Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Eurostat, the statistical office of the European Union
1.2. Contact organisation unit
F4: Income and living conditions; Quality of Life
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
2920 Luxembourg LUXEMBOURG
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
2.1. Metadata last certified
24 October 2024
2.2. Metadata last posted
24 October 2024
2.3. Metadata last update
24 October 2024
3.1. Data description
The European Statistics of Income and Living Condition (EU-SILC) survey contains a small module on health, composed of 3 variables on health status and 4 variables on unmet needs for health care.
The variables on health status represent the so called Minimum European Health Module (MEHM), and measures 3 different concepts of health:
Self-perceived health
Chronic morbidity (people having a long-standing illness or health problem)
Activity limitation – disability (self-perceived long-standing limitations in usual activities due to health problems)
The variables on unmet needs for health care targets two broad types of services: medical care and dental care. The variables refer to the respondent's own assessment of whether he or she needed the respective type of examination or treatment, but did not have it and if so what was the main reason of not having it, Eurostat currently disseminates the following indicators for unmet needs:
Self-reported unmet needs for medical examination for reasons of barriers of access
Self-reported unmet needs for medical examination by reason
Self-reported unmet needs for dental examination by reason
All indicators are expressed as percentages within (or share of) the population and breakdowns are given by: sex, age, labour status, educational attainment level, and income quintile group.
Data for individual countries are disseminated starting the fourth quarter of year N+1 (where N = year of data collection). EU aggregates and health indicators for all countries (provided that the data is available) for year N are usually published by the end of February N+2.
3.2. Classification system
The EU-SILC results are produced in accordance with the relevant international classification systems. For more information, please consult EU-SILC reference metadata file.
Country codes are based on the ISO 3166 (International Organisation of Standardisation – alpha-2 format), with two main exceptions for Greece and the United Kingdom which are coded as EL and UK respectively. For more details on the classification, please consult: Country codes.
The International standard classification of education (ISCED) is used to measure the educational attainment level. Data are disseminated according to ISCED 1997 (until 2013) and ISCED 2011 (from 2014). For more details on the classification, please consult: Eurostat-Metadata (ISCED).
3.3. Coverage - sector
EU-SILC is a general population survey and health variables describe general population health and access to health care services.
3.4. Statistical concepts and definitions
Self-perceived health: the concept is operationalized by a question on how a person perceives his/her health in general using one of the answer categories very good/ good/ fair/ bad/ very bad.
Chronic morbidity: the concept is operationalized by a question asking if the respondent suffers from any longstanding (of a duration of at least six months) illness or health problem.
Activity limitation: the concept is operationalized by using the Global Activity Limitation Indicator (GALI) for observing limitation in activities people usually do because of one or more health problems. The limitation should have lasted for at least the past six months. Three answer categories are possible: ‘severely limited’, ‘limited but not severely’ or ‘not limited at all’.
Self-reported unmet needs: Person’s own assessment of whether he or she needed examination or treatment for a specific type of health care, but didn't have it or didn't seek for it. EU-SILC collects data on two types of health care services: medical care and dental care.
Medical care: refers to individual health care services (medical examination or treatment excluding dental care) provided by or under direct supervision of medical doctors or equivalent professions according to national health care systems.
Dental care: refers to individual health care services provided by or under direct supervision of stomatologists (dentists). Health care provided by orthodontists is included.
Main reasons for unmet needs observed in SILC are the following:
Could not afford to (too expensive)
Waiting list
Could not take time because of work, care for children or for others
Too far to travel or no means of transportation
Fear of doctors (resp. dentists), hospitals, examination or treatment
Wanted to wait and see if problem got better on its own
Didn't know any good medical doctor (resp. dentist)
Other reasons.
"Reasons of barriers of access" combines the following three reasons: ‘Could not afford to (too expensive)’, ‘Waiting list’ and ‘Too far to travel or no means of transportation’.
For further details on the concepts of health status and unmet needs variables, please refer to the descriptions provided in the document: EU-SILC variables on health.
Age: the age completed at the time of the interview.
Educational attainment level: the education attainment levels of individuals are classified according to the International Standard Classification of Education (ISCED) version of 1997 and are grouped as follows:
Pre-primary, primary and lower secondary education (ED0-2):
Level 0: no formal education or below primary education
Level 1: Primary education or first stage of basic education
Level 2: Lower secondary or second stage of basic education
Upper secondary and post-secondary non-tertiary education (ED3_4):
Level 3: Upper secondary education
Level 4: Post-secondary non-tertiary education
First and second stage of tertiary education (ED5_6):
Level 5: First stage of tertiary education
Level 6: Second stage of tertiary education.
Labour status: most frequent/main labour status (derived from self-reported data on number of months of year spent in labour statuses). The following breakdown for disseminating of data is used:
Employed persons (EMP)
Unemployed persons (UNE)
Retired persons (RET)
Other inactive persons (INAC_OTH)
Income quintile group: is computed on the basis of the total equivalised disposable income attributed to each member of the household (for more details on the definition, please consult EU-SILC reference metadata file).
The data (of each person) are ordered according to the value of the total equivalised disposable income. Four cut-point values (the so-called quintile cut-off points) of income, dividing the survey population into five groups equally represented by 20 % of individuals each, are found:
First quintile group of equivalised income (Q0_20)
Second quintile group of equivalised income (Q20_40)
Third quintile group of equivalised income (Q40_60)
Fourth quintile group of equivalised income (Q60_80)
Fifth quintile group of equivalised income (Q80_100).
The first quintile group represents 20 % of population with lowest income and the fifth quintile group 20 % of population with highest income.
3.5. Statistical unit
Individuals aged 16 years old and over living in private households.
3.6. Statistical population
The EU-SILC target population in each country consists of all persons living in private households. Persons living in collective households and in institutions are generallyexcluded from the target population.
3.7. Reference area
Countries: EU Member States, Iceland, Norway, Switzerland, Montenegro, the former Yugoslav Republic of Macedonia, Serbia, Turkey.
Aggregates: EU level
3.8. Coverage - Time
EU-SILC was launched by the countries at different times:
2003: BE, DK, EL, IE, LU, AT, NO
2004: EE, ES, FR, IT, PT, FI, SE, IS
2005: CZ, DE, CY, LV, LT, HU, MT, NL, PL, SI, SK, UK
2006: BG, TR
2007: RO
2008: CH
2010: HR, MK
2013: ME, RS
Data are disseminated from 2004 onwards.
3.9. Base period
Not applicable.
Indicators are reported as percentages.
The reference period for the health status variables is the current situation and for the unmet needs variables the past 12 months.
The reference period for the demographic and educational characteristics is the current situation. The reference period for the labour status is the income reference period.
The income reference period is a fixed 12-month period (such as the previous calendar or tax year) for all countries except UK for which the income reference period is the current year and IE for which the survey is continuous and income is collected for the last twelve months.
6.1. Institutional Mandate - legal acts and other agreements
The EU-SILC (Statistics on Income and Living Conditions) project was launched in 2003, on the basis of a 'gentlemen's agreement' in six Member States (Belgium, Denmark, Greece, Ireland, Luxembourg, and Austria) as well as in Norway. EU-SILC now operates under a framework Regulation of the Council and the Parliament (Regulation (EC) No 1177/2003) and a series of Commission implementing Regulations:
The Framework Regulations (regulation CE 1177/2003 of European parliament and Council adopted on 16 June 2003 and published in the OJ on 3 July 2003
Regulation CE 1553/2005 of EP and Council adopted on 7 September 2005 and published in the OJ on 30 September 2005
Regulation CE 1980/2003 on definitions published in the OJ on 21 October 2003
Regulation CE 1981/2003 on fieldwork aspect and imputation procedures published in the OJ on 21 October 2003
Regulation CE 1982/2003 on sampling and tracing rules published in the OJ on 21 October 2003
Regulation CE 1983/2003 on the list of target primary variables published in the OJ on 7 November 2003
Regulation CE 16/2004 on the content of intermediate and final quality reports published in the OJ on 6 January 2004
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
EU-SILC microdata do not contain any administrative information such as names or addresses that would allow direct identification. For more details see access to microdata.
In order to ensure disclosure control and confidentiality of EU-SILC microdata when disseminating them to the researchers via the UDB, some variables collected were removed or changed. On the other hand, in order to ease the use of the data, some variables were added. For more details see: User Database (UDB).
For the purposes of dissemination of aggregated data the following rules are applied:
An estimate should not be published if it is based on fewer than 20 sample observations or if the non-response for the item concerned exceeds 50%.
An estimate should be published with a flag "low reliability" if it is based on 20 to 49 sample observations or if non-response for the item concerned exceeds 20% and is lower or equal to 50%.
An estimate shall be published in the normal way when based on 50 or more sample observations and the item's non-response does not exceed 20%.
8.1. Release calendar
There is no special release calendar for disseminating health indicators from SILC. In general, data for individual countries are disseminated starting the fourth quarter of year N+1 (where N = year of data collection). EU aggregates and health indicators for all countries for year N are published by the end of February N+2.
8.2. Release calendar access
Not applicable.
8.3. Release policy - user access
In line with the European Union legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see item 10 - 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.
Due to the confidential character of the EU-SILC microdata, direct access to the anonymised data is only provided by means of research contracts. Access is in principle restricted to universities, research institutes, national statistical institutes, central banks inside the EU, as well as to the European Central Bank. Individuals cannot be granted direct access. Contact point: Estat-microdata-access@ec.europa.eu.
Detailed guidelines of EU-SILC (EU-SILC 065 Description of target variables: Cross-sectional and Longitudinal) can be found on CIRCABC: EU-SILC Guidelines.
10.7. Quality management - documentation
Regulation CE 28/2004 on the content of intermediate and final quality reports published in the OJ on 5 January 2004
Comparative EU Quality Reports are available on Eurostat website: EU Quality Reports
EU-SILC is based on a framework Regulation (1177/2003) that defines the scope, definitions, time reference, characteristics of the data, data required, sampling, sample sizes, transmission of data, publication, access for scientific purposes, financing, reports and studies. In addition, Eurostat and Member States have developed the technical aspects of the instrument, in particular one Regulation on 'Quality Reports' (28/2004).
Eurostat and Member States have carried out several methodological studies on different areas. Eurostat also launched several consultations with Member States on the evaluation of implementing health variables in national SILC surveys. These consultations served as a basis for improving methodological guidelines and further harmonization of national surveys.
11.2. Quality management - assessment
Output standardisation is achieved by defining the list and content of target variables, data format and the timetable of data transmission. This is complemented by Eurostat consistency and integrity checks on the microdata. In addition, countries should report to Eurostat on any deviation from the standard and agreements of the Commission Regulations ruling EU-SILC.
Information on all aspects of data quality is available in:
As regards the quality aspects of health data in EU-SILC:
Relevance: Health indicators available from EU-SILC are important policy indicators which are widely used.
Comparability: The comparability of health data from EU-SILC has improved over time. However, there is still room for further improvement and some efforts to further progress has been made.
Coherence: Differences in some national implementions of the Minimum European Health Module between EU-SILC and the European Health Interview Survey (EHIS) wave 1 were found. The situation should improve with the implementation of EHIS wave 2.
12.1. Relevance - User Needs
The main users of the SILC data on health care are:
Institutional users like:
other Commission services, particularly DG SANTE and DG EMPL for their needs in relation to the European Core Health Indicators (ECHI), the European social indicators in the health and long-term care strand developed under the Open Method of Coordination (OMC) on social protection and social inclusion and the Monitoring framework of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA);
national administrations (mainly those in charge of public health),
other international organisations;
Statistical users in Eurostat or in Member States National Statistical Institutes to feed sectorial or transversal publications such as the Eurostat yearbook and various pocketbooks;
Researchers having access to microdata; and
End users - including the media - interested in public health in the EU.
The geographical coverage of EU-SILC by year is explained above under 3.8. EU-SILC covers only people living in private households (all persons aged 16 and over within the household are eligible for the operation), i.e. persons living in collective households and in institutions are generally excluded from the target population.
EU-SILC may also exclude small parts of the national territory amounting to no more than 2 % of the national population and the national territories. National territories that may be excluded include the French Overseas Departments and territories, the Dutch West Frisian Islands, with the exception of Texel, the all Irish offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia, and finally the Scotland north of the Caledonian Canal, the Scilly Islands.
13.1. Accuracy - overall
According to the Regulation 1982/2003 on sampling and tracing rules, for all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data are to be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. The sampling frame and methods of sample selection should ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
Regulation 1177/2003 defines the minimum effective sample sizes to be achieved, i.e. the actual sample sizes will have to be larger to the extent that the design effect exceeds 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. The allocation of the effective sample size is done according to the size of the country and ensuring minimum precision criteria for the key indicator at national level (absolute precision of the at-risk-of-poverty rate of 1 %).
13.2. Sampling error
Standard errors of key indicators are commonly used as a measure of the reliability of data collected through sample survey. EU-SILC was designed to provide measure of at-risk-of-poverty rate with an absolute precision of about one point. The sample sizes were defined taking into account this accuracy requirement. Member States compute variance estimates for the main indicators; Linearisation, Jacknife and Bootstrap techniques are programmed.
The term 'non-sampling error' is a generic one that encompasses any errors other than sampling errors. The non-sampling errors discussed in this section are: coverage errors, measurement and processing errors, and non-response errors.
Coverage errors
Coverage errors are caused by the imperfections of a sampling frame for the target population of the survey.
In EU-SILC two main groups can be defined in terms of the sampling source used:
Some countries have relied on household information from population registers. In order to make the best coverage of the target population, registers have to be updated frequently. It means any modification in the population (both people moving in and people moving out) must be reported as quickly as possible.
Other countries have used Census databases in order to select addresses. The databases also have to be updated to ensure the cross-sectional representativeness of the sample.
A systematic source of coverage problems is the time lag between the reference date for the selection of the sample and the fieldwork period, which should be made the shortest.
In addition, some countries carried out EU-SILC as a sub-sample of the units (addresses) that successfully cooperated to other existing surveys. Assuming selective non-response in these surveys, this may entail selection bias (under-coverage).
Measurement and processing errors
Generally, measurement errors arise from the questionnaire, the interviewer, the interviewee and the data collection method used.
It is vital in a survey like EU-SILC, which collects a multitude of complex income components, that the questionnaire is constructed so that the interviewee can provide as quickly as possible all the correct information. It appears that most of the countries took care in designing the questionnaire. In particular, experiences from pilot surveys and/or former EU-SILC waves were used in order to optimize the data collection process. The questionnaires were also tested in order to identify potential sources of problems.
Due to the complexity and the sensitivity of the survey, the interviewees could not or did not want to give information about all their incomes. For instance, capital of self-employment income may have been under-reported. Besides, EU-SILC collects non-monetary income components (imputed rent, income from private use of company car...) that could have an unfamiliar terminology to some people. The risk of confusion on the information to report is then higher than with more conventional monetary income components.
Non-response errors
All surveys have to deal with non-response, i.e. information missing for some of the sample units. Unit non-response happens when no interview can be obtained, while item non-response does when only some of the items are missing. EU-SILC suffers from these two types of non-response:
Unit non-response: when a household refuses to cooperate or is away during the fieldwork period. Other reasons can explain unit non-response: the questionnaire is lost; the household is unable to respond because of incapacity or illness... It may also happen that a person in a household refuses to cooperate although the household interview has been accepted ('individual' non-response).
Item non-response: typically happens to questions the interviewee does not answer because he considers them personal or not easily understandable.
Non-response is a potential source of bias particularly if the non-responding units have specific survey patterns ('non-ignorable' non-response). For instance, one might expect persons with high incomes to be more reluctant to give income information to an interviewer, thus making the upper income class under-represented in the sample and the estimates downwardly biased.
The Commission Regulation 28/2004 has defined indicators aiming at measuring unit non-response in EU-SILC: Address contact rate (Ra), Household response rate (Rh), Individual response rate (Rp).
At this step, elaborate models controlling many external control variables are desirable in order to correct non-response. Most of the countries did apply either a standard post-stratification based on homogeneous response groups or a more sophisticated logistic regression model.
Individual non-response rate appears to be marginal. Most of the countries have actually imputed missing individual questionnaires.
Item non-response is high for some income components. It has been dealt with by imputation. The technique aims at 'filling the holes' in a distribution, so only unit non-response can be assumed. However, it has to be kept in mind imputed values are not exact values and underlain on a model that could not be the perfect fit of the reality.
Imputation can have a significant effect on the overall accuracy: it generally skews a sample distribution so estimates will be biased. Furthermore, variance estimates assuming that imputed values are exact ones will be generally biased. The impact of imputation on the EU-SILC data is difficult to assess as yet.
Total non-response of selected household/individuals is required to be below 40 %.
Item non-response for non income variable is limited to 5 %. When non-response in income components affects a subcomponent collected through interview, statistical imputation or modelling is required. This aspect is controlled in the datasets through imputation flags which represent the proportion of collected over recorded amounts.
14.1. Timeliness
Indicators based on national SILC data are published on Eurostat website soon after its delivery and acceptance. In general it takes place in the course of year N+1 (where N = year of data collection) in case of indicators based on cross-sectional data and starting from the second half of year N+1 in case of indicators based on longitudinal data.
Health indicators for individual countries are disseminated starting the fourth quarter of year N+1. EU aggregates and indicators for all countries for year are published by the end of February N+2.
14.2. Punctuality
Some information on punctuality can be found in Comparative EU Quality Reports which are available on Eurostat website: EU Quality Reports.
In general, the punctuality has been improving for majority of countries. However, there are still some countries which deliver data far after the requested deadline which complicates estimating the EU averages.
15.1. Comparability - geographical
EU-SILC is based on a common framework defined by harmonized lists of target primary and secondary variables, common concepts, a recommended design, common requirements (for imputation, weighting, sampling errors calculation) and classifications aiming at maximising comparability of the information produced. To anchor EU-SILC in the National Statistical System, survey design is flexible. The framework can be seen as a trade off in terms of standardisation of surveys leading to a good degree of comparability and flexibility allowing country's specificities to be taken into account in order to maximise quality of data. Eurostat and Member States work together to develop common guidelines and procedures aimed at maximising comparability.
The EU-SILC common framework aims ensuring standardisation at different levels.
1) Conceptual standardisation is achieved because the common concepts/definitions underlying each measure/variable, the scope and time reference are defined and documented.
2) Implementation and process standardisation is achieved by editing recommendations about collection unit to be considered, sample size to be achieved for each country, a recommended design for implementing EU-SILC (the so called 4-year rotational panel which almost all countries are using), common requirements for sampling and tracing rules for the longitudinal components, common requirement for imputation and weighting procedures. International classifications aiming at maximising comparability of the information produced are also enforced. Specific fieldwork aspects are also controlled by the framework: to limit the use of proxy interviews; to limit the use of controlled substitutions, to limit the interval between the end of the income reference period and the time of the interview, to limit to the extent for the total fieldwork of one-shot surveys, to define precise follow up rules of individuals and households in case of refusals, non-contact...
3) For the health component of EU-SILC, a data translation protocol has been elaborated in order to check data comparability in all languages.
Eurostat launched several consultations with Member States on the evaluation of implementing health variables in the national SILC surveys. These consultations served as a basis for revising the methodological guidelines with a view of enhancing input harmonization of national questions with EU standard methodology.
An evaluation of national translations of SILC questions on health status was also conducted within the Joint Action on European Health and Life Expectancy Information System (JA EHLEIS).
The harmonisation of national health questions has improved over time but the process is still on-going and the comparability of the results is to be further improved for some countries. The major progress was reached between 2007 and 2008 based on an agreement on harmonisation and closer collaboration between national SILC and EHIS teams.
15.2. Comparability - over time
Since 2005 comparability over time is ensured by the EU Regulation on EU-SILC.
15.3. Coherence - cross domain
EU-SILC follows international standards: ISCO, NACE, ISCED, degree of urbanisation, Canberra recommendations for income data.
The sets of weights available in EU-SILC datasets have been obtained using calibration techniques which ensure basic coherence of estimates obtained from EU-SILC micro datasets and demographic counts.
A coherence analysis with the European Health Interview Survey (EHIS wave 1) which includes exactly the same three questions of the MEHM revealed significant differences in results for some countries. An overview of problems and comments on the progress in the harmonisation of the questions on health in the EU-SILC and with the EHIS questions (2004 - 2007) is provided in the annex.
Further analysis between SILC and EHIS wave 2 data is anticipated and results of that analysis will preferably be used for evaluating the coherence of MEHM for two reasons: all Member States can be included in the analysis and more harmonization of national questions used in SILC and EHIS can be expected.
EU-SILC estimates based on health data for a given reference period have full internal coherence, as they are based on the compatible microdata and they are calculated using the same estimation methods.
EU-SILC was designed to keep respondent burden controlled so to avoid to high non-response rate and to ensure good quality of the information collected. The target is to limit the total length of interviewing household in average below 60 minutes. Significant decrease of interview duration is observed in countries using administrative data.
All reported errors (once validated) result in corrections of the disseminated data.
Reported errors are corrected in the disseminated data as soon as the correct data have been validated.
Data may be published even if they are missing for certain countries or flagged as provisional or of low reliability for some of them. They are replaced with final data once transmitted and validated. European aggregates are updated accordingly.
Whenever new data are provided and validated, the already disseminated data are updated. There is no specific updating schedule for incorporating ‘spontaneously’ provided new data.
Revisions of previously released EU-SILC data may happen in case adjustments are implemented at national level (for example, the availability of new census data) or in other exceptional cases (for examples changes in the indicator definitions or in the EU-SILC methodology).
No substantial country-specific revisions are applied at the national level (the main driver of data revisions being changes that are coordinated within the ESS).
The EU-SILC team promptly shares information on any data revision with the Income and Living conditions Working Group members as well as with the Social Protection Committee – Indicators Sub-Group.
18.1. Source data
In most cases participant countries launch EU-SILC from scratch with integrated cross-sectional and longitudinal elements (this is the Eurostat recommendation). Other countries use a combination of registers and interviews. Others seek to adapt existing national sources.
Precision requirements are set via the prescription of minimum effective sample sizes and are specified in the EU-SILC framework regulation 1177/2003. They should be carefully designed to ensure representativeness - and are to be increased by participant countries to the extent that their national sample is not determined on a simple random basis, or to reflect likely levels of non-response, or to reflect any specific national requirements. Separate values are specified for the cross-sectional and longitudinal elements.
The minimum effective sample size for the total EU cross-sectional element covers some 273,000 individuals living in 130,000 private households (ranging from 3,250 in LU to 8,250 households in DE).
18.2. Frequency of data collection
Annually.
18.3. Data collection
Member States apply different modes of data collection and these modes of data collection may change in time.
18.4. Data validation
There is a comprehensive validation procedure applied prior to finalisation of the EU-SILC database for a particular cross-sectional and longitudinal "wave" (year of survey plus any re-working of prior year data). Source data is initially reviewed at national level and subsequently submitted to Eurostat for multilateral validation together with a detailed quality report. For more information, please consult the EU-SILC reference metadata file.
As regards health variables, a comparison of the data from the current and previous years is done to identify unusual changes in time series.
18.5. Data compilation
Estimates at aggregate level (e.g. EU) are calculated as the population-weighted arithmetic average of individual national figures.
Missing survey data is imputed using procedures specified in EU-SILC implementation regulation 1981/2003. This includes income data, household composition data and other elements.
18.6. Adjustment
Not applicable.
Not applicable.
The European Statistics of Income and Living Condition (EU-SILC) survey contains a small module on health, composed of 3 variables on health status and 4 variables on unmet needs for health care.
The variables on health status represent the so called Minimum European Health Module (MEHM), and measures 3 different concepts of health:
Self-perceived health
Chronic morbidity (people having a long-standing illness or health problem)
Activity limitation – disability (self-perceived long-standing limitations in usual activities due to health problems)
The variables on unmet needs for health care targets two broad types of services: medical care and dental care. The variables refer to the respondent's own assessment of whether he or she needed the respective type of examination or treatment, but did not have it and if so what was the main reason of not having it, Eurostat currently disseminates the following indicators for unmet needs:
Self-reported unmet needs for medical examination for reasons of barriers of access
Self-reported unmet needs for medical examination by reason
Self-reported unmet needs for dental examination by reason
All indicators are expressed as percentages within (or share of) the population and breakdowns are given by: sex, age, labour status, educational attainment level, and income quintile group.
Data for individual countries are disseminated starting the fourth quarter of year N+1 (where N = year of data collection). EU aggregates and health indicators for all countries (provided that the data is available) for year N are usually published by the end of February N+2.
24 October 2024
Self-perceived health: the concept is operationalized by a question on how a person perceives his/her health in general using one of the answer categories very good/ good/ fair/ bad/ very bad.
Chronic morbidity: the concept is operationalized by a question asking if the respondent suffers from any longstanding (of a duration of at least six months) illness or health problem.
Activity limitation: the concept is operationalized by using the Global Activity Limitation Indicator (GALI) for observing limitation in activities people usually do because of one or more health problems. The limitation should have lasted for at least the past six months. Three answer categories are possible: ‘severely limited’, ‘limited but not severely’ or ‘not limited at all’.
Self-reported unmet needs: Person’s own assessment of whether he or she needed examination or treatment for a specific type of health care, but didn't have it or didn't seek for it. EU-SILC collects data on two types of health care services: medical care and dental care.
Medical care: refers to individual health care services (medical examination or treatment excluding dental care) provided by or under direct supervision of medical doctors or equivalent professions according to national health care systems.
Dental care: refers to individual health care services provided by or under direct supervision of stomatologists (dentists). Health care provided by orthodontists is included.
Main reasons for unmet needs observed in SILC are the following:
Could not afford to (too expensive)
Waiting list
Could not take time because of work, care for children or for others
Too far to travel or no means of transportation
Fear of doctors (resp. dentists), hospitals, examination or treatment
Wanted to wait and see if problem got better on its own
Didn't know any good medical doctor (resp. dentist)
Other reasons.
"Reasons of barriers of access" combines the following three reasons: ‘Could not afford to (too expensive)’, ‘Waiting list’ and ‘Too far to travel or no means of transportation’.
For further details on the concepts of health status and unmet needs variables, please refer to the descriptions provided in the document: EU-SILC variables on health.
Age: the age completed at the time of the interview.
Educational attainment level: the education attainment levels of individuals are classified according to the International Standard Classification of Education (ISCED) version of 1997 and are grouped as follows:
Pre-primary, primary and lower secondary education (ED0-2):
Level 0: no formal education or below primary education
Level 1: Primary education or first stage of basic education
Level 2: Lower secondary or second stage of basic education
Upper secondary and post-secondary non-tertiary education (ED3_4):
Level 3: Upper secondary education
Level 4: Post-secondary non-tertiary education
First and second stage of tertiary education (ED5_6):
Level 5: First stage of tertiary education
Level 6: Second stage of tertiary education.
Labour status: most frequent/main labour status (derived from self-reported data on number of months of year spent in labour statuses). The following breakdown for disseminating of data is used:
Employed persons (EMP)
Unemployed persons (UNE)
Retired persons (RET)
Other inactive persons (INAC_OTH)
Income quintile group: is computed on the basis of the total equivalised disposable income attributed to each member of the household (for more details on the definition, please consult EU-SILC reference metadata file).
The data (of each person) are ordered according to the value of the total equivalised disposable income. Four cut-point values (the so-called quintile cut-off points) of income, dividing the survey population into five groups equally represented by 20 % of individuals each, are found:
First quintile group of equivalised income (Q0_20)
Second quintile group of equivalised income (Q20_40)
Third quintile group of equivalised income (Q40_60)
Fourth quintile group of equivalised income (Q60_80)
Fifth quintile group of equivalised income (Q80_100).
The first quintile group represents 20 % of population with lowest income and the fifth quintile group 20 % of population with highest income.
Individuals aged 16 years old and over living in private households.
The EU-SILC target population in each country consists of all persons living in private households. Persons living in collective households and in institutions are generallyexcluded from the target population.
Countries: EU Member States, Iceland, Norway, Switzerland, Montenegro, the former Yugoslav Republic of Macedonia, Serbia, Turkey.
Aggregates: EU level
The reference period for the health status variables is the current situation and for the unmet needs variables the past 12 months.
The reference period for the demographic and educational characteristics is the current situation. The reference period for the labour status is the income reference period.
The income reference period is a fixed 12-month period (such as the previous calendar or tax year) for all countries except UK for which the income reference period is the current year and IE for which the survey is continuous and income is collected for the last twelve months.
According to the Regulation 1982/2003 on sampling and tracing rules, for all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data are to be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. The sampling frame and methods of sample selection should ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
Regulation 1177/2003 defines the minimum effective sample sizes to be achieved, i.e. the actual sample sizes will have to be larger to the extent that the design effect exceeds 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. The allocation of the effective sample size is done according to the size of the country and ensuring minimum precision criteria for the key indicator at national level (absolute precision of the at-risk-of-poverty rate of 1 %).
Indicators are reported as percentages.
Estimates at aggregate level (e.g. EU) are calculated as the population-weighted arithmetic average of individual national figures.
Missing survey data is imputed using procedures specified in EU-SILC implementation regulation 1981/2003. This includes income data, household composition data and other elements.
In most cases participant countries launch EU-SILC from scratch with integrated cross-sectional and longitudinal elements (this is the Eurostat recommendation). Other countries use a combination of registers and interviews. Others seek to adapt existing national sources.
Precision requirements are set via the prescription of minimum effective sample sizes and are specified in the EU-SILC framework regulation 1177/2003. They should be carefully designed to ensure representativeness - and are to be increased by participant countries to the extent that their national sample is not determined on a simple random basis, or to reflect likely levels of non-response, or to reflect any specific national requirements. Separate values are specified for the cross-sectional and longitudinal elements.
The minimum effective sample size for the total EU cross-sectional element covers some 273,000 individuals living in 130,000 private households (ranging from 3,250 in LU to 8,250 households in DE).
Annual.
Indicators based on national SILC data are published on Eurostat website soon after its delivery and acceptance. In general it takes place in the course of year N+1 (where N = year of data collection) in case of indicators based on cross-sectional data and starting from the second half of year N+1 in case of indicators based on longitudinal data.
Health indicators for individual countries are disseminated starting the fourth quarter of year N+1. EU aggregates and indicators for all countries for year are published by the end of February N+2.
EU-SILC is based on a common framework defined by harmonized lists of target primary and secondary variables, common concepts, a recommended design, common requirements (for imputation, weighting, sampling errors calculation) and classifications aiming at maximising comparability of the information produced. To anchor EU-SILC in the National Statistical System, survey design is flexible. The framework can be seen as a trade off in terms of standardisation of surveys leading to a good degree of comparability and flexibility allowing country's specificities to be taken into account in order to maximise quality of data. Eurostat and Member States work together to develop common guidelines and procedures aimed at maximising comparability.
The EU-SILC common framework aims ensuring standardisation at different levels.
1) Conceptual standardisation is achieved because the common concepts/definitions underlying each measure/variable, the scope and time reference are defined and documented.
2) Implementation and process standardisation is achieved by editing recommendations about collection unit to be considered, sample size to be achieved for each country, a recommended design for implementing EU-SILC (the so called 4-year rotational panel which almost all countries are using), common requirements for sampling and tracing rules for the longitudinal components, common requirement for imputation and weighting procedures. International classifications aiming at maximising comparability of the information produced are also enforced. Specific fieldwork aspects are also controlled by the framework: to limit the use of proxy interviews; to limit the use of controlled substitutions, to limit the interval between the end of the income reference period and the time of the interview, to limit to the extent for the total fieldwork of one-shot surveys, to define precise follow up rules of individuals and households in case of refusals, non-contact...
3) For the health component of EU-SILC, a data translation protocol has been elaborated in order to check data comparability in all languages.
Eurostat launched several consultations with Member States on the evaluation of implementing health variables in the national SILC surveys. These consultations served as a basis for revising the methodological guidelines with a view of enhancing input harmonization of national questions with EU standard methodology.
An evaluation of national translations of SILC questions on health status was also conducted within the Joint Action on European Health and Life Expectancy Information System (JA EHLEIS).
The harmonisation of national health questions has improved over time but the process is still on-going and the comparability of the results is to be further improved for some countries. The major progress was reached between 2007 and 2008 based on an agreement on harmonisation and closer collaboration between national SILC and EHIS teams.
Since 2005 comparability over time is ensured by the EU Regulation on EU-SILC.
