two adults with dependent children

Two adults with three or more dependent children

Two adults younger than 65 years

Two adults, at least one aged 65 years or over

Two or more adults with dependent children

Two or more adults without dependent children

16 years or over

18 years or over

60 years or over

65 years or over

75 years or older

Cut-off point: 40% of mean equivalised income

Cut-off point: 40% of the median equivalised income

Cut-off point: 50% of mean equivalised income

Cut-off point: 50% of median equivalised income

Cut-off point: 60% of mean equivalised income

Cut-off point: 60% of median equivalised income after social transfers

Cut-off point: 70% of median equivalised income

Female

From 12 to 17 years

From 15 to 19 years

From 15 to 24 years

From 15 to 29 years

From 16 to 19 years

From 16 to 24 years

From 16 to 29 years

From 16 to 64 years

From 18 to 24 years

From 18 to 64 years

From 20 to 24 years

From 20 to 29 years

From 25 to 29 years

From 25 to 49 years

From 25 to 54 years

From 50 to 64 years

From 55 to 64 years

From 6 to 11 years

From 65 to 74 years

Less than 16 years

Less than 18 years

Less than 6 years

Less than 60 years

Less than 65 years

Less than 75 years

Male

Total

Above 60% of median equivalised income

Below 60% of median equivalised income

Households with dependent children

Households without dependent children

One adult 65 years or over

One adult younger than 65 years

Single female

Single male

Single person

Single person with dependent children

Three or more adults

Three or more adults with dependent children

Total

Two adults

Two adults with one dependent children

Two adults with three or more dependent children

Two adults with two dependent children

Two adults younger than 65 years

Two adults, at least one aged 65 years or over

Actual rental payments made for housing

Electricity, gas, and other fuels

Food and non-alcoholic beverages

Health

Goods and services for routine household maintenance

Imputed rental payments made for housing

Maintenance, repair and security of the dwelling

Water supply and miscellaneous services related to the dwelling

Central heating

District heating network/teleheating

Individual heating

No fixed heating

No heating

Unknown

Every day

Every month

Every week

Less than once a month

Never

Operational of personal transport equipment

Passenger transport services

Purchase of vehicles

Total

Transport services for goods

Total

0-14 years

15-44 years

45-64 years

65-74 years

75-84 years

65+ years

85+ years

Total cold stress days (min. daily temperature below 9°C)

Very strong (min. daily temperature between -40°C and -27°C)

Extreme (min. daily temperature below -40°C)

Strong (min. daily temperature between -27°C and -13°C)

Moderate (min. daily temperature between -13°C and 0°C)

Slight (min. daily temperature between 0°C and 9°C)

Total heat stress days (max. daily temperature above 26°C)

Very strong (max. daily temperature between 38°C and 46°C)

Extreme (max. daily temperature above 46°C)

Strong (max. daily temperature between 32°C and 38°C)

Moderate (max. daily temperature between 26°C and 32°C)

If the EU-average is marked with an asterisk (*), the value is calculated based on the country's data and is not provided by Eurostat.

Unit

Households (%)

Share of households (%)

Population (%)

% of population

Rate

Number of days

Purchasing power standard (PPS, EU27 from 2020), per inhabitant

% of dwellings

% of energy expenses on income

Population (%)

EUROSTAT Population (%)

Number of days

EUROSTAT Population (%)

Population (%)

% of population

Population (%)

% of population

EUROSTAT Population (%)

number of deaths per 100,000 inhabitants

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

Households (%)

Population (%)

% of energy expenses on income

[PJ] PetaJoule

€/kWh

Households (%)

Population (%)

[PJ] PetaJoule

[TJ] Terajoule

[PJ] PetaJoule

Population (%)

Households (%)

Average z-score value

Population (%)

Share of household final consumption expenditure (%)

Population (%)

Share of household final consumption expenditure (%)

Average z-score value

Number of days

Source

JRC (based on EU-SILC data)

Oeko-Institut and DG EMPL

EU-SILC and JRC128084" target="_blank">JRC

EUROSTAT

Building Stock Observatory

EU-SILC

Building Stock Observatory

EU-SILC

EU-SILC

EU-SILC and JRC

EU-SILC and JRC

HBS

EU-SILC

Building Stock Observatory

HBS

Data reporting period

2023/2025

2023

2016/2019/2022

2020

2004-2025

2004-2024

2007-2015

2015

2005-2014

2004-2025

2007

2007/2012

2011-2021

2004-2025

2014/2019

2014-2025

2004-2025

2021-2025

2010/2015/2020

2014

2005/2010/2015/2020

2010-2024

2007-2025

2005-2015

2004-2008/2015

2004-2015

2007-2025

2010/2015/2020

2007/2012

2010-2024

2010-2020/2023

2021-2025

2019-2025

2023

2023/2025

2003-2025

2023

2024

2003-2025

2019-2025

2003-2024

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Dataset: CSV / EXCEL

Map: PNG

Compare countries

Bear in mind

This indicator provides valuable insight into national progress towards improving household energy efficiency. However, it does not differentiate between types or depth of energy efficiency measures, treating a single window replacement equally to a deep renovation. Moreover, it does not capture the impacts of applied measures on thermal comfort or energy expenditure.

Click here to explore previous national data for 2007 and 2012. These data are presented as the share of the population living in dwellings that are comfortably warm during winter time, representing a contrasting measure to this indicator.

Click here to explore previous national data for 2007 and 2012. These data are presented without disaggregation options by heating system type, contrary to what is reported for this indicator.

This indicator offers relevant insight into summer energy poverty conditions linked to dwelling insulation and cooling system adequacy, a dimension not fully captured by other indicators, which predominantly focus on winter conditions. However, it does not precisely identify the underlying causes of thermal discomfort, and perceived thermal comfort may vary culturally, regionally, and over time. Non-recognition of energy poverty by vulnerable households may also affect reported results.

Click here to explore previous national data for 2007 and 2012. These data refer to the share of the population living in dwellings that are comfortably cool during summer, providing an inverse measure of this indicator. Note that, unlike the current indicator, which is based on the share of households, the previous data are expressed as a share of the population.

This indicator captures an important dimension of transport poverty. However, it does not identify the reasons for car ownership, such as lack of adequate public transport, unaffordable transport alternatives, reduced mobility, or personal preferences, which are relevant for distinguishing forced ownership from other conditions. Disaggregation by degree of urbanisation is also unavailable, limiting analysis of rural versus urban patterns.

Click here to explore previous national data for 2005 to 2014. These data refer to excess winter mortality/deaths, expressed as a share of the population. Note that these data are drawn from a different source (Building Stock Observatory) and use a different calculation method; therefore, they cannot be directly compared with the current indicator.

This indicator may primarily capture poverty in general, cross-examination with impact assessments of energy-related social policies would be needed for using the indicator in an energy poverty diagnosis.
Learn more

This indicator measures climate-driven cooling energy needs intrinsically connected to energy poverty vulnerability. However, it does not account for building energy efficiency or household affordability, which can vary significantly across households and regions. As it focuses on average daily temperatures, it is less suited to capturing short-term fluctuations such as heat waves, which can considerably impact residential energy consumption and thermal comfort. Cross-analysis with indicators such as "Cold stress days", "Heat stress days", "Final Energy Consumption in Households", and "Inability to heat or cool" contributes to a deeper understanding of energy poverty vulnerability.

Disposable income is a key determinant of energy poverty vulnerability, as low income levels directly constrain households' capacity to meet energy needs. However, this indicator cannot fully reflect the complexity of energy poverty and should be complemented with indicators on energy expenditure, thermal comfort, and dwelling energy efficiency to support a more complete assessment of household vulnerability across Member States.

Being the only indicator that directly focuses on this dimension, it is of significant relevance for national assessments. However, focusing only on energy label A leaves behind information on the worst performing buildings, and additional indicators on the economic and social dimensions can significantly expand the use and relevance of this indicator in an energy poverty diagnosis.

This indicator captures one of the most severe potential consequences of winter energy poverty but cannot establish a direct causal link without cross-analysis with complementary indicators. Note that this indicator has been updated by the "Excess mortality during winter" and "Excess mortality during summer" indicators, which use more recent data and improved methodology based on weekly z-scores. Cross-analysis with building energy efficiency, energy expenditure, income, and access to medical services indicators is recommended to contextualise mortality patterns.

This indicator measures climate-driven heating energy needs intrinsically connected to energy poverty vulnerability. However, it does not account for building energy efficiency or household affordability, which can vary significantly across households and regions. As it focuses on average daily temperatures, it is less suited to capturing short-term fluctuations such as cold spells, which can considerably impact residential energy consumption and thermal comfort. Cross-analysis with indicators such as "Heat stress days", "Cold stress days", "Final Energy Consumption in Households", and "Inability to heat or cool" contributes to a deeper understanding of energy poverty vulnerability.

This indicator reflects the availability of active cooling equipment but does not capture whether households are able or willing to use it. A household may avoid using air conditioning due to high electricity prices, avoid high energy bills or rely on alternative equipment for space heating in winter. Cross-analysis with indicators on electricity prices, thermal comfort, and energy expenditure is recommended to assess the full relationship between air conditioning ownership and energy poverty vulnerability.

Ownership of heating equipment does not guarantee its regular or adequate use. Cross-analysis with data on space heating patterns, including duration, schedule, proportion of space heated, energy carrier type, and equipment age and efficiency, can provide more detailed insight into actual heating conditions. Combined with indicators on energy prices, thermal comfort, and energy expenditure, this indicator contributes to a more comprehensive understanding of winter energy poverty vulnerability.

Summer energy poverty is a growing concern in the EU and remains an underexplored dimension of energy vulnerability. Combined with data on cooling system ownership and space cooling consumption patterns, this indicator supports a more comprehensive understanding of summer energy poverty. It contrasts with the "Households unable to keep dwelling comfortably cool in summer", which captures a potential opposite condition. Learn more

As a self-reported indicator, results are influenced by subjective factors, including gender, age, socioeconomic situation, culture, and social practices, which may produce varying outcomes within and across countries. It should be read alongside the "Inability to keep home adequately warm" indicator, which captures affordability-driven inability, and contrasts with "Population living in a dwelling not comfortably warm in winter time", which captures a potential opposite condition. Cross-analysis between these indicators provides a more complete picture of underlying causes and vulnerabilities.

The cause of death can be determined by a diversity of factors, some of which may be related to energy poverty conditions. As this indicator captures only the primary recorded cause, it does not reflect all contributing risk factors. It should be analysed jointly with the "Population reporting chronic disease" indicator to identify potential links with energy poverty, and alongside the "Excess mortality during winter" and "Excess mortality during summer" indicators to contextualise mortality patterns within seasonal climate exposure. Note that data is also available at NUTS 1 and NUTS 2 regional levels, enabling subnational analysis.

This indicator reflects individual perceptions of adequate warmth, which may vary across countries, age groups, and cultural contexts. It covers only winter conditions and does not address summer energy poverty. As it only captures inability caused by affordability issues, cross-analysis with indicators on dwelling energy efficiency and energy expenditure is recommended to identify the full range of underlying drivers. Regional data is available at NUTS 1 and NUTS 2 levels.

Chronic diseases can be both a symptom and an exacerbating factor of energy poverty conditions, particularly where poor indoor air quality, dampness, or inadequate thermal comfort are present. Due to their multicausal nature, establishing a direct link with energy poverty requires a wider set of indicators and robust cross-analysis. Results should be interpreted with caution as they are based on self-reporting, which may not fully capture the prevalence of chronic conditions within a population.

This indicator captures general poverty and social and material deprivation conditions, and should not be interpreted as a direct measure of energy poverty. Households in these conditions may not face energy poverty if their dwelling is energy efficient, if they have lower energy needs, or if they benefit from adequate support mechanisms. Cross-analysis with dwelling condition and energy expenditure indicators is recommended for a more complete picture. Note that this indicator differs from the "At-risk-of-poverty rate", which is one of the four energy poverty indicators under the Energy Efficiency Directive (EU/2023/1791). Regional data is available at NUTS 1 and NUTS 2 levels.

This indicator is based on a yes/no question that enables clear cross-country comparisons but does not capture the reasons behind non-payment. It also misses situations where households borrow money to pay bills on time, masking underlying vulnerability, or where energy self-restriction prevents arrears from occurring despite genuine energy poverty conditions.

This indicator measures housing affordability but does not capture housing quality, energy efficiency, or thermal comfort conditions. Rising housing costs can reduce households' capacity to meet energy needs, but may also reflect financial decisions that do not affect other essential services. Cross-analysis with income, energy expenditure, energy efficiency, and thermal comfort indicators is recommended to investigate the connection with energy poverty vulnerability. Regional data is available at NUTS 1 and NUTS 2 levels.

This indicator identifies households facing a disproportionately high energy cost burden relative to the national population, but its relative nature makes it difficult to use as a standalone measure for cross-country comparisons of energy poverty levels. It does not capture underconsumption or energy self-restriction. It is most informative when read alongside the "Low absolute energy expenditure (M/2)" indicator, which captures the opposite condition, and income-related indicators for a more complete picture of household vulnerability.

This indicator addresses the financial barriers to accessing public transportation, a relevant determinant of transport energy poverty. However, it overlooks other transportation-related factors like service availability and quality. It is advised to combine this indicator with indicators reflecting domestic hardship, analysing energy expenditure, inability to heat, or housing costs to understand the connection between the different vulnerability types and the possible trade-offs in accessing basic needs.

This indicator captures the financial burden of energy costs across income groups, contributing to the economic dimension of energy poverty assessment. The map and data displayed here focus on income quintile 1 — the lowest-income households — as the most relevant group for energy poverty analysis. However, it does not provide information on the level or type of energy consumption underlying the observed expenditure, nor on the causes behind expenditure levels. Cross-analysis with energy consumption data, dwelling characteristics, and energy efficiency indicators is recommended for a more complete understanding of energy poverty vulnerability across income groups.

This indicator helps identify which energy uses consume the most energy and supports the detection of potential challenges in accessing specific energy services when compared to national average or median consumption levels. Low consumption of space heating or cooling services may signal energy poverty conditions, which can be further investigated through cross-analysis with income data, dwelling characteristics, heated/cooled area and self-reported thermal comfort indicators.

Electricity prices are one of the key cost-side drivers of energy poverty, particularly for households exclusively or heavily dependent on electricity for their energy services. Higher nominal prices in one country do not necessarily indicate greater vulnerability if the overall cost of living or tax burden is lower, analysis in Purchasing Power Standards (PPS) is recommended for meaningful cross-country comparisons. Pairing this indicator with income data and energy consumption patterns provides a broader picture of national energy poverty conditions.

Biomass prices can vary significantly depending on product quality, sourcing conditions, and regional availability. The prevalence of freely or informally sourced biomass, particularly in rural areas, can considerably affect energy poverty assessments based on market prices alone. Cross-analysis with data on fuel and technology mixes, dwelling characteristics, and social vulnerability indicators is recommended to contextualise this indicator within a broader energy poverty diagnosis.

Coal prices are directly linked to household energy affordability and represent one of the main cost-side drivers of energy poverty. For meaningful cross-country comparisons, this indicator, alongside all other fuel price indicators, should be analysed when possible in Purchasing Power Standards (PPS), which eliminates differences in price levels across EU Member States. Cross-analysis with data on fuel and technology mixes and social vulnerability indicators is recommended for a more complete energy poverty assessment.

District heating prices alone do not provide sufficient information to characterise energy poverty or assess household vulnerability. The use of district heating is geographically concentrated, being predominantly relevant in Northern and Eastern European Member States, which limits the comparability and coverage of this indicator at EU level. It is particularly informative when combined with data on energy affordability, socio-economic conditions, climate zones, energy mix, and dwelling energy performance. For meaningful cross-country comparisons, analysis in Purchasing Power Standards (PPS) is recommended.

Fuel oil prices are directly linked to international oil markets, making households dependent on this fuel particularly exposed to price volatility and external shocks. For a contextualised understanding of the direct impact of fuel oil prices on energy poverty, this indicator should be linked with data on household fuel and technology mixes at country, regional, and local levels. For meaningful cross-country comparisons, analysis in Purchasing Power Standards (PPS) is recommended.

Natural gas prices are one of the key cost-side drivers of energy poverty, particularly for households heavily dependent on gas for space heating and water heating. Higher nominal prices in one country do not necessarily indicate greater vulnerability if strong social protection measures, such as subsidised tariffs or bill support schemes are in place. For meaningful cross-country comparisons, analysis in Purchasing Power Standards (PPS) is recommended. Cross-analysis with fuel mix data and income indicators provides a more complete picture of energy poverty exposure.

This indicator captures the economic dimension of energy poverty by identifying households with abnormally low energy expenditure, which may signal self-restriction or severe deprivation. However, it does not account for dwelling energy efficiency, household composition, or climate variability, which can produce low expenditure for reasons unrelated to poverty. It is most informative when read alongside the "High share of energy expenditure in income (2M)" indicator, which captures the opposite condition of abnormally high expenditure.

Household dependency on expensive or inefficient fuels may create affordability and environmental challenges, increasing vulnerability to energy poverty. The cost and efficiency of energy transformation vary significantly by fuel type, impacting both primary and final energy consumption levels. Regional differences in fuel access conditions and cultural fuel use patterns should also be considered. Cross-analysis with dwelling characteristics, energy efficiency, income, and thermal comfort indicators is recommended to assess the connection between fuel type and energy poverty vulnerability.

This indicator captures self-reported perception of indoor light conditions, which may vary according to personal preference, culture, building orientation, and design. While it does not directly measure energy poverty, a reported lack of artificial light can signal energy self-restriction behaviour or deeper vulnerability linked to affordability constraints. Cross-analysis with income, housing condition, energy efficiency, and thermal comfort indicators is recommended to investigate its connection to energy poverty conditions.

This indicator captures broader financial vulnerability than the "Arrears on utility bills" indicator, covering housing and hire purchase costs alongside energy bills. However, its aggregated nature prevents identification of which type of arrear is driving results. It should be read alongside income, housing cost overburden, and energy expenditure indicators to contextualise the underlying causes of financial difficulty. Data is available at NUTS 1 and NUTS 2 regional levels, enabling subnational analysis across Member States.

This indicator offers valuable insight into the health impacts of heat exposure and heat wave periods on the population. However, it does not capture causes of death, meaning cases linked to energy poverty conditions cannot be identified. Higher summer mortality may also reflect factors unrelated to energy poverty, such as overburdened health systems, insufficient heat warning systems, or a higher share of elderly or chronically ill populations.

This indicator provides a direct measure of winter thermal discomfort linked to poor dwelling insulation or inadequate heating equipment. However, it does not identify the exact cause of discomfort, and perceived thermal comfort may vary culturally, regionally, and over time. Non-recognition of energy poverty by vulnerable households may also affect results. Note that this indicator differs from "Inability to keep the dwelling comfortably warm", which captures the inability to afford warmth regardless of dwelling or equipment conditions, thus being complementary.

Click here to explore previous national data for 2007 and 2012. These data are presented as the share of the population living in dwellings that are comfortably warm during winter time, representing a contrasting measure to this indicator.

This indicator captures underlying economic vulnerability and enables consistent income-based comparisons across populations. However, as it is exclusively based on disposable income, it does not capture other possible drivers of energy poverty. Households not classified as income-poor may still experience energy poverty due to extreme climate exposure, high energy expenditure, or poor dwelling energy performance.

This indicator may be affected by varying perceptions of car ownership affordability, with associated costs potentially being both under- and overestimated by respondents. It does not capture the underlying drivers of financial constraints that lead to the inability to afford a vehicle, such as energy bill arrears, high housing costs, or broader conditions of material deprivation. Cross-analysis with income, housing cost, and public transport accessibility indicators is recommended to contextualise results within broader transport and domestic vulnerability patterns.

Analysing household expenditure by category may reveal patterns of excessive costs that contribute to financial constraints and intensify or create energy poverty conditions. However, this indicator lacks disaggregation by income level, preventing identification of specific impacts on low- and middle-income households, and does not capture the underlying causes of relatively high or low expenditure in specific cost categories.

This indicator offers valuable insight into heating system patterns across Member States and supports cross-analysis with indicators on thermal discomfort, inability to keep home adequately warm, and cold stress days. However, it does not capture the age, condition, efficiency, or frequency of use of installed equipment, nor does it distinguish cases where the absence of heating reflects lower heating needs or different thermal comfort perceptions.

Click here to explore previous national data for 2007 and 2012. These data are presented without disaggregation options by heating system type, contrary to what is reported for this indicator.

This indicator does not capture the underlying causes of public transport usage patterns, such as accessibility, affordability, degree of urbanisation, or personal preferences. It therefore cannot distinguish between voluntary non-use and constrained mobility, limiting its capacity to identify transport poverty conditions on its own. Cross-analysis with indicators on car ownership, inability to afford public transport, housing costs, and degree of urbanisation is recommended for a more complete picture.

This indicator provides a direct measure of the relevance of transport costs relative to other categories of final household consumption expenditure (COICOP 2018). However, it does not capture the possible causes of relatively high or low transport expenditure shares, and the absence of disaggregation by income level or material and social deprivation prevents identification of the specific impact on vulnerable households.

An analysis of excess winter mortality can help evaluate the health impacts of cold exposure on the population. However, this indicator does not capture causes of death, meaning cases directly linked to energy poverty cannot be identified. Higher winter mortality may also reflect unrelated factors, such as overburdened health systems or a higher share of elderly or chronically ill populations.

Click here to explore previous national data for 2005 to 2014. These data refer to excess winter mortality/deaths, expressed as a share of the population. Note that these data are drawn from a different source (Building Stock Observatory) and use a different calculation method; therefore, they cannot be directly compared with the current indicator.

This indicator captures scenarios of severe cold exposure based exclusively on climate data, using categories of minimum daily temperature from the EU Copernicus Programme. It does not measure the effects of cold stress on the population, nor the capacity of national infrastructure and housing stock to adapt to severe cold exposure events.

This indicator captures scenarios of severe heat exposure based exclusively on climate data, using categories of maximum daily temperature from the EU Copernicus Programme. It does not measure the effects of heat stress on the population, nor the capacity of national infrastructure and housing stock to adapt to severe heat exposure events.

Arrears (mortgage or rent, utility bills or hire purchase)

At-risk-of-poverty rate

Cold stress days

Excess mortality during summer

Heat stress days

Population living in dwellings whose energy efficiency improved in the last 5 years

Population living in a dwelling not comfortably warm during winter

Population using or not public transport, by frequency

Population who cannot afford a personal car

Population living in private households by heating system used in the dwelling

Household final consumption expenditure by purpose

Household final consumption expenditure allocated to transport costs

Households unable to keep dwelling comfortably cool in the summer

Population that is Materially and Socially Deprived (MSD) and owns a car

Arrears on utility bills

Excess mortality during winter

At risk of poverty or social exclusion

Causes of death

Cooling degree days

Disposable annual household income

Dwellings with energy label A

Energy expenses by income quintile

Energy prices

Excess winter mortality/deaths

Final energy consumption in households by energy use

Final energy consumption in households by type of fuel

Heating degree days

High share of energy expenditure in income (2M)

Housing cost overburden rate

Inability to keep home adequately warm

Low absolute energy expenditure (M/2)

Population considering their dwelling as too dark

Population living in a dwelling equipped with air conditioning

Population living in a dwelling equipped with heating facilities

Population living in a dwelling with presence of leak, damp and rot

Population living in dwellings comfortably cool in summer time

Population living in dwellings comfortably warm in winter time

Population reporting a chronic disease

Population who cannot afford a regular use of public transport

Albania (AL)

Austria (AT)

Belgium (BE)

Bosnia and Herzegovina (BA)

Bulgaria (BG)

Croatia (HR)

Cyprus (CY)

Czechia (CZ)

Denmark (DK)

Estonia (EE)

EU-18 (EU-18)

Finland (FI)

France (FR)

Georgia (GE)

Germany (DE)

Greece (EL)

Hungary (HU)

Iceland (IS)

Ireland (IE)

Italy (IT)

Latvia (LV)

Liechtenstein (LI)

Lithuania (LT)

Luxembourg (LU)

Malta (MT)

Moldova (the Republic of) (MD)

Montenegro (ME)

Netherlands (NL)

Poland (PL)

Portugal (PT)

Republic of Kosovo (XK)

Republic of North Macedonia (MK)

Romania (RO)

Serbia (RS)

Slovakia (SK)

Slovenia (SI)

Spain (ES)

Sweden (SE)

Switzerland (CH)

Turkey (TR)