Diversity of cause-of-death coding practices across Russian regions
Inna Danilova, Max-Planck Institute for Demographic Research and National Research University Higher School of Economics
Vladimir M. Shkolnikov, Max-Planck Institute for Demographic Research and New Economic School, Russia
Dmitri A. Jdanov, Max-Planck Institute for Demographic Research and New Economic School, Russia
France Meslé, Institut National d'Études Démographiques (INED)
Jacques Vallin, Institut National d'Études Démographiques (INED)
Reliable and comparable data on causes of death are crucial for public health analysis. But the usefulness of these data can be markedly diminished when the approach to coding is not standardized across territories or/and over time. The Russian system of producing information on causes of death is highly decentralized, which causes potential hazards of discrepancies of coding practices within the country. In this study, we evaluate the uniformity of cause of death coding practices across Russian regions with an indirect method. Based on 2002-2012 mortality data, we estimate the prevalence of the major causes of death in mortality structures of 52 Russian regions. For every region-cause combination we measured how different the share of a certain cause in the mortality structure of a certain region is compared with the respective inter-regional average share. We use regression model to determine whether there is regularity with respect to causes and regions that are more likely to deviate from the average level. We also inspect the regional cause-of-death time series to detect causes with very high variability of temporal trends across regions. A high consistency was found for transport accidents, most of the neoplasms, congenital malformations both across regions and over time. Very high inconsistency was found for mental and behavioral disorders, diseases of the nervous system, endocrine disorders, ill-defined causes of death, and certain cardio-vascular diseases, suggesting a lack of concordance between regional coding practices for these causes of death. This systematic analysis allows us to present a broader landscape of the quality of cause-of-death coding at the regional level. For some causes of death there is a high variance of coding practices across regions in choosing them as underlying. For some causes, mortality statistics reflect the coding practices rather than yielding information about the real epidemiological situation.
Presented in Session 106: Advances in cause of death analysis