Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

The Malmö longitudinal study on education

Education and Learning
Relevance for this Topic
Country Sweden
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Contact information

Denny Vågerö / CHESS
University of Stockholm
106 91 Stockholm
Phone: +468-162000
Email: Denny.vagero(at)

Timeliness, transparency

Data is only available for research purposes (agreement with principal investigator needed).

Type of data

Registry + Survey

Type of Study

Longitude survey: long-term study of the same sample

Data gathering method

Face-to-face interview (CAPI, PAPI)


individual tests

Access to data

Data is only available for research purposes; an agreement with the principal investigator is needed.

Conditions of access

Contact principal investigator

Between two and four months

anonymised microdata, aggregated tables, etc.

Dataset is compatible to Excel, SAS, SPSS, STATA, Text, etc.

Dataset is in Swedish – general information is available in English.


The Malmö study is one of the oldest longitudinal study in education. The cohort includes all the third graders in the county of Malmö in 1938 with a total of 1,542 pupils were included in the study, of which 1,342 were normal-aged (born 1928). Register data has been collected at intervals, fourteen times: 1948, 1953, 1958, 1963, 1968, 1969, 1971, 1978, 1980, 1982, 1984, 1986, 1991, and 1993. For the five first occasions, the county tax registers were the source of information, and the people involved collected data more or less manually. For 1969 and 1971, data was bought from Statistics Sweden, while from 1978 and onward data was bought from SPAR (a special State Register established at the State Computing Center (DAFA) in 1978). Additional studies have been done in recent years.


Registry plus cohort follow ups

cohort of school pupils 1938 in Malmö City

10 years of age at start – today 85 years of age for surviving respondents


IQ, school achievement, health and family context, social selection and occupation over the life span.

• Lager, A. “The role of education and cognitive skills in understanding mortality inequalities.” Dissertation, University of Stockholm (2011). • Lager, A., Bremberg, S., & Vågerö, D. “The association of early IQ and education with mortality: 65 year longitudinal study in Malmö, Sweden.” BMJ 339(b5282) (2009). • Lager, A., Vågerö, D., & Bremberg, S. “The effects of own childhood intelligence, own education and partner’s education on mortality between age 54 and 78: A prospective study.” [Submitted] • Lager, A., & Torssander, J. “The causal effect of education on mortality: 58-year follow-up of a quasi-experiment on 1.2 million Swedes.” [Submitted] • Lager, A., Modin, B., De Stavola, B., & Vågerö, D. “Social origin, schooling and individual change in intelligence during childhood influence long-term mortality: a 68-year follow-up study.” International Journal of Epidemiology 41(2) (2012): 398-404. doi: 10.1093/ije/dyr139 • Sandgren, S. "Learning and earning: studies on a cohort of Swedish men". Dissertation. KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Fastigheter och (2005).


Data harmonised with ISCED taxonomy.

Connections with other Swedish datasets are possible, but have to be related to ethical issues and access to data.

Data quality

Contact principal investigator.

In 1964, Husén, together with a group at his department, carried out the first questionnaire follow-up, while at the same time collecting data from registers. In 1971, 1984 and 1994 further questionnaires were distributed and collected. The response rate has generally been between 72 and 75 per cent.

High level of consistency during the process of investigation.


The strength of this dataset is that it provides the possibility to follow a cohort in a life-course perspective from education to work, family building and retirement. It can also focus on the role of early cognitive skills and its impact on adaptation in a life-course perspective. The weaknesses is, of course, that it is a selective geographical context.

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