Mortality Trajectories at Extreme Old Ages: A Comparative Study of Different Data Sources on U.S. Old-Age Mortality.

Living to 100 monograph Pub Date : 2014-01-01
Natalia S Gavrilova, Leonid A Gavrilov
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Abstract

The growing number of individuals living beyond age 80 underscores the need for accurate measurement of mortality at advanced ages. Our earlier published study challenged the common view that the exponential growth of mortality with age (Gompertz law) is followed by a period of deceleration, with slower rates of mortality increase (Gavrilov and Gavrilova 2011). This refutation of mortality deceleration was made using records from the U.S. Social Security Administration's Death Master File (DMF). Taking into account the significance of this finding for actuarial theory and practice, we tested these earlier observations using additional independent datasets and alternative statistical approaches. In particular, the following data sources for U.S. mortality at advanced ages were analyzed: (1) data from the Human Mortality Database (HMD) on age-specific death rates for 1890-99 U.S. birth cohorts, (2) recent extinct birth cohorts of U.S. men and women based on DMF data, and (3) mortality data for railroad retirees. In the case of HMD data, the analyses were conducted for 1890-99 birth cohorts in the age range 80-106. Mortality was fitted by the Gompertz and logistic (Kannisto) models using weighted nonlinear regression and Akaike information criterion as the goodness-of-fit measure. All analyses were conducted separately for men and women. It was found that for all studied HMD birth cohorts, the Gompertz model demonstrated better fit of mortality data than the Kannisto model in the studied age interval. Similar results were obtained for U.S. men and women born in 1890-99 and railroad retirees born in 1895-99 using the full DMF file (obtained from the National Technical Information Service, or NTIS). It was also found that mortality estimates obtained from the DMF records are close to estimates obtained using the HMD cohort data. An alternative approach for studying mortality patterns at advanced ages is based on calculating the age-specific rate of mortality change (life table aging rate, or LAR) after age 80. This approach was applied to age-specific death rates for Canada, France, Sweden and the United States available in HMD. It was found that for all 24 studied single-year birth cohorts, LAR does not change significantly with age in the age interval 80-100, suggesting no mortality deceleration in this interval. Simulation study of LAR demonstrated that the apparent decline of LAR after age 80 found in earlier studies may be related to biased estimates of mortality rates measured in a wide five-year age interval. Taking into account that there exists several empirical estimates of hazard rate (Nelson-Aalen, actuarial and Sacher), a simulation study was conducted to find out which one is the most accurate and unbiased estimate of hazard rate at advanced ages. Computer simulations demonstrated that some estimates of mortality (Nelson-Aalen and actuarial) as well as kernel smoothing of hazard rates may produce spurious mortality deceleration at extreme ages, while the Sacher estimate turns out to be the most accurate estimate of hazard rate. Possible reasons for finding apparent mortality deceleration in earlier studies are also discussed.

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极端老年死亡率轨迹:美国老年死亡率不同数据来源的比较研究。
年龄超过80岁的人越来越多,这凸显了精确测量高龄死亡率的必要性。我们早期发表的研究挑战了一种普遍观点,即死亡率随年龄呈指数增长(Gompertz定律)之后是一段减速期,死亡率增长较慢(Gavrilov和Gavrilova 2011)。这种对死亡率下降的反驳是根据美国社会保障局死亡主档案(DMF)的记录提出的。考虑到这一发现对精算理论和实践的重要性,我们使用额外的独立数据集和替代统计方法测试了这些早期观察结果。特别地,本文分析了美国高龄死亡率的以下数据来源:(1)来自人类死亡率数据库(HMD)的1890- 1999年美国出生队列的年龄特定死亡率数据,(2)基于DMF数据的最近灭绝的美国男性和女性出生队列,以及(3)铁路退休人员的死亡率数据。在HMD数据的情况下,对1890-99个年龄在80-106岁之间的出生队列进行了分析。死亡率采用加权非线性回归和Akaike信息准则作为拟合优度度量,采用Gompertz和logistic (Kannisto)模型进行拟合。所有的分析都是分别对男性和女性进行的。研究发现,对于所有研究的HMD出生队列,Gompertz模型在研究的年龄区间比Kannisto模型显示出更好的死亡率数据拟合。使用完整的DMF文件(从国家技术信息服务处获得,或NTIS),对1890-99年出生的美国男性和女性以及1895-99年出生的铁路退休人员也得到了类似的结果。研究还发现,从DMF记录中获得的死亡率估计值与使用HMD队列数据获得的估计值接近。研究高龄死亡率模式的另一种方法是基于计算80岁以后年龄特异性死亡率变化率(生命表老化率,LAR)。该方法应用于HMD中提供的加拿大、法国、瑞典和美国的特定年龄死亡率。研究发现,在所有24个研究的单年出生队列中,在80-100岁区间,LAR不随年龄发生显著变化,这表明在这一区间内死亡率没有下降。对LAR的模拟研究表明,早期研究中发现的80岁以后LAR的明显下降可能与以广泛的5年年龄间隔测量的死亡率估计有偏差有关。考虑到存在几种对风险率的经验估计(Nelson-Aalen, actuarial和Sacher),我们进行了模拟研究,以找出哪一种是最准确和无偏的高龄风险率估计。计算机模拟表明,对死亡率的一些估计(Nelson-Aalen和精算)以及对危险率的核平滑可能会在极端年龄产生虚假的死亡率减速,而Sacher估计结果是对危险率的最准确估计。在早期的研究中发现明显的死亡率下降的可能原因也进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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