Why do lifespan variability trends for the young and old diverge? A perturbation analysis

Background: Variation in lifespan has followed strikingly different trends for the young and old: while overall lifespan variability has decreased as life expectancy at birth has risen, the variability conditional on survival to older ages has increased. These diverging trends reflect changes in the underlying demographic parameters determining age-specific mortality. Objective: We ask why the variation in the adult ages at death has followed a different trend than the variation at younger ages, and aim to explain the diverging patterns in terms of historical changes in the age schedule of mortality. Methods: Using simulations, we show that the empirical trends in lifespan variation are well characterized using the Siler model, which describes the mortality hazard across the full lifespan using functions representing early-life, later-life, and background mortality. We then obtain maximum likelihood estimates of the Siler parameters over time. Finally, we express lifespan variation in terms of a Markov chain model, and apply matrix calculus perturbation analysis to compute the sensitivity of age-specific lifespan variance trends to the changing Siler model parameters. Results: Our analysis produces a detailed quantification of the impact of changing demographic parameters on the pattern of lifespan variability at all ages, highlighting the impact of declining childhood mortality on the reduction of lifespan variability and the impact of improved survival in adulthood on the rising variability of lifespans at older ages. Conclusions: These findings provide insight into the dynamic relationship between the age pattern of survival improvements and time trends in lifespan variability