Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

Survey of Health, Ageing, and Retirement in Europe (SHARE)
Survey of Health, Ageing, and Retirement in Europe (SHARE)

Topic
Education and Learning
Social Systems and Welfare
Health and Performance
Work and Productivity
Housing, Urban Development and Mobility
Public Attitudes towards Older Age
Social, Civic and Cultural Engagement
Uses of Technology
Wellbeing
Intergenerational Relationships
Relevance for this Topic
Country Belgium
URL
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
www.share-project.be
More Topics

Governance

Contact information

Aaron Van den Heede / Jérôme Schoenmaeckers
University of Antwerp, Herman Deleeck Centre for Social Policy (CSB) / University of Liège, Center of Research in Public Economics and Population Economics (CREPP)
Sint-Jacobsstraat 2 / Boulevard du Rectorat 7 (B31 - box 39)
Belgium
Phone: Aaron Van den Heede: + 32 3 265 55 54 / Jérôme Schoenmaeckers: +32 4 366 29 65
Email: aaron.vandenheede(at)ua.ac.be / jerome.schoenmaeckers(at)ulg.ac.be
Url: www.share-project.be

Timeliness, transparency

Data is released two years after it is collected.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of random or different samples


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Refreshment samples are added to include new age-eligible households

Data gathering method

Telephone interview (CATI)

Face-to-face interview (CAPI, PAPI)


The interviewers used computer-assisted personal interviewing (CAPI) to collect most of the data in all waves. Self-administered questionnaires were handed out in Waves 1, 2, and 4 after completion of the CAPI. Starting in Wave 2, end-of-life interviews (CATI, CAPI) on deceased respondents were administered to relatives or other individuals (proxy) close to the deceased. Proxy interviews were also used when the respondent was not able to do the interview due to for example health problems.


Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.

Access to data


Access to data is granted for scientific purposes after registration and is free of charge. Data is easily downloadable from the project's website. Researchers must submit an application (available at: http://www.share-project.org/fileadmin/pdf_documentation/SHARE_Data_Statement.pdf) in order to obtain a login and password for the data download. The login details remain valid for all further releases of SHARE data as long as the scientific affiliation indicated at registration does not change.

Conditions of access


Access to data is restricted to scientific research purposes (signed agreement needed). Data is available free of charge.


Within a few days


Microdata


SPSS, STATA


The SHARE questionnaires for Belgium are provided in French and Dutch.


Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, who speak the official language of the country and do not live abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9 (1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110 (2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110 (2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).

Coverage


Specifically for Belgium, the following should be noted: The survey population includes all individuals aged 50 or over at the moment of data collection, speak the official language of the country and do not living abroad or in an institution, such as a prison, during the duration of the field work. In Belgium, elderly living in residential care facilities were explicitly excluded from the sample population. However, elderly moving to a residential care facility between waves are not removed from the sample in subsequent waves. Also, elderly living in one of the municipalities in the German-speaking Community in the east of Belgium are excluded from the target population. In wave 1, a three-stage sampling procedure was used for the selection of the respondents: a selection of municipalities in stage 1, a selection of households within the selected municipalities in stage 2, and a screening of the age eligibility of the selected households in stage 3. Respectively, 20% (in the French-speaking part of Belgium) and 25% (in the Dutch-speaking part) of the sample households within each municipality were selected for the wave 1 sample. In the second wave, a two-stage sampling (municipalities; households within municipalities) of age-eligible households was done. The wave 2 refreshment sample, including an over-representation of individuals born in 1956 or 1957, was only drawn in the French-speaking part of Belgium. Wave 3 does not include a refreshment sample; wave 4 does. After data collection, non-response at both interview and item level were corrected through weighting factors when necessary.


2004


Belgium; breakdown by Region and Province


Population aged 50+; Wave 1 SHARE baseline study: all individuals born in 1954 or earlier; Wave 2: all individuals born in 1956 or earlier; Wave 4: all individuals born in 1960 or earlier


As noted in the overview of European datasources, the main goal of SHARE is to provide data to better understand the ageing process and how it affects individuals in the diverse cultural settings of Europe. The SHARE dataset includes cross-national information on economic circumstances, health, wellbeing, as well as integration into family and social networks. It also includes rich information on the socio-economic background of the surveyed individuals and their family members (parents and children), such as gender, age, marital status, educational level, current work, income, and living arrangements. SHARE data from Waves 1, 2 and 4 deal with respondents’ current living conditions, whereas Wave 3 (SHARELIFE) was conducted as retrospective survey and provides information about life histories. More specifically, SHARELIFE data provides information about childhood living circumstances, partners, children, accommodation, employment and wellbeing and health conditions. Thus, it allows for the study of ageing from a life-course perspective. Wave 4 data can also be used to disentangle the influences of the economic crisis on healthy ageing and intergenerational solidarity in different European countries. More specifically, the SHARE data covers: Health and Performance: Within this main topic, SHARE covers data on physical functioning (objective health measures and biomarkers, such as blood pressure and cholesterol), self-reported health, psychological health, health behaviour, cognitive functioning, and use of health facilities. Given the wide range of health data that SHARE provides, it is a very suitable database to study different aspects of health among older people, as well as health care. For example, SHARE allows for studying mental and self-reported health, and their relationship with social support, work and retirement. With regard to self reported health, participants were asked to classify their own health in six domains: mobility, cognition, pain, sleep, breathing, and emotional health. Furthermore, SHARE allows for studying the unmet needs for health care and the reasons behind it. Since SHARE provides data on educational attainment, it is also possible to study the effect of education on health inequalities. Biomarkers also allow for studying the relationships between social status and health, as well as the identification of pre-disease pathways.


The following publications use the SHARE data: • Capéau, B., & Pacolet, J. “The welfare of poorer older people in Belgium and the Netherlands. An application of quantile regression”. Brussels Economic Review - Cahiers Economiques de Bruxelles 52(1) (2009): 5-33. • Geerts, J., & Van den Bosch, K. “Transitions in formal and informal care utilization amongst older Europeans: the impact of national contexts”. European journal of ageing 9(1) (2012): 27-37. For an analysis of the bias encountered by not including the institutionalised elderly, see: • Peeters, H., Debels, A., & Verpoorten, R. “Excluding Institutionalized Elderly from Surveys: Consequences for Income and Poverty Statistics”. Social Indicators Research 110(2) (2013): 751-769. For an analysis of the bias encountered by not including lump sum payments (cf. strengths and weaknesses), see: • Peeters, H., Verschraegen, G., & Debels, A. “Commensuration and policy comparison: how the use of standardized indicators affects the rankings of pension systems”. Journal of European Social Policy (2014, forthcoming).


Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.

Linkage


Education variables are coded following ISCED. Occupation and economic activity follow ISCO and NACE codes respectively.


As the Belgian sample was drawn from the National Register, the (confidential) data contain the National Register number for each respondent. Theoretically, this makes it possible to link the SHARE data to administrative datasets. Such a link so far has not been made and it is unclear to what extent such linkage would be accepted by the Belgian Privacy Commission.


Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.

Data quality


The Belgian part of the SHARE has been conducted in a scientifically sound way.


Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning about the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.

Applicability


Strengths: see overview of European data sources. Weaknesses: An important weakness of the dataset is the exclusion of the institutionalized elderly in the initial sample. This can lead to important problems of comparability across different welfare states. A second weakness refers to the questioning on the receipt of second and third pillar pensions, which does not take into account that in Belgium these are almost exclusively paid out as single lump sum payments. Respondents are only asked about the receipt of second and third pillar pensions in the year preceding the moment of data collection, thus disregarding lump sum payments received in the years before. In practice, therefore, second and third pillar pension protection of current pensioners cannot be investigated in Belgium using the SHARE.


  • The information about this dataset was compiled by the author:
  • Hans Peeters
  • (see Partners)