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The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research

Ludvigsson, Jonas F., Svedberg, Pia, Olén, Ola, Bruze, Gustaf, Neovius, Martin·2019·European Journal of Epidemiology
DOI 10.1007/s10654-019-00511-8PMC PMC6451717
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Fig. 1 Number of immigrants to Sweden annually between 2000 and 2017
Fig. 1 Number of immigrants to Sweden annually between 2000 and 2017CC BY · PubMed Central
Fig. 2 Levels of education. Theoretical education denotes years of education in the highest education category a person belongs to. Persons who have completed 3 years of upper secondary school (and no college/university education) will receive a code for “upper secondary” and the value “3” (3 years of theoretical education in their education category). Values in Fig. 2 may not represent all persons belonging to a certain career type (for instance, there are of course farmers with a theoretical education). The easiest way to retrieve data on education from LISA is to use the seven levels of SUN2000Niva_Old (1 = not completed compulsory education (< 9 years), 2 = completed compulsory education (9 years), 3 = upper secondary (2 years), 4 = upper secondary (3 years), 5 = college/university < 3 years, 6 = college/university ≥ 3 years, 7 = research education). In the newer SUN2000 the levels 3 + 4 from SUN2000Niva_Old have been merged (value “3”). This means that the new SUN2000NIVA ranges only has six levels
Fig. 2 Levels of education. Theoretical education denotes years of education in the highest education category a person belongs to. Persons who have completed 3 years of upper secondary school (and no college/university education) will receive a code for “upper secondary” and the value “3” (3 years of theoretical education in their education category). Values in Fig. 2 may not represent all persons belonging to a certain career type (for instance, there are of course farmers with a theoretical education). The easiest way to retrieve data on education from LISA is to use the seven levels of SUN2000Niva_Old (1 = not completed compulsory education (< 9 years), 2 = completed compulsory education (9 years), 3 = upper secondary (2 years), 4 = upper secondary (3 years), 5 = college/university < 3 years, 6 = college/university ≥ 3 years, 7 = research education). In the newer SUN2000 the levels 3 + 4 from SUN2000Niva_Old have been merged (value “3”). This means that the new SUN2000NIVA ranges only has six levelsCC BY · PubMed Central
Fig. 3 Sickness benefits for people aged 15–64 years. The LISA database only contains data on sick leave after the first 14 days. LISA data on sick leave originate from income data reported from the Swedish Social Insurance Agency (and from this it can be deduced that an individual is on sick leave). In 1990–1993, the sickness benefit after the first 14 days was registered by the variable SjukPA and since 1990 also as SjukPP. LISA contains data on days of sick leave as well as the actual income. Number of days always refers to the same year, but income for sickness in December will be paid in January the next year. Number of days is recorded by the variables SjukP_bdag/SjukP_ndag (and for rehabilitation allowance, Rehab_bdag/Rehab_ndag). Bdag represents the gross number of days away from work due to sickness, whereas Ndag is the net number of days (“full sickness days”; e.g., an individual is on sick leave all afternoons (50%) for 14 days. He or she will then have 14 SjukP_bdag but only 7 SjukP_ndag). In the future, Statistics Sweden plan to retrieve data on a monthly basis (rather than annually), which will facilitate studies on the relationship between timing of disease and prior/later work absence. The qualifying day was removed in Sweden in 2019
Fig. 3 Sickness benefits for people aged 15–64 years. The LISA database only contains data on sick leave after the first 14 days. LISA data on sick leave originate from income data reported from the Swedish Social Insurance Agency (and from this it can be deduced that an individual is on sick leave). In 1990–1993, the sickness benefit after the first 14 days was registered by the variable SjukPA and since 1990 also as SjukPP. LISA contains data on days of sick leave as well as the actual income. Number of days always refers to the same year, but income for sickness in December will be paid in January the next year. Number of days is recorded by the variables SjukP_bdag/SjukP_ndag (and for rehabilitation allowance, Rehab_bdag/Rehab_ndag). Bdag represents the gross number of days away from work due to sickness, whereas Ndag is the net number of days (“full sickness days”; e.g., an individual is on sick leave all afternoons (50%) for 14 days. He or she will then have 14 SjukP_bdag but only 7 SjukP_ndag). In the future, Statistics Sweden plan to retrieve data on a monthly basis (rather than annually), which will facilitate studies on the relationship between timing of disease and prior/later work absence. The qualifying day was removed in Sweden in 2019CC BY · PubMed Central
Fig. 4 Number of individuals in labour market policy measures in Sweden by year
Fig. 4 Number of individuals in labour market policy measures in Sweden by yearCC BY · PubMed Central
Fig. 5 Disposable income. After taxes and allowances, the mother earns 150,000 SEK and the father 200,000 SEK for the year. In this family the son earns money (50,000 SEK, but he is not included in LISA because he is < 15 years old). The total disposable income of the family, however, is 400,000 SEK (represented by the value of DispInkFam(04) assigned to all individuals in the family). When divided by the consumption weight of this family (2.45), each family member is assigned the value 1633 (representing 163,300 SEK). In LISA, all statistics on income represent multiples of 100 SEK
Fig. 5 Disposable income. After taxes and allowances, the mother earns 150,000 SEK and the father 200,000 SEK for the year. In this family the son earns money (50,000 SEK, but he is not included in LISA because he is < 15 years old). The total disposable income of the family, however, is 400,000 SEK (represented by the value of DispInkFam(04) assigned to all individuals in the family). When divided by the consumption weight of this family (2.45), each family member is assigned the value 1633 (representing 163,300 SEK). In LISA, all statistics on income represent multiples of 100 SEKCC BY · PubMed Central
Fig. 6 Basic amount (Swedish: “basbelopp”)
Fig. 6 Basic amount (Swedish: “basbelopp”)CC BY · PubMed Central

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Metadata

Authors
Ludvigsson, J. F., Svedberg, P., Olén, O., Bruze, G., & Neovius, M.
Venue
European Journal of Epidemiology
Publisher
Springer Science and Business Media LLC
Published
2019-03-30
Volume
34
Issue
4
Pages
423-437
ISSN
  • 0393-2990
  • 1573-7284
DOI
10.1007/s10654-019-00511-8
PMC
PMC6451717
Cited by
1,021
References
2
Language
en
Licence
creativecommons.org/licenses/by/4.0 (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research. https://app.cochat.ai/papers/10.1007/s10654-019-00511-8
The paper
Ludvigsson, J. F., Svedberg, P., Olén, O., Bruze, G., & Neovius, M. (2019). The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research. European Journal of Epidemiology. https://doi.org/10.1007/s10654-019-00511-8