Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

German Ageing Survey
Deutscher Alterssurvey (DEAS)

Topic
Housing, Urban Development and Mobility
Health and Performance
Social Systems and Welfare
Work and Productivity
Public Attitudes towards Older Age
Social, Civic and Cultural Engagement
Wellbeing
Intergenerational Relationships
Relevance for this Topic
Country Germany
URL
More Topics

Governance

Contact information

Research Data Centre of the German Ageing Survey, German Centre of Gerontology (DZA Berlin)
Manfred-von-Richthofen-Straße 2
12101 Berlin
Germany
Phone: +49 (0)30 - 260740-0
Fax: +49 (0)30 - 7854350
Email: fdz(at)dza.de
Url: www.dza.de/.../access-to-deas-data.html

Timeliness, transparency

The scientific use file is available about 2 years after data collection.

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Cross-section, regular


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Cross-section, regular


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Cross-section, regular


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Cross-section, regular


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Cross-section, regular


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire

Type of data


Survey

Type of Study

Longitude survey: long-term study of the same sample

Cross-section, regular


Cohort-sequential design

Data gathering method

Face-to-face interview (CAPI, PAPI)

Self-administered questionnaire


Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)

Access to data


Available for scientific, non-profit use

Conditions of access


It is required to sign a data distribution contract prior to obtaining the data; data set is free of charge.


1-2 weeks


anonymised microdata


SPSS, STATA


Documentation (in parts), variables and value labels are available in German and English. (All basic information, i.e. data access, is in English; documentation of instruments in English for each wave is available, however the majority of detailed descriptions are available in German only, with translations ongoing.)


Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. A new base sample will be drawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative of community-dwelling people between 40-85 years (base sample).


The assessment of housing and living situation has been similar in all waves. In 2008 and 2011, questions concerning housing facilities and furnishing, and residential environment were extended. The housing indicators cover: ownership status, housing cost, moving, neighborhood surroundings and residential environment, residential history, type of dwelling, household facilities, and satisfaction with housing (current, past and future expectations). Mobility, besides ownership of a car, is not assessed.


• Kohli, M., & Künemund, H. (Hrsg.). Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, 2005. • Mahne, K., Naumann, D., & Block, J. Das Wohnumfeld Älterer. Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart (2010): 142-162. • Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010. • Tesch-Römer, C., Engstler, H., & Wurm, S. (Hrsg.). Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001)with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. A new base sample will be drawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry Sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative of community-dwelling people between 40-85 years (base sample)


Within the health domain, approximately 150 comparable variables are available within each wave. More health information (up to 200 variables) is assessed at each wave, but may not be reassessed. The variables cover: physical health, functional health, subjective health, mental health, health behaviour, need of care, need of assistance, health care utilisation, sentinal health events, pain, sleep, health test and information on mortality.


• Kohli, M. & Künemund, H. (Hrsg.). Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, 2005. • Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010. • Schöllgen, I., Huxhold, O., & Schmiedek, F. Emotions and Physical Health in the Second Half of Life: Interindividual Differences in Age-Related Trajectories and Dynamic Associations According to Socioeconomic Status. Psychology and aging, 27(2) (2012): 338. • Schöllgen, I., Huxhold, O., & Tesch-Römer, C. Socioeconomic status and health in the second half of life: findings from the German Ageing Survey. European Journal of Ageing, 7(1) (2010): 17-28. • Schüz, B., Wurm, S., Warner, L. M., & Tesch-Römer, C. Health and subjective well-being in later adulthood: Different health states - different needs? Applied Psychology: Health and Well-Being, 1(1) (2009): 23-45. • Tesch-Römer, C., Engstler, H. & Wurm, S. (Hrsg.). Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006. • Wiest, M., Schüz, B., Webster, N., & Wurm, S. Subjective Weil-Being and Mortality Revisited: Differential Effects of Cognitive and Emotional Facets of Weil-Being on Mortality. Health Psychology, 30(6) (2011): 728. • Wurm, S., Tomasik, M. J., & Tesch-Römer, C. Serious health events and their impact on changes in subjective health and life satisfaction: The role of age and a positive view on ageing. European Journal of Ageing, 5(2) (2008): 117-127.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. The base sample will be redrawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative of community-dwelling people between 40-85 years (base sample)


The survey looks at employment careers, transition to retirement, incomes, property, financial and material transfers, saving and dissaving, subjective fulfilment of needs, and living standards.


• Kohli, M. & Künemund, H. (Hrsg.). Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, 2005. • Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010. • Tesch-Römer, C., Engstler, H. & Wurm, S. (Hrsg.). Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry Sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative for community-dwelling people between 40-85 years (base sample)


Up to 120 variables within the work domain are available in each wave, covering • education and first employment • the current employment (position, average number of working hours, number of employees, workplace sector), • breaks in employment and their reasons and durations • the last employment (position, hours worked, number of employees, part-time employment prior to retirement) • transition to retirement • work beyond retirement (hours, motivation and reasons ), • subjective indicators such as satisfaction with current working conditions (working hours, income, further education etc.), stresses and strains • and a self-assessment of the probability of unemployment and the chances of finding new employment • education and employment of the current and the last partner


• Kohli, M. & Künemund, H. (Hrsg.). Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, 2005. • Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010. • Scherger, S., Lux, T., Hagemann, S., & Hokema, A. Between privilege and burden. Work past retirement age in Germany and the UK ZeS-Working paper. Bremen: Zentrum für Sozialpolitik, 2012. • Simonson, J., Romeu Gordo, L., & Kelle, N. Statistical matching of the German Ageing Survey and the sample of active pension accounts as a source for analysing life courses and old age incomes. Historical Social Research / Historische Sozialforschung, 37(2) (212): 185-210. • Simonson, J. Die Erwerbsbiografien der Babyboomer - ein Risiko für Altersarmut? In H.-G. Soeffner (Ed.), Transnationale Vergesellschaftungen. Verhandlungen des 35. Kongresses der Deutschen Gesellschaft für Soziologie in Frankfurt am Main 2010 (pp. 12). Wiesbaden: Springer VS, CD-Rom. • Tesch-Römer, C., Engstler, H. & Wurm, S. (Hrsg.). Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. A new base sample will be drawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative of community-dwelling people between 40-85 years (base sample).


There are around 20 comparable variables available within each wave. More aspects with regard to attitudes towards one’s own ageing (up to 45 variables) are assessed at each wave, but may not be reassessed. The variables cover individual views on ageing, images of ageing in society, subjective age, attitudes towards retirement and ageism. Individual views on ageing are assessed domain-specifically and allow differentiation between expecting losses or gains in different life domains with ageing.


• Dittmann-Kohli, F., Kohli, M., Künemund, H., Motel, A., Steinleitner, C., & Westerhof, G., with the infas Sozialforschung (1997). Lebenszusammenhänge, Selbst- und Lebenskonzeptionen [Life contexts, conceptions of self and life]. Berlin: Free University. • Kohli, M. & Künemund, H. (Hrsg.) Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, (2005). • Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, (2010). • Tesch-Römer, C., Engstler, H. & Wurm, S. (Hrsg.) Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, (2006). • Steverink, N., Westerhof, G. J., Bode, C., & Dittmann-Kohli, F. The personal experience of aging, individual resources, and subjective well-being. Journal of Gerontology: Psychological Sciences, 56B (2001):364-P373. • Spuling, S. M., Miche, M., Wurm, S., & Wahl, H. W. Exploring the Causal Interplay of Subjective Age and Health Dimensions in the Second Half of Life. Zeitschrift für Gesundheitspsychologie, 21(1) (2013): 5-15. • Wurm, S., Tesch-Römer, C., & Tomasik, M. J.. Longitudinal findings on aging-related cognitions, control beliefs, and health in later life. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 62(3) (2007): 156-P164. • Wurm, S., Tomasik, M. J., & Tesch-Römer, C. Serious health events and their impact on changes in subjective health and life satisfaction: The role of age and a positive view on ageing. European Journal of Ageing, 5(2) (2008): 117-127. • Wurm, S., Tomasik, M. J. & Tesch-Römer, C. On the importance of a positive view on ageing for physical exercise among middle-aged and older adults: Cross-sectional and longitudinal findings. Psychology and Health, 25(1) (2010): 25-42. • Wurm, S., Warner, L.M., Ziegelmann, J., Wolff, J.K., & Schüz, B. (in press). How Do Negative Self-Perceptions of Aging Become a Self-Fulfilling Prophecy? Psychology and Aging.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. A new base sample will be drawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative for community-dwelling people between 40-85 years (base sample)


The survey looks at memberships in associations for older people and in other associations, the duration of membership, frequency of volunteering, honorary office, expenditure of time for volunteering, barriers to volunteering, volunteering in the past, being interested in (more) volunteering, area of volunteering and informal help for others.


• Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010. • Tesch-Römer, C., Engstler, H. & Wurm, S. (Hrsg.). Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006. • Kohli, M. & Künemund, H. (Hrsg.). Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, 2005.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. A new base sample will be drawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative of community-dwelling people between 40-85 years (base sample).


The DEAS assesses different facets of wellbeing. In all waves, the same indicators for cognitive (life satisfaction in general, domain-specific satisfaction) and emotional wellbeing (frequency of experiencing positive and negative emotions) are available. Since 2002, a screening instrument for depression has been applied. Loneliness and optimism as further proxies for wellbeing are assessed as well in all waves. In 2014, the wellbeing module will be expanded by adding a measure of stress and by extending how wellbeing is measured.


• Kohli, M., & Künemund, H. (Hrsg.). Die zweite Lebenshälfte. Gesellschaftliche Lage und Partizipation im Spiegel des Alters-Survey (2. erweiterte Auflage). Wiesbaden: VS Verlag für Sozialwissenschaften, 2005. • Motel-Klingebiel, A., Wurm, S., & Tesch-Römer, C. (Hrsg.). Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010. • Schöllgen, I., Huxhold, O., & Schmiedek, F. Emotions and Physical Health in the Second Half of Life: Interindividual Differences in Age-Related Trajectories and Dynamic Associations According to Socioeconomic Status. Psychology and aging, 27(2) (2012): 338. • Schüz, B., Wurm, S., Warner, L. M., & Tesch-Römer, C. Health and subjective well-being in later adulthood: Different health states - different needs? Applied Psychology: Health and Well-Being, 1(1) (2009): 23-45. • Tesch-Römer, C., Engstler, H. & Wurm, S. (Hrsg.). Altwerden in Deutschland. Sozialer Wandel und individuelle Entwicklung in der zweiten Lebenshälfte. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006. • Wiest, M., Schüz, B., Webster, N., & Wurm, S. Subjective Weil-Being and Mortality Revisited: Differential Effects of Cognitive and Emotional Facets of Weil-Being on Mortality. Health Psychology, 30(6) (2011): 728. • Wiest, M., Schuez, B. E. C., & Wurm, S. Life satisfaction and feeling in control: Indicators of successful aging predict mortality in old age. Journal of Health Psychology: An Interdisciplinary, International Journal (2008): 1-10. • Wurm, S., Tomasik, M. J., & Tesch-Römer, C. Serious health events and their impact on changes in subjective health and life satisfaction: The role of age and a positive view on ageing. European Journal of Ageing, 5(2) (2008): 117-127.

Coverage


Wave 1: Data collected in 1996 (DOI 10.5156/DEAS.1996.M.001) with a sample size of 4, 838 individuals. Wave 2: Data collected in 2002 (DOI 10.5156/DEAS.2002.M.001) with a base sample of 3,084 individuals, a migrant sample of 586 individuals, and a panel sample of 1,524 individuals. Wave 3: Data collected in 2008 (DOI 10.5156/DEAS.2008.M.001) with a base sample of 6,205 individuals and a panel sample of 1,995 individuals. Wave 4: Data collected in 2011 with a panel sample of 4, 855 individuals. Wave 5: Data will be collected in 2014. A new base sample will be drawn and the panel sample will be reassessed.


1996


age (40-54, 55-69, 70-85 years), sex, region (East/West)


Registry sample


national, NUTS3-level (Kreise)


baseline samples: 40-85 years; Panel sample: 40-90 years


Population representative of community-dwelling people between 40-85 years (base sample).


The dataset allows for an analysis of intergenerational relationships in the context of psychological, economic and sociological variables. Aspects captured within the domain of intergenerational relationships are • relatives who can be asked for advice and turned to when in need for comfort and cheering up • instrumental support and financial transfers (given and received) • housework done for relatives • worries, quarrels and joy/happiness related to relatives • paternalism • spatial distance, frequency of contacts, emotional closeness (parents, children, grandchildren) • importance of the grandparent-role and childcare provided by grandparents • existence and number of great-grandchildren • evaluation of family relations


• Engstler, Heribert, & Huxhold, Oliver. Beeinflusst die Beziehung älterer Menschen zu ihren erwachsenen Kindern die räumliche Nähe zwischen den Generationen? Wechselbeziehungen zwischen Wohnentfernung, Kontakthäufigkeit und Beziehungsenge im Längsschnitt. In A. Ette, K. Ruckdeschel & R. Unger (Eds.), Potenziale intergenerationaler Beziehungen: Chancen und Herausforderungen für die Gestaltung des demografischen Wandels (2010): 175-197. Würzburg: Ergon. • Mahne, Katharina, & Motel-Klingebiel, Andreas. The importance of the grandparent role - A class specific phenomenon? Evidence from Germany. Advances in Life Course Research, 17(3) (2012): 145-155. doi: 10.1016/j.alcr.2012.06.001. • Mahne, Katharina, & Huxhold, Oliver. Social contact between grandparents and older grandchildren: a three-generation perspective. In S. Arber & V. Timonen (Eds.), Contemporary Grandparenting (2012): 225-246. Bristol, UK: The Policy Press, University of Bristol. • Mahne, Katharina. Großelternschaft in Deutschland – aktuelle Forschungsergebnisse. Stimme der Familie, 58(6) (2011). • Mahne, Katharina, & Motel-Klingebiel, Andreas. Familiale Generationenbeziehungen. In A. Motel-Klingebiel, S. Wurm & C. Tesch-Römer (Eds.), Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS) (2010): 188-214. Stuttgart: Kohlhammer. • Motel-Klingebiel, Andreas, Mahne, Katharina, & Huxhold, Oliver. Was treibt Transfers zwischen Eltern und erwachsenen Kindern an? Zur Dynamik familiärer Generationenbeziehungen im späten Lebenslauf. In A. Ette, K. Ruckdeschel & R. Unger (Eds.), Potenziale intergenerationaler Beziehungen: Chancen und Herausforderungen für die Gestaltung des demografischen Wandels (2010):. 199-216. Würzburg: Ergon. • Motel-Klingebiel, Andreas, Wurm, Susanne, & Tesch-Römer, Clemens. (Hrsg.). : Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Kohlhammer, 2010.


Linkage


The data set contains various internationally harmonised standards (e.g. ISCED-97 (International Standard Classification of Education), ISCO-88 (International Standard Classification of Occupation))., Instruments concerning housing are commonly used or self-developed.


Only regional linkage on a district level via NUTS3-level (Kreise) is possible.

Linkage


The data set contains various internationally harmonised standards (e.g. ISCED-97 (International Standard Classification of Education), ISCO-88 (International Standard Classification of Occupation)). Most health instruments are standardised questions and scales. Within the health domain, two-thirds of measures are comparable with international research (e.g. the European health module is assessed in parts).


Only regional linkage on district level via NUTS3-level (Kreise) is possible.

Linkage


Most instruments are standardised questions and scales (e.g. ISCO-88: International Standard Classification of Occupation).


not possible

Linkage


Most instruments are standardised questions and scales (e.g. ISCO-88: International Standard Classification of Occupation).


Not possible

Linkage


The dataset contains various internationally harmonised standards (e.g. ISCED-97 (International Standard Classification of Education), ISCO-88 (International Standard Classification of Occupation)). With some exceptions, the instruments in regard to attitudes towards aging are self-developed validated scales. One of the best-established scales on attitudes towards ageing (PGCMS, Lawton, 1975) is available in 2008.


Only regional linkage on district level via NUTS3-level (Kreise) is possible.

Linkage


Most instruments are standardised questions and scales (e.g. ISCO-88: International Standard Classification of Occupation).


Not possible

Linkage


The data set contains various internationally harmonised standards (e.g. ISCED-97 (International Standard Classification of Education), ISCO-88 (International Standard Classification of Occupation)). All well-being instruments are standardised, validated questions and scales. In international research, the same measurements of life satisfaction and emotional well-being are often used.


Only regional linkage on district level via NUTS3-level (Kreise) is possible.

Linkage


Most instruments are standardised questions and scales (e.g. ISCO-88).


Not possible.


Data quality


Raw data is cleaned by project organisers and checked for inconsistencies; data is further checked by the Research Data Centre, then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they have been conducted via CAPI.


Due to a change in research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies; data is further checked by the Research Data Centre, then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they have been conducted via CAPI.


Due to change in research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies; data is further checked by the Research Data Centre and then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they are conducted via CAPI.


Due to a change of the research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies. Data is further checked by the Research Data Centre and then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they have been conducted via CAPI.


Due to a change of research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies, data is further checked by the Research Data Centre, then a scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002 however, they have been conducted via CAPI.


Due to change in research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies, data is further checked by the Research Data Centre, then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they are conducted via CAPI.


Due to a change of the research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies, data is further checked by the Research Data Centre, then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they have been conducted via CAPI.


Due to a change in the research group, the documentation for 1996 is incomplete.

Data quality


Raw data is cleaned by project organisers and checked for inconsistencies. Data is further checked by the Research Data Centre, then the scientific use file (SUF) is created.


Research group changed between first and second wave (1996: Freie Universität Berlin, since 2002: German Centre of Gerontology). In 1996, interviews were conducted via PAPI, since 2002, however, they have been conducted via CAPI.


Due to a change of the research group, the documentation for 1996 is incomplete.


Applicability


The DEAS can be used to analyse questions on housing and residential environment in old age. The possible linkage of subjective data to registry information on regional context factors (such as population structure in the community, gross-domestic product of community etc.) on the NUTS3 level is a great potential of the DEAS. Further, the survey allows investigating individual changes over time (a period of 15 years), as well as differences in housing and attitudes towards housing and residential environment between cohorts. Moreover, housing needs and expectations can be linked to life transitions such as retirement and widowhood. As there is a huge variety of indicators of different life domains available, underlying mechanisms of changes over time and within age groups can be addressed. The DEAS stands out because of its interdisciplinary approach and cohort-sequential design. There are also some weaknesses. The DEAS do not include information on mobility, which limit the survey to questions concerning housing. Since regional data on mobility can be linked to the data, it is possible to investigate the association between subjective and objective data. Although the DEAS assesses participants over the age of 85 and participants living in care facilities, the sample is not representative of very old age individuals (85 years and older) and people living in retirement or care homes. Therefore, housing and housing needs within these important sub-populations cannot be investigated without loss in data quality. The first wave of the DEAS was limited to participants with German citizenship, since 2002 the inclusion criteria is ability to speak and understand German. Despite the effort to include foreigners and people with migration background, the DEAS still is not representative for this sub-population.

Applicability


The DEAS is one of the best data sources to answer questions about health in old age within Germany. Health is assessed as a multi-dimensional construct (e.g. functional, physical, subjective, and objective health measures are available). The DEAS allows investigation of individual changes over time (a period of 15 years), as well as health differences between cohorts. Moreover, health can be linked to life transitions such as retirement and widowhood. As there is a huge variety of indicators of different life domains available, underlying mechanisms of health changes over time and within age groups can be addressed. The DEAS stands out because of its interdisciplinary approach and cohort-sequential design. There are also some weaknesses. First, the majority of health indicators are self-assessed, objective health indicators are limited, bio markers are not available. Although the DEAS assesses participants over the age of 85 and participants living in care facilities, the sample is not representative for very old age (85 years and older) and persons living in retirement or care homes, therefore, health status and health changes within these important sub-populations cannot be investigated without loss of data quality. The first wave of the DEAS was limited to participants with German citizenship, since 2002 the inclusion criteria is ability to speak and understand German. Despite the effort to include foreigners and people with migration background, the DEAS still is not representative for this sub-population.

Applicability


The DEAS is a suitable data set to analyse social change and the consequences of an ageing society. It has a cohort-sequential design, so empirical analyses can be conducted in different ways – with a cross-sectional, a longitudinal or a cohort focus. The DEAS stands out because of his interdisciplinary approach. It is a multi-topic dataset, therefore items can be analysed in the context of many other variables, e.g. family structures, socio-economic status, health, attitudes on age, regional variables. Moreover, the German Ageing Survey includes variables on a wide variety of topics combining psychological, economic and sociological aspects as well as subjective indicators. For the topic “Social Systems and Welfare State” the DEAS provides information on various aspects of the socio-economic status, on employment and transition to retirement, on household incomes, financial transfers and living standards. There is no information on foreigners living in Germany (with the exception of the wave in 2002) or on people not living in private households (these groups are not in the sample). The very old population is missing or underrepresented. Nevertheless, it can be pointed out that there is good documentation (survey instruments, methodological reports, codebooks, correspondence of variables) available on the website of the Research Data Centre (www.dza.de/.../deas-documentation.html
).

Applicability


Due to the panel design of the German Ageing Survey, individual changes in work and productivity over time (a period of up to 15 years), as well as differences in work and productivity between cohorts (social change) and retirement policies can be analysed. However, the survey does not provide detailed retrospective data but mainly data on current employment instead. What is more, the survey also provides information on the employment situation of officially unemployed persons (job-seeking, black labour, 1Euro-Jobs etc.). Moreover, the German Ageing Survey includes variables on a wide variety of topics combining psychological, economic and sociological aspects, as well as subjective indicators which can be linked to research on work and productivity. Moreover, the survey provides information on the educational attainment and the occupational position of the current and the last partner of the respondent, as well as for his/her parents and children. Therefore, intergenerational occupational mobility can be analysed. Moreover, information on the occupational positions of network members is provided. However, the first wave of the DEAS was limited to participants with German citizenship, but since 2002, the inclusion criteria is the ability to speak and understand German. Despite the effort to include foreigners and people with migration background, the DEAS still is not representative for this sub-population. In addition, it should be pointed out that there is a good documentation (survey instruments, methodological reports, codebooks, correspondence of variables) provided on the website of the Research Data Centre (www.dza.de/.../deas-documentation.html
).

Applicability


The DEAS is the best data source to describe and analyse attitudes towards ageing in Germany. Individual images of ageing have been assessed in all waves. However, public attitudes towards ageing have so far only been assessed explicitly in 2008. Moreover, the DEAS assessed if individuals have experienced ageism in 2008 as well. Due to the cohort-sequential design and interdisciplinary focus, the DEAS allows analysis of how attitudes toward one’s own ageing affect other life domains and which factors influence attitudes towards own ageing. There are also some weaknesses. Although the DEAS assesses participants over the age of 85 and participants living in care facilities, the sample is not representative for very old age (85 years and older) and persons living in institutions, therefore, images of ageing and changes in images of ageing within these sub-populations cannot be investigated without loss of data quality. The first wave of the DEAS was limited to participants with German citizenship, since 2002 the inclusion criteria is ability to speak and understand German. Despite the effort to include foreigners and people with migration background, the DEAS is still not representative for this sub-population.

Applicability


The DEAS reports several issues on volunteering: membership in clubs, frequency of and time spent on voluntary activities in clubs and organisations, and areas of volunteering. As an ageing survey with respondents aged 40 and above, the DEAS gives, in addition, in-detail-information on specialised clubs and organisations for the elderly. The DEAS is a multi-topic data set, therefore these items can be analysed in the context of many other variables, e. g. family structure, socio-economic status, health, attitudes on age, regional indicators. The DEAS provides longitudinal data and because of its cohort-sequential design the analysis of different cohorts regarding volunteering is possible. There is no information on foreigners living in Germany (with the exception of wave 2002) and on people not living in private households – these groups are not in the sample. Nevertheless, it can be pointed out that there is a good documentation (survey instruments, methodological reports, codebooks, correspondence of variables) available on the website of the Research Data Centre (www.dza.de/.../deas-documentation.html
).

Applicability


Differences in wellbeing and changes in wellbeing over time and between cohorts, age groups and other sub-groups can be described and investigated using the DEAS due to the cohort-sequential design. The assessment of multiple facets of wellbeing and the interdisciplinary focus of the DEAS allows detailed analysis of underlying mechanisms and effects of wellbeing. In contrast to other surveys, emotional wellbeing is assessed using a standardised measurement. Most surveys focus on cognitive wellbeing and ask about life satisfaction or domain-specific satisfaction. Although the DEAS assesses participants over the age of 85 and participants living in care facilities, the sample is not representative of people of a very old age (85 years and older) and individuals living in retirement or care homes; hence wellbeing and changes in wellbeing within these important sub-populations cannot be investigated without loss of data quality.

Applicability


With the German Ageing Survey, individual changes in intergenerational relationships over time (a period of 15 years), as well as differences in intergenerational relationships between cohorts (social change) can be analysed. Moreover, intergenerational relationships can be analysed in the context of psychological, health, economic and sociological aspects. Due to the composition of the sample, the focus of intergenerational relationships is on relationships in old age, which means that early parent-child-relationships are not captured. The grandparents’ perspective in particular is not part of many studies on intergenerational relationships. However, certain aspects of intergenerational relationships, such as support or conflicts, are not captured or at least not (yet) in detail. Moreover, intergenerational relationships are not captured in a dyadic perspective (no multi-actor design). What is more, the first wave of the DEAS was limited to participants with German citizenship, but since 2002, the inclusion criteria is ability to speak and understand German. Despite the effort to include foreigners and people with migration background, the DEAS still is not representative of this sub-population. In addition, it should be pointed out that there is good documentation (survey instruments, methodological reports, codebooks, correspondence of variables) provided on the website of the Research Data Centre (www.dza.de/.../deas-documentation.html
).


  • The information about this dataset was compiled by the author:
  • Andreas Motel-Klingebiel
  • (see Partners)