Studying and developing meaningful lifespan inequality measures was the first major aim. The cross-sectional average inequality in lifespan (Nepomuceno et al., 2022) is a novel measure that relates the variation of lifespans in a given year to the experience of the cohorts present in the study population. The dynamics in Drewnowski's index (Aburto et al., 2022) and outsurvival (Bergeron-Boucher et al., 2022) uncover useful relationships with life expectancy and lifespan inequality, while mortality crises (Vigezzi et al., 2022) and violence (Aburto et al., 2023) appear to be major determinants of high dispersion in lifetime uncertainty. In addition, a major breakthrough is developing a decomposition method for lifespan inequality (Permanyer et al., 2023) that accounts not only for inter- and intra-group differences, but also for the average inter-individual difference.
Quantifying the progress in old-age mortality, as well as developing relevant mathematical and forecasting models inspires the second major set of findings. Missov et al. (forthcoming) propose a novel method to accurately estimate (with uncertainty bounds) the rates of mortality improvement at the oldest ages: while age-specific death rates until age 100 in ten European countries decrease at an average pace from 0.5% to 2% per year, the mortality progress for centenarians is negligibly small. In two forthcoming papers, Patricio and Missov develop a mathematical framework of old-age mortality based on competing risks that allows separating old-age from premature deaths: differences in mortality between populations are mostly due to differences in premature deaths. Vazquez-Castillo et al. (forthcoming) develop a model for accurately estimating the modal age at death. The latter is used by Bergeron-Boucher et al. (forthcoming) to develop a model to forecast the age-at-death distribution that directly forecasts the modal age at death and lifespan variation while accounting for dependence between ages. As it takes advantage of the almost linear increase in the mode, the introduced model increases forecast accuracy compared with other forecasting models and provides consistent trends in life expectancy and lifespan variation at age 40 over time.
