Gavrilova Natalia S, Gavrilov Leonid A
Center on Aging, NORC at the University of Chicago, Chicago, Illinois.
J Gerontol A Biol Sci Med Sci. 2015 Jan;70(1):1-9. doi: 10.1093/gerona/glu009. Epub 2014 Feb 17.
The growing number of persons living beyond age 80 underscores the need for accurate measurement of mortality at advanced ages and understanding the old-age mortality trajectories. It is believed that exponential growth of mortality with age (Gompertz law) is followed by a period of deceleration, with slower rates of mortality increase at older ages. This pattern of mortality deceleration is traditionally described by the logistic (Kannisto) model, which is considered as an alternative to the Gompertz model. Mortality deceleration was observed for many invertebrate species, but the evidence for mammals is controversial. We compared the performance (goodness-of-fit) of two competing models-the Gompertz model and the logistic (Kannisto) model using data for three mammalian species: 22 birth cohorts of U.S. men and women, eight cohorts of laboratory mice, and 10 cohorts of laboratory rats. For all three mammalian species, the Gompertz model fits mortality data significantly better than the "mortality deceleration" Kannisto model (according to the Akaike's information criterion as the goodness-of-fit measure). These results suggest that mortality deceleration at advanced ages is not a universal phenomenon, and survival of mammalian species follows the Gompertz law up to very old ages.
80岁以上人口数量的不断增加凸显了准确测量高龄死亡率以及了解老年死亡率轨迹的必要性。人们认为,死亡率随年龄呈指数增长(冈珀茨定律)之后会有一个减速期,在老年阶段死亡率的增长速度会放缓。这种死亡率减速模式传统上由逻辑斯蒂(卡尼斯托)模型来描述,该模型被视为冈珀茨模型的替代方案。在许多无脊椎动物物种中都观察到了死亡率减速现象,但哺乳动物的相关证据存在争议。我们使用三种哺乳动物的数据比较了两种竞争模型——冈珀茨模型和逻辑斯蒂(卡尼斯托)模型的性能(拟合优度):22个美国男性和女性出生队列、8个实验室小鼠队列以及10个实验室大鼠队列。对于所有这三种哺乳动物物种,根据作为拟合优度度量的赤池信息准则,冈珀茨模型对死亡率数据的拟合明显优于“死亡率减速”的卡尼斯托模型。这些结果表明,高龄阶段的死亡率减速并非普遍现象,哺乳动物物种的生存直至非常老龄阶段都遵循冈珀茨定律。