Register based research in the nordic countries
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Register-based research in the Nordic countries. Mika Gissler Nordic School of Public Health, Gothenburg, Sweden & THL National Institute for Health and Welfare, Helsinki, Finland. Why good possibilities to register-based studies?.

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Register-based research in the Nordic countries

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Register-based research in the Nordic countries

Mika Gissler

Nordic School of Public Health, Gothenburg, Sweden &

THL National Institute for Health and Welfare, Helsinki, Finland

Why good possibilities to register-based studies?

  • Traditions: population statistics have been collected more than 250 years and health statistics more than 150 years in the Nordic countries.

  • First real registers were started in the 1940-1950s, when improved computers were available: health care personnel, cancer register.

  • Personal identification numbers since 1960s.

  • Several data quality studies have shown the high quality of routinely collected registers.

  • Data protection allows research use of register data.

Important registers in the Nordic countries

  • Cancer register1940s

  • Registers on infectious diseases1950s

  • Hospital discharge registers1960s

  • Cause-of-death registers1960s

  • Birth and malformation registers1960s

  • Register-based Census1990s

  • Health care quality registers1990s

  • Prescription registers1990s

  • Hospital outpatient registers1990s

Unique registers and data in the Nordic countries

  • IVF (in vitro fertilization) register, Denmark

  • Register on induced abortions and sterilisations, Finland

  • Register on visual impairments, Finland

  • Register on breast and cervical cancer screening, Finland

  • Multiple generation register, Sweden

  • Multiple generation studies in the Norwegian Medical Birth Register

  • Biobanks in all Nordic countries + possibilities to link them to other registers.

Important registers for studies in psychiatry and mental health

  • Hospital discharge registers1960s

  • Cause-of-death registers1960s

  • Pension Registers1960s

  • Register-based Census1990s

  • Prescription registers1990s

  • Hospital outpatient registers1990s

Examples of register-based studies in psychiatry and mental health

  • Register-based studies:

    • Cross-sectional studies

    • Trends

    • Longitudinal studies

  • Combination of data from different sources:

    • Medical records

    • Questionnaires

    • Biobank material

Example 1: Life expectancy among psychiatric patients

  • Registers:

    • THL: Hospital Discharge Register 1980-2003

    • Finnish Centre of Pension: Pension Register 1980-2003

    • Statistics Finland: Cause-of-Death Register 1981-2003

  • Data:

    • The data included 361 898 persons aged 15 years or more

    • 17 638 persons with dementia and 2 630 with intellectual disability were excluded

  • Life expectancy at 15 years and for ages 15-64 years were calculated separately by using Wiesler's method.

Life expectancy increased


  • Life expectancy at 15 years has increased among Finnish population with hospital discharge or pension due to mental disorders between 1981 and 2003:

    • Finland: +3.5 years, psychiatric patients +5.8 years

      • F30-39: +10 years, F40-49: +8 years, F20-29: +6 years, but

      • F10-19: -0.6 years

  • Risk for death

    • diseases and medical conditions 2-fold

    • external causes and poisoning 6-fold

  • Similar results from other Nordic countries.

Example 2: Maternal smoking and children’s F-diagnoses

  • Registers:

    • THL: Medical Birth Register 1987-1989

    • THL: Hospital Discharge Register 1987-2007

    • Social Insurance Institute: Reimbursed psychotropic medicine 1994-2007

    • Statistics Finland: Cause-of-Death registers 1987-2008

  • Data:

    • Children born in 1987-1989, excluding perinatal deaths, multiples, and children with major congenital anomalies

    • Final study population: 175 869 children (94.4%)

Risk for adverse psychiatric outcomes by maternal smoking

Adjusted by maternal age, parity, sex, gestational age, birth weight, 5 minute Apgar score and

maternal psychiatric diagnosis before birth.


  • Children exposed to maternal smoking has an increased risk for receiving a F-diagnosis in inpatient or outpatient care in childhood and adolescent.

  • The increased risk can be observed for all diagnosis excluding schizophrenia and anorexia.

  • Register studies cannot confirm the real effect of smoking.

    • However, a recent local study in Turku has shown that prenatal smoking exposure is associated with smaller regional brain volumes in preterm infants (Ekblad et al., J Pediatrics 2009).

Example 3: Use of psychotropic drugs and pregnancy outcomes

  • Registers:

    • The ‘Drug and Pregnancy’ -database 1996-2006, to be annually completed 2007 onwards

  • Data:

    • All births in the Medical Birth Register

    • All induced abortions in the Abortion Register

    • All congenital anomalies in the Malformation Register

      • Use of prescribed & reimbursed drugs (Social Insurance Institution)

        • 3 months before pregnancy

        • during pregnancy

        • 3 months after pregnancy

The use of psychotropic medicine before the pregnancy starts

  • The Drug and Pregnancy -database 1996-2006:

    • Total 622 671 births and 117 229 induced abortions

    • Excluded: induced abortions due to fetal reasons

    • Separate analysis: first pregnancies

  • All drug purchases 3 months before pregnancy were used as a proxy measure of mental health disorders.


  • Measured by the use of psychotropic medicine, women’s pre-existing mental health status is worse for women having an induced abortion than for women giving a birth.

    • All pregnancies: Adjusted OR 1.94 (95% CI 1.87-2.02)

    • First pregnancies: Adjusted OR 1.56 (95% CI 1.44-1.68)

    • Highest risk for women using hypnotics and sedatives, antipsychotics and antidepressants.

  • This essential confounding factor should not be neglected when investigating the occurrence of pregnancy-related mental health problems.

Example 4: Mothers’ and children’s long-term follow-up after substance abuse during pregnancy

  • Basic data:

    • 524 women followed-up prenatally at special out-patient clinics and a control group of 1792 women matched for maternal age, parity, time and place of delivery.

  • Registers:

    • THL: Medical Birth Register, Hospital Discharge Register, Child Welfare Register

    • Statistics Finland: Cause-of-Death Register

    • Social Insurance Institution: Information on prescribed medicine, social benefits, pensions and rehabilitations

Mothers’ outcome, %


  • Death 8.0 0.2***

  • F-diagnosis, inpatient46.0 3.6 ***

  • F-diagnosis, outpatient47.1 8.3 ***

  • Intoxication care41.3 1.8 ***

  • Pensions, any cause16.8 2.2 ***

  • Rehabilitation, any cause 9.5 5.6 ***

  • Special reimbursement27.018.4 ***

    • Psychosis10.9 1.4 ***

  • Drug reimbursement N0571.420.9 ***

  • Drug reimbursement N0668.126.5 ***

Children’s outcome, %


  • Death 1.4 1.0NS

  • F-diagnosis, inpatient 7.1 2.8 ***

  • F-diagnosis, outpatient 8.1 2.6 ***

  • Care benefit for sick child25.0 13.9 ***

  • Rehabilitation, any cause 5.1 2.4 ***

  • Special reimbursement12.111.1 NS

  • Drug reimbursement N05 9.1 5.6 **

  • Drug reimbursement N06 4.6 1.4 ***

  • Child taken into custody46.0 2.4***


  • Combination of medical records and registers was feasible, even though it was difficult to get all the necessary permissions.

  • Women with substance abuse displayed significant long-term abuse-related morbidity and mortality, rehabilitation, early retirement, and use of prescribed medicine.

  • Also their children had increased morbidity, rehabilitation, and use of prescribed medicine, and almost half of them were taken into custody.

Why register research?

  • Easy to form data:

    • cross-sectional studies

    • longitudinal studies (history, follow-up)

  • Easy to repeat the same study.

  • No limitations for sample size (rare cases --- total population).

  • Population-based studies feasible.

  • No need to contact patients.

  • Follow-up relatively easy.

  • No participation bias nor research bias.

  • No reporting bias.

Problems related to register research

  • The data is unavailable

    • primary health care, diseases and conditions not requiring a contact to health care system, self-rated health, opinions, experiences,...

  • Data protection: are such studies possible in general?

  • Ethically controversial topics:

    • abortion, miscarriage, infertility, malformations, psychiatric disorders, family studies, contact to relatives of a death patient, genetics…

  • High data costs: Statistical offices, Central Population Register

  • Data overload syndrome

    • Too much data, too little time…?

  • Fishing:

    • Easy to find statistically significant results, if the data is large.


  • Register-based studies seems to be feasible, e.g. for cross-sectional, longitudinal and trend studies

  • Combination of data from other registers and from other sources, such as medical records, questionnaires and even biobank material is possible.

  • Data protection questions have not been an issue, at least until now.

  • The lack of information from primary health care will be solved after the national electronic patient journal system is in use.

Promotion of register research

  • Denmark: National Centre for Register-based Research, Århus Universitet

  • Finland: Finnish Information Centre for Register Research

  • Norway: Special issue on register-based research in Norsk Epidemiologi 14 (1): 2004.

  • Sweden: Grants for register-based research by the National Board of Welfare and Health (Social-styrelsen)

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