Losses of expected lifetime in the United States and other developed countries: methods and empirical analyses

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.

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.

Global health inequality: analyses of life disparity and healthy life disparity

BACKGROUND

Alongside average health measures, namely, life expectancy (LE) and healthy life expectancy (HLE), we sought to investigate the inequality in lifespan and healthy lifespan at the worldwide level with an alternative indicator.

METHODS

Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, we evaluated the global distribution of life disparity (LD) and healthy life disparity (HLD) for 204 countries and territories in 2019 by sex and socio-demographic index (SDI), and also explored the relationships between average and variation health indicators.

RESULTS

Substantial gaps in all observed health indicators were found across SDI quintiles. For instance, in 2019, for low SDI, female LE and HLE were 67.3 years (95% confidence interval 66.8, 67.6) and 57.4 years (56.6, 57.9), and their LD and HLD were 16.7 years (16.5, 17.0) and 14.4 years (14.1, 14.7). For high SDI, female LE and HLE were greater [83.7 years (83.6, 83.7) and 70.2 years (69.3, 70.7)], but their LD and HLD were smaller [10.4 years (10.3, 10.4) and 7.9 years (7.7, 8.0)]. Besides, all estimates varied across populations within each SDI quintile. There were also gaps in LD and HLD between males and females, as those found in LE and HLE.

CONCLUSION

In addition to the disadvantaged LE and HLE, greater LD and HLD were also found in low SDI countries and territories. This reveals the serious challenge in achieving global health equality. Targeted policies are thus necessary for improving health performance among these populations.

Average lifespan variation among people with mental disorders in Denmark: a nationwide, register-based cohort study

AIMS

Mortality associated with mental disorders has been estimated using metrics such as mortality rate ratios and life expectancy. However, the variation around the average life expectancy has never been quantified. The main aim of this study was to measure life disparity for people with mental disorders as a measure of inequality at the time of death.

METHODS

Using data from Danish registries, average life disparity was introduced and calculated to measure the lifespan variation associated with major types of mental disorders. Average life expectancy is also reported for completeness.

RESULTS

Compared with the general population, people with mental disorders not only had shorter average life expectancy, but experienced larger average life disparity. For those diagnosed with a mental disorder, average life expectancy increased between 1995 and 2021; however, average life disparity declined in women only, and did not change for men. In addition, the differences in both metrics between those with mental disorders and the general population were largest for substance use disorders and schizophrenia spectrum disorders. For these disorders, the differences even increased during the study period.

CONCLUSIONS

Mortality rates for individuals with mental disorders have been declining in recent decades in Denmark; however, the increase in the average life disparity emphasizes the increasing heterogeneity and inequality in lifespans within this group, which requires measures to promote a longer and more equal life for those with mental disorders.

Trends in mortality patterns in two countries with different welfare models: comparisons between CUBA and Denmark 1955–2020

Cuba and Denmark represent states with different welfare models that have reached the same level of life expectancy. The purpose was to investigate and compare mortality changes in the two countries. Systematically collected information on population numbers and deaths for the entire Cuban and Danish populations was the basis of life table data used to quantify differences in the change in age-at-death distributions since 1955, age-specific contributions to differences in life expectancy, lifespan variation, and other changes in mortality patterns in Cuba and Denmark. Life expectancy in Cuba and Denmark converged until 2000, when the increase in life expectancy for Cuba slowed down. Since 1955, infant mortality has fallen in both countries but mostly in Cuba. Both populations experienced compression of mortality as lifespan variation decreased markedly, primarily due to postponement of early deaths. Given the different starting point in the mid-1900s and living conditions for Cubans and Danes, health status achieved among Cubans is striking. A rapidly ageing population is challenging both countries, but Cuban health and welfare are further burdened by a deteriorating economy in recent decades.

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

BACKGROUND

While 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.

METHODS

We 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.

RESULTS

CoD 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.

CONCLUSION

As 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.

Top and bottom longevity of nations: a retrospective analysis of the age-at-death distribution across 18 OECD countries

BACKGROUND

Similar to the study of the distribution of income within countries, population-level health disparities can be examined by analyzing the distribution of age at death.

METHODS

We sourced period-specific death counts for 18 OECD countries over 1900-2020 from the Human Mortality Database. We studied the evolution of country-year-specific distributions of age at death, with an examination of the lower and upper tails of these distributions. For each country-year, we extracted the 1st, 5th, 10th, 90th, 95th and 99th percentiles of the age-at-death distribution. We then computed the corresponding shares of longevity-the sum of the ages weighted by the age-at-death distribution as a fraction of the sum of the ages weighted by the distribution-for each percentile. For example, for the 10th percentile, this would correspond to how much longevity accrues to the bottom 10% of the age-at-death distribution in a given country-year.

RESULTS

We expose a characterization of the age-at-death distribution across populations with a focus on the lower and upper tails of the distribution. Our metrics, specifically the gap measures in age and share across the 10th and 90th percentiles of the distribution, enable a systematic comparison of national performances, which yields information supplementary to the cross-country differences commonly pointed by traditional indicators of life expectancy and coefficient of variation.

CONCLUSIONS

Examining the tails of age-at-death distributions can help characterize the comparative situations of the better- and worse-off individuals across nations, similarly to depictions of income distributions in economics.

A global assessment of the impact of violence on lifetime uncertainty

Uncertainty around age at death, or lifetime uncertainty, is a key public health indicator and a marker of inequality in survival. How does the extent of violence affect lifetime uncertainty? We address this question by quantifying the impact of violence on dispersion in the ages at death, the metric most used to measure lifetime uncertainty. Using mortality data from the Global Burden of Disease Study and the Internal Peace Index between 2008 and 2017, we find that the most violent countries are also those with the highest lifetime uncertainty. In the Middle East, conflict-related deaths are the largest contributor to lifetime uncertainty. In Latin America, a similar pattern is attributable to homicides. The effects are larger in magnitude for men, but the consequences remain considerable for women. Our study points to a double burden of violence on longevity: Not only does violence shorten individual lives, but it also makes the length of life less predictable.

The role of age inequalities in cause of death in the slow pace of epidemiological transition in India

In developed countries, low disparity in lifespan contributed by the reduction in the burden of noncommunicable diseases (NCDs) is the key to advances in epidemiological transition. Contrarily, India passing through a phase of the dual burden of CDs and NCDs shows a heavy burden of NCDs responsible for the high disparity in lifespan. The Gini coefficient was decomposed for examining the contribution of 22 causes of death and their repercussions for inequality in age at death for 30 years between 1990-1994 and 2015-2019, using Global Burden of Disease data. The outcomes of the study reveal that India's epidemiological transition has been just modest on account of high inequality in mortality by NCDs emplaced in the middle through old age despite a consistent mortality decline at infant through old age for communicable diseases (CDs). The structural changes in causes of death structure is shaped by CDs rather than NCDs, but overall bolstered by the adult mortality decline, especially in women. However, the process is restrained by the small contribution of the middle age group and a benign contribution of old mortality decline owing to the low threshold age. India needs to target health interventions in seeking significant mortality decline in the middle age group of 50-69 years that is warranted for epidemiological transition apace as evident in the developed nations.

Trends in lifespan variation across the spectrum of rural and urban places in the United States, 1990–2017

Mortality disparities between urban and rural areas in the United States widened in recent decades as mortality improvements in rural areas slowed. Although the existence of a rural mortality penalty is well-documented, previous research in this area has focused almost exclusively on differences in average levels of mortality between rural and urban areas rather than differences in levels of lifespan variation within rural and urban areas. This oversight is important because monitoring trends in lifespan variation provides unique insights into levels of inequality in the age-at-death distribution within a population. Does the rural mortality penalty in life expectancy extend to lifespan variation? We used U.S. Multiple Cause of Death data files to measure life disparity at birth (e0†) from 1990 to 2017. We found that the rural mortality penalty extends to lifespan variation as large metropolitan areas had greater improvements in life disparity than nonmetropolitan areas. Beginning around 2011, all areas began to show increased life disparity with the largest increases occurring in nonmetropolitan areas. Age decomposition results showed that the nonmetropolitan increases were due to rising working-age mortality. Greater variability in the age-at-death distribution represents an additional dimension of inequality for Americans living in rural places.

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Improvements in metropolitan mortality beginning in the early 1990s resulted in a growing rural mortality penalty

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Recent increases in working-age mortality have contributed to the rural mortality penalty.

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Life expectancy improvements in metropolitan areas are associated with a decrease in lifespan variation.

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Greater lifespan inequality represents an additional dimension of inequality for rural Americans.

Life span inequality as a function of the moments of the deaths distribution: Connections and insights

Recent work has unearthed many empirical regularities in mortality trends, including the inverse correlation between life expectancy and life span inequality, and the compression of mortality into older age ranges. These regularities have furnished important insights into the dynamics of mortality by describing, in demographic terms, how different attributes of the life table deaths distribution interrelate and change over time. However, though empirical evidence suggests that the demographically-meaningful metrics these regularities involve (e.g., life span disparity and life table entropy) are correlated to the moments of the deaths distribution (e.g., variance), the broader theoretical connections between life span inequality and the moments of the deaths distribution have yet to be elucidated. In this article we establish such connections and leverage them to furnish new insights into mortality dynamics. We prove theoretical results linking life span disparity and life table entropy to the central moments of the deaths distribution, and use these results to empirically link statistical measures of variation of the deaths distribution (e.g., variance, index of dispersion) to life span disparity and life table entropy. We validate these results via empirical analyses using data from the Human Mortality Database and extract from them several new insights into mortality shifting and compression in human populations.

Normalized lifespan inequality: disentangling the longevity-lifespan variability nexus

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.

From convergence to divergence: Lifespan variation in US states, 1959-2017

BACKGROUND

Large disparities in life expectancy exist across US states and the gaps have been widening in recent decades. Less is known about the lifespan variability - a measure that can provide important insights into mortality inequalities both between and within states.

METHOD

Using yearly lifetables from the United States Mortality Database, we explore geographic and temporal patterns in lifespan variation (unconditional and conditional on survival to age 10, 35 and 65) across US states between 1959 and 2017. We also examine the contribution of state differences in life expectancy to overall lifespan variation using standard decomposition techniques.

RESULTS

Despite overall convergence in lifespan variation across states over the last six decades, in more recent years there has been notable divergence. Gender-specific analyses show that lifespan variation was generally greater among males than among females; but this pattern reverses for mortality past age 65. Much of the state disparities in lifespan variation, unconditional and conditional on survival to age 10 and 35, were due to mortality differences under the age 65. Decomposition analysis shows that while within-state variability remains the primary driver of overall lifespan variation, the contribution of cross-state differences in life expectancy is growing.

CONCLUSIONS

Variation in longevity is greater within US States than between them, yet cross-states disparities in mortality are increasing. This likely reflects the long-term consequences of rising social, economic, and political stratification for health inequalities both within and across states.

Inequality in Place: Effects of Exposure to Neighborhood-Level Economic Inequality on Mortality

This study contributes to the debate on whether income inequality is harmful for health by addressing several analytical weaknesses of previous studies. Using the Panel Study of Income Dynamics in combination with tract-level measures of income inequality in the United States, we estimate the effects of differential exposure to income inequality during three decades of the life course on mortality. Our study is among the first to consider the implications of income inequality within U.S. tracts for mortality using longitudinal and individual-level data. In addition, we improve upon prior work by accounting for the dynamic relationship between local areas and individuals' health, using marginal structural models to account for changes in exposure to local income inequality. In contrast to other studies that found no significant relation between income inequality and mortality, we find that recent exposure to higher local inequality predicts higher relative risk of mortality among individuals at ages 45 or older.

The Cross-sectional Average Inequality in Lifespan (CAL†): A Lifespan Variation Measure That Reflects the Mortality Histories of Cohorts

Lifespan variation is a key metric of mortality that describes both individual uncertainty about the length of life and heterogeneity in population health. We propose a novel and timely lifespan variation measure, which we call the cross-sectional average inequality in lifespan, or CAL†. This new index provides an alternative perspective on the analysis of lifespan inequality by combining the mortality histories of all cohorts present in a cross-sectional approach. We demonstrate how differences in the CAL† measure can be decomposed between populations by age and cohort to explore the compression or expansion of mortality in a cohort perspective. We apply these new methods using data from 10 low-mortality countries or regions from 1879 to 2013. CAL† reveals greater uncertainty in the timing of death than the period life table-based indices of variation indicate. Also, country rankings of lifespan inequality vary considerably between period and cross-sectional measures. These differences raise intriguing questions as to which temporal dimension is the most relevant to individuals when considering the uncertainty in the timing of death in planning their life courses.

What Can We Learn from the Functional Clustering of Mortality Data? An Application to the Human Mortality Database

This study analyzed whether there are different patterns of mortality decline among low-mortality countries by identifying the role played by all the mortality components. We implemented a cluster analysis using a functional data analysis (FDA) approach, which allowed us to consider age-specific mortality rather than summary measures, as it analyses curves rather than scalar data. Combined with a functional principal component analysis, it can identify what part of the curves is responsible for assigning one country to a specific cluster. FDA clustering was applied to the data from 32 countries in the Human Mortality Database from 1960 to 2018 to provide a comprehensive understanding of their patterns of mortality. The results show that the evolution of developed countries followed the same pattern of stages (with different timings): (1) a reduction of infant mortality, (2) an increase of premature mortality and (3) a shift and compression of deaths. Some countries were following this scheme and recovering the gap with precursors; others did not show signs of recovery. Eastern European countries were still at Stage (2), and it was not clear if and when they will enter Stage 3. All the country differences related to the different timings with which countries underwent the stages, as identified by the clusters.

Progress of Inequality in Age at Death in India: Role of Adult Mortality

India has seen a reduction in infant and child mortality rates for both the sexes since the early 1980s. However, a decline in mortality at adult ages is marked by significant differences in the subgroups of sex and regions. This study assesses the progress of inequality in age at death with the advances in mortality transition during 36 years period between 1981-1985 and 2012-2016 in India, using the Gini coefficients at the age of zero (G ₀ ). The Gini coefficients show that in the mid-2000s, women outpaced men in G ₀ . The reduction in inequality in age at death is a manifestation of the process of homogeneity in mortality. The low G ₀ is concomitant of high life expectancy at birth (e ₀ ) in India. The results show the dominance of adult mortality over child mortality in the medium-mortality and low-mortality regimes. Varying adult mortality in the subgroups of sex and variance in the mortality levels of regions are the predominant factors for the variation in inequality in age at death. By lowering of the mortality rates in the age group of 15-29 years, India can achieve a high e ₀ that appears at high demographic development and the narrow sex differentials in e ₀ and G ₀ in a short time. Men in the age group of 15-29 years are the most vulnerable subgroup with respect to mortality. There is an immediate need for health policies in India to prioritise the aversion of premature deaths in men aged 15-29 years.

Smoothing, Decomposing and Forecasting Mortality Rates

The Lee-Carter (LC) model represents a landmark paper in mortality forecasting. While having been widely accepted and adopted, the model has some limitations that hinder its performance. Some variants of the model have been proposed to deal with these drawbacks individually, none coped with them all at the same time. In this paper, we propose a Three-Component smooth Lee-Carter (3C-sLC) model which overcomes many of the issues simultaneously. It decomposes mortality development into childhood, early-adult and senescent mortality, which are described, individually, by a smooth variant of the LC model. Smoothness is enforced to avoid irregular patterns in projected life tables, and complexity in the forecasting methodology is unaltered with respect to the original LC model. Component-specific schedules are considered in projections, providing additional insights into mortality forecasts. We illustrate the proposed approach to mortality data for ten low-mortality populations. The 3C-sLC captures mortality developments better than a smooth improved version of the LC model, and it displays wider prediction intervals. The proposed approach provides actuaries, demographers, epidemiologists and social scientists in general with a unique and valuable tool to simultaneously smooth, decompose and forecast mortality.

What can lifespan variation reveal that life expectancy hides? Comparison of five high-income countries

OBJECTIVES

In most countries, life expectancy at birth (e0) has improved for many decades. Recently, however, progress has stalled in the UK and Canada, and reversed in the USA. Lifespan variation, a complementary measure of mortality, increased a few years before the reversal in the USA. To assess whether this measure offers additional meaningful insights, we examine what happened in four other high-income countries with differing life expectancy trends.

DESIGN

We calculated life disparity (a specific measure of lifespan variation) in five countries -- USA, UK, France, Japan and Canada -- using sex- and age specific mortality rates from the Human Mortality Database from 1975 to 2017 for ages 0--100 years. We then examined trends in age-specific mortality to identify the age groups contributing to these changes.

SETTING

USA, UK, France, Japan and Canada.

PARTICIPANTS

aggregate population data of the above nations.

MAIN OUTCOME MEASURES

Life expectancy at birth, life disparity and age-specific mortality.

RESULTS

The stalls and falls in life expectancy, for both males and females, seen in the UK, USA and Canada coincided with rising life disparity. These changes may be driven by worsening mortality in middle-age (such as at age 40). France and Japan, in contrast, continue on previous trajectories.

CONCLUSIONS

Life disparity is an additional summary measure of population health providing information beyond that signalled by life expectancy at birth alone.

Social Inequality and the Future of U.S. Life Expectancy

Despite decades of progress, the future of life expectancy in the United States is uncertain due to widening socioeconomic disparities in mortality, continued disparities in mortality across racial/ethnic groups, and an increase in extrinsic causes of death. These trends prompt us to scrutinize life expectancy in a high-income but enormously unequal society like the United States, where social factors determine who is most able to maximize their biological lifespan. After reviewing evidence for biodemographic perspectives on life expectancy, the uneven diffusion of health-enhancing innovations throughout the population, and the changing nature of threats to population health, we argue that sociology is optimally positioned to lead discourse on the future of life expectancy. Given recent trends, sociologists should emphasize the importance of the social determinants of life expectancy, redirecting research focus away from extending extreme longevity and towards research on social inequality with the goal of improving population health for all.

Changes in life expectancy and lifespan variability by income quartiles in four Nordic countries: a study based on nationwide register data

OBJECTIVES

Levels, trends or changes in socioeconomic mortality differentials are typically described in terms of means, for example, life expectancies, but studies have suggested that there also are systematic social disparities in the dispersion around those means, in other words there are inequalities in lifespan variation. This study investigates changes in income inequalities in mean and distributional measures of mortality in Denmark, Finland, Norway, and Sweden over two decades.

DESIGN

Nationwide register-based study.

SETTING

The Danish, Finnish, Norwegian and Swedish populations aged 30 years or over in 1997 and 2017.

MAIN OUTCOME MEASURES

Income-specific changes in life expectancy, lifespan variation and the contribution of 'early' and 'late' deaths to increasing life expectancy.

RESULTS

Increases in life expectancy has taken place in all four countries, but there are systematic differences across income groups. In general, the largest gains in life expectancy were observed in Denmark, and the smallest increase among low-income women in Sweden and Norway. Overall, life expectancy increased and lifespan variation decreased with increasing income level. These differences grew larger over time. In all countries, a marked postponement of early deaths led to a compression of mortality in the top three income quartiles for both genders. This did not occur for the lowest income quartile.

CONCLUSION

Increasing life expectancy is typically accompanied by postponement of early deaths and reduction of lifespan inequality in the higher-income groups. However, Nordic welfare societies are challenged by the fact that postponing premature deaths among people in the lowest-income groups is not taking place.

Mortality Forecasting with the Lee-Carter Method: Adjusting for Smoothing and Lifespan Disparity

Reliable mortality forecasts are an essential component of healthcare policies in ageing societies. The Lee-Carter method and its later variants are widely accepted probabilistic approaches to mortality forecasting, due to their simplicity and the straightforward interpretation of the model parameters. This model assumes an invariant age component and linear time component for forecasting. We apply the Lee-Carter method on smoothed mortality rates obtained by LASSO-type regularization and hence adjust the time component with the observed lifespan disparity. Smoothing with LASSO produces less error during the fitting period than do spline-based smoothing techniques. As a more informative indicator of longevity, matching with lifespan disparity makes the time component more reflective of mortality improvements. The forecasts produced by the new method were more accurate during out-of-sample evaluation and provided optimistic forecasts for many low-mortality countries.

Black-white disparities during an epidemic: Life expectancy and lifespan disparity in the US, 1980-2000

Covid-19 has demonstrated again that epidemics can affect minorities more than the population in general. We consider one of the last major epidemics in the United States: HIV/AIDS from ca. 1980-2000. We calculate life expectancy and lifespan disparity (a measure of variance in age at death) for thirty US states, finding noticeable differences both between states and between the black and white communities. Lifespan disparity allows us to examine distributional effects, and, using decomposition methods, we find that for six states lifespan disparity for blacks increased between 1980 and 1990, while life expectancy increased less than for whites. We find that we can attribute most of this to the impact of HIV/AIDS.

The ratio of expansion to compression: A new measure of lifespan disparity

Numerous studies have shown that high life expectancy is closely related to low life disparity. Unlike life expectancy, which can be increased by mortality decline at any age, life disparity can either increase or decrease in response to mortality decline. Disparity can thus be decomposed into two opposite components, called compression and expansion, depending on the effect of mortality decline on the age distribution of mortality. Without specifying the two components, various conventional measures of disparity may provide misleading information relating to how life chances in society can be equalized. Based on the relevant properties of changes in disparity, we develop a new measure of disparity—the ratio of expansion to compression—that can account for the relative importance of the two components. This simple measure not only provides a clear view of the evolution of disparity, but also permits changes in disparity related to mortality decline to be interpreted in a consistent manner similar to life expectancy. Simulations and an empirical analysis demonstrated the advantages of this new measure over conventional measures of disparity.

What has contributed to the large sex differentials in lifespan variation and life expectancy in South Korea?

To date, research on sex differentials in lifespan variation and life expectancy has mainly been conducted in Western countries and there is a dearth of data from South Korea. This study aimed to further the understanding of mortality transition and life expectancy in South Korea, and the associated trajectories of age-at-death variation, through an analysis of life disparity by gender. Using complete life tables for South Korea for 1970-2015, sex differentials (female-male differences) in life disparity and life expectancy at birth were estimated, and sex differentials in life expectancy were decomposed by age and cause of death. The results showed that sex differentials in life expectancy at birth have not reduced significantly in the last 45 years (1970: 7.1 years; 2015: 6.2 years). Life disparity has reduced more rapidly for females than males, and the difference increased from -0.1 year in 1981 to -1.6 years in 2015. Sex differentials in life expectancy and life disparity in South Korea were higher during 1970-2015 than in several Western countries with high life expectancy. The elderly age group (60 and above) contributed 50% of the total sex difference in life expectancy at birth in 1970, and this increased to 70% in 2015. The contribution of the age group 15-59 years reduced significantly over the period. Decomposition of life expectancy at birth by cause revealed that diseases of the circulatory system (2.2 years), followed by external causes (1.3 years), were the most important causes of the sex differences in life expectancy at birth in 1983, and in 2015 neoplasms (2.2 years) and external causes (1.1 years) explained half of the total sex differences. There has been a significant shift in the age-specific pattern of the contribution towards each cause of death. Overall, sex differentials in life disparity and life expectancy at birth have remained significant in South Korea in the last 45 years.

The impact of violence on Venezuelan life expectancy and lifespan inequality

BACKGROUND

Venezuela is one of the most violent countries in the world. According to the United Nations, homicide rates in the country increased from 32.9 to 61.9 per 100 000 people between 2000 and 2014. This upsurge coincided with a slowdown in life expectancy improvements. We estimate mortality trends and quantify the impact of violence-related deaths and other causes of death on life expectancy and lifespan inequality in Venezuela.

METHODS

Life tables were computed with corrected age-specific mortality rates from 1996 to 2013. From these, changes in life expectancy and lifespan inequality were decomposed by age and cause of death using a continuous-change model. Lifespan inequality, or variation in age at death, is measured by the standard deviation of the age-at-death distribution.

RESULTS

From 1996 to 2013 in Venezuela, female life expectancy rose 3.57 [95% confidence interval (CI): 3.08-4.09] years [from 75.79 (75.98-76.10) to 79.36 (78.97-79.68)], and lifespan inequality fell 1.03 (-2.96 to 1.26) years [from 18.44 (18.01-19.00) to 17.41 (17.30-18.27)]. Male life expectancy increased 1.64 (1.09-2.25) years [from 69.36 (68.89-59.70) to 71.00 (70.53-71.39)], but lifespan inequality increased 0.95 (-0.80 to 2.89) years [from 20.70 (20.24-21.08) to 21.65 (21.34-22.12)]. If violence-related death rates had not risen over this period, male life expectancy would have increased an additional 1.55 years, and lifespan inequality would have declined slightly (-0.31 years).

CONCLUSIONS

As increases in violence-related deaths among young men (ages 15-39) have slowed gains in male life expectancy and increased lifespan inequality, Venezuelan males face more uncertainty about their age at death. There is an urgent need for more accurate mortality estimates in Venezuela.

Dynamics of life expectancy and life span equality

As people live longer, ages at death are becoming more similar. This dual advance over the last two centuries, a central aim of public health policies, is a major achievement of modern civilization. Some recent exceptions to the joint rise of life expectancy and life span equality, however, make it difficult to determine the underlying causes of this relationship. Here, we develop a unifying framework to study life expectancy and life span equality over time, relying on concepts about the pace and shape of aging. We study the dynamic relationship between life expectancy and life span equality with reliable data from the Human Mortality Database for 49 countries and regions with emphasis on the long time series from Sweden. Our results demonstrate that both changes in life expectancy and life span equality are weighted totals of rates of progress in reducing mortality. This finding holds for three different measures of the variability of life spans. The weights evolve over time and indicate the ages at which reductions in mortality increase life expectancy and life span equality: the more progress at the youngest ages, the tighter the relationship. The link between life expectancy and life span equality is especially strong when life expectancy is less than 70 y. In recent decades, life expectancy and life span equality have occasionally moved in opposite directions due to larger improvements in mortality at older ages or a slowdown in declines in midlife mortality. Saving lives at ages below life expectancy is the key to increasing both life expectancy and life span equality.

Greater mortality variability in the United States in comparison with peer countries

BACKGROUND

Over the past several decades, US mortality declines have lagged behind other high-income countries. However, scant attention has been devoted to how US mortality variability compares with other countries.

OBJECTIVE

We examine trends in mortality and mortality variability in the US and 16 peer countries from 1980 through 2016.

METHODS

We employ the Human Mortality Database and demographic techniques - with a focus on patterns in the interquartile (IQR), interdecile (IDR), and intercentile (ICR) ranges of survivorship - to better understand US mortality and mortality variability trends in comparative perspective.

RESULTS

Compared to other high-income countries, the US: (1) mortality ranking has slipped for nearly all age groups; (2) is losing its old age mortality advantage; (3) has seen growth in relative age-specific mortality gaps from infancy through midlife; and (4) exhibits greater concentrations of deaths from infancy through adulthood, resulting in much greater mortality variability.

CONCLUSIONS

We contribute to calls for renewed attention to the relatively low and lagging US life expectancy. The ICR draws particular attention to the comparatively high US early and midlife mortality.

CONTRIBUTION

We find comparatively high variability in US mortality. Further reductions in early and midlife mortality could diminish variability, reduce years of potential life lost, and increase life expectancy. Consistent with previous research, we encourage policymakers to focus on reducing the unacceptably high early and midlife mortality in the US. And we urge researchers to more frequently monitor and track mortality variation in conjunction with mortality rates and life expectancy estimates.

Lifespan Dispersion in Times of Life Expectancy Fluctuation: The Case of Central and Eastern Europe

Central and Eastern Europe (CEE) have experienced considerable instability in mortality since the 1960s. Long periods of stagnating life expectancy were followed by rapid increases in life expectancy and, in some cases, even more rapid declines, before more recent periods of improvement. These trends have been well documented, but to date, no study has comprehensively explored trends in lifespan variation. We improved such analyses by incorporating life disparity as a health indicator alongside life expectancy, examining trends since the 1960s for 12 countries from the region. Generally, life disparity was high and fluctuated strongly over the period. For nearly 30 of these years, life expectancy and life disparity varied independently of each other, largely because mortality trends ran in opposite directions over different ages. Furthermore, we quantified the impact of large classes of diseases on life disparity trends since 1994 using a newly harmonized cause-of-death time series for eight countries in the region. Mortality patterns in CEE countries were heterogeneous and ran counter to the common patterns observed in most developed countries. They contribute to the discussion about life expectancy disparity by showing that expansion/compression levels do not necessarily mean lower/higher life expectancy or mortality deterioration/improvements.

Potential gains in life expectancy by reducing inequality of lifespans in Denmark: an international comparison and cause-of-death analysis

BACKGROUND

Reducing lifespan inequality is increasingly recognized as a health policy objective. Whereas lifespan inequality declined with rising longevity in most developed countries, Danish life expectancy stagnated between 1975 and 1995 for females and progressed slowly for males. It is unknown how Danish lifespan inequality changed, which causes of death drove these developments, and where the opportunities for further improvements lie now.

METHODS

We present an analytical strategy based on cause-by-age decompositions to simultaneously analyze changes in Danish life expectancy and lifespan inequality from 1960 to 2014, as well as current Swedish-Danish differences.

RESULTS

Stagnation in Danish life expectancy coincided with a shorter period of stagnation in lifespan inequality (1975-1990). The stagnation in life expectancy was mainly driven by increases in cancer and non-infectious respiratory mortality at higher ages (-.63 years) offsetting a reduction in cardiovascular and infant mortality (+ 1.52 years). Lifespan inequality stagnated because most causes of death did not show compression over the time period. Both these observations were consistent with higher smoking-related mortality in Danes born in 1919-1939. After 1995, life expectancy and lifespan equality increased in lockstep, but still lag behind Sweden, mainly due to infant mortality and cancer.

CONCLUSIONS

Since 1960, Danish improvements in life expectancy and lifespan equality were halted by smoking-related mortality in those born 1919-1939, while also reductions in old-age cardiovascular mortality held back lifespan equality. The comparison with Sweden suggests that Denmark can reduce inequality in lifespans and increase life expectancy through a consistent policy target: reducing cancer and infant mortality.

Decomposing Current Mortality Differences Into Initial Differences and Differences in Trends: The Contour Decomposition Method

This study proposes a new decomposition method that permits a difference in an aggregate measure at a final time point to be split into additive components corresponding to the initial differences in the event rates of the measure and differences in trends in these underlying event rates. For instance, when studying divergence in life expectancy, this method allows researchers to more easily contrast age-specific mortality trends between populations by controlling for initial age-specific mortality differences. Two approaches are assessed: (1) an additive change method that uses logic similar to cause-of-death decomposition, and (2) a contour decomposition method that extends the stepwise replacement algorithm along an age-period demographic contour. The two approaches produce similar results, but the contour method is more widely applicable. We provide a full description of the contour replacement method and examples of its application to life expectancy and lifetime disparity differences between the United States and England and Wales in the period 1980–2010.

Bring out your dead!: A study of income inequality and life expectancy in the United States, 2000-2010

We test whether income inequality undermines female and male life expectancy in the United States. We employ data for all 50 states and the District of Columbia and two-way fixed effects to model state-level average life expectancy as a function of multiple income inequality measures and time-varying characteristics. We find that state-level income inequality is inversely associated with female and male life expectancy. We observe this general pattern across four measures of income inequality and under the rigorous conditions of state-specific and year-specific fixed effects. If income inequality undermines life expectancy, redistribution policies could actually improve the health of states.

Life expectancy versus lifespan inequality: A smudge or a clear relationship?

Interest in inequality, including lifespan inequality, is growing. Several studies, using various measures of variation in the length of life, reveal that as life expectancy increases, lifespan inequality tends to decrease, albeit with considerable variation across populations and over time. The aim of this article is to understand why the strength of the relationship between life expectancy and lifespan inequality varies across publications. Results differ in large part because they are based on different data sources. In addition, some measures show more smudginess than others. All the analyses presented here support the basic finding of a strong relationship between life expectancy and lifespan inequality.

Socially disparate trends in lifespan variation: a trend study on income and mortality based on nationwide Danish register data

BACKGROUND

Social inequality trends in life expectancy are not informative as to changes in social disparity in the age-at-death distribution. The purpose of the study was to investigate social differentials in trends and patterns of adult mortality in Denmark.

METHODS

Register data on income and mortality from 1986 to 2014 were used to investigate trends in life expectancy, life disparity and the threshold age that separates 'premature' and 'late' deaths. Mortality compression was quantified and compared between income quartiles.

RESULTS

Since 1986, male life expectancy increased by 4.2 years for the lowest income quartile and by 8.4 years for the highest income quartile. The clear compression of mortality apparent in the highest income quartile did not occur for the lowest income quartile. Premature and late deaths accounted both by 2.1 years of the increase in life expectancy in the lowest income quartile and by 6.0 and 2.4 years, respectively, in the highest income quartile. Life expectancy increased by 5.2 years among women in the lowest income quartile, 2.4 years due to premature deaths and 2.8 years due to late deaths. The gain in life expectancy among women in the highest income quartile of 5.6 years was distributed by 5.0 and 0.6 years due to premature and late deaths, respectively.

CONCLUSION

The study demonstrates that the increasing social gap in mortality appears differently in the change of the age-at-death distribution. Thus, no compression of mortality was seen in the lowest income quartile. The results do not provide support for a uniformly extension of pension age for all.

Increasing inequality in age of death at shared levels of life expectancy: A comparative study of Scotland and England and Wales

There is a strong negative correlation between increasing life expectancy and decreasing lifespan variation, a measure of inequality. Previous research suggests that countries achieving a high level of life expectancy later in time generally do so with lower lifespan variation than forerunner countries. This may be because they are able to capitalise on lessons already learnt. However, a few countries achieve a high level of life expectancy later in time with higher inequality. Scotland appears to be such a country and presents an interesting case study because it previously experienced lower inequality when reaching the same level of life expectancy as its closest comparator England and Wales. We calculated life expectancy and lifespan variation for Scotland and England and Wales for the years 1950 to 2012, comparing Scotland to England and Wales when it reached the same level of life expectancy later on in time, and assessed the difference in the level of lifespan variation. The lifespan variation difference between the two countries was then decomposed into age-specific components. Analysis was carried out for males and females separately. Since the 1950s Scotland has achieved the same level of life expectancy at least ten years later in time than England and Wales. Initially it did so with lower lifespan variation. Following the 1980s Scotland has been achieving the same level of life expectancy later in time than England and Wales and with higher inequality, particularly for males. Decomposition revealed that higher inequality is partly explained by lower older age mortality rates but primarily by higher premature adult age mortality rates when life expectancy is the same. Existing studies suggest that premature adult mortality rates are strongly associated with the social determinants of health and may be amenable to social and economic policies. So addressing these policy areas may have benefits for both inequality and population health in Scotland.

The emergence of longevous populations

The human lifespan has traversed a long evolutionary and historical path, from short-lived primate ancestors to contemporary Japan, Sweden, and other longevity frontrunners. Analyzing this trajectory is crucial for understanding biological and sociocultural processes that determine the span of life. Here we reveal a fundamental regularity. Two straight lines describe the joint rise of life expectancy and lifespan equality: one for primates and the second one over the full range of human experience from average lifespans as low as 2 y during mortality crises to more than 87 y for Japanese women today. Across the primate order and across human populations, the lives of females tend to be longer and less variable than the lives of males, suggesting deep evolutionary roots to the male disadvantage. Our findings cast fresh light on primate evolution and human history, opening directions for research on inequality, sociality, and aging.

Disparities in length of life across developed countries: measuring and decomposing changes over time within and between country groups

Background

Over the past half century the global tendency for improvements in longevity has been uneven across countries. This has resulted in widening of inter-country disparities in life expectancy. Moreover, the pattern of divergence appears to be driven in part by processes at the level of country groupings defined in geopolitical terms. A systematic quantitative analysis of this phenomenon has not been possible using demographic decomposition approaches as these have not been suitably adapted for this purpose. In this paper we present an elaboration of conventional decomposition techniques to provide a toolkit for analysis of the inter-country variance, and illustrate its use by analyzing trends in life expectancy in developed countries over a 40-year period.

Methods

We analyze trends in the population-weighted variance of life expectancy at birth across 36 developed countries and three country groups over the period 1970–2010. We have modified existing decomposition approaches using the stepwise replacement algorithm to compute age components of changes in the total variance as well as variance between and within groups of Established Market Economies (EME), Central and Eastern Europe (CEE), and the Former Soviet Union (FSU). The method is generally applicable to the decomposition of temporal changes in any aggregate index based on a set of populations.

Results

The divergence in life expectancy between developed countries has generally increased over the study period. This tendency dominated from the beginning of 1970s to the early 2000s, and reversed only after 2005. From 1970 to 2010, the total standard deviation of life expectancy increased from 2.0 to 5.6 years among men and from 1.0 to 3.6 years among women. This was determined by the between-group effects due to polarization between the EME and the FSU. The latter contrast was largely fueled by the long-term health crisis in Russia. With respect to age, the increase in the overall divergence was attributable to between-country differences in mortality changes at ages 15–64 years compared to those aged 65 and older. The within-group variance increased, especially among women. This change was mostly produced by growing mortality differences at ages 65 and older.

Conclusions

From the early 1970s to the mid-2000s, the strong divergence in life expectancy across developed countries was largely determined by the between-group variance and mortality polarization linked to the East–West geopolitical division.

How have trends in lifespan variation changed since 1950? A comparative study of 17 Western European countries

Lifespan variation adds to life expectancy by measuring the inequality surrounding age of death that a population faces. Countries that tackle premature mortality generally have decreasing lifespan variation but this is the first study to compare and statistically assess when and to what extent trends in lifespan variation have changed across Western Europe. Lifespan variation was measured using e† and joinpoint regression analysed the timing and rate of change. Trends have been mostly downward with the recent exception of men in Scotland, Northern Ireland, Ireland and Finland where trends have flattened or show slight increases. Future research aimed at identifying the ages and causes of death, driving trends in these countries, is key to preventing increasing inequalities.

MEASURING EARLY LIFE DISPARITY IN INDIA

Early life disparity - defined as the average life years lost due to death by the age of 60 years - can be used to assess more systematically the effect of savings from death at a young age. In addition, it can give valuable insight into the consequences of death in the early stages of life. Early life disparity can further be categorized into child life disparity (0-14 years) and adult life disparity (15-60 years). This study estimated early life disparity using complete life tables for the period 1970-1975 to 2006-2010, which were constructed from abridged life tables and death rates provided by the Sample Registration System (SRS) in India. The contribution of premature deaths to the difference in life disparity was estimated using a replacement algorithm. The findings clearly indicated an overall declining trend in early life disparity in India, with a notable reduction in child life disparity, and a deceleration of adult life disparity during the period 1970-1975 to 2006-2010. Interstate variations in early life disparity were seen to converge with time. Decomposition analysis suggested that these variations could be minimized further by averting death during childhood.

Income inequality, life expectancy and cause-specific mortality in 43 European countries, 1987-2008: a fixed effects study

Whether income inequality is related to population health is still open to debate. We aimed to critically assess the relationship between income inequality and mortality in 43 European countries using comparable data between 1987 and 2008, controlling for time-invariant and time-variant country-level confounding factors. Annual data on income inequality, expressed as Gini index based on net household income, were extracted from the Standardizing the World Income Inequality Database. Data on life expectancy at birth and age-standardized mortality by cause of death were obtained from the Human Lifetable Database and the World Health Organization European Health for All Database. Data on infant mortality were obtained from the United Nations World Population Prospects Database. The relationships between income inequality and mortality indicators were studied using country fixed effects models, adjusted for time trends and country characteristics. Significant associations between income inequality and many mortality indicators were found in pooled cross-sectional regressions, indicating higher mortality in countries with larger income inequalities. Once the country fixed effects were added, all associations between income inequality and mortality indicators became insignificant, except for mortality from external causes and homicide among men, and cancers among women. The significant results for homicide and cancers disappeared after further adjustment for indicators of democracy, education, transition to national independence, armed conflicts, and economic freedom. Cross-sectional associations between income inequality and mortality seem to reflect the confounding effects of other country characteristics. In a European context, national levels of income inequality do not have an independent effect on mortality.

The entropy of the life table: A reappraisal

The life table entropy provides useful information for understanding improvements in mortality and survival in a population. In this paper we take a closer look at the life table entropy and use advanced mathematical methods to provide additional insights for understanding how it relates to changes in mortality and survival. By studying the entropy (H) as a functional, we show that changes in the entropy depend on both the relative change in life expectancy lost due to death (e(†)) and in life expectancy at birth (e0). We also show that changes in the entropy can be further linked to improvements in premature and older deaths. We illustrate our methods with empirical data from Latin American countries, which suggests that at high mortality levels declines in H (which are associated with survival increases) linked with larger improvements in e0, whereas at low mortality levels e(†) made larger contributions to H. We additionally show that among countries with low mortality level, contributions of e(†) to changes in the life table entropy resulted from averting early deaths. These findings indicate that future increases in overall survival in low mortality countries will likely result from improvements in e(†).

Truncated cross-sectional average length of life: A measure for comparing the mortality history of cohorts

Period life expectancies are commonly used to compare populations, but these correspond to simple juxtapositions of current mortality levels. In order to construct life expectancies for cohorts, a complete historical series of mortality rates is needed, and these are available for only a subset of developed countries. The truncated cross-sectional average length of life (TCAL) is a new measure that captures historical information about all cohorts present at a given moment and is not limited to countries with complete cohort mortality data. The value of TCAL depends on the rates used to complete the cohort series, but differences between TCALs of two populations remain similar irrespective of the data used to complete the cohort series. This result is illustrated by a comparison of TCALs for the US with those for Denmark, Japan, and other high-longevity countries. Specific cohorts that account for most of the disparity in mortality between the populations are identified.

Diagnoses associated with the greatest years of potential life lost for in-hospital deaths in the United States, 1988-2010

OBJECTIVE

Premature mortality is a public health concern that can be quantified as years of potential life lost (YPLL). Studying premature mortality from in-hospital mortality can help guide hospital initiatives and resource allocation. This paper identified the diagnosis categories associated with in-hospital deaths that account for the highest YPLL and their trends over time.

STUDY DESIGN

Retrospective review of the Nationwide Inpatient Sample (NIS), 1988-2010.

METHODS

Using the NIS, YPLL on patients hospitalized in the United States from 1988 to 2010 was calculated. Hospitalizations were categorized by related principal diagnoses using the Healthcare Cost and Utilization Project (HCUP) single-level Clinical Classification Software (CCS) definitions.

RESULTS

Between 1988 and 2010, total in-hospital estimated mortality of 20,154,186 people accounted for 198,417,257 YPLL (9.84 YPLL per in-hospital mortality; 8,626,837 estimated annual mean YPLL). The ten highest YPLL diagnosis categories accounted for 51% of the overall YPLL. The liveborn disease category (i.e., in-hospital live births) was the most common principal diagnosis and accounted for the highest YPLL at 1,070,053. The septicemia category accounted for the second highest YPLL at 548,922. The highest in-hospital mortality rate (20.8%) was associated with adult respiratory failure/insufficiency/arrest. The highest estimated in-hospital annual mean deaths occurred in patients with pneumonia at 69,134. For all in-hospital mortality, the inflation adjusted total in-hospital charges per YPLL was highest for acute myocardial infarction at $9292 per YPLL.

CONCLUSIONS

Using YPLL, a framework has been provided to compare the impact of premature in-hospital mortality from dissimilar diseases. The methodology and results may be used to help guide further investigation of hospital quality initiatives and resource allocation.

The role of smoking in changes in the survival curve: an empirical study in 10 European countries

PURPOSE

We examined the role of smoking in the two dimensions behind the time trends in adult mortality in European countries, that is, rectangularization of the survival curve (mortality compression) and longevity extension (increase in the age-at-death).

METHODS

Using data on national sex-specific populations aged 50 years and older from Denmark, Finland, France, West Germany, Italy, the Netherlands, Norway, Sweden, Switzerland, and the United Kingdom, we studied trends in life expectancy, rectangularity, and longevity from 1950 to 2009 for both all-cause and nonsmoking-related mortality and correlated them with trends in lifetime smoking prevalence.

RESULTS

For all-cause mortality, rectangularization accelerated around 1980 among men in all the countries studied, and more recently among women in Denmark and the United Kingdom. Trends in lifetime smoking prevalence correlated negatively with both rectangularization and longevity extension, but more negatively with rectangularization. For nonsmoking-related mortality, rectangularization among men did not accelerate around 1980. Among women, the differences between all-cause mortality and nonsmoking-related mortality were small, but larger for rectangularization than for longevity extension. Rectangularization contributed less to the increase in life expectancy than longevity extension, especially for nonsmoking-related mortality among men.

CONCLUSIONS

Smoking affects rectangularization more than longevity extension, both among men and women.