Mortality Measurement at Advanced Ages

Abstract

Accurate estimates of mortality at advanced ages are essential to improving forecasts of mortality and the population size of the oldest old age group. However, estimation of hazard rates at extremely old ages poses serious challenges to researchers: (1) The observed mortality deceleration may be at least partially an artifact of mixing different birth cohorts with different mortality (heterogeneity effect); (2) standard assumptions of hazard rate estimates may be invalid when risk of death is extremely high at old ages and (3) ages of very old people may be exaggerated. One way of obtaining estimates of mortality at extreme ages is to pool together international records of persons surviving to extreme ages with subsequent efforts of strict age validation. This approach helps researchers to resolve the third of the above-mentioned problems but does not resolve the first two problems because of inevitable data heterogeneity when data for people belonging to different birth cohorts and countries are pooled together. In this paper we propose an alternative approach, which gives an opportunity to resolve the first two problems by compiling data for more homogeneous single-year birth cohorts with hazard rates measured at narrow (monthly) age intervals. Possible ways of resolving the third problem of hazard rate estimation are elaborated. This approach is based on data from the Social Security Administration Death Master File (DMF). Some birth cohorts covered by DMF could be studied by the method of extinct generations. Availability of month of birth and month of death information provides a unique opportunity to obtain hazard rate estimates for every month of age. Study of several single-year extinct birth cohorts shows that mortality trajectory at advanced ages follows the Gompertz law up to the ages 102–105 years without a noticeable deceleration. Earlier reports of mortality deceleration (deviation of mortality from the Gompertz law) at ages below 100 appear to be artifacts of mixing together several birth cohorts with different mortality levels and using cross-sectional instead of cohort data. Age exaggeration and crude assumptions applied to mortality estimates at advanced ages may also contribute to mortality underestimation at very advanced ages.

New Developments in the Biodemography of Aging and Longevity

“…This differential survival leads to excess of fall-born persons among centenarians [40]. These findings support the idea of early-life programming of human aging and longevity, and are in a good agreement with our earlier reports on the effects of month-of-birth on mortality in the United States [41], and are consistent with our study of centenarians and shorter-lived peers (see above). The results of our study were obtained by using a more conclusive within-family analysis, and were not confounded by between-family variation.…”

“…First, mortality deceleration may be caused by age misreporting in death data for older individuals [18, 19]. Studies conducted more than 10 years ago used data for older birth cohorts when age reporting was not particularly accurate.…”

Aging in the Context of Cohort Evolution and Mortality Selection

“…Rather than making the strong assumption of a linear decline in vitality, and also for the purpose of focusing on the aging process in old age, I confine the analysis to the decline in vitality after age 70. 2 Because of problems of death underregistration and age uncertainty at very old ages, even in the best historical data (Crimmins and Finch 2006; Gavrilov and Gavrilova 2011), I restrict the upper end of age in my analysis to 94.…”

“…This contributes to the deceleration of mortality at late ages: the rate at which the mortality hazard changes with age levels off after age 110 (Thatcher et al 1998; Vaupel 2010b; Vaupel et al 1998). The deceleration of mortality in very late life might be due to the underregistration of deaths or age uncertainty among very old adults, and these problems might plague even the best historical data (Crimmins and Finch 2006; Gavrilov and Gavrilova 2011). Keeping this possible limitation in mind, I aim to study how population heterogeneity may shape cohort patterns in mortality acceleration before very late ages (e.g., age 95).…”

Mortality Increase in Late-Middle and Early-Old Age: Heterogeneity in Death Processes as a New Explanation

“…Because the law is considered to be a good approximation of the mortality pattern that occurs between sexual maturity and old age, recent research has paid more attention to what happens beyond rather than within the predictable age interval of the law. Researchers have generally observed that a leveling off of the mortality rate at very old ages (later than age 85)—the so-called old-age plateau—would directly follow the exponential increase (Carey and Liedo 1995; Horiuchi and Wilmoth 1998; Vaupel et al 1998), although controversy remains regarding the age to which the Gompertz law can be extended (Gavrilov and Gavrilova 2011). However, a relatively subtle but systematic deviation from the law between late-middle and early-old ages (50–70) was identified in a few studies, which found that the rate of mortality increase became either faster or slower than the predicted exponentially increasing trajectory (Ekonomov et al 1989; Himes et al 1994; Horiuchi 1983, 1997; Horiuchi and Coale 1990; Horiuchi and Wilmoth 1998; Milne 2007; Pakin and Hrisanov 1984).…”