Demografische Daten

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Consistency of Cause-Specific Mortality Data (Dissertation)

Inna Danilova, Roland Rau, Vladimir M. Shkolnikov

Ausführliche Beschreibung

Cause-specific mortality analysis is a powerful diagnostic tool that can shed light on the mechanisms of mortality changes, inform about the epidemiological patterns in the population, and guide interventions to reduce avoidable mortality. But the validity and the usefulness of such analysis highly depend on the quality and consistency of the  relevant data. One of the important issues to address in this context is the spatial and temporal uniformity of cause-specific mortality data.

Studies analyzing mortality levels from specific causes in different countries have found that the approaches to cause-of-death certification and coding can vary markedly across countries. However, these comparability issues arise not only across countries. Certification and coding practices may differ significantly within countries as well. And the uniformity of certification and coding practices within a given country is especially crucial for the evaluation of the epidemiological situation in a population.

Another comparability problem is the changes in the system of collecting data on causes of death over time. These may produce artificial breaks or shifts in cause-specific series. The issue of temporal consistency of cause-specific mortality series has intensified in recent decades. First, unlike the previous versions of ICD-Classifications, the 10th ICD Revision (currently in use in most of the countries) is continuously updated. Second, automatization tools to collect and process data on causes of death are increasingly implemented. 

Countries choose different ways of producing information on causes of death. Whereas in some countries, the processing of death certificates and cause-of-death coding is centralized and carried out all in one place, in other countries it is done at the level of administrative units or even medical organizations. Countries also differ in terms of the automation of cause-of-death certification and coding procedures. 

This Ph.D. project addresses the issues of spatial and temporal uniformity of cause-specific mortality data within countries. Particularly, we are interested in how the different systems the countries adopt to produce data on causes of death affect data consistency.


Alterung, Sterblichkeit und Langlebigkeit, Daten und Erhebungen, Gesundheitsversorgung, Public Health, Medizin und Epidemiologie


Danilova, I. A.:
Demographic Review 7:1, 6–26. (2020)    
Danilova, I. A.; Rau, R.; Barbieri, M.; Grigoriev, P.; Jdanov, D. A.; Meslé, F.; Vallin, J.; Shkolnikov, V. M.:
Population: English Edition. forthcoming. (2020)    
Danilova, I. A.; Shkolnikov, V. M.; Jdanov, D. A.; Meslé, F.; Vallin, J.:
Population Health Metrics 14:8. (2016)
Das Max-Planck-Institut für demografische Forschung (MPIDR) in Rostock ist eines der international führenden Zentren für Bevölkerungswissenschaft. Es gehört zur Max-Planck-Gesellschaft, einer der weltweit renommiertesten Forschungsgemeinschaften.