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Epidemiological Research

Epidemiological research deals with mapping of health and disease in populations and studying factors affecting initiation and prognosis.

The course of musculoskeletal disorders (MSD) and the factors affecting prognosis are not well understood. This is because there is a lack of longitudinal studies investigating these prevalent conditions which occur at all ages, in clusters, and very often alongside other health problems of both physical and psychological natures in complex social contexts. A "pain in the back" or in another body location is no longer always being regarded as an isolated disease entity but in many instances as an expression of overall poor health in the individual. Depending on co-occurring symptoms and diseases, ability to cope with pain, psychological well-being, and social factors, presumably simple pains can therefore have very variable courses in individuals and result in different consequences. Mapping of such patterns and longitudinal studies reporting on the course and prognosis in groups of the population has recently provided new insights and it is likely that future epidemiological studies will bring forward crucial evidence that will fundamentally change the way we manage MSD.

In Denmark we have unique opportunities for epidemiological research using the large population-based databases and public registries. These data sources are easily and cheaply accessible and information can be combined using the person-specific cpr number which is assigned to all Danes by law.

Researchers from The Research Unit for Clinical Biomechanics have published extensively in this area using data from The Danish Twin Registry and Statistics Denmark. These collaborations will be strengthened and expanded and new data sources such as the Danish National Cohort Study (DANCOS) and new quality assurance databases in the Region of Southern Denmark will be incorporated.

Specifically, we will

  • Investigate and map patterns of co-occurring musculoskeletal and other health complaints at all ages
  • Study the longitudinal course of these patterns in relation to impact on quality of life and consequences in the form of seeking of health care, functional limitation, change in participation in social life and sports, and loosing work
  • Identify predictors of consequences and prognostic markers both in population-based and patient populations
  • Study how clinical, anamnestic, psychosocial, and physiological information can be combined in defining clinically relevant subgroups
  • Participate in prognosis research based on advanced statistical models in cohorts aiming at identifying groups of patients with particularly poor or particularly good prognoses