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

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          Abstract

          Education, income, and occupation are factors known to affect health and disease. In this review we describe the Swedish Longitudinal Integrated Database for Health Insurance and Labour Market Studies (LISA, Longitudinell Integrationsdatabas för Sjukförsäkrings- och Arbetsmarknadsstudier). LISA covers the adult Swedish population aged ≥ 16 years registered on December 31 each year since 1990 (since 2010 individuals aged ≥ 15 years). The database was launched in response to rising levels of sick leave in the country. Participation in Swedish government-administered registers such as LISA is compulsory, and hence selection bias is minimized. The LISA database allows researchers to identify individuals who do not work because of injury, disease, or rehabilitation. It contains data on sick leave and disability pension based on calendar year. LISA also includes information on unemployment benefits, disposable income, social welfare payments, civil status, and migration. During 2000–2017, an average of 97,000 individuals immigrated to Sweden each year. This corresponds to about 1% of the Swedish population (10 million people in 2017). Data on occupation have a completeness of 95%. Income data consist primarily of income from employment, capital, and allowances, including parental allowance. In Sweden, work force participation is around 80% (2017: overall: 79.1%; men 80.3% and women 77.9%). Education data are available in > 98% of all individuals aged 25–64 years, with an estimated accuracy for highest attained level of education of 85%. Some information on civil status, income, education, and employment before 1990 can be obtained through the Population and Housing Census data (FoB, Folk- och bostadsräkningen).

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          The Swedish Multi-generation Register.

          The Swedish Multi-generation Register consists of data of more than nine million individuals, with information available on mothers in 97% and on fathers in 95% of index persons. Index persons are confined to those born from 1932 onwards and those alive on January 1, 1961. This register is a unique resource but is still underutilized.
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            Weight Loss and Heart Failure

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              Schizophrenia and subsequent neighborhood deprivation: revisiting the social drift hypothesis using population, twin and molecular genetic data

              Neighborhood influences in the etiology of schizophrenia have been emphasized in a number of systematic reviews, but causality remains uncertain. To test the social drift hypothesis, we used three complementary genetically informed Swedish cohorts. First, we used nationwide Swedish data on approximately 760 000 full- and half-sibling pairs born between 1951 and 1974 and quantitative genetic models to study genetic and environmental influences on the overlap between schizophrenia in young adulthood and subsequent residence in socioeconomically deprived neighborhoods. Schizophrenia diagnoses were ascertained using the National Patient Registry. Second, we tested the overlap between childhood psychotic experiences and neighborhood deprivation in early adulthood in the longitudinal Twin Study of Child and Adolescent Development (TCHAD; n=2960). Third, we investigated to what extent polygenic risk scores for schizophrenia predicted residence in deprived neighborhoods during late adulthood using the TwinGene sample (n=6796). Sibling data suggested that living in deprived neighborhoods was substantially heritable; 65% (95% confidence interval (95% CI): 60–71%) of the variance was attributed to genetic influences. Although the correlation between schizophrenia and neighborhood deprivation was moderate in magnitude (r=0.22; 95% CI: 0.20–0.24), it was entirely explained by genetic influences. We replicated these findings in the TCHAD sample. Moreover, the association between polygenic risk for schizophrenia and neighborhood deprivation was statistically significant (R 2=0.15%, P=0.002). Our findings are primarily consistent with a genetic selection interpretation where genetic liability for schizophrenia also predicts subsequent residence in socioeconomically deprived neighborhoods. Previous studies may have overemphasized the relative importance of environmental influences in the social drift of schizophrenia patients. Clinical and policy interventions will therefore benefit from the future identification of potentially causal pathways between different dimensions of cognitive functions and socioeconomic trajectories derived from studies adopting family-based research designs.
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                Author and article information

                Contributors
                +46 (0) 8-52480000 , jonasludvigsson@yahoo.com
                Journal
                Eur J Epidemiol
                Eur. J. Epidemiol
                European Journal of Epidemiology
                Springer Netherlands (Dordrecht )
                0393-2990
                1573-7284
                30 March 2019
                30 March 2019
                2019
                : 34
                : 4
                : 423-437
                Affiliations
                [1 ]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Department of Medical Epidemiology and Biostatistics, , Karolinska Institutet, ; Stockholm, Sweden
                [2 ]ISNI 0000 0001 0123 6208, GRID grid.412367.5, Department of Paediatrics, , Örebro University Hospital, ; Örebro, Sweden
                [3 ]ISNI 0000 0004 1936 8868, GRID grid.4563.4, Division of Epidemiology and Public Health, School of Medicine, , University of Nottingham, ; Clinical Sciences Building 2, City Hospital, Nottingham, UK
                [4 ]ISNI 0000000419368729, GRID grid.21729.3f, Department of Medicine, , Columbia University College of Physicians and Surgeons, ; New York, NY USA
                [5 ]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Clinical Epidemiology Unit, Department of Medicine Stockholm, , Karolinska Institutet, ; Stockholm, Sweden
                [6 ]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Division of Insurance Medicine, Department of Clinical Neuroscience, , Karolinska Institutet, ; Stockholm, Sweden
                Author information
                http://orcid.org/0000-0003-1024-5602
                http://orcid.org/0000-0003-2300-3055
                Article
                511
                10.1007/s10654-019-00511-8
                6451717
                30929112
                624f8f04-5757-4be6-8600-07bdb8c7059d
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 29 January 2019
                : 12 March 2019
                Categories
                Data Resources
                Custom metadata
                © Springer Nature B.V. 2019

                Public health
                education,income,labour market,occupation,social support,sweden
                Public health
                education, income, labour market, occupation, social support, sweden

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