How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment

International organizations, research institutions, insurance companies, pension funds and health policymakers calculate human mortality measures from life tables. Life-table data, though, are usually right-censored; that is, the last open-end age group does not contain information about the exact ages at death of individuals there, and mortality measures are sensitive to the way censoring is addressed. The standard way of closing the life table assumes a constant hazard of death for the last age group. This might lead to erroneous conclusions about mortality measures, especially when the open-end age interval contains a large proportion of the study population. In this article, we propose, instead, fitting a parametric model that well describes human mortality patterns, the gamma-Gompertz-Makeham, accounting for censoring, and constructing model-based equivalents of five mortality measures: life expectancy, the modal age at death, life disparity, entropy and the Gini coefficient. We show that, in comparison to conventional life-table measures, model-based measures are less sensitive to the age at censoring or, equivalently, to the proportion of censored individuals, and can be only slightly distorted even if the age at censoring is low. This study also compares life-table and model-based mortality measures for a non-human population with an underlying Gompertz mortality schedule in which a fixed proportion of the population is censored. Using model-based mortality measures is essential when studying the mortality of populations subjected to substantial censoring; for instance, many life tables for developing countries contain an open-end interval that contains more than 10% of the population. In this study, we show that life expectancy at birth for Brazilian females in 2007, calculated by standard life-table algebra, exceeds by almost 3 years the gamma-Gompertz-Makeham model-based life expectancy. This article might serve as a basis for recalculation of mortality measures for all populations subjected to substantial censoring.