ObjectivesTo determine the contribution of progress in averting premature deaths to the increase in life expectancy and the decline in lifespan variation.DesignInternational comparison of national life table data from the Human Mortality Database.Setting40 developed countries and regions, 1840–2009.PopulationMen and women of all ages.Main outcome measureWe use two summary measures of mortality: life expectancy and life disparity. Life disparity is a measure of how much lifespans differ among individuals. We define a death as premature if postponing it to a later age would decrease life disparity.ResultsIn 89 of the 170 years from 1840 to 2009, the country with the highest male life expectancy also had the lowest male life disparity. This was true in 86 years for female life expectancy and disparity. In all years, the top several life expectancy leaders were also the top life disparity leaders. Although only 38% of deaths were premature, fully 84% of the increase in life expectancy resulted from averting premature deaths. The reduction in life disparity resulted from reductions in early-life disparity, that is, disparity caused by premature deaths; late-life disparity levels remained roughly constant.ConclusionsThe countries that have been the most successful in averting premature deaths have consistently been the life expectancy leaders. Greater longevity and greater equality of individuals' lifespans are not incompatible goals. Countries can achieve both by reducing premature deaths.

Inequality in length of life is the most fundamental of all inequalities; every other type of inequality is conditional upon being alive. As has long been recognized in studies of economic inequality, we can compare populations based on per capita gross national income, but there is a pressing need to further examine how income varies within populations via Gini coefficients and percentile-based metrics. Mortality inequalities should be approached in the same way. Human population health is generally monitored by average mortality levels, typically in terms of life expectancies, which belie substantial variation in length of life. Variation in ages at death, captured by a metric of lifespan variation, should be used to supplement measures of average longevity when comparing or monitoring societies and population subgroups (1). Although lifespan variation has historically been strongly inversely correlated with life expectancy (2, 3), we are beginning to see this relationship reversed, resulting in positive correlation in some countries or subnational populations. Often these changes reflect midlife mortality crises with roots in stratified education and wealth. We discuss these measures and trends and how they can have profound implications for how individuals might plan and live their lives, and for how societies might organize and manage health care, insurance, pensions, and other social policies and programs. Life expectancy at birth (or simply life expectancy, as we refer to it in the rest of the text) is the most common metric of survival. It is the hypothetical average age at death given age-specific death rates in a given year. Lifespan variation, the variability in ages at death around that average, can be measured by using an index of variation or inequality-for instance, the standard deviation, Gini coefficient, or interquartile range. To illustrate, consider age-at-death distributions of non-Hispanic black and non-Hispanic white men in the United States based on 2012-2016 death rates. The life expectancy from this distribution is 72 years for blacks and 77 years for whites [see supplementary materials (SM)]. But the timing of death was variable, skewed below the average in both groups, meaning that deaths were more spread out below the life expectancy than above it. Among blacks, the spread in survival was noticeably wider. Men in the 25th to 75th percentile (the interquartile range) died between 63 and 85 years in the black distribution, whereas those in the white distribution died between 69 and 88 years. Although life expectancy for blacks was only 6% lower than for whites, the age window over which these deaths occurred was 17% larger for blacks. Some early efforts by the Organization for Economic Cooperation and Development (OECD) to monitor within-group variability included a one-off report that measured lifespan variation conditional upon survival to age 10 (4). However, although we currently monitor life expectancy at birth in all countries of the world, which captures between-country differenc...

A number of indices exist to calculate lifespan variation, each with different underlying properties. Here we present new formulae for the response of seven of these indices to changes in the underlying mortality schedule (life disparity, the Gini coefficient, the standard deviation, the variance, Theil's index, the mean logarithmic deviation, and the inter-quartile range). We derive each of these indices from an absorbing Markov chain formulation of the life table, and use matrix calculus to obtain the sensitivity and the elasticity (i.e., the proportional sensitivity) to changes in age-specific mortality. Using empirical French and Russian male data we compare the underlying sensitivities to mortality change under different mortality regimes in order to test under which conditions the indices might differ in their conclusions about the magnitude of lifespan variation. Finally, we demonstrate how the sensitivities can be used to decompose temporal changes in the indices into contributions of age-specific mortality changes. The result is an easily computable method for calculating the properties of this important class of longevity indices.