Lifecourses in Europe Analyses of SHARE & ELSA
by Morten Wahrendorf, ICLS
Home Chronogram Maps Methods References
  • Data sources

  • The graphs on these pages are based on two studies on ageing, the 'English Longitudinal Study of Ageing' (ELSA) and the 'Survey of Health, Ageing and Retirement in Europe' (SHARE). Both studies were developed in close coordination, with a focus on harmonization of research methods and study designs to allow for cross-national comparisons. While ELSA began 2002 (in England only), the first wave of SHARE was 2004-2005 (Sweden, Denmark, Germany, Netherlands, Belgium, France, Switzerland, Austria, Italy, Spain and Greece) with on-going waves of data collection in two-year intervals in both studies and two new countries joining SHARE in 2006-2007 (Czech Republic and Poland). In each country, samples consist of a probability household sample, with individuals aged 50 years or older plus their (possibly younger) partners being interviewed using Computer Assisted Personal Interviews (CAPI). New cohorts (so called "refreshers") are added subsequently to maintain population representation.
    In addition to "regular" waves focussing on the collection of current circumstances, both surveys also conducted separate retrospective interviews collecting information on previous life courses (ELSA life history in 2007 and SHARELIFE in 2008-2009, see figure below). Details about the entire SHARE project are available at and at for ELSA. By using data from the retrospective surveys, it is possible to analyse previous employment and family histories across 14 European countries.

  • The lifegrid-approach

  • In both surveys, life-course information were collected with the so called "lifegrid approach", where data collection is supported by a visual representation of respondent's life that is filled in the course of the interview. The lifegrid method was developed first for use in the Boyd Orr Cohort as a self-completion questionnaire (Blane, 1996) with subsequent development of a CAPI version by UK National Centre for Social Research for ELSA (Scholes et al., 2009) which was adopted for SHARELIFE (Schröder, 2011). Several advantages of this method were described compared to prospective data collections. Foremost, it is a fast and less expensive method to obtain longitudinal information and assures that comparable information (referring to different time points) is collected, without missing data due to drop out during follow-up periods. Furthermore, studies show that the accuracy of recalled information is very high when asking about sociodemographic factors (Berney & Blane, 1997; Havari & Mazzona, 2011) including previous employment and family histories (Baumgarten, Siemiatycki, & Gibbs, 1983; Bourbonnais, Meyer, & Theriault, 1988).

  • Employment histories

  • The employment modules of both surveys ask when the respondents left full-time education and collects details on each job a respondent had during his or her working career together with each period when the respondent was not employed. Information on jobs includes the starting and ending date and whether the job was part-time or full-time. Information on periods when the respondent was not in paid employment includes a description of the situation, including retirement, domestic work (looking after the home and family), unemployment, further full-time education or a period of sickness absence. For our analyses, we combined these data and created a categorical variable describing the occupational situation for each age between 15 and 65. More specifically, we considered existing information on gaps, on jobs or on age when leaving full-time education, resulting in a variable distinguishing between nine categories: : (1) full-time work (35 hours or longer), (2) part-time work (less than 35 hours), (3) unemployment, (4) sick or disabled, (5) domestic work, (6) retirement, (7) voluntary work (8) full-time education, and (9) other. Because of low frequencies, "sick or disbaled" and "voluntary work" were additionally counted as "other" in case of the chronogram-graphs.

  • Family histories

  • The family modules include details on the partnership and children histories. In case of children history, the birth year of each child is assessed (or year of adoption) an - in case - the year of death. Based on this information, we measured for each age between 15 and 65 number and ages of children (either own or adopted). We then constructed three variables, one describing the overall number of children at a given age (regardless of age of children), one measuring the number of children under 6 at each age, and finally a variables counting the number of children under age 17.
    With regards to living arrangements, we combined information of whether the respondents lived with a partner at the age (without considering the marital status), resulting in a simple binary variables (partnership yes/no).

  • Graphs

  • Graphs are based on visualization tools provided by Google (motionchart and maps) or based on D3.js (chronogram). Details about Google visualizations can be found here. Information on D3.js is provided here. Analyses and recoding procedures were done with STATA. All codes are avaialble on request.

    Baumgarten, M., Siemiatycki, J., & Gibbs, G. W. (1983). Validity of Work Histories Obtained by Interview for Epidemiologic Purposes. American Journal of Epidemiology, 118(4), 583-591.
    Berney, L. R., & Blane, D. B. (1997). Collecting retrospective data: Accuracy of recall after 50 years judged against historical records. Social Science & Medicine, 45(10), 1519-1525. doi: Doi 10.1016/S0277-9536(97)00088-9
    Blane, D. B. (1996). Collecting retrospective data: Development of a reliable method and a pilot study of its use. Social Science & Medicine, 42(5), 751-757. doi: Doi 10.1016/0277-9536(95)00340-1
    Bourbonnais, R., Meyer, F., & Theriault, G. (1988). Validity of Self Reported Work History. British Journal of Industrial Medicine, 45(1), 29-32.
    Havari, E., & Mazzona, F. (2011). Can we trust older people's statements on their childhood circumstances? Evidence from SHARELIFE. SHARE Working Paper Series(05-2011).
    Scholes, S., Medina, J., Cheshire, H., Cox, K., Hacker, E., & Lessof, C. (2009). Living in the 21st century: older people in England. The 2006 English Longitudinal Study of Ageing Technical Report. London.
    Schröder, M. (2011). Retrospective Data Collection in the Survey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology. Mannheim.
Mail: Based on SHARELIFE and ELSA lifehistory data