Sociocultural Mortality Differentials in Lithuania: Results Obtained by Matching Vital Records with the 2001 Census Data
Jasilionis, Domantas, Shkolnikov, Vladimir M., Andreev, Evgueni M., Jdanov, Dmitri A., Ambrozaitiene, Dalia, Stankuniene, Vlada, Meslé, France, Vallin, Jacques, Population
Demographers have long been aware that death rates calculated using statistics derived from vital records (the deceased person's status reported at the time of death by the proxy informant) as numerator and from census reports as denominator do not always give a reliable measurement of sociocultural mortality differences, notably on account of frequent discrepancies between these two sources. The solution adopted in France in the 1960s and since used in many developed countries involves linking individual data from both sources, in such a way that the content of the sociocultural categories is established from one and the same type of information. In this article, Domantas JASILIONIS, Vladimir M. SHKOLNIKOV, Evgueni ANDREEV, Dmitri A. JDANOV, Dalia AMBROZAITIENE, Vlada STANKUNIENE, France MESLÉ and Jacques VALLIN apply the method for the first time to Lithuania, for which the rare studies that existed until now were limited to small samples. The results show the existence of sharp mortality differentials between social classes and constitute a timely addition to our understanding of social inequalities in Europe essential for monitoring the effects of public health policies.
Social class differences in mortality have persisted and in many cases even accentuated over recent decades in all the industrialized countries for which studies are available (Valkonen, 2001; Mackenbach et al., 1997). In the FSU (Former Soviet Union) countries, the stagnation in life expectancy that characterized the region for so long seems to have been associated with marked social inequality in mortality. This at least is the conclusion drawn from a number of studies on mortality variations as a function of factors such as educational level, marital status, or ethnicity (Andreev and Dobrovolskaya, 1993; Shkolnikov, Leon et al., 1999; Shkolnikov, Deev et al., 2004; Kalediene and Petrauskiene, 2000, 2005; Shkolnikov, Andreev and Maleva, 2000; Valkonen, 2001; Leinsalu, Vagero and Kunst, 2003, 2004).
Concerning the Baltic countries in particular, a systematic review of published works dealing with this question was carried out by Vlada Stankuniene, Domantas Jasilionis and Juris Krumins (1999), as part of a study of trends in mortality and causes of death since the 1950s. For Lithuania, four key studies have been conducted on marital status, showing that married people (men and women) enjoy a mortality advantage over those in the never-married, widowed or divorced states, notably for mortality from accidents and suicide (Petrauskiene et al., 1995; Kalediene et al., 1997; Kalediene, 1999; Kalediene and Petrauskiene et al, 1999); and four others on educational level (Kalediene, 1996; Petrauskiene et al., 1996; Kalediene and Petrauskiene, 2000, 2005). We should also mention three comparative studies in which the three Baltic countries are compared on ethnic differences (Zvidrine and Krumins, 1993; Krumins, 1995).
The findings of such studies have major implications for public health policy, but all are based on rates calculated using numerators and denominators from different sources (records of deaths by age and sociocultural category on the one hand, census data for populations by age and sociocultural category on the other) between which there may be discrepancies. The rates thus risk being heavily biased if the information given by the deceased person's family or next-of-kin when registering the death diverges substantially from that supplied by the individual himself during the previous census (Vallin, 1980; Levy and Vallin, 1981; Valkonen, 1993, 2002).
To avoid bias of this kind, the death records of individuals must be linked to the corresponding census data, so that the content of the sociocultural categories on both sides is formed from exactly the same source of information. INSEE was in fact the first to do this on a national scale with a population sample drawn from the 1954 French census, where each individual's survival was systematically followed using the Registre national d'identification des personnes physiques (national register of personal identities, RNIPP) (Calot and Febvay, 1965). …