Lifespan Inequality Research Articles

Implausibility of radical life extension in humans in the twenty-first century.

Over the course of the twentieth century, human life expectancy at birth rose in high-income nations by approximately 30 years, largely driven by advances in public health and medicine. Mortality reduction was observed initially at an early age and continued into middle and older ages. However, it was unclear whether this phenomenon and the resulting accelerated rise in life expectancy would continue into the twenty-first century. Here using demographic survivorship metrics from national vital statistics in the eight countries with the longest-lived populations (Australia, France, Italy, Japan, South Korea, Spain, Sweden and Switzerland) and in Hong Kong and the United States from 1990 to 2019, we explored recent trends in death rates and life expectancy. We found that, since 1990, improvements overall in life expectancy have decelerated. Our analysis also revealed that resistance to improvements in life expectancy increased while lifespan inequality declined and mortality compression occurred. Our analysis suggests that survival to age 100 years is unlikely to exceed 15% for females and 5% for males, altogether suggesting that, unless the processes of biological aging can be markedly slowed, radical human life extension is implausible in this century.

The reciprocal relation between rising longevity and temperature-related mortality risk in older people, Spain 1980–2018

Temperature-related mortality mostly affects older people and is attributable to a combination of factors. We focussed on a key non-temperature factor – rising longevity – and aimed to quantify its reciprocal relation with temperature-related mortality risk in Spain over 1980–2018.We obtained average annual temperature-attributable deaths among people aged 65y+, by sex and age group, for different temperature ranges (extreme cold, moderate cold, moderate heat, and extreme heat), from a previous study. Combining this with population and mortality data as well as life table information, we used: (i) a counterfactual approach to assess the contribution of rising longevity to changes in the absolute risk of temperature-related mortality, and (ii) decomposition to assess the contribution of changes in temperature-related mortality to changes in longevity and its variation (lifespan inequality).Rising longevity led to considerable declines in the absolute risk of temperature-related mortality in females and males across the entire temperature range. For extreme heat, it accounted for about a 30 % decrease in absolute risk (half of the total decrease over the study period). For moderate and extreme cold, it accounted for about a 20 % fall in absolute risk (a quarter of the total fall). In the opposite direction, changing patterns of temperature-related deaths contributed to higher life expectancy (accounting for > 20 % of the total rise in both females and males) but also higher lifespan inequality amongst older people. Most of the influence (about 80 %) was via moderate cold, but declines in risk at both moderate and extreme heat led to small rises in life expectancy.Our study points to the benefits of adopting risk-reduction strategies that aim, not only at modifying hazards and reducing exposure, but that also address socially-generated vulnerability among older people. This includes ensuring that lifespans lengthen primarily through increases in years lived in good health.

Faltering mortality improvements at young-middle ages in high-income English-speaking countries.

Before the COVID-19 pandemic, stagnating life expectancy trends were reported in some high-income countries (HICs). Despite previous evidence from country-specific studies, there is a lack of comparative research that provides a broader perspective and challenges existing assumptions. This study aims to examine longevity trends and patterns in six English-speaking countries (Australia, Canada, Ireland, New Zealand, United Kingdom, United States) by combining period and cohort perspectives and to compare them with other HICs. Using data from the Human Mortality and World Health Organization Mortality Databases, we estimated partial life expectancy, lifespan inequality and cohort survival differences for 1970-2021, as well as the contribution of causes of death to the gap in life expectancy between English-speaking countries and the average for other HICs in 2017-19. In the pre-pandemic period, the increase in life expectancy slowed in all English-speaking countries, except Ireland, mainly due to stagnating or rising mortality at young-middle ages. Relative to other HICs, those born in Anglophone countries since the 1970s experienced relative survival disadvantage, largely attributable to injuries (mainly suicides) and substance-related mortality (mainly poisonings). In contrast, older cohorts enjoyed advantages for females in Australia and Canada and for males in all English-speaking countries except the United States. Although future gains in life expectancy in wealthy societies will increasingly depend on reducing mortality at older ages, adverse health trends at younger ages are a cause for concern. This emerging and avoidable threat to health equity in English-speaking countries should be the focus of further research and policy action.

Longer healthy life, but for how many? A stochastic analysis of healthy lifespan inequality

AbstractOver the past 150 years, life expectancy doubled and healthy life expectancy increased. Expectations reveal nothing about variability, so we present a stochastic analysis to investigate changes over time, age and gender of variation, among individuals, in healthy lifespan, for different levels of country income. To complement health-adjusted life expectancy (HALE) data from the Global Burden of Disease Study, we use a stochastic model to compute the standard deviation of healthy life (SDHL). The model is a finite-state absorbing Markov chain with rewards. It includes stochastic survival, mortality, and loss of good health status. An individual surviving from one age to the next gains, as a "reward," a year of good health. This method provides all the moments of healthy longevity. The mean healthy longevity is exactly the HALE. As a measure of variation, here we focus on the standard deviation of healthy longevity. From 1990 to 2019, HALE increased, with greater increases at younger ages. At the same time, SDHL at younger ages decreased and at older ages increased. The most significant changes at birth occurred in low- and lower-middle-income countries. High- and upper-middle-income countries saw notable increases at old ages. Women generally have longer HALE and higher SDHL, but the overall HALE increase was greater for men. The reduction in SDHL over time suggests that more individuals benefit from increased longevity, particularly in low-income countries closing the gap with high-income countries. However, improvements in healthy survival at older ages appear unevenly distributed among individuals in high-income countries.

Historical Patterns in the Intergenerational Transmission of Lifespan and Longevity: A Research Note on U.S. Cohorts Born Between 1700 and 1900

This research note examines historical trends in lifespan inequality and the intergenerational transmission of lifespan and longevity in the United States over the eighteenth, nineteenth, and twentieth centuries. We contribute to the literature by expanding the estimates of the familial component beyond parent–child associations to include multigenerational and horizontal classes of relatives of different sexes. We also examine how lifespan inequality and the role of the family in lifespan and longevity changed over time. We address the challenge of studying extended family networks in historical times by leveraging recent online crowdsourced genealogical data. Results confirm the presence of a familial component for all classes of relatives considered and highlight a stronger association for horizontal than for vertical relationships. Despite decreasing lifespan inequality, we find no evidence of decreased familial lifespan stratification throughout history. If anything, the results suggest a strengthening of the parent–child association. Finally, the results contribute to the debate on the representativeness and usability of crowdsourced genealogical data by emphasizing the importance of sample selection based on the quality of the information collected.

Ranking Age-at-Death Distributions Using Dominance: Robust Evaluation of United States Mortality Trends, 2006–2021

Diverging mortality trends at different ages motivate the monitoring of lifespan inequality alongside life expectancy. Conclusions are ambiguous when life expectancy and lifespan inequality move in the same direction or when inequality measures display inconsistent trends. We propose using nonparametric dominance analysis to obtain a robust ranking of age-at-death distributions. Application to U.S. period life tables for 2006–2021 reveals that, until 2014, more recent years generally dominate earlier years, implying improvement if longer lifespans that are less unequally distributed are considered better. Improvements were more pronounced for non-Hispanic Black and Hispanic individuals than for non-Hispanic White individuals. Since 2014, for all subpopulations—particularly Hispanics—earlier years often dominate more recent years, indicating worsening age-at-death distributions if shorter and more unequal lifespans are considered worse. Dramatic deterioration of the distributions in 2020–2021 during the COVID-19 pandemic is most evident for Hispanic individuals.

Cross-sectional Average Length of Life Entropy (HCAL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal{H}}_{\ ext{CAL}}$$\\end{document}): International Comparisons and Decompositions

Keyfitz and Leser’s life table entropy was proposed to serve as a relative inequality in mortality measure. Entropy considers the variation around the age at death relative to the length of lifespan in a population, allowing comparisons across time and populations. It is used widely in period and cohort applications. Here, we propose extending this measure and present an index that incorporates the history of survival of all cohorts present at a given time, namely the cross-sectional average length of life entropy, or CAL-entropy (HCAL\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal{H}}_{\ ext{CAL}}$$\\end{document}). We decompose cross-population differences of CAL-entropy into the contribution of longevity and lifespan variation, and the change of those differences across time. Our illustrations show that populations are converging regarding lifespan inequality. Lifespan variation holds a noticeable share in the CAL-entropy gap among selected European populations. Longevity held once a pronounced share in CAL-entropy differences and their change, but its influence has receded over the years. The US demonstrates a unique trend where it performs worse across time compared to the selected European populations, and lifespan variation has played a major role in this process. This study signals the importance of lifespan variation in reducing inequality in mortality among developed and longevous populations.

The Lifespan Disparity Dataset: An open repository on inequality and polarization in length of life (1950–2021)

Monitoring health is key for identifying priorities in public health planning and improving healthcare services. Life expectancy has conventionally been regarded as a valuable indicator to compare the health status of different populations. However, this measure is simply the mean of the distribution of the length of life and, as such, neglects individual disparities in health outcomes. In this paper, we use life tables from the UN World Population Prospects to develop the most comprehensive dataset of lifespan inequality and polarization for 258 countries and areas for the period 1950–2021. These extensive series on lifespan distributions provide access to crucial information for researchers, practitioners, and the general public, thus contributing to a better understanding of health differences within and between nations.

The Average Uneven Mortality index: Building on the ‘e-dagger’ measure of lifespan inequality

The Average Uneven Mortality index: Building on the ‘e-dagger’ measure of lifespan inequality

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the “Inequality” component), (2) the total share of deaths attributable to each cause (the “Proportion” component), or (3) the cause-specific mean age at death (the “Mean” component). This so-called Inequality–Proportion–Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, “circulatory system” and “neoplasms”) do not necessarily contribute the most to overall levels of lifespan inequality. In fact, “perinatal and congenital” causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Healthy Lifespan Statistics Derived From Cross-Sectional Prevalence Data Using the Sullivan Method are Informative Summary Measures of Population Health

Health expectancy (HE), commonly derived from cross-sectional prevalence data using the Sullivan method, serves as the most frequently used summary measure of population health. Like lifespan distribution statistics, which are often discussed alongside life expectancy (LE) in demographic studies, analogous statistics on healthy lifespans can provide valuable information on population health. We examine whether healthy lifespan distribution statistics beyond HE can be estimated based on cross-sectional prevalence data and the life table, the data inputs of the Sullivan method. To do so, we treat the Sullivan method as an extension of the stationary population model to health and distinguish between health conditions with and without recovery from the state of decreased health. Our empirical demonstration is based on the prevalence of chronic diseases in selected European countries in 2017 from the Survey of Health, Ageing and Retirement in Europe (SHARE), as well as on life tables from EUROSTAT. We find that the Sullivan method, when considered as an extension of the stationary population model to health, allows for the estimation of a healthy survival distribution and its statistics, beyond HE, for health characteristics with no recovery from the state of decreased health. We show that for such health conditions, the method requires that the number of persons in full health in a stationary population does not increase with age. We argue that for such health dimensions, HE conditional on being in good health at the life table radix age is of relevance for health policy interventions. In our empirical application, we show that the conditional and unconditional measures of HE can give substantially different pictures of population health. Furthermore, we show that across European countries, in contrast to the negative relationship between LE and lifespan inequality, higher HE is associated with greater inequality in healthy years lived when conditional on being healthy at age 50. Overall, the Sullivan method, when considered as an extension of the stationary population model, proves to be a valuable tool for deriving summary statistics of population health beyond HE, which are highly relevant to public policy. * This article belongs to a special issue on “Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity”.

On the measurement of cause of death inequality.

Attempts at assessing heterogeneity in countries' mortality profiles often rely on measures of cause of death (CoD) diversity. Unfortunately, such indicators fail to take into consideration the degree of (dis)similarity among pairs of causes (e.g. 'transport injuries' and 'unintentional injuries' are implicitly assumed to be as dissimilar as 'transport injuries' and 'Alzheimer's disease')－an unrealistic and unduly restrictive assumption. We extend diversity indicators proposing a broader class of heterogeneity measures that are sensitive to the similarity between the causes of death one works with. The so-called 'CoD inequality' measures are defined as the average expected 'dissimilarity between any two causes of death'. A strength of the approach is that such measures are decomposable, so that users can assess the contribution of each cause to overall CoD heterogeneity levels-a useful property for the evaluation of public health policies. We have applied the method to 15 low-mortality countries between 1990 and 2019, using data from the Global Burden of Disease project. CoD inequality and CoD diversity generally increase over time across countries and sex, but with some exceptions. In several cases (notably, Finland), both indicators run in opposite directions. CoD inequality and diversity indicators capture complementary information about the heterogeneity of mortality profiles, so they should be analysed alongside other population health metrics, such as life expectancy and lifespan inequality.

Modelling Mortality in Kenya

This research work seeks to analysis the mortality trend experienced in Kenya over the sample period 1950 to 2021 using a multidimensional modeling framework. Life table functions, namely; life expectancy, survival function and age at death distribution are applied to depict mortality characteristics. Life expectancy and survival rate have significantly improved. There has been a shift in mortality status from a high mortality population, to an intermediate stage and mortality risk factors have increased across age. Mortality concentration curve and index within the Lorenz curve and Gini coefficient framework are used to analyze the lifespan inequality. Lifespan inequality is high with negligible improvements over time. Gompertz force of mortality is then estimated, which is statistically significant at 5% level. Deaths at exact age 25 is about 35 per ten thousand, with the rate death rate increasing by 6.09% per year starting from age 25. Under the assumptions of stable population, where the mortality and fertility functions are independent of time, Malthusian parameter is estimated which is less than zero for selected years. Kenya is a shrinking population and death rate decrease with increase in Malthusian parameter. Finally, to model long-term mortality rate forecast, Lee-Carter model is estimated. The model is statistically significant at 5% level explaining 78.4% of the variations. Expected life expectancy at a given age is projected to increase, with life expectancy at birth in 2030 and 2071 being 65.6 and 70.5 years respectively.

Distributionally sensitive measurement and valuation of population health

We introduce a measure of population health that is sensitive to inequality in both age-specific health and lifespan and can be calculated from a health-extended period life table. By allowing for inequality aversion, the measure generalises health-adjusted life expectancy without requiring more data. A transformation of change in the (life-years) measure gives a distributionally sensitive monetary valuation of change in population health and disease burden. Application to Sub-Saharan Africa between 1990 and 2019 reveals that the change in population health is sensitive to allowing for lifespan inequality but is less sensitive to age-specific health inequality. Allowing for distributional sensitivity changes relative burdens of diseases, reduces convergence between the burdens of communicable and non-communicable diseases, and so could influence disease prioritisation. It increases the value of health improvements relative to GDP.

Perceived health inequalities: are the UK and US public aware of occupation-related health inequality, and do they wish to see it reduced?

BackgroundOne underexamined factor in the study of lay views of socioeconomic health inequalities is occupation-related health. Examining health by occupational social class has a long history in the UK but has been comparatively overlooked in US public health literatures, where the relationship between health and work has attended more to hazard exposure.MethodsRepresentative samples of the UK and US indicated the perceived and ideal lifespan of people working in “higher managerial/professional” and “routine” occupations. We examine perceptions of inequality and desires for equality across occupation groups as a function of country and key socio-demographic variables.Results67.8% of UK and 53.7% of US participants identified that professionals live longer than routine workers. Multivariate models indicated that US participants were markedly less likely to be aware of occupation-related inequalities after controlling for age, gender, and education. Awareness was negatively related to age (in the US) and recent voting behaviours (both samples). Desiring equal life expectancy was less likely in the US sample, and less likely across both samples among older participants and those with lower levels of education.ConclusionEmploying a novel approach to measuring perceived and ideal life expectancy inequality, this is the first study to examine perceptions of lifespan inequality by occupational groups. It reports widespread understanding of the occupation-related gradient in lifespan and a desire that these inequalities be eliminated in the UK, but considerably less awareness and desire for equality in the US. Greater tolerance for social status inequalities in the US than other similar countries appear to also extend to differences in life expectancy.

Inequality in the Face of Death under Covid-19 in Ukraine

If there is a decline in mortality, it is mainly in younger age groups. As a result, more and more deaths are occurring in older age groups. In advanced societies, therefore, people are becoming “more equal in the face of death”. A sharp increase in mortality, such as that caused by the Covid-19 pandemic, affects different age groups of the population to different degrees. It is therefore relevant to study the change in inequality of life expectancy under the conditions of a sudden shock. The purpose of this paper is to analyse the inequality of lifespan variation in Ukraine in 2020—2021 and to compare it with countries with different levels of mortality. Previous studies of lifespan variation specifically devoted to Ukraine, or those that used data for Ukraine, were conducted or related to the pre-Covid period. The novelty of this work is the study of the behaviour of indicators characterising the inequality of lifespan before and during the two years of the epidemic, for which data are available. The demographic me t hod for constructing life tables and statistical methods for calculating lifespan variation indicators were used. Those are: Gini coefficient, average inter-individual difference in length of life, lifespan disparity, entropy of the life table, standard deviation of age at death, coefficient of variation. These indicators were calculated for the period 1989—2021 for Ukraine, Poland, Sweden, Spain, Japan, and England and Wales. It was confirmed that life expectancy is generally inversely related to inequality in the life table. It was found that this rule can be violated during mortality shocks such as the Covid-19 pandemic. It is shown that male life expectancy and lifespan inequality in Ukraine decreased in 2020—2021. Average inter-individual difference in length of life and lifespan disparity have decreased by 6.6—6.9 %. On the other hand, almost all indicators of inequality for women have increased. The life expectancy elasticity indicator (entropy of the life table) turned out to be the most sensitive, increasing to 4.9 %. At the same time, it is interesting to note that the standard deviation of age at death for women in Ukraine decreased by 1.8 %. The Covid-19 pandemic has affected inequality depending on sex and the country’s pre-Covid level. Inequality indicators in Japan have hardly changed. Inequality rates rose in Spain and Sweden before returning to their previous downward trend. Available data for England and Wales suggest a continued slow trend towards greater inequality.

Healthy lifespan inequality: morbidity compression from a global perspective

Current measures of population health lack indicators capturing the variability in age-at-morbidity onset, an important marker to assess the timing patterns of individuals’ health deterioration and evaluate the compression of morbidity. We provide global, regional, and national estimates of the variability in morbidity onset from 1990 to 2019 using indicators of healthy lifespan inequality (HLI). Using data from the Global Burden of Disease Study 2019, we reconstruct age-at-death distributions to calculate lifespan inequality (LI), and age-at-morbidity onset distributions to calculate HLI. We measure LI and HLI with the standard deviation. Between 1990 and 2019, global HLI decreased from 24.74 years to 21.92, and has been decreasing in all regions except in high-income countries, where it has remained stable. Countries with high HLI are more present in sub-Saharan Africa and south Asia, whereas low HLI values are predominant in high-income countries and central and eastern Europe. HLI tends to be higher for females than for males, and HLI tends to be higher than LI. Globally, between 1990 and 2019 HLI at age 65 increased from 6.83 years to 7.44 for females, and from 6.23 to 6.96 for males. Improvements in longevity are not necessarily accompanied by further reductions in HLI among longevity vanguard countries. Morbidity is compressing, except in high-income countries, where it stagnates. The variability in the ages at morbidity onset tends to be larger than the variability in lifespans, and such divergence broadens over time. As longevity increases worldwide, the locus of health inequality is moving from death-related inequalities to disease- and disability-centered ones.

Levels, trends, and determinants of cause-of-death diversity in a global perspective: 1990–2019

BackgroundWhile much is known about the leading causes of death (CoD) and how they have evolved over time, much less is known about the diversity of such causes of death. CoD diversity is an important marker of population health heterogeneity that has been largely overlooked in the study of contemporary health dynamics.MethodsWe provide regional and national estimates of CoD diversity from 1990 to 2019. We rely on data from the Global Burden of Disease project, using information on 21 CoD. Results are presented for 204 countries and territories, for women and men separately. CoD diversity is measured with the index of Fractionalization. Results are disaggregated by age and cause of death.ResultsCoD diversity has declined across world regions, except for Latin America and the Caribbean, the region of High-income countries and women in Central Europe, Eastern Europe, and Central Asia. Changes in mortality at adult and older ages have been mostly responsible for CoD diversity dynamics, except for the regions of South Asia and Sub-Saharan Africa, where infant and child mortality still play a non-negligible role. The relationship between CoD diversity, life expectancy, and lifespan inequality is strongly non-monotonic, with turning points differing by sex and indicator. Among longevity vanguard countries, further increases in life expectancy are associated with decreasing lifespan inequality but increasing CoD diversity.ConclusionAs mortality declines, there is no universal pathway toward low CoD diversity, thus casting doubts on the ability of Epidemiological Transition Theory to predict prospective CoD dynamics among high- and middle-mortality countries. Despite the postponement and increasing predictability of the ages at which individuals die, low-mortality populations are composed of an increasingly heterogenous mix of robust and frail individuals, thus increasing the diversity of health profiles among older persons – an issue that could potentially complicate further improvements in longevity.

Evaluation of age-specific causes of death in the context of the Italian longevity transition

In many low-mortality countries, life expectancy at birth increased steadily over the last century. In particular, both Italian females and males benefited from faster improvements in mortality compared to other high-income countries, especially from the 1960s, leading to an exceptional increase in life expectancy. However, Italy has not become the leader in longevity. Here, we investigate life expectancy trends in Italy during the period 1960–2015 for both sexes. Additionally, we contribute to the existing literature by complementing life expectancy with an indicator of dispersion in ages at death, also known as lifespan inequality. Lifespan inequality underlies heterogeneity over age in populating health improvements and is a marker of uncertainty in the timing of death. We further quantify the contributions of different age groups and causes of death to recent trends in life expectancy and lifespan inequality. Our findings highlight the contributions of cardiovascular diseases and neoplasms to the recent increase in life expectancy but not necessarily to the decrease in lifespan inequality. Our results also uncover a more recent challenge across Italy: worsening mortality from infectious diseases and mortality at older age.

Regional inequalities in life expectancy and lifespan variation by educational attainment in Spain, 2014–2018

AbstractTwo important sources of inequality in mortality are regional variation and individuals' socioeconomic status. While many studies have investigated the effect that each of these two factors might have had on mortality levels separately, they have rarely been studied simultaneously. Using linked data from the Spanish National Institute of Statistics, we study regional levels of life expectancy and lifespan inequality by sex and educational attainment in contemporary Spain (2014–2018). In all regions, life expectancy was higher (and lifespan variation lower) for individuals with higher educational attainment and among women. We find a negative relationship between life expectancy and lifespan inequality across subnational regions among all sex‐education groups. However, the relationship is much weaker among the highly educated. These findings suggest that spatial conditions still matter as health determinants, but even more among individuals with disadvantaged socioeconomic positions, not only in terms of lower life expectancy but also of higher lifespan variation.