title: [The benefit of large-scale cohort studies for health research: the example of the German National Cohort].
abstract: The prospective nature of large-scale epidemiological multi-purpose cohort studies with long observation periods facilitates the search for complex causes of diseases, the analysis of the natural history of diseases and the identification of novel pre-clinical markers of disease. The German National Cohort (GNC) is a population-based, highly standardised and in-depth phenotyped cohort. It shall create the basis for new strategies for risk assessment and identification, early diagnosis and prevention of multifactorial diseases. The GNC is the largest population-based cohort study in Germany to date. In the year 2014 the examination of 200,000 women and men aged 20-69 years started in 18 study centers. The study facilitates the investigation of the etiology of chronic diseases in relation to lifestyle, genetic, socioeconomic, psychosocial and environmental factors. By this the GNC creates the basis for the development of methods for early diagnosis and prevention of these diseases. Cardiovascular and respiratory diseases, cancer, diabetes, neurodegenerative/-psychiatric diseases, musculoskeletal and infectious diseases are in focus of this study. Due to its mere size, the study could be characterized as a Big Data project. We deduce that this is not the case.
authors.affiliation: Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Bremen, Achterstraße 30, 28359, Bremen, Deutschland. ahrens@bips.uni-bremen.de.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Ahrens
authors.affiliation: Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Essen, Deutschland.
authors.forename: K-H
authors.initials: KH
authors.lastname: Jöckel
mesh_terms: D002908:Chronic Disease / Q000453:epidemiology*; D015331:Cohort Studies; D057225:Data Mining / Q000379:methods*; D066264:Datasets as Topic / Q000706:statistics & numerical data*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005858:Germany / Q000453:epidemiology; D006302:Health Services Research / Q000639:trends*; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D012307:Risk Factors