Lifespan variation by occupational class: compression or stagnation over time?

Cross-sectional Average Length of Life Entropy ( H CAL ): 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 ( H CAL ). 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.

Decomposition of life expectancy differentials with (and without) conditions by educational attainment for major groups of causes in contemporary Spain: where is the advantage?

Introduction

Healthy life expectancy is higher among individuals with higher socioeconomic standing. However, it is unclear whether such advantage is attributable to longer (i.e., mortality advantage) or to healthier (morbidity advantage) lifespans across different health conditions.

Objective

Estimate the contribution of mortality and morbidity components in differences in condition-free life expectancies (CFLE) and life expectancy with conditions (LEWC) for five major groups of conditions by sex and educational attainment, instead of using a global indicator of morbidity.

Methods

Using the Sullivan Method, we computed remaining life expectancies at age 40 and 65, CFLE, and LEWC and applied a stepwise decomposition technique, using national health surveys along with mortality data, in a cross-sectional analysis.

Results

An educational gradient was present in almost all conditions, with different intensities. For females, morbidity was the main contributor to educational differences in health expectancies, but mainly in the older age groups. For males, the drivers behind higher health expectancies for high-educated males were evenly distributed across mortality and morbidity between ages 40 and 65, but after that, the mortality gradient vanished between high-educated and middle-educated individuals.

Discussion

The changing contribution of the mortality and morbidity gradient for different conditions across age-groups brings evidence to adequately plan health policies to mitigate health gaps and improve quality of life of the populations in a lower social standing.

Educational composition effect on the sex gap in life expectancy: A research note based on evidence from Australia

Life expectancy for females has exceeded that of males globally this century. There is considerable within-country variation in life expectancy related to education. Sex gaps in life expectancy can be decomposed into two components: sex differences in education-specific mortality and sex differences in educational composition. We illustrate this using Australian data for 2016, when the sex gap in life expectancy at age 25 was 3.8 years. The sex gap would be as large as 4.5 years if males and females had the same educational composition; however, it is reduced by 0.7 years, given the lower levels of education among women than men. In a hypothetical scenario accounting for recent increases in females' educational achievement (holding the educational composition at all ages constant at that observed at ages 25-39 for both sexes), we estimate a potential increase in the sex gap (to 4.1 years) in favour of females.

Trends in socioeconomic inequalities in life expectancy and lifespan variation in Chile

Background

Socioeconomic disparities in life expectancy are well-documented in various contexts, including Chile. However, there is a lack of research examining trends in life expectancy inequalities and lifespan variation over time. Addressing these gaps can provide crucial insights into the dynamics of health inequalities.

Methods

This study utilizes data from census records, population surveys, and death certificates to compare the life expectancy and the lifespan variation at age 26 of individuals according to their rank in the distribution of years of education within their own birth cohort. The analysis spans three periods (1991, 2002, and 2017) and focuses on two educational groups: individuals in the first (lowest) quintile and tenth (highest) decile of educational attainment. Changes in life expectancy are disaggregated by major causes of death to elucidate their contributions to overall trends.

Results

Consistent with existing literature, our findings confirm that individuals with lower education levels experience lower life expectancy and higher lifespan variation compared to their more educated counterparts. Notably, by 2017, life expectancy for individuals in the lowest quintile of education has caught up with that of the top decile in 1991, albeit with contrasting trends between genders. Among women, the gap has reduced, while it has increased for males. Moreover, lifespan variation decreased (increased) over time for individuals in the tenth decile (first quintile). The leading causes of death that explain the increase in life expectancy in women and men in the tenth decile as well as women in the first quintile are cardiovascular, cancer, respiratory and digestive diseases. In the case of males in the first quintile, few gains have been made in life expectancy resulting from cancer and a negative contribution is associated with digestive conditions.

Conclusions

This study underscores persistent socioeconomic disparities in life expectancy in Chile, emphasizing the importance of ongoing monitoring of health inequalities across different demographic segments. The gender-specific and educational gradient trends highlight areas for targeted interventions aimed at reducing health disparities and improving overall population health outcomes. Further research is warranted to delve into specific causes of death driving life expectancy differentials and to inform evidence-based policy interventions.

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.

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.

The importance of education for understanding variability of dementia onset in the United States

BACKGROUND

Greater levels of education are associated with lower risk of dementia, but less is known about how education is also associated with the compression of dementia incidence.

OBJECTIVE

We extend the literature on morbidity compression by evaluating whether increased levels of education are associated with greater dementia compression. We evaluate these patterns across race and gender groups.

METHODS

We use the Health and Retirement Study (2000-2016), a nationally representative longitudinal study of older adults in the United States. To evaluate the onset and compression of dementia across education groups, we examine the age-specific distribution of dementia events, identifying the modal age of onset and the standard deviation above the mode (a measure of compression).

RESULTS

While the modal age of onset is around 85 years among adults with a college degree, the modal age for adults with less than a high school education occurs before age 65 - at least a 20-year difference. The standard deviation of dementia onset is about three times greater for adults with less than a high school education compared to adults with a college degree. Patterns were consistent across race and gender groups.

CONCLUSION

This research highlights the variability of dementia experiences in the older population by documenting differences in longevity without dementia and compression of dementia onset among more educated adults and less educated adults.

CONTRIBUTION

We incorporate conceptual insights from the life span variability and compression literature to better understand education-dementia disparities in both the postponement and uncertainty of dementia onset in the US population.

Contributions of age groups and causes of death to the sex gap in lifespan variation in Europe

Much less is known about the sex gap in lifespan variation, which reflects inequalities in the length of life, than about the sex gap in life expectancy (average length of life). We examined the contributions of age groups and causes of death to the sex gap in lifespan variation for 28 European countries, grouped into five European regions. In 2010-15, males in Europe displayed a 6.8-year-lower life expectancy and a 2.3-year-higher standard deviation in lifespan than females, with clear regional differences. Sex differences in lifespan variation are attributable largely to higher external mortality among males aged 30-39, whereas sex differences in life expectancy are due predominantly to higher smoking-related and cardiovascular disease mortality among males aged 60-69. The distinct findings for the sex gap in lifespan variation and the sex gap in life expectancy provide additional insights into the survival differences between the sexes.

Reversals in past long-term trends in educational inequalities in life expectancy for selected European countries

BACKGROUND

Across Europe, socioeconomic inequalities in mortality are large and persistent. To better understand the drivers of past trends in socioeconomic mortality inequalities, we identified phases and potential reversals in long-term trends in educational inequalities in remaining life expectancy at age 30 (e30), and assessed the contributions of mortality changes among the low-educated and the high-educated at different ages.

METHODS

We used individually linked annual mortality data by educational level (low, middle and high), sex and single age (30+) from 1971/1972 onwards for England and Wales, Finland and Italy (Turin). We applied segmented regression to trends in educational inequalities in e30 (e30 high-educated minus e30 low-educated) and employed a novel demographic decomposition technique.

RESULTS

We identified several phases and breakpoints in the trends in educational inequalities in e30. The long-term increases (Finnish men, 1982-2008; Finnish women, 1985-2017; and Italian men, 1976-1999) were driven by faster mortality declines among the high-educated aged 65-84, and by mortality increases among the low-educated aged 30-59. The long-term decreases (British men, 1976-2008, and Italian women, 1972-2003) were driven by faster mortality improvements among the low-educated than among the high-educated at age 65+. The recent stagnation of increasing inequality (Italian men, 1999) and reversals from increasing to decreasing inequality (Finnish men, 2008) and from decreasing to increasing inequality (British men, 2008) were driven by mortality trend changes among the low-educated aged 30-54.

CONCLUSION

Educational inequalities are plastic. Mortality improvements among the low-educated at young ages are imperative for achieving long-term decreases in educational inequalities in e30.

Focus on age at death in field epidemiology

Age at death (AD) is an old metric recently re-evaluated for the study of longevity and mainly used in demography. Developed experience using AD in field epidemiology is summarized with cohorts followed-up for variable periods of time, frequently until extinction or close to extinction, a must to correctly adopt this metric. For practical purposes, a small number of examples is reported condensing previously published results to highlight various aspects of the problem. AD became the alternative of overall death rates when comparing cohorts reaching extinction or near extinction. AD was useful to characterize different causes of death in order to describe their natural history and possible etiology. With the use of multiple linear regression, a large number of possible determinants of AD were identified and some combinations of them resulted in large estimated differences in AD of 10 years or more across individuals. AD is a powerful tool to study population samples followed-up until extinction or near extinction. It allows to compare the life-long experience of different populations, to compare the role of different causes of death and to study the determinants of AD that are conditioning longevity.

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.

A distributional approach to measuring lifespan stratification

The study of the mortality differences between groups has traditionally focused on metrics that describe average levels of mortality, for example life expectancy and standardized mortality rates. Additional insights can be gained by using statistical distance metrics to examine differences in lifespan distributions between groups. Here, we use a distance metric, the non-overlap index, to capture the sociological concept of stratification, which emphasizes the emergence of unique, hierarchically layered social strata. We show an application using Finnish registration data that cover the entire population over the period from 1996 to 2017. The results indicate that lifespan stratification and life-expectancy differences between income groups both increased substantially from 1996 to 2008; subsequently, life-expectancy differences declined, whereas stratification stagnated for men and increased for women. We conclude that the non-overlap index uncovers a unique domain of inequalities in mortality and helps to capture important between-group differences that conventional approaches miss.

Exploring inequalities in life expectancy and lifespan variation by race/ethnicity and urbanicity in the United States: 1990 to 2019

Background/Objective

Investigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019.

Methods

Using vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990-1994 to 2015-2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables.

Results

In 2015-2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time.

Conclusion

Despite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.

Occupational differences in mortality and life expectancy persist after retirement and throughout life

AIMS

There are substantial differences in remaining life expectancy at higher ages between occupational groups. These differences may be the effect of work-related exposures, lifestyle factors of workers in specific occupations, socioeconomic position or a combination of this. The scope of this paper is the extent to which occupational differences in remaining life expectancy persist after retirement, which would suggest that occupational exposures alone are not likely to explain all the difference.

METHODS

All individuals born between 1925 and 1939 who reported occupational information in the Census 1985 and were residents in Sweden to the end of 2020 or who died were included and followed for death until 2020. The Nordic Classification of Occupations was used to create nine occupational groups. Partial life expectancy and age-specific death rates were applied to examine mortality differentials.

RESULTS

This study showed substantial differences in partial life expectancy across the occupational cohorts with the biggest difference being about 2 years. The mortality differences persisted with increasing age, both when measured as absolute numbers as well as relative numbers.

CONCLUSIONS

The lack of convergence in mortality at high ages suggests that factors associated with lifestyle may play a larger role than occupational factors for the mortality differences between occupational groups at high ages. However, it cannot be ruled out that long-lasting effects of earlier occupational exposures also contribute. Regardless of the exact mechanism, we conclude that there is room for further reduction in mortality at high ages and, thus, for further improvement in life expectancy.

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.

On the measurement of healthy lifespan inequality

Background

Current measures to monitor population health include indicators of (i) average length-of-life (life expectancy), (ii) average length-of-life spent in good health (health expectancy), and (iii) variability in length-of-life (lifespan inequality). What is lacking is an indicator measuring the extent to which healthy lifespans are unequally distributed across individuals (the so-called ‘healthy lifespan inequality’ indicators).

Methods

We combine information on age-specific survival with the prevalence of functional limitation or disability in Spain (2014–2017) by sex and level of education to estimate age-at-disability onset distributions. Age-, sex- and education-specific prevalence rates of adult individuals’ daily activities limitations were based on the GALI index derived from Spanish National Health Surveys held in 2014 and 2017. We measured inequality using the Gini index.

Results

In contemporary Spain, education differences in health expectancy are substantial and greatly exceed differences in life expectancy. The female advantage in life expectancy disappears when considering health expectancy indicators, both overall and across education groups. The highly educated exhibit lower levels of lifespan inequality, and lifespan inequality is systematically higher among men. Our new healthy lifespan inequality indicators suggest that the variability in the ages at which physical daily activity limitations start are substantially larger than the variability in the ages at which individuals die. Healthy lifespan inequality tends to decrease with increasing educational attainment, both for women and for men. The variability in ages at which physical limitations start is slightly higher for women than for men.

Conclusions

The suggested indicators uncover new layers of health inequality that are not traceable with currently existing approaches. Low-educated individuals tend to not only die earlier and spend a shorter portion of their lives in good health than their highly educated counterparts, but also face greater variation in the eventual time of death and in the age at which they cease enjoying good health—a multiple burden of inequality that should be taken into consideration when evaluating the performance of public health systems and in the elaboration of realistic working-life extension plans and the design of equitable pension reforms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12963-021-00279-8.

What have we learned about mortality patterns over the past 25 years?

In this paper, I examine progress in the field of mortality over the past 25 years. I argue that we have been most successful in taking advantage of an increasingly data-rich environment to improve aggregate mortality models and test pre-existing theories. Less progress has been made in relating our estimates of mortality risk at the individual level to broader mortality patterns at the population level while appropriately accounting for contextual differences and compositional change. Overall, I find that the field of mortality continues to be highly visible in demographic journals, including Population Studies. However much of what is published today in field journals could just as easily appear in neighbouring disciplinary journals, as disciplinary boundaries are shrinking.

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 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.

Insight into stagnating adult life expectancy: Analyzing cause of death patterns across socioeconomic groups

This study analyzes the complexity of female longevity improvements. As socioeconomic status is found to influence health and mortality, we partition all individuals, at each age in every year, into five socioeconomic groups based on an affluence measure that combine an individual's income and wealth. We identify the particular socioeconomic groups that have been driving the standstill for Danish females at older ages. Within each socioeconomic group, we further analyze the cause of death patterns. The decline in life expectancy for Danish females is present for four out of five subgroups, however, with particular large decreases for the low-middle and middle-affluence groups. Cancers, smoking-related lung and bronchus causes, and other diseases particularly contribute to the stagnation. For four of the five socioeconomic groups only small cardiovascular improvement are experienced during the period of stagnating life expectancy compared to an equally long and subsequent period.

Longevity and Lifespan Variation by Educational Attainment in Spain: 1960-2015

For a long time, studies of socioeconomic gradients in health have limited their attention to between-group comparisons. Yet, ignoring the differences that might exist within groups and focusing on group-specific life expectancy levels and trends alone, one might arrive at overly simplistic conclusions. Using data from the Spanish Encuesta Sociodemográfica and recently released mortality files by the Spanish Statistical Office (INE), this is the first study to simultaneously document (1) the gradient in life expectancy by educational attainment groups, and (2) the inequality in age-at-death distributions within and across those groups for the period between 1960 and 2015 in Spain. Our findings suggest that life expectancy has been increasing for all education groups but particularly among the highly educated. We observe diverging trends in life expectancy, with the differences between the low- and highly educated becoming increasingly large, particularly among men. Concomitantly with increasing disparities across groups, length-of-life inequality has decreased for the population as a whole and for most education groups, and the contribution of the between-group component of inequality to overall inequality has been extremely small. Even if between-group inequality has increased over time, its contribution has been too small to have sizable effects on overall inequality. In addition, our results suggest that education expansion and declining within-group variability might have been the main drivers of overall lifespan inequality reductions. Nevertheless, the diverging trends in longevity and lifespan inequality across education groups represent an important phenomenon whose underlying causes and potential implications should be investigated in detail.

Latin American convergence and divergence towards the mortality profiles of developed countries

It is uncertain whether Latin America and Caribbean (LAC) countries are approaching a single mortality regime. Over the last three decades, LAC has experienced major public health interventions and the highest number of homicides in the world. However, these interventions and homicide rates are not evenly shared across countries. This study documents trends in life expectancy and lifespan variability for 20 LAC countries, 2000-14. By extending a previous method, we decompose differences in lifespan variability between LAC and a developed world benchmark into cause-specific effects. For both sexes, dispersion of amenable diseases through the age span makes the largest contribution to the gap between LAC and the benchmark. Additionally, for males, the concentration of homicides, accidents, and suicides in mid-life further impedes mortality convergence. Great disparity exists in the region: while some countries are rapidly approaching the developed regime, others remain far behind and suffer a clear disadvantage in population health.

The increasing lifespan variation gradient by area-level deprivation: A decomposition analysis of Scotland 1981-2011

Life expectancy inequalities are an established indicator of health inequalities. More recent attention has been given to lifespan variation, which measures the amount of heterogeneity in age at death across all individuals in a population. International studies have documented diverging socioeconomic trends in lifespan variation using individual level measures of income, education and occupation. Despite using different socioeconomic indicators and different indices of lifespan variation, studies reached the same conclusion: the most deprived experience the lowest life expectancy and highest lifespan variation, a double burden of mortality inequality. A finding of even greater concern is that relative differences in lifespan variation between socioeconomic group were growing at a faster rate than life expectancy differences. The magnitude of lifespan variation inequalities by area-level deprivation has received limited attention. Area-level measures of deprivation are actively used by governments for allocating resources to tackle health inequalities. Establishing if the same lifespan variation inequalities emerge for area-level deprivation will help to better inform governments about which dimension of mortality inequality should be targeted. We measure lifespan variation trends (1981-2011) stratified by an area-level measure of socioeconomic deprivation that is applicable to the entire population of Scotland, the country with the highest level of variation and one of the longest, sustained stagnating trends in Western Europe. We measure the gradient in variation using the slope and relative indices of inequality. The deprivation, age and cause specific components driving the increasing gradient are identified by decomposing the change in the slope index between 1981 and 2011. Our results support the finding that the most advantaged are dying within an ever narrower age range while the most deprived are facing greater and increasing uncertainty. The least deprived group show an increasing advantage, over the national average, in terms of deaths from circulatory disease and external causes.

Global trends in lifespan inequality: 1950-2015

Using data from the UN World Population Prospects, we document global trends in lifespan inequality from 1950 until 2015. Our findings indicate that (i) there has been a sustained decline in overall lifespan inequality, (ii) adult lifespan variability has also declined, but some plateaus and trend reversals have been identified, (iii) lifespan inequality among the elderly has increased virtually everywhere, and (iv) most of the world variability in age-at-death can be attributed to within-country variability. Such changes have occurred against a backdrop of generalized longevity increases. Our analyses suggest that the world is facing a new challenge: the emergence of diverging trends in longevity and age-at-death inequality among the elderly around the globe-particularly in high-income areas. As larger fractions of the world population survive to more advanced ages, it will be necessary for national and international health planners to recognize the growing heterogeneity that characterizes older populations.

Changing contribution of area-level deprivation to total variance in age at death: a population-based decomposition analysis

OBJECTIVES

Two processes generate total variance in age at death: heterogeneity (between-group variance) and individual stochasticity (within-group variance). Limited research has evaluated how these two components have changed over time. We quantify the degree to which area-level deprivation contributed to total variance in age at death in Scotland between 1981 and 2011.

DESIGN

Full population and mortality data for Scotland were obtained and matched with the Carstairs score, a standardised z-score calculated for each part-postcode sector that measures relative area-level deprivation. A z-score above zero indicates that the part-postcode sector experienced higher deprivation than the national average. A z-score below zero indicates lower deprivation. From the aggregated data we constructed 40 lifetables, one for each deprivation quintile in 1981, 1991, 2001 and 2011 stratified by sex.

PRIMARY OUTCOME MEASURES

Total variance in age at death and the proportion explained by area-level deprivation heterogeneity (between-group variance).

RESULTS

The most deprived areas experienced stagnating or slightly increasing variance in age at death. The least deprived areas experienced decreasing variance. For males, the most deprived quintile life expectancy was between 7% and 11% lower and the SD is between 6% and 25% higher than the least deprived. This suggests that the effect of deprivation on the SD of longevity is comparable to its effect on life expectancy. Decomposition analysis revealed that contributions from between-group variance doubled between 1981 and 2011 but at most only explained 4% of total variance.

CONCLUSIONS

This study adds to the emerging body of literature demonstrating that socio-economic groups have experienced diverging trends in variance in age at death. The contribution from area-level deprivation to total variance in age at death, which we were able to capture, has doubled since 1981. Area-level deprivation may play an increasingly important role in mortality inequalities.

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.

Complexity of the relationship between life expectancy and overlap of lifespans

Longevity has long been recognised as a key facilitator of reciprocal altruism because repeated cooperation of partners hinges on mutual survival. Although demographic tools can be used to quantify mutual survival and expected overlapping lifespans, studies on the evolutionary theory of cooperation take only limited advantage of demography. Overlap of lifespans depends on variation in survival across ages and can be high or low independently of high or low life expectancies. Here we develop formal demographic measures to study the complex relationships between shared life expectancy of two birth cohort peers, the proportion of their lives that they can expect to overlap, and longevity. We simulate age-specific mortality schedules using a Siler model to reveal how infant and senescent mortality, along with age-independent mortality, affect the relationship between the proportion of life shared and life expectancy. We find that while the proportion of life shared can vary vastly for similar life expectancies, almost all changes to mortality schedules that result in higher life expectancies also result in higher proportions of life shared. A distinct exception occurs if life expectancy increases due to lowering the rate of senescence. In this case the proportion of life shared decreases. Our work shows that almost all selective pressures that result in higher life expectancies also result in a larger proportion of life shared. Therefore, selective forces that extend life also improve the chances that a cooperative system would be stable in terms of reciprocal interactions. Since reciprocal interactions may also reduce mortality and result in a feedback loop with the evolution of longevity, our measures and findings can be used for future cross-species comparisons that aim to disentangle predecessor and successor in the evolution of longevity and cooperation.

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.

Longevity and concentration in survival times: the log-scale-location family of failure time models

Evidence suggests that the increasing life expectancy levels at birth witnessed over the past centuries are associated with a decreasing concentration of the survival times. The purpose of this work is to study the relationships that exist between longevity and concentration measures for some regression models for the evolution of survival. In particular, we study a family of survival models that can be used to capture the observed trends in longevity and concentration over time. The parametric family of log-scale-location models is shown to allow for modeling different trends of expected value and concentration of survival times. An extension towards mixture models is also described in order to take into account scenarios where a fraction of the population experiences short term survival. Some results are also presented for such framework. The use of both the log-scale-location family and the mixture model is illustrated through an application to period life tables from the Human Mortality Database.

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.

Hispanic-White Differences in Lifespan Variability in the United States

This study is the first to investigate whether and, if so, why Hispanics and non-Hispanic whites in the United States differ in the variability of their lifespans. Although Hispanics enjoy higher life expectancy than whites, very little is known about how lifespan variability-and thus uncertainty about length of life-differs by race/ethnicity. We use 2010 U.S. National Vital Statistics System data to calculate lifespan variance at ages 10+ for Hispanics and whites, and then decompose the Hispanic-white variance difference into cause-specific spread, allocation, and timing effects. In addition to their higher life expectancy relative to whites, Hispanics also exhibit 7 % lower lifespan variability, with a larger gap among women than men. Differences in cause-specific incidence (allocation effects) explain nearly two-thirds of Hispanics' lower lifespan variability, mainly because of the higher mortality from suicide, accidental poisoning, and lung cancer among whites. Most of the remaining Hispanic-white variance difference is due to greater age dispersion (spread effects) in mortality from heart disease and residual causes among whites than Hispanics. Thus, the Hispanic paradox-that a socioeconomically disadvantaged population (Hispanics) enjoys a mortality advantage over a socioeconomically advantaged population (whites)-pertains to lifespan variability as well as to life expectancy. Efforts to reduce U.S. lifespan variability and simultaneously increase life expectancy, especially for whites, should target premature, young adult causes of death-in particular, suicide, accidental poisoning, and homicide. We conclude by discussing how the analysis of Hispanic-white differences in lifespan variability contributes to our understanding of the Hispanic paradox.

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.

Social class based on occupation is associated with hospitalization for A(H1N1)pdm09 infection. Comparison between hospitalized and ambulatory cases

This study aimed to analyse the existence of an association between social class (categorized by type of occupation) and the occurrence of A(H1N1)pmd09 infection and hospitalization for two seasons (2009-2010 and 2010-2011). This multicentre study compared ambulatory A(H1N1)pmd09 confirmed cases with ambulatory controls to measure risk of infection, and with hospitalized A(H1N1)pmd09 confirmed cases to asses hospitalization risk. Study variables were: age, marital status, tobacco and alcohol use, pregnancy, chronic obstructive pulmonary disease, chronic respiratory failure, cardiovascular disease, diabetes, chronic liver disease, body mass index >40, systemic corticosteroid treatment and influenza vaccination status. Occupation was registered literally and coded into manual and non-manual worker occupational social class groups. A conditional logistic regression analysis was performed. There were 720 hospitalized cases, 996 ambulatory cases and 1062 ambulatory controls included in the study. No relationship between occupational social class and A(H1N1)pmd09 infection was found [adjusted odds ratio (aOR) 0·97, 95% confidence interval (CI) 0·74-1·27], but an association (aOR 1·53, 95% CI 1·01-2·31) between occupational class and hospitalization for A(H1N1)pmd09 was observed. Influenza vaccination was a protective factor for A(H1N1)pmd09 infection (aOR 0·41, 95% CI 0·23-0·73) but not for hospitalization. We conclude that manual workers have the highest risk of hospitalization when infected by influenza than other occupations but they do not have a different probability of being infected by influenza.

Why lifespans are more variable among blacks than among whites in the United States

Lifespans are both shorter and more variable for blacks than for whites in the United States. Because their lifespans are more variable, there is greater inequality in length of life-and thus greater uncertainty about the future-among blacks. This study is the first to decompose the black-white difference in lifespan variability in America. Are lifespans more variable for blacks because they are more likely to die of causes that disproportionately strike the young and middle-aged, or because age at death varies more for blacks than for whites among those who succumb to the same cause? We find that it is primarily the latter. For almost all causes of death, age at death is more variable for blacks than it is for whites, especially among women. Although some youthful causes of death, such as homicide and HIV/AIDS, contribute to the black-white disparity in variance, those contributions are largely offset by the higher rates of suicide and drug poisoning deaths for whites. As a result, differences in the causes of death for blacks and whites account, on net, for only about one-eighth of the difference in lifespan variance.