Archive:Quality of life indicators - health

Data from January 2018. Most recent data: Further Eurostat information, Main tables and Database. Planned update: June 2019.

This article is part of a Eurostat online publication that focuses on Quality of life indicators, providing recent statistics for the European Union (EU). The publication presents a detailed view of various dimensions that can form the basis for a more profound analysis of the quality of life, complementing gross domestic product (GDP) which has traditionally been used to provide a general overview of economic and social developments.

This article focuses on the third dimension — health — of the nine quality of life indicators that form part of a framework endorsed by an expert group on quality of life indicators. Ill health not only undermines an individual’s (and their family’s) quality of life, it can shorten their life span. At a collective level, poor health hinders economic and social development by reducing the human capital available within society. Thus, long and healthy lives may not just be a personal aim, but also an indication of societal well-being and success.

Health is a multifaceted concept and there is no single indicator that can adequately assess its impact in relation to the quality of life. Overall, EU citizens enjoy near-universal access to healthcare, their life expectancy — already among the highest in the world — continues to increase while infant mortality rates have dropped to such low levels that the indicator is often no longer relevant (for this part of the world). Health expenditure constitutes a significant part of government and private expenditure in the EU. Its effectiveness can be measured by a combination of objective health outcome indicators, such as life expectancy, healthy life years or self -perceived health. However, the framework for measuring the quality of life also includes information on the share of the population with unmet needs for medical and/or dental care and a contrasting set of health determinant indicators, on the one hand healthy behaviours such as physical activity or the consumption of fruit and vegetables, and on the other unhealthy behaviours such as smoking or over eating.

Figure 1: Life expectancy at birth, by sex, 2015
(years)
Source: Eurostat (demo_mlexpec)

Figure 2: Life expectancy at birth, 2005 and 2015
(years)
Source: Eurostat (demo_mlexpec)

Figure 3: Life expectancy at birth and GDP per capita, 2015
Source: Eurostat (nama_10_pc) and (demo_mlexpec)

Map 1: Gender gap for healthy life years at birth, 2015
(years, female healthy life years minus male healthy life years)
Source: Eurostat (hlth_hlye)

Figure 4: Proportion of the population aged 16 and over, by perceived health status, 2016
(%)
Source: Eurostat (hlth_silc_10)

Figure 5: Proportion of the population, by perceived health status and by age group, 2016
(%)
Source: Eurostat (hlth_silc_10)

Map 2: Change in the proportion of the population aged 65 and over perceiving their health status as good or very good, 2008-2016
(percentage points, 2016 minus 2008)
Source: Eurostat (hlth_silc10)

Figure 6: Proportion of the population suffering from a long-standing illness or health problem, by income situation, 2015
(%)
Source: Eurostat (hlth_silc_11)

Figure 7: Proportion of the population reporting unmet needs for medical care because care was too expensive, too far away or the waiting list was too long, by income situation, 2016
(%)
Source: Eurostat (hlth_silc_08) and (hlth_silc_09)

Figure 8: Proportion of the population reporting unmet needs for dental care because care was too expensive, too far away or the waiting list was too long, by income situation, 2016
(%)
Source: Eurostat (hlth_silc_08) and (hlth_silc_09)

Figure 9: Proportion of people aged 15 and over who were overweight or obese, by income situation, 2014
(%)
Source: Eurostat (hlth_ehis_bm1i)

Figure 10: Proportion of the population aged 15 and over who were daily smokers of cigarettes, by income situation, 2014
(%)
Source: Eurostat (hlth_ehis_sk3i)

Figure 11: Proportion of the population aged 15 and over who ate at least five portions of fruit and vegetables daily, by income situation, 2014
(%)
Source: Eurostat (hlth_ehis_fv3i)

Figure 12: Proportion of the population aged 15 and over who did aerobic and muscle-strengthening exercise, by level of educational attainment, 2014
(%)
Source: Eurostat (hlth_ehis_pe9e)

Main statistical findings

Europeans live longer and healthier lives

The term life expectancy at birth refers to the mean number of years a new-born child can expect to live if subjected throughout his or her life to the current mortality conditions. This demographic measure has often been used as a proxy for the state of a nation’s health, partly because it is based on a concept that is simple and easy to understand — namely, that of death (mortality conditions provide information on the age-specific probabilities of dying). Indeed, life expectancy at birth remains one of the most frequently quoted indicators of health status and economic development.

In 2015, life expectancy at birth in the EU-28 averaged 80.6 years. A child born in 2015 in Spain, Italy, France, Luxembourg or Sweden could expect to live longer than a child born in any of the other EU Member States, as life expectancy at birth in each of these countries was above 82 years. The lowest levels of life expectancy at birth — 75.0 years or less — were recorded in Romania, Latvia and Bulgaria, as well as in Lithuania where the lowest figure, 74.6 years, was found.

Women may expect to live longer than men, as there was a gender gap of 5.4 years across the EU-28 in 2015, with male life expectancy at birth equal to 77.9 years compared with a figure of 83.3 years for women (see Figure 1). This gender gap was most pronounced in EU Member States with some of the lowest levels of life expectancy at birth and in particular the Baltic Member States. For example, in Lithuania a woman born in 2015 could expect to live 10.5 years longer than a man, while in Latvia there was a difference of 9.8 years between the sexes and in Estonia this gender gap was 9.0 years. By contrast, the difference in life expectancies between the sexes was less than 4.0 years in Denmark, Ireland, Cyprus, Sweden, the United Kingdom and the Netherlands, where the smallest gender gap was recorded, at 3.3 years.

Overall, life expectancy has improved steadily within the EU over the last century due to a range of factors, including: reductions in infant mortality, rising living standards, improved lifestyles, better education, as well as advances in healthcare and medicine. During the period from 2005 to 2015, life expectancy at birth in the EU-28 rose from 78.5 years to 80.6 years (see Figure 2); there was some evidence that the gains in life expectancy made in previous decades were slowing.

Among the EU Member States, life expectancy at birth rose by just 1.3 years in Germany between 2005 and 2015 (note there is a break in series for 2011, so comparability over time may be affected), while the increases in Greece and Sweden were only slightly higher (both saw a rise of 1.5 years during the period under consideration). By contrast, life expectancy at birth was 5.0 years higher in Estonia in 2015 when compared with a decade before (note also there is a break in series), while relatively large increases were recorded in the other two Baltic Member States, with a gain of 4.2 years in Latvia and 3.4 years in Lithuania, which was the same as the increase in Slovenia (where there was also a break in series).

It is also interesting to note that while life expectancy for both men and women continues to rise across the EU-28, it was more commonplace to find male life expectancy rising at a faster pace than female life expectancy, with the gap between the sexes narrowing as a consequence.

Figure 3, which plots GDP per capita against life expectancy at birth, shows that countries can be broadly divided into three groups: those in the Baltic Member States and eastern Europe, with relatively low life expectancy at birth and relatively low levels of GDP per capita; those in the Mediterranean, with relatively high life expectancy at birth and medium levels of GDP per capita; and those in western Europe and Nordic Member States, with life expectancy at birth no greater than in the Mediterranean Member States (and sometimes lower) but with the highest levels of GDP per capita.

It is interesting to note that life expectancy at birth in 2015 was higher than the EU-28 average in all of the southern EU Member States, despite some of them having relatively low levels of GDP per capita. For example, life expectancy at birth for a child born in Portugal in 2015 was 81.3 years, which was higher than in Denmark or Germany (see Figure 3). While it would appear that the advancement of science and the near-universal delivery of healthcare services to populations across the EU seem to be closing the gap in life expectancy between countries, these figures also suggest that economic output is just one of many determinants for health outcomes across the EU; for example, climatic conditions and/or differences in diet may explain, at least to some degree, the higher levels of life expectancy recorded across southern Member States.

Gender, age and income-related differences

Although women in the EU may live longer than men, it is not necessarily the case that they enjoy better health. Indeed, it is relatively common to find that men spend a comparatively greater part of their lives in good health. To measure the overall quality of a population’s health it is common to make use of the healthy life years indicator, defined as the number of years a person is expected to continue to live in a healthy condition, which itself may be defined as an individual’s self-declared ability to live without limitations in his/her daily functioning. As such, healthy life years focus on the quality of life that is spent in a healthy state, rather than a more simple measure covering the full length of life (as for life expectancy). Healthy life years may therefore be seen as an important measure for analysing the relative health of EU populations. Healthy life years are however limited by the fact that these limitations in activity are self-declared, and as such can be influenced by differences in response styles between the sexes or between residents of different countries; for example, it has been shown that women are more prone to report ill health than men.

As such, the difference between life expectancy and healthy life years provides a more nuanced picture of the health of Europeans. Across the whole of the EU-28 there was almost no difference between men and women in terms of the number of healthy life years they might expect to live in 2015, the average for women was 63.3 years, while that for men was 62.6 years. While women generally live longer than men, they were often found to spend more of their lives with functioning limitations.

Map 1 shows the gender gap for healthy life years^[1] in 2015, with newly-born men more likely to live healthier lives (than women) in several of the western and northern Member States. By contrast, it was more commonplace to find that women would live longer and healthier lives in most of the eastern and Baltic Member States, with the gap in healthy life years between the sexes peaking at 4.7 years in favour of women in Lithuania, 3.5 years in Bulgaria and 3.1 years in Poland.

Figure 4 contrasts the share of the population (aged 16 years and over) according to their self-perceived health status. In 2016, more than two thirds (67.6 %) of all adults in the EU-28 declared that they were in good or very good health, compared with less than one tenth (8.8 %) who considered that they were in bad or very bad health. Among the EU Member States, the share of the population aged 16 and over who considered their health to be good or very good ranged from a high of 82.8 % in Ireland and more than three quarters of the adult populations in Cyprus, the Netherlands and Sweden, down to less than half of the adult population in Portugal (47.7 %) , Latvia (47.2 %) and Lithuania (43.4 %).

Figure 5 shows that health tends to deteriorate with age: in every EU Member State, the share of the population that considered its health status as bad or very bad increased as a function of age. While an average of 8.8 % of the EU-28 adult population evaluated their own health status as bad or very bad in 2016, this share was as low as 2.7 % among people aged 16-44 years, rising to 9.4 % for people aged 45-64 and peaking at 19.3 % for people aged 65 years and over.

There were considerable variations between EU Member States that may be attributed to real objective differences but may also reflect, at least to some degree, national characteristics/attitudes (for example, differences between populations that have a more positive or negative view of life); this was particularly the case concerning the self-perception of ill health among people aged 65 and over. For example, less than 1 in 10 of the elderly populations of Malta, Ireland, Sweden and the Netherlands were of the opinion that they had bad or very bad health, which could be contrasted with shares of 40-50 % in Latvia, Lithuania and Croatia.

During the period 2008 to 2016, the proportion of the EU-28 population aged 65 and over that perceived their own health status as good or very good increased by 3.0 percentage points. There was an increase in the proportion of the elderly population that considered their own health to be good or very good in the vast majority of the EU Member States. During the period under consideration, the biggest gains were recorded in Italy (up 12.5 percentage points) and Finland (10.0 points), while there was an improvement in all but five Member States. The only exceptions, where a smaller share of the elderly population considered their own health to be good or very good in 2016 than in 2008, were Greece, Lithuania and Luxembourg (where there was almost no change in self-perceived health status), Denmark (with a reduction of 3.1 percentage points) and the United Kingdom (4.8 points).

With regard to long-standing health problems or diseases (see Figure 6), around one third (34.1 %) of the EU-28 population reported that they suffered from a chronic condition in 2015. These health problems are more prevalent among people with lower incomes: for example, while 27.3 % of the top (fifth) income quintile reported having a long-standing illness or health problem, the equivalent share for the bottom (first) income quintile was as high as 38.2 %. Recent epidemiological research has shown that people with lower incomes, lower levels of educational attainment, or people with manual jobs tend to die younger and to suffer more often from serious health issues.

In 2015, more than half of the population in the first income quintile in Estonia, Finland, Latvia and Germany suffered from a long-standing illness or health problem. At the other end of the range, there were four EU Member States where less than 25.0 % of people in the first income quintile suffered from a long-standing illness or health problem: Italy, Luxembourg, Greece and Romania (which had the lowest share, at 17.3 %). Turning attention to the top income quintile, Germany, France, Portugal and Finland each reported that more than one third of their highest earners suffered from a long-standing illness or health problem in 2015, with a peak share of 37.4 % in Finland. The lowest shares of people in this income quintile suffering from a long-standing illness or health problem were recorded in Ireland, Malta and Lithuania (all within the range of 16.0-17.0 %), Belgium (14.9 %) and Bulgaria (14.2 %).

There were seven EU Member States where the share of the population in the first income quintile suffering from a long-standing illness or health problem in 2015 was at least double the share recorded for the fifth income quintile, with this ratio rising to 2.8 times as high in Lithuania. By contrast, Romania was the only Member State where a higher proportion of the population in the fifth income quintile (compared with the first income quintile) suffered from a long-standing illness or health problem, 17.6 % compared with 17.3 %.

Access to healthcare provision

Medical examinations and treatment are among some of the most important aspects of healthcare. It is therefore important that EU populations do not encounter barriers when seeking access to healthcare. In the EU-28, just 2.6 % of the population in 2016 reported unmet needs for medical care (examinations or healthcare provision); the majority of these unmet needs could be linked to the price of care, the distance to medical care being too far away, or waiting lists being too long. Figure 7 shows that among the ‘poorest‘ 20 % of the EU-28 population (the first income quintile), some 5.3 % of the population declared that they had unmet needs for medical care, compared with just 1.0 % of the population in the top income quintile (the ‘richest’ 20 % of the population). There were much wider disparities between income groups in some of the EU Member States. For example, the share of the first income quintile in Romania, Italy, Latvia, Estonia and Greece that stated that they had unmet medical needs was in double-digits, peaking in Greece at 35.2 %; these figures could be contrasted with shares of less than 3.0 % for the subpopulations covered by the top income quintile (with the exception of Estonia; 13.4 %).

Access to dental healthcare is also an important element that contributes to an individual's quality of life — see Figure 8. Although not usually life-threatening, dental conditions may cause considerable pain and, if left untreated, may have long-term detrimental effects on health and well-being. It was commonplace to find that a higher proportion of the population in the EU Member States stated that they had unmet dental care needs rather than unmet medical needs; this share averaged 4.1 % across the EU-28 in 2016 compared with 2.6 % for unmet medical needs. The only exceptions to this pattern were in Estonia, Poland and Croatia, where it was more common for people to have unmet medical needs.

Across the EU Member States, at least 1 in 10 Estonians, Latvians, Greeks and Portuguese stated that they had unmet dental needs in 2016. Barriers to access dental care were considerably higher among for the poorest members of society, as more than one quarter of those people in the first income quintile in Latvia, Portugal and Greece reported unmet dental needs. In Greece, there was a very wide disparity between the shares of the top and bottom income quintiles who reported that they had unmet dental needs (0.4 % compared with 26.5 %), while there was also a considerable gap in Portugal (2.7 % compared with 27.0 %). There were several other EU Member States where those people with the lowest incomes were much more likely to have unmet dental needs: for example, in Luxembourg, Spain, Malta, Hungary and Austria, the share of the lowest income quintile with unmet dental needs was more than 10 times as high as the share recorded for the highest income quintile.

Health behaviours

This section contains some of the most common and measureable behaviours that influence the health of Europeans. The term overweight covers people with a Body Mass Index (BMI) that is equal to or greater than 25 but less than 30, while those considered as obese have a BMI that is equal to or greater than 30. Figure 9 shows information in relation to the proportion of the population aged 15 and over who were either overweight or obese; these covered just over half (50.2 %) of the EU-28 population in 2014.

Malta had the highest share among the EU Member States, at 59.6 %, while a majority of the Member States also recorded more than half of their respective adult populations as being either overweight or obese. There were nine Member States where fewer than half of the adult population could be considered to be overweight or obese in 2014 and none of these were Baltic or eastern Member States. The lowest shares of adult populations that were overweight or obese were recorded in France (45.5 %) and Italy (43.8 %). An analysis by income quintile reveals that both the ‘poorest’ and ‘richest’ 20 % of the EU-28 population were less likely to be overweight or obese than the average for the total population. This pattern was reproduced in a majority of the EU Member States and was particularly clear for people in the fifth income quintile where eating habits are thought to be better (for example, this subpopulation find it easier to afford fresh food such as fish, vegetables and fruit). There were however four Member States where the share of the population in the fifth income quintile that were overweight or obese was higher than the average for the total population, namely, Greece, Poland, Luxembourg and Sweden. By contrast, the share of the first income quintile that were overweight or obese fell to 29.2 % in Sweden, some 18.5 percentage points less than the average for the total adult population.

Tobacco consumption remains the single largest avoidable health risk in the EU. It is the most significant cause of premature death, responsible for nearly 700 thousand deaths each year, while smokers spend a considerably longer period of their lives in poor health. In 2014, almost one in five adults — defined here as people aged 15 and over — in the EU-28 were daily smokers of cigarettes (see Figure 10). This share rose to more than one in four of the adult population in Cyprus, Hungary and Greece and peaked at 27.3 % of the adult population in Bulgaria. At the other end of the range, less than 15.0 % of the adult population were daily smokers in Luxembourg, the United Kingdom, Ireland, Denmark and Finland, with Sweden the only EU Member State to record a single-digit share (8.7 %).

There was a clear relationship between smoking habits and income situations. In all but two of the EU Member States a higher proportion of the ‘poor’ (the first income quintile) compared with the ‘rich’ (the fifth income quintile) were daily smokers in 2016; the only exceptions were Bulgaria and Romania. In Bulgaria, almost one third (32.0 %) of people in the fifth income quintile were daily smokers, while the corresponding share among people in the first income quintile was 29.7 %. In Romania, the proportion of daily smokers was just above one fifth (20.7 %) among people in the fifth income quintile, which was somewhat higher than the share recorded for people in the first income quintile (18.3 %).

In 2016, the share of daily smokers among people in the first income quintile in Denmark, Belgium, the United Kingdom and Luxembourg was more than twice as high as the share recorded for people in the fifth income quintile. For example, while more than one fifth (21.4 % and 21.0 %) of people in the first income quintile in Luxembourg and the United Kingdom were daily smokers, this share fell to less than one tenth for people in the fifth income quintile (8.3 % in Luxembourg and 8.6 % in the United Kingdom).

Fruits and vegetables are often cited as important components of a healthy diet. High levels of fruit and vegetable consumption — at least five portions a day — are linked to good health and a reduced risk of several diseases that include cardiovascular disease and certain types of cancer. In 2014, the share of the EU-28 adult population who ate at least five portions of fruit and vegetables daily was 14.3 % (see Figure 11). This share ranged across the EU Member States from a high of 33.1 % in the United Kingdom down to less than 10.0 % of the adult population in Germany, the Czech Republic, Sweden, Greece, Slovenia, Austria, Croatia, Bulgaria and Romania (in the latter two, this share fell to less than 5.0 %).

The ‘richest’ members in society tend to have a higher propensity to eat more fruit and vegetables daily. Across the whole of the EU-28, some 17.3 % of the fifth income quintile ate at least five portions of fruit and vegetables daily in 2014, while the corresponding share for the first income quintile was 11.6 %. This pattern was reproduced in all but two of the EU Member States, as Sweden and Slovenia were the only exceptions to report that a higher proportion of the ‘poorest’ 20 % of their adult populations (compared with the ‘richest’ 20 %) ate at least five portions of fruit and vegetables daily. By contrast, in the southern Member States of Cyprus, Portugal and Italy it was common to find that almost twice as many adults in the ‘richest’ 20 % of the population (compared with the ‘poorest’ 20 %) stated that they were eating at least five portions of fruit and vegetables daily.

Increased physical activity may contribute to the reduction of mortality for a range of causes of death and in particular from cardiovascular disease. In 2014, the share of the EU-28 adult population who did aerobic and muscle-strengthening exercises was 12.6 % (see Figure 12). This share ranged from a high of 31.3 % in Sweden and upwards of 25.0 % of the adult populations in Finland, Denmark and Austria, down to less than 10.0 % of the adult population in 13 of the EU Member States, among which there were three — Croatia, Poland and Romania — where less than 5.0 % of the adult population did aerobic and muscle-strengthening exercises.

A much higher share (17.4 %) of the EU-28 adult population with a tertiary level of educational attainment (ISCED levels 5-8) did aerobic and muscle-strengthening exercises in 2014, when compared with the corresponding share (8.1 %) for people with a low level of educational attainment (ISCED levels 0-2). This pattern was repeated in all but one of the EU Member States, with the only exception being Lithuania, where a slightly higher proportion of people with a low level of educational attainment did aerobic and muscle-strengthening exercise. It was commonplace to find a much higher share of the adult population with a tertiary level of educational attainment doing aerobic and muscle-strengthening exercise, this was particularly true in some of the Member States with the lowest overall levels of participation. For example, adults with a high level of educational attainment were three or more times as likely to do aerobic and muscle-strengthening exercises as adults with a low level of educational attainment in Portugal, Cyprus and Malta, with this ratio almost rising to four times as high in Greece.

Conclusions

In conclusion, the information available suggests that while the health status of a population may be linked, at least to some degree, to the level of GDP, there are nevertheless other factors beyond the wealth of a country which play a role in determining health outcomes. These include, for example, the effectiveness of national healthcare systems, the quality of healthcare services, inequalities in access to healthcare, environmental factors as well as individual/cultural differences (for example, dietary habits).

Furthermore, aside from (national) wealth being linked health outcomes, another finding apparent from the information presented in this article is that higher incomes (for individuals) are also associated with better health outcomes; this relationship appears to be quite robust when analysing different income levels, as the middle classes are more healthy than those people living at risk of poverty or social exclusion, but the middle classes in turn have worse health outcomes than those people with the highest incomes (the top income quintile).

Data sources and availability

The statistical assessment of health requires both mortality and morbidity-related measures (in other words, information on health outcomes), as well as data on health determinants (drivers) and access to healthcare.

Data on health outcomes include information on life expectancy (the number of remaining years a person is expected to live at birth or at a certain age), as well as data on morbidity and health status, including healthy life years or an individual’s self-perceived health. Data on life expectancy are provided from population statistics and are based on administrative records. Healthy life years are estimated using data referring to life expectancy and a question on limitations in activities collected from the EU’s statistics of income and living conditions (EU-SILC) survey. Data for the self-perception of health are also collected as part of EU-SILC.

Health determinants (drivers) refer to healthy or unhealthy behaviour of individuals. For the purpose of the framework on quality of life indicators these include unhealthy behaviour such as overeating (reflected in the BMI), daily smokers and hazardous levels of alcohol consumption, or healthy behaviours such as practising physical activities or consuming a certain amount of fruits and vegetables; these indicators are compiled using data from European Health Interview Survey (EHIS).

Access to healthcare is gauged by measuring self-reported unmet medical needs (in terms of barriers to access) for medical and dental care; these data are collected as part of EU-SILC.

Context

Health is not only a fundamental determinant of both the length and the quality of people’s lives, it also plays an important role in determining an individual’s other functional capabilities that in turn determine their overall quality of life.

While there has been a general improvement in health conditions and longevity across the EU, this does not exclude potential risks/threats to future health, for example, through changes in the behaviour of the population or the spread of new epidemics. Obesity is of increasing concern in most EU Member States as a cause of premature deaths, while it is also linked to an increase in diseases such as diabetes or heart disease. Furthermore, physical and mental problems, as well as ill health, undermine the quality and may shorten the length of people’s lives; they also inhibit economic and social development at a national level, by reducing human capital. Poor health conditions mean that a significant part of a given population is unable to benefit from the general progress of society, or actively engage in civic activities. Long and healthy lives are therefore not just an overarching personal aim for most people, they may also be considered as an almost universally acceptable measure of societal well-being, for example, they are incorporated in indices that measure the quality of life, such as the United Nations Human Development Index (HDI).

Health is not only a value in itself: rather, it is a European policy goal of the utmost importance. Regulation (EU) No 282/2014 established the third programme for EU action in the field of health covering the period 2014-2020. It underlines the importance of health policy, especially in light of challenges related to demographic change, as well as the need for action to reduce health inequalities as a condition for inclusive growth across the EU. By doing so, the EU has proposed a series of reforms that are designed to: make healthcare services more sustainable and innovative; improve the overall level of health; provide protection from cross-border health threats (for example, epidemics). More information on the state of the health in the EU may be obtained by referring to the website of the European Commission’s Directorate-General for health and food safety.

Further Eurostat information

Main tables

Health care

Income and living conditions (t_ilc), see:

People at risk of poverty or social exclusion (Europe 2020 indicators) (t_ilc_pe)

Income distribution and monetary poverty (t_ilc_ip)

Living conditions (t_ilc_lv)

Material deprivation (t_ilc_md)

Population (t_populat), see:

Demography (t_pop)

Demography - National data (t_demo)

Mortality (t_demo_mor)

Life expectancy at 60 (tps00026)

Infant mortality (tps00027)

Database

Health (hlth), see:

Health status (hlth_state)

Healthy life years (hlth_hly)

Self-perceived health and well-being (hlth_sph)

Functional and activity limitations (hlth_fal)

Self-reported chronic morbidity (hlth_srcm)

Injuries from accidents (hlth_ifa)

Health determinants (hlth_det)

Body mass index (BMI) (hlth_bmi)

Physical activity (hlth_pha)

Consumption of fruits and vegetables (hlth_cfv)

Tobacco consumption (hlth_smok)

Alcohol consumption (hlth_alc)

Health care (hlth_care)

Consultations (hlth_consult)

Preventive services (hlth_prev)

Medicine use (hlth_med)

Unmet needs for health care (hlth_unm)

Income and living conditions (ilc), see:

People at risk of poverty or social exclusion (Europe 2020 indicators) (ilc_pe)

Income distribution and monetary poverty (ilc_ip)

Living conditions (ilc_lv)

Material deprivation (ilc_md)

EU SILC ad-hoc modules (ilc_ahm)

Demography and migration (demo), see:

Population (demo_pop)

Mortality (demo_mor)

Infant mortality rates (demo_minfind)

Life expectancy by age and sex (demo_mlexpec)

Dedicated section

Publications

Quality of life in Europe - Facts and Views

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

Quality of life — Health

External links

Notes

↑ It should be noted that the information on healthy life years is collected on the basis of an individual’s perceptions as to the extent of their own limitations in their daily activities due to one or more health problems. As such, individuals and (sub) populations who are better informed about health issues may report being sick to a greater extent than those who are less well informed; for example, this appears to be the case when comparing results between the sexes, as women are often more conscious of their own health status than men. Although women tend to report more negatively when asked to judge their own health, this does not necessarily mean they are unhealthier than men, it could simply reflect greater awareness of their health status.

[1] It should be noted that the information on healthy life years is collected on the basis of an individual’s perceptions as to the extent of their own limitations in their daily activities due to one or more health problems. As such, individuals and (sub) populations who are better informed about health issues may report being sick to a greater extent than those who are less well informed; for example, this appears to be the case when comparing results between the sexes, as women are often more conscious of their own health status than men. Although women tend to report more negatively when asked to judge their own health, this does not necessarily mean they are unhealthier than men, it could simply reflect greater awareness of their health status.

[1]