Lifespan Inequality
Also known as: Lifespan Variation, Life Disparity, Variation in Age at Death
Lifespan inequality measures how unequally length of life is distributed within a population — the spread of the life-table ages at death, not just their average. Two populations can share the same life expectancy yet differ sharply in how predictable death is: in one nearly everyone reaches old age, in the other deaths are scattered across all ages. A family of measures — life disparity (e†), the standard deviation of age at death, the life-table Gini coefficient, and Keyfitz entropy — quantifies this dispersion, complementing life expectancy with a measure of how fairly survival is shared.
Key highlights
- Adds a second dimension — equality of survival — to the conventional focus on average length of life.
- Reveals that populations with equal life expectancy can differ markedly in the predictability of lifespan.
- Most measures share a threshold age below which saving lives reduces inequality and raises life expectancy together, giving a unified policy lens.
- Computable directly from standard life-table columns, with a coherent family of absolute and relative variants.
Intuition
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How it works
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When to use it
Use lifespan-inequality measures whenever you report life expectancy and want to characterize how equally that longevity is shared, or to study whether mortality improvements have made age at death more or less predictable. They are central to research on health inequality, the compression of mortality, and the relationship between longevity and equality. Assumptions: a complete, accurate life table and a clear choice between absolute (years) and relative (scale-free) measures. Do NOT report a single inequality measure as definitive — different measures (e†, standard deviation, Gini, entropy) can rank populations differently, especially absolute versus relative ones; and do NOT confuse lifespan inequality, which is variation within a single life table, with socioeconomic mortality differences between groups, which require between-group decomposition.
Strengths & limitations
- Adds a second dimension — equality of survival — to the conventional focus on average length of life.
- Reveals that populations with equal life expectancy can differ markedly in the predictability of lifespan.
- Most measures share a threshold age below which saving lives reduces inequality and raises life expectancy together, giving a unified policy lens.
- Computable directly from standard life-table columns, with a coherent family of absolute and relative variants.
- Different inequality measures can rank the same populations differently, so conclusions can hinge on the chosen index.
- Absolute and relative measures can move in opposite directions, complicating interpretation of trends.
- Measures are sensitive to how the open-ended oldest age interval and infant mortality are handled in the life table.
- They describe variation within a single life table and do not by themselves capture inequalities between social groups.
Common pitfalls
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Applications
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Frequently asked
What is life disparity (e†)?
Life disparity is the average number of remaining life-years lost at the ages where deaths occur — each death weighted by the remaining life expectancy at that age. It is large when many people die young (losing many potential years) and small when deaths cluster at old ages. It is the absolute lifespan-inequality measure most directly tied to Keyfitz entropy, since entropy equals e†/e₀.
Can two populations have the same life expectancy but different lifespan inequality?
Yes, and this is the whole point of the measure. Life expectancy is the mean of the age-at-death distribution and says nothing about its spread. One population may have nearly everyone dying around the same old age (low inequality) while another with the identical mean has deaths scattered from infancy to extreme age (high inequality).
What is the threshold age?
The threshold age is the age below which reducing mortality lowers lifespan inequality and above which reducing mortality raises it. Saving lives at young ages pulls deaths toward older, more uniform ages and compresses the distribution, whereas postponing deaths that already occur at old ages spreads the distribution out. The threshold typically lies in middle to older adulthood and unifies the level and inequality effects of mortality change.
Sources
- 1.Vaupel, J. W., & Canudas-Romo, V. (2003). Decomposing change in life expectancy: A bouquet of formulas in honor of Nathan Keyfitz's 90th birthday. Demography, 40(2), 201–216.
- 2.Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell.ISBN 9781557864512
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Cite this page
ScholarGate. (2026, June 22). Lifespan Inequality. ScholarGate. https://scholargate.app/demography/lifespan-inequality