The study of the mortality differences between groups has traditionally focused on metrics such as life expectancy and standardized mortality rates, which give insights into how group characteristics are linked with average levels of mortality. Additional insights can be gained by examining differences in lifespan distributions between groups. Here, we propose a new summary measure of mortality inequality by comparing group-specific lifespan distributions. Our proposed index, mortality stratification, measures the degree of overlap in the lifespan distributions. It helps to capture important between-group differences that conventional life-expectancy comparisons miss. In order to test its utility, we apply the stratification index to Finnish income quintile groups over the period from 1996 to 2017. We find that both stratification and life-expectancy differences between income groups increased substantially from 1996 to 2008; subsequently, the life-expectancy difference declined, whereas stratification stagnated for men and increased for women. By comparing results between different summary measures, we conclude that the stratification index can behave in different ways empirically and thus uncover a unique domain of inequalities in mortality.
Previous studies have documented a historically strong and negative association between countries’ life expectancy (i.e., average longevity) and length-of-life inequality (i.e., variability in ages at death). The relationship between both variables might be partially explained by life expectancy increasing at a faster pace than maximal length of life, a phenomenon that mechanically compresses the age-at-death distribution and has not been taken into consideration in previous studies. In this paper, we propose a new approach to lifespan inequality measurement that accounts for the (uncertainly) bounded nature of length-of-life. Applying the new approach to the countries of the Human Mortality Database, we observe that the decline in overall lifespan variability typically associated with increases in longevity seems to stop and even reverse at higher levels of life expectancy. This suggests the emergence of worrying ethical dilemmas, whereby higher achievements in longevity would only be possible at the expense of higher lifespan variability.
Income is a strong predictor of adult mortality. Measuring income is not as simple as it may sound. It can be conceptualized at the individual or the household level, with the former better reflecting an individual's earning ability, and the latter better capturing living standards. Furthermore, respondents are often grouped into income categories based on their positions in the income distribution, and this operationalization can be done on the basis of age-specific or total population income distributions. In this study, we look at how four combinations of different conceptualizations (individual vs. household) and operationalizations (age-specific vs. total population) of income can affect mortality inequality estimates. Using Finnish registry data, we constructed period life tables for ages 25+ from 1996 to 2017 by gender and for four income definitions. The results indicated that the slope index of inequality for life expectancy varied by 1.1–5.7 years between income definitions, with larger differences observed for women than for men. The overall age patterns of relative index of inequality for mortality rates yielded by the four definitions were similar, but the levels differed. The period trends across income definitions were consistent for men, but not for women. We conclude that researchers should pay particular attention to the choice of the income definitions when analyzing the association between income and mortality, and when comparing the magnitude of inequality across studies and over time.
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