, 8128 Sewell Social Science Building, 1180 Observatory Drive, Madison, WI, 53706, USA,
Demography. 2014 Feb;51(1):51-71. doi: 10.1007/s13524-013-0256-7.
Unobserved heterogeneity in mortality risk is pervasive and consequential. Mortality deceleration-the slowing of mortality's rise with age-has been considered an important window into heterogeneity that otherwise might be impossible to explore. In this article, I argue that deceleration patterns may reveal surprisingly little about the heterogeneity that putatively produces them. I show that even in a very simple model-one that is composed of just two subpopulations with Gompertz mortality-(1) aggregate mortality can decelerate even while a majority of the cohort is frail; (2) multiple decelerations are possible; and (3) mortality selection can produce acceleration as well as deceleration. Simulations show that these patterns are plausible in model cohorts that in the aggregate resemble cohorts in the Human Mortality Database. I argue that these results challenge some conventional heuristics for understanding the relationship between selection and deceleration; undermine certain inferences from deceleration timing to patterns of social inequality; and imply that standard parametric models, assumed to plateau at most once, may sometimes badly misestimate deceleration timing-even by decades.
未被观察到的死亡率异质性普遍存在且具有重要影响。死亡率减速——即死亡率随年龄增长而减缓——被认为是探索异质性的一个重要窗口，否则这种异质性可能无法被探索。在本文中，我认为减速模式可能无法揭示产生这些模式的异质性。我表明，即使在一个非常简单的模型中——由两个具有戈特曼死亡率的亚群组成——（1）即使大多数队列都很脆弱，总死亡率也可能减速；（2）可能存在多种减速；（3）死亡率选择既可以产生加速，也可以产生减速。模拟表明，这些模式在模型队列中是合理的，这些队列在总体上类似于人类死亡率数据库中的队列。我认为，这些结果挑战了一些关于理解选择和减速之间关系的传统启发式方法；破坏了从减速时机推断社会不平等模式的某些推论；并暗示，标准参数模型（假定最多只能稳定一次）可能会严重错误估计减速时机——甚至是几十年。
