Abstract
Mortality information of populations is aggregated in life tables that serve as a basis for calculation of life expectancy and various life disparity measures. Conventional life-table methods address right-censoring inadequately by assuming a constant hazard in the last open-ended age group. As a result, life expectancy can be substantially distorted, especially in the case when the last age group in a life table contains a large proportion of the population. Previous research suggests addressing censoring in a gamma-Gompertz-Makeham model setting as this framework incorporates all major features of adult mortality. In this article, we quantify the difference between gamma-Gompertz-Makeham life expectancy values and those published in the largest publicly available high-quality life-table databases for human populations, drawing attention to populations for which life expectancy values should be reconsidered. We also advocate the use of gamma-Gompertz-Makeham life expectancy for three reasons. First, model-based life-expectancy calculation successfully handles the problem of data quality or availability, resulting in severe censoring due to the unification of a substantial number of deaths in the last open-end age group. Second, model-based life expectancies are preferable in the case of data scarcity, i.e. when data contain numerous age groups with zero death counts: here, we provide an example of hunter-gatherer populations. Third, gamma-Gompertz-Makeham-based life expectancy values are almost identical to the ones provided by the major high-quality human mortality databases that use more complicated procedures. Applying a gamma-Gompertz-Makeham model to adult mortality data can be used to revise life-expectancy trends for historical populations that usually serve as input for mortality forecasts.
Highlights
Mortality of populations is summarized in life tables
Closing a life table according to another assumption leads to a completely new set of remaining life expectancy values at all ages as each assumption imposes a particular structure of mortality in the last age group
For four hunter-gatherer populations presented in Fig 1, conventional life-table calculation overestimates the average length of life by 5.3 years
Summary
Mortality of populations is summarized in life tables. The latter contain certain measures of mortality (e.g. remaining life expectancy, survival probability at age x), but researchers calculate other characteristics of the distribution of deaths based on life-table information (e.g. Gini coefficient, Human Development Index, etc.) to use them as input in public and health policy making, insurance and investments. The authors did not have special access privileges
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