title: [Methodological considerations for data linkage of primary and secondary data in occupational epidemiology studies].
abstract: Within the scope of an aging population, the topic age, work and health becomes more and more important. So far, research in occupational epidemiology utilizes various primary or secondary data sources. However, data linkage has rarely been used as an instrument in this field. The study presented here combines two large databases within a so-called "age-work matrix", stratified by sex, age group and occupational group. This matrix is based on the German classification of occupations and uses its occupation codes as a key variable. The first database is the representative BIBB/BAuA employment survey for employees of all occupations in Germany 2005/06. The second database consists in sickness absence data of the insurees of a German statutory health insurance fund. Using the matrix approach, the study investigates associations of reported subjectively perceived psychosocial work strains and health impairments provided by health insurance claims data. These claims data offer sickness absence data as an indicator for health impairments. Usability of sickness absence data for studies in occupational epidemiology, their methodological challenges and the solutions realized in this study are discussed.
authors: Institut für Sozialmedizin und Gesundheitsökonomie (Institutsleitung Prof. Dr. med. B.-P. Robra, M.P.H.), Medizinische Fakultät der Otto-von-Guericke-Universität Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Deutschland. stefanie.march@med.ovgu.de
authors: S
authors: S
authors: March
authors: M
authors: M
authors: Iskenius
authors: J
authors: J
authors: Hardt
authors: E
authors: E
authors: Swart
mesh_terms: D017677:Age Distribution; D003627:Data Interpretation, Statistical; D004651:Employment / Q000706:statistics & numerical data*; D004812:Epidemiologic Methods; D005858:Germany / Q000453:epidemiology; D006801:Humans; D008498:Medical Record Linkage / Q000379:methods*; D009784:Occupational Diseases / Q000453:epidemiology*; D017678:Sex Distribution; D018582:Sick Leave / Q000706:statistics & numerical data*