[Family reconstitution and online genealogies to analyze the sex-specific differential mortality in the historical context]. / Familienrekonstitution und Online-Genealogien zur Analyse der geschlechtsspezifischen differenziellen Sterblichkeit im historischen Kontext.

BACKGROUND: Family reconstitution and data from online genealogies, such as FamiLinx, are two potential sources for investigating mortality dynamics for the period before official lifetables became available. In this paper, we use two of them, the family reconstitution of Imhof and the FamiLinx dataset based on geni.com, to estimate dynamics in life expectancy and discuss the sex-specific differential mortality in the German Empire. METHOD: Sex-specific lifetables are estimated for the territory of the German Empire from the individual data of the family reconstitution and the online genealogies. On the basis of these lifetables, we estimate the conditional life expectancy and derive the corresponding sex-specific differential mortality. Findings are compared with the official lifetable of the German Empire in 1871-1910. The contribution of each age group to the differential mortality is determined using the stepwise-replacement algorithm. RESULTS: The family reconstitution overestimates conditional life expectancy less than FamiLinx after 1871, when official lifetables are available in the German Empire. However, both sources fail to capture the sex-specific mortality differentials of the official lifetables at the end of the nineteenth century and show a higher life expectancy for males instead of females. The bias in sex-specific mortality rates is particularly pronounced in the age groups 15 to 45. DISCUSSION: Finally, we discuss possible explanations for the biased findings. Notability bias, the patriarchal approach to family trees, and maternal mortality are important mechanisms in the FamiLinx dataset. Censoring due to mobility serves as a potential reason for the bias in the family reconstitution.

Representativeness is crucial for inferring demographic processes from online genealogies: Evidence from lifespan dynamics.

Crowdsourced online genealogies have an unprecedented potential to shed light on long-run population dynamics, if analyzed properly. We investigate whether the historical mortality dynamics of males in familinx, a popular genealogical dataset, are representative of the general population, or whether they are closer to those of an elite subpopulation in two territories. The first territory is the German Empire, with a low level of genealogical coverage relative to the total population size, while the second territory is The Netherlands, with a higher level of genealogical coverage relative to the population. We find that, for the period around the turn of the 20th century (for which benchmark national life tables are available), mortality is consistently lower and more homogeneous in familinx than in the general population. For that time period, the mortality levels in familinx resemble those of elites in the German Empire, while they are closer to those in national life tables in The Netherlands. For the period before the 19th century, the mortality levels in familinx mirror those of the elites in both territories. We identify the low coverage of the total population and the oversampling of elites in online genealogies as potential explanations for these findings. Emerging digital data may revolutionize our knowledge of historical demographic dynamics, but only if we understand their potential uses and limitations.

Leaders and Laggards in Life Expectancy Among European Scholars From the Sixteenth to the Early Twentieth Century.

When did mortality first start to decline, and among whom? We build a large, new data set with more than 30,000 scholars covering the sixteenth to the early twentieth century to analyze the timing of the mortality decline and the heterogeneity in life expectancy gains among scholars in the Holy Roman Empire. The large sample size, well-defined entry into the risk group, and heterogeneity in social status are among the key advantages of the new database. After recovering from a severe mortality crisis in the seventeenth century, life expectancy among scholars started to increase as early as in the eighteenth century, well before the Industrial Revolution. Our finding that members of scientific academies-an elite group among scholars-were the first to experience mortality improvements suggests that 300 years ago, individuals with higher social status already enjoyed lower mortality. We also show, however, that the onset of mortality improvements among scholars in medicine was delayed, possibly because these scholars were exposed to pathogens and did not have germ theory knowledge that might have protected them. The disadvantage among medical professionals decreased toward the end of the nineteenth century. Our results provide a new perspective on the historical timing of mortality improvements, and the database accompanying our study facilitates replication and extensions.