The case for monitoring life-span inequality

Inequalities in lifespan and mortality risk in the US, 2015-2019: a cross-sectional analysis of subpopulations by social determinants of health

OBJECTIVE

To quantify inequalities in lifespan across multiple social determinants of health, how they act in tandem with one another, and to create a scoring system that can accurately identify subgroups of the population at high risk of mortality.

DESIGN

Comparison of life tables across 54 subpopulations defined by combinations of four social determinants of health: sex, marital status, education and race, using data from the Multiple Cause of Death dataset and the American Community Survey.

SETTING

United States, 2015-2019.

MAIN OUTCOME MEASURES

We compared the partial life expectancies (PLEs) between age 30 and 90 years of all subpopulations. We also developed a scoring system to identify subgroups at high risk of mortality.

RESULTS

There is an 18.0-year difference between the subpopulations with the lowest and highest PLE. Differences in PLE between subpopulations are not significant in most pairwise comparisons. We visually illustrate how the PLE changes across social determinants of health. There is a complex interaction among social determinants of health, with no single determinant fully explaining the observed variation in lifespan. The proposed scoring system adds clarification to this interaction by yielding a single score that can be used to identify subgroups that might be at high risk of mortality. A similar scoring system by cause of death was also created to identify which subgroups could be considered at high risk of mortality from specific causes. Even if subgroups have similar mortality levels, they are often subject to different cause-specific mortality risks.

CONCLUSIONS

Having one characteristic associated with higher mortality is often not sufficient to be considered at high risk of mortality, but the risk increases with the number of such characteristics. Reducing inequalities is vital for societies, and better identifying individuals and subgroups at high risk of mortality is necessary for public health policy.

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.

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

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

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.

Trends in Life Expectancy in Residential Long-Term Care by Sociodemographic Position in 1999-2018: A Multistate Life Table Study of Finnish Older Adults

OBJECTIVES

Residential long-term care (LTC) use has declined in many countries over the past years. This study quantifies how changing rates of entry, exit, and mortality have contributed to trends in life expectancy in LTC (i.e., average time spent in LTC after age 65) across sociodemographic groups.

METHODS

We analyzed population-register data of all Finns aged ≥65 during 1999-2018 (n = 2,016,987) with dates of LTC and death and sociodemographic characteristics. We estimated transition rates between home, LTC, and death using Poisson generalized additive models, and calculated multistate life tables across 1999-2003, 2004-2008, 2009-2013, and 2014-2018.

RESULTS

Between 1999-2003 and 2004-2008, life expectancy in LTC increased from 0.75 (95% CI: 0.74-0.76) to 0.89 (95% CI: 0.88-0.90) years among men and from 1.61 (95% CI: 1.59-1.62) to 1.83 (95% CI: 1.81-1.85) years among women, mainly due to declining exit rates from LTC. Thereafter, life expectancy in LTC decreased, reaching 0.80 (95% CI: 0.79-0.81) and 1.51 (95% CI: 1.50-1.53) years among men and women, respectively, in 2014-2018. Especially among women and nonmarried men, the decline was largely due to increasing death rates in LTC. Admission rates declined throughout the study period, which offset the increase in life expectancy in LTC attributable to declining mortality in the community. Marital status differences in life expectancy in LTC narrowed over time.

DISCUSSION

Recent declines in LTC use were driven by postponed LTC admission closer to death. The results suggest that across sociodemographic strata older adults enter LTC in even worse health and spend a shorter time in care than before.

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.

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.

Trends and structural factors affecting health equity in the United States at the local level, 1990-2019

Health equity is fundamental to improving the health of populations, but in recent decades progress towards this goal has been mixed. To better support this mission, a deeper understanding of the local heterogeneity within population-level health equity is vital. This analysis presents trends in average health and health equity in the United States at the local level from 1990 to 2019 using three different health outcomes: mortality, self-reported health status, and healthy days. Furthermore, it examines the association between these measures of average health and health equity with several structural factors. Results indicate growing levels of geographic inequality disproportionately impacting less urbanized parts of the country, with rural counties experiencing the largest declines in health equity, followed by Medium and Small Metropolitan counties. Additionally, lower levels of health equity are associated with poorer local socioeconomic context, including several measures that are proxies for structural racism. Altogether, these findings strongly suggest social and economic factors play a pivotal role in explaining growing levels of geographic health inequality in the United States. Policymakers invested in improving health equity must adopt holistic and upstream approaches to improve and equalize economic opportunity as a means of fostering health equity.

Life expectancy in relation to societal development level: significant discordant factors

OBJECTIVES

The aim of this study is to determine the interdependence between life expectancy and numerous social indicators, i.e., to determine the factors that encourage an increase or decrease in life expectancy.

METHODS

Pearson coefficients as well as linear and logarithmic trends and correlations between the dependent variable of life expectancy and numerous independent variables were calculated and analysed. The calculations were carried out for all countries in the world for which data is available. Based on the strength of the correlations between life expectancy and numerous indicators, we have tried to determine the reasons for the different values of life expectancy in the various countries.

RESULTS

Important factors for achieving high life expectancy values are economic development and healthcare spending but the spread of "diseases of the modern era", such as obesity or diabetes, have a significant negative impact on life expectancy. Other important limiting factors for life expectancy are large income inequalities, a higher share of private healthcare expenditure in total healthcare expenditure and lower total healthcare expenditure. Less developed societies can significantly increase their life expectancy by providing clean water and safe sanitation and by combating various infectious diseases (especially HIV).

CONCLUSIONS

Life expectancy is a meaningful indicator of the state of social development and accurately reflects the general state of a particular society. It has been shown that GDP per capita (PPP) is a key determinant of life expectancy, while other important factors play the role of a further modifier.

Forecasting Inequalities in Survival to Retirement Age by Socioeconomic Status in Denmark and Sweden

In Denmark and Sweden, statutory retirement age is indexed to life expectancy to account for mortality improvements in their populations. However, mortality improvements have not been uniform across different sub-populations. Notably, in both countries, individuals of lower socioeconomic status (SES) have experienced slower mortality improvements. As a result, a uniform rise in the statutory retirement age could disproportionally affect these low-SES groups and may unintentionally lead to a reverse redistribution effect, shifting benefits from short-lived low-SES individuals to long-lived high-SES individuals. The aim of this study is twofold: to quantify and contextualise mortality inequalities by SES in Denmark and Sweden, and to assess how indexing retirement age will affect future survival to retirement age by SES in these countries. We used Danish and Swedish registry data (1988-2019), to aggregate individuals aged 50 + based on their demographic characteristics and SES. We computed period life tables by year, sex, and SES to estimate the difference in survival across different SES groups. We then forecast mortality across SES groups to assess how indexing retirement age will affect survival inequalities to retirement age, using two forecasting models-the Mode model and the Li-Lee model. Mortality inequalities are comparable in Denmark and Sweden, even though the latter generally has higher survival. We also find that indexing retirement age to life expectancy will have two main consequences: it will reduce the probability of reaching retirement for all SES groups, particularly those of low SES, and time spent in retirement will be reduced, particularly for those of high SES.

A modal age at death approach to forecasting adult mortality

Recent studies have shown that there are some advantages to forecasting mortality with indicators other than age-specific death rates. The mean, median, and modal ages at death can be directly estimated from the age-at-death distribution, as can information on lifespan variation. The modal age at death has been increasing linearly since the second half of the twentieth century, providing a strong basis from which to extrapolate past trends. The aim of this paper is to develop a forecasting model that is based on the regularity of the modal age at death and that can also account for changes in lifespan variation. We forecast mortality at ages 40 and above in 10 West European countries. The model we introduce increases forecast accuracy compared with other forecasting models and provides consistent trends in life expectancy and lifespan variation at age 40 over time.

Mortality variability and differentials by age and causes of death in rural South Africa, 1994-2018

INTRODUCTION

Understanding mortality variability by age and cause is critical to identifying intervention and prevention actions to support disadvantaged populations. We assessed mortality changes in two rural South African populations over 25 years covering pre-AIDS and peak AIDS epidemic and subsequent antiretroviral therapy (ART) availability.

METHODS

Using population surveillance data from the Agincourt Health and Socio-Demographic Surveillance System (AHDSS; 1994-2018) and Africa Health Research Institute (AHRI; 2000-2018) for 5-year periods, we calculated life expectancy from birth to age 85, mortality age distributions and variation, and life-years lost (LYL) decomposed into four cause-of-death groups.

RESULTS

The AIDS epidemic shifted the age-at-death distribution to younger ages and increased LYL. For AHDSS, between 1994-1998 and 1999-2003 LYL increased for females from 13.6 years (95% CI 12.7 to 14.4) to 22.1 (95% CI 21.2 to 23.0) and for males from 19.9 (95% CI 18.8 to 20.8) to 27.1 (95% CI 26.2 to 28.0). AHRI LYL in 2000-2003 was extremely high (females=40.7 years (95% CI 39.8 to 41.5), males=44.8 years (95% CI 44.1 to 45.5)). Subsequent widespread ART availability reduced LYL (2014-2018) for women (AHDSS=15.7 (95% CI 15.0 to 16.3); AHRI=22.4 (95% CI 21.7 to 23.1)) and men (AHDSS=21.2 (95% CI 20.5 to 22.0); AHRI=27.4 (95% CI 26.7 to 28.2)), primarily due to reduced HIV/AIDS/TB deaths in mid-life and other communicable disease deaths in children. External causes increased as a proportion of LYL for men (2014-2018: AHRI=25%, AHDSS=17%). The share of AHDSS LYL 2014-2018 due to non-communicable diseases exceeded pre-HIV levels: females=43%; males=40%.

CONCLUSIONS

Our findings highlight shifting burdens in cause-specific LYL and persistent mortality differentials in two populations experiencing complex epidemiological transitions. Results show high contributions of child deaths to LYL at the height of the AIDS epidemic. Reductions in LYL were primarily driven by lowered HIV/AIDS/TB and other communicable disease mortality during the ART periods. LYL differentials persist despite widespread ART availability, highlighting the contributions of other communicable diseases in children, HIV/AIDS/TB and external causes in mid-life and non-communicable diseases in older ages.

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.

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.

Contribution of causes of death to changing inequalities in life expectancy by income in Finland, 1997-2020

BACKGROUND

Socioeconomic inequalities in mortality originate from different causes of death. Alcohol-related and smoking-related deaths are major drivers of mortality inequalities across Europe. In Finland, the turn from widening to narrowing mortality disparities by income in the early 2010s was largely attributable to these causes of death. However, little is known about recent inequalities in life expectancy (LE) and lifespan variation.

METHODS

We used individual-level total population register-based data with annual information on disposable household income and cause-specific mortality for ages 30-95+, and assessed the contribution of smoking on mortality using the Preston-Glei-Wilmoth method. We calculated trends in LE at age 30 and SD in lifespan by income quintile in 1997-2020 and conducted age and cause-of-death decompositions of changes in LE.

RESULTS

Disparity in LE and lifespan variation by income increased in 2015-2020, largely attributable to the stagnation of both measures in the lowest income quintile. The LE gap between the extreme quintiles in 2018-2020 was 11.2 (men) and 5.9 (women) years, of which roughly 40% was attributable to alcohol and smoking. However, the recent widening of the gap and the stagnation in LE in the lowest quintile over time were not driven by any specific cause-of-death group.

CONCLUSIONS

After a decade of narrowing inequalities in LE and lifespan variation in Finland, the gaps between income groups are growing again. Increasing LE disparity and stagnating mortality on the lowest income levels are no longer attributable to smoking and alcohol-related deaths but are more comprehensive, originating from most cause-of-death groups.

On the measurement of cause of death inequality

BACKGROUND

Attempts at assessing heterogeneity in countries' mortality profiles often rely on measures of cause of death (CoD) diversity. Unfortunately, such indicators fail to take into consideration the degree of (dis)similarity among pairs of causes (e.g. 'transport injuries' and 'unintentional injuries' are implicitly assumed to be as dissimilar as 'transport injuries' and 'Alzheimer's disease')－an unrealistic and unduly restrictive assumption.

DEVELOPMENT

We extend diversity indicators proposing a broader class of heterogeneity measures that are sensitive to the similarity between the causes of death one works with. The so-called 'CoD inequality' measures are defined as the average expected 'dissimilarity between any two causes of death'. A strength of the approach is that such measures are decomposable, so that users can assess the contribution of each cause to overall CoD heterogeneity levels-a useful property for the evaluation of public health policies.

APPLICATION

We have applied the method to 15 low-mortality countries between 1990 and 2019, using data from the Global Burden of Disease project. CoD inequality and CoD diversity generally increase over time across countries and sex, but with some exceptions. In several cases (notably, Finland), both indicators run in opposite directions.

CONCLUSIONS

CoD inequality and diversity indicators capture complementary information about the heterogeneity of mortality profiles, so they should be analysed alongside other population health metrics, such as life expectancy and lifespan inequality.

Convergence and divergence in mortality: A global study from 1990 to 2030

An empirical question that has motivated demographers is whether there is convergence or divergence in mortality/longevity around the world. The epidemiological transition is the starting point for studying a global process of mortality convergence. This manuscript aims to provide an update on the concept of mortality convergence/divergence. We perform a comprehensive examination of nine different mortality indicators from a global perspective using clustering methods in the period 1990-2030. In addition, we include analyses of projections to provide insights into prospective trajectories of convergence clubs, a dimension unexplored in previous work. The results indicate that mortality convergence clubs of 194 countries by sex resemble the configuration of continents. These five clubs show a common steady upward trend in longevity indicators, accompanied by a progressive reduction in disparities between sexes and between groups of countries. Furthermore, this paper shows insights into the historical evolution of the convergence clubs in the period 1990-2020 and expands their scope to include projections of their expected future evolution in 2030.

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.

Social security cuts and life expectancy: a longitudinal analysis of local authorities in England, Scotland and Wales

BACKGROUND

The UK Government's 'welfare reform' programme included reductions to social security payments, phased in over the financial years 2011/2012-2015/2016. Previous studies of social security cuts and health outcomes have been restricted to analysing single UK countries or single payment types (eg, housing benefit). We examined the association between all social security cuts fully implemented by 2016 and life expectancy, for local authorities in England, Scotland and Wales.

METHODS

Our unit of analysis was 201 upper tier local authorities (unitary authorities and county councils: 147 in England, 32 in Scotland, 22 in Wales). Our exposure was estimated social security loss per head of the working age population per year for each local authority, calculated against the baseline in 2010/2011. The primary outcome was annual life expectancy at birth between the calendar years 2012 and 2016 (year lagged following exposure). We used a panel regression approach with fixed effects.

RESULTS

Social security cuts implemented by 2016 were estimated to be £475 per head of the working age population in England, £390 in Scotland and £490 in Wales since 2010/2011. During the study period, there was either no improvement or only marginal increases in national life expectancy. Social security loss and life expectancy were significantly associated: an estimated £100 decrease in social security per head of working age population was associated with a 1-month reduction in life expectancy.

CONCLUSIONS

Social security cuts, at the UK local authority level, were associated with lower life expectancy. Further research should examine causality.

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.

Impact of COVID-19 on subnational variations in life expectancy and life disparity at birth in India: evidence from NFHS and SRS data

BACKGROUND

Measuring life expectancy and life disparity can assist in comprehending how the COVID-19 pandemic has affected the mortality estimates in the Indian population. The present study aims to study the life expectancy and life disparity at birth at the national and subnational levels before and during the COVID-19 pandemic using the NFHS and SRS data.

METHODS

The measures Life expectancy at birth ([Formula: see text]) and Life disparity at birth ([Formula: see text]) were computed for the non-pandemic and pandemic years from NFHS (2015-16), SRS (2015) and NFHS (2019-21), SRS (2020) respectively at the national and Subnational level in India. Using NFHS data for the 36 states and SRS data for the 22 states, the study calculates [Formula: see text] and [Formula: see text] by total, male and female population.

RESULTS

The [Formula: see text] for male and female decline from 64.3 years and 69.2 years in 2015-16 to 62.9 years and 68.9 years in 2019-21. The [Formula: see text] shows a drop of approximately 1.4 years for males and 0.3 years for females in the pandemic year 2019-21 when compared to the non-pandemic year 2015-16. At the subnational level [Formula: see text] shows a decline for 22 states in person, 23 states in males and 21 states in females in the pandemic year 2019-21 as compared to the non-pandemic years 2015-16. The [Formula: see text] shows a increase for 21 states in person, 24 states in females and 17 states in males in the pandemic year than non-pandemic year. The findings shows a significant losses in [Formula: see text] and gains in [Formula: see text] for males than females in the pandemic year as compared to the non-pandemic year at the subnational level in India.

CONCLUSIONS

COVID-19 pandemic has decreased [Formula: see text] and increased [Formula: see text] in the pandemic year 2019-21 at the national and subnational level in India. COVID-19 had a significant impact on the age pattern of mortality for many states and male, female population and delayed the mortality transition in India.

Age and cause-of-death contributions to educational inequalities in life expectancy and lifespan variation in a low-mortality country: A cross-sectional study of 1.67 million deaths in Spain (2016-19)

BACKGROUND

We aim to assess the age- and cause-specific contributions to differences in life expectancy and lifespan variation between the high- and low-educated groups in Spain.

METHODS

We use sex-, age-, education- and cause-specific mortality and population data for individuals aged 30 and over for 2016-19 in Spain. We estimated life expectancies, and standard deviations of the age-at-death distribution (lifespan variation), and we disentangled the contribution of age-causes of death to educational differences in both indicators.

FINDINGS

Life expectancy at age 30 was higher for high-educated groups compared to low-educated groups, 5.5 years for males and 3.0 years for females. Lifespan variation was higher for low-educated groups compared to high-educated groups, 2.9 years for males and 2.2 years for females. The main contributors to the life expectancy gaps in males were lung cancer (0.58 years) and ischaemic heart diseases (0.42 years), and in females were other cardiovascular causes (0.26 years), and ischaemic heart diseases (0.22 years). The main contributors to the lifespan variation gaps were in males lung cancer (-0.25 years) and ischaemic heart diseases (-0.22 years), while in females were other neoplasms and other diseases of the nervous system.

INTERPRETATION

Whereas behavioural causes are more important in explaining educational inequalities in mortality among men, ageing-related causes of death seem more important among women. Attempts at narrowing socioeconomic gaps in mortality may benefit from applying gender-specific preventive policy measures.

Lifespan variation among people with a given disease or condition

In addition to fundamental mortality metrics such as mortality rates and mortality rate ratios, life expectancy is also commonly used to investigate excess mortality among a group of individuals diagnosed with specific diseases or conditions. However, as an average measure, life expectancy ignores the heterogeneity in lifespan. Interestingly, the variation in lifespan-a measure commonly used in the field of demography-has not been estimated for people with a specific condition. Based on recent advances in methodology in research within epidemiology and demography, we discuss two metrics, namely, the average life disparity and average lifetable entropy after diagnosis, which estimate the variation in lifespan for time-varying conditions in both absolute and relative aspects. These metrics are further decomposed into early and late components, separated by their threshold ages. We use mortality data for women with mental disorders from Danish registers to design a population-based study and measure such metrics. Compared with women from the general population, women with a mental disorder had a shorter average remaining life expectancy after diagnosis (37.6 years vs. 44.9 years). In addition, women with mental disorders also experienced a larger average lifespan variation, illustrated by larger average life disparity (9.5 years vs 9.1 years) and larger average lifetable entropy (0.33 vs 0.27). More specifically, we found that women with a mental disorder had a larger early average life disparity but a smaller late average life disparity. Unlike the average life disparity, both early and late average lifetable entropy were higher for women with mental disorders compared to the general population. In conclusion, the metric proposed in our study complements the current research focusing merely on life expectancy and further provides a new perspective into the assessment of people's health associated with time-varying conditions.

Mechanisms of equality and inequality in mammalian societies

The extent of (in)equality is highly diverse across species of social mammals, but we have a poor understanding of the factors that produce or inhibit equitable social organizations. Here, we adopt a comparative evolutionary perspective to test whether the evolution of social dominance hierarchies, a measure of social inequality in animals, exhibits phylogenetic conservatism and whether interspecific variation in these traits can be explained by sex, age or captivity. We find that hierarchy steepness and directional consistency evolve rapidly without any apparent constraint from evolutionary history. Given this extraordinary variability, we next consider multiple factors that have evolved to mitigate social inequality. Social networks, coalitionary support and knowledge transfer advantage to privilege some individuals over others. Nutritional access and prenatal stressors can impact the development of offspring, generating health disparities with intergenerational consequences. Intergenerational transfer of material resources (e.g. stone tools, food stashes, territories) advantage those who receive. Nonetheless, many of the same social species that experience unequal access to food (survival) and mates (reproduction) engage in levelling mechanisms such as food sharing, adoption, revolutionary coalitions, forgiveness and inequity aversion. Taken together, mammals rely upon a suite of mechanisms of (in)equality to balance the costs and benefits of group living. This article is part of the theme issue 'Evolutionary ecology of inequality'.

Contributions of avoidable mortality to the sex gap in life expectancy and life disparity in Iran

BACKGROUND

Public health policies and healthcare quality play a pivotal role on the health outcome level and disparities across sociodemographic groups. However, there is little evidence on their role on disparities in life expectancy (LE) and life disparity (LD) in low and middle income countries. The present study aimed to assess the contributions of avoidable mortality, as a measure of inter-sectoral public health policies and healthcare quality, into the sex gap in LE (SGLE) and LD (SGLD) in Iran.

METHODS

Latest available data of death causes, according to the ICD codes, for Iran was obtained from the WHO mortality database for the period 2015-2016. An upper age limit of 75 years was applied to define avoidable causes of death. LD was measured as the average years of life lost at birth. The SGLE and SGLD (both females minus males) were decomposed by age and cause of death using a continuous-change model.

RESULTS

Females, on average, outlived males for 3.8 years (80.0 vs. 76.2 years) with 1.9 lower life years lost (12.6 vs. 14.4 years). Avoidable causes accounted for 2.5 (67%) and 1.5 (79%) years of the SGLE and SGLD, respectively. Among avoidable causes, injury-related deaths followed by ischaemic heart disease had the greatest contributions to both SGLE and SGLD. Across age groups, the age groups 55-59 and 60-64 accounted for the greatest contributions of avoidable causes to SGLE (0.3 years each), while age groups 20-24 and 55-59 had the greatest contributions to SGLD (0.15 years each). Lower mortality rates for females than males in age groups 50-74 years accounted for about half of the SGLE, while age groups 20-29 and 50-64 years accounted for around half of SGLD.

CONCLUSION

More than two third of the SGLE and SGLD in Iran were attributed to the avoidable mortality, particularly preventable causes. Our results suggest the need for public health policies targeting injuries in young males as well as lifestyle risk factors including smoking in middle aged males in Iran.

Measuring the shape of mortality across animals and plants: Alternatives to H entropy metrics reveal hidden type IV survivorship curves and associations with parental care at macro-ecological scales

The shape of mortality, or how mortality is spread across an organism's life course, is fundamental to a range of biological processes, with attempts to quantify it rooted in ecology, evolution, and demography. One approach to quantify the distribution of mortality over an organism's life is the use of entropy metrics whose values are interpreted within the classical framework of survivorship curves ranging from type I distributions, with mortality concentrated in late life stages, to type III survivorship curves associated with high early stage mortality. However, entropy metrics were originally developed using restricted taxonomic groups and the behavior of entropy metrics over larger scales of variation may make them unsuitable for wider-ranging contemporary comparative studies. Here, we revisit the classic survivorship framework and, using a combination of simulations and comparative analysis of demography data spanning the animal and plant kingdoms, we show that commonly used entropy metrics cannot distinguish between the most extreme survivorship curves, which in turn can mask important macroecological patterns. We show how using H entropy masks a macroecological pattern of how parental care is associated with type I and type II species and for macroecological studies recommend the use of metrics, such as measures of area under the curve. Using frameworks and metrics that capture the full range of variation of survivorship curves will aid in our understanding of the links between the shape of mortality, population dynamics, and life history traits.

US Racial-Ethnic Mortality Gap Adjusted for Population Structure

BACKGROUND

US racial-ethnic mortality disparities are well documented and central to debates on social inequalities in health. Standard measures, such as life expectancy or years of life lost, are based on synthetic populations and do not account for the real underlying populations experiencing the inequalities.

METHODS

We analyze US mortality disparities comparing Asian Americans, Blacks, Hispanics, and Native Americans/Alaska Natives to Whites using 2019 CDC and NCHS data, using a novel approach that estimates the mortality gap, adjusted for population structure by accounting for real-population exposures. This measure is tailored for analyses where age structures are fundamental, not merely a confounder. We highlight the magnitude of inequalities by comparing the population structure-adjusted mortality gap against standard metrics' estimates of loss of life due to leading causes.

RESULTS

Based on the population structure-adjusted mortality gap, Black and Native American mortality disadvantage exceedsmortality from circulatory diseases. The disadvantage is 72% among Blacks (men: 47%, women: 98%) and 65% among Native Americans (men: 45%, women: 92%), larger than life expectancy measured disadvantage. In contrast, estimated advantages for Asian Americans are over three times (men: 176%, women: 283%) and, for Hispanics, two times (men: 123%; women: 190%) larger than those based on life expectancy.

CONCLUSIONS

Mortality inequalities based on standard metrics' synthetic populations can differ markedly from estimates of the population structure-adjusted mortality gap. We demonstrate that standard metrics underestimate racial-ethnic disparities through disregarding actual population age structures. Exposure-corrected measures of inequality may better inform health policies around allocation of scarce resources.

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.

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.

State-Level Trends in Lifespan Variability in the United States, 1960-2019: A Research Note

State-level disparities in life expectancy are wide, persistent, and potentially growing in the United States. However, the extent to which differences in lifespan variability by state have changed over time is unclear. This research note describes trends in lifespan variability for the United States overall and by state from 1960 to 2019 using period life table data from the United States Mortality Database. Lifespan disparity at birth (e0†) decreased over time in the United States overall from 14.0 years in 1960-1964 to 12.2 in 2015-2019. Lifespan variability decreased in all states, but states differed in the level and pace with which these changes occurred. Southern states and the District of Columbia exhibited consistently higher (i.e., less equitable) levels of lifespan variability than the nation overall. Conversely, lifespan variability was lower among several states in the Northeast (e.g., Connecticut and Massachusetts), Upper Midwest (e.g., Iowa, Minnesota, and Wisconsin), and West (e.g., California, Oregon, Utah, and Washington). We observe a particularly worrisome trend of increasing lifespan variability for the United States overall and for most states from 2010-2014 to 2015-2019. Monitoring state-level trends in lifespan variability has the potential to inform policies designed to ameliorate population health disparities.

The contributions of injury deaths to the gender gap in life expectancy and life disparity in Eastern Mediterranean Region

BACKGROUND

Injury deaths constitute a major avoidable cause of death affecting life expectancy to a different degree in men and women. This study quantified the contributions of injury deaths to the gender gap in life expectancy (GGLE) and life disparity (GGLD) in nine Eastern Mediterranean Region (EMR) countries.

METHODS

We retrieved annual data on age-sex specific causes of death from the World Health Organization mortality database for EMR countries with at least 2-year consecutive data during 2010-2019. The injury-related deaths were categorized into five groups: transport accidents, other accidental injuries, intentional self-harm, assault and events of undetermined intent. Considering women as the reference, the GGLE and GGLD were decomposed by age and causes of death, using a continuous-change model.

RESULTS

The largest and smallest GGLE were observed in Kuwait (5.2 years) and Qatar (- 1.2 years), respectively. Qatar (- 2.2 years) and Oman (0.2 years) had the highest and lowest GGLD. The highest contributions of injury deaths to the GGLE/GGLD were seen in Libya (1.8/- 1.2 years), followed by Iran (1.2/- 0.8 years). Among injury causes, transport accidents were the leading cause of GGLE in all countries but Libya and Morocco, with Iran having the greatest contributions (0.6 years). Injury deaths in men aged 15-29 years accounted for 33% [41%] (Kuwait) to 55% [65%] (Oman) of total GGLE [GGLD] attributable to injury deaths.

CONCLUSIONS

High injury deaths, particularly transport accidents, among young men contributed substantially to the GGLE and GGLD across nine EMR countries in this study. This highlights the need for implementing preventing policies to reduce the burden of injury deaths specifically in young men.

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

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

Mortality Advantage Reversed: The Causes of Death Driving All-Cause Mortality Differentials Between Immigrants, the Descendants of Immigrants and Ancestral Natives in Sweden, 1997-2016

A small but growing body of studies have documented the alarming mortality situation of adult descendants of migrants in a number of European countries. Nearly all of them have focused on all-cause mortality to reveal these important health inequalities. This paper takes advantage of the Swedish population registers to study all-cause and cause-specific mortality among men and women aged 15-44 in Sweden from 1997 to 2016 to a level of granularity unparalleled elsewhere. It adopts a multi-generation, multi-origin and multi-cause-of-death approach. Using extended, competing-risks survival models, it aims to show (1) how the all-cause mortality of immigrants arriving as adults (the G1), immigrants arriving as children (the G1.5) and children of immigrants born in Sweden to at least one immigrant parent (the G2) differs versus ancestral Swedes and (2) what causes-of-deaths drive these differentials. For all-cause mortality, most G1 (not Finns or Sub-Saharan Africans) have a mortality advantage. This contrasts with a near systematic reversal in the mortality of the G1.5 and G2 (notably among men), which is driven by excess accident and injury, suicide, substance use and other external cause mortality. Given that external causes-of-death are preventable and avoidable, the findings raise questions about integration processes, the levels of inequality immigrant populations are exposed to in Sweden and ultimately, whether the legacy of immigration has been positive. Strengths of the study include the use of quality data and advanced methods, the granularity of the estimates, and the provision of evidence that highlights the precarious mortality situation of the seldom-studied G1.5.

Drewnowski's index to measure lifespan variation: Revisiting the Gini coefficient of the life table

The Gini coefficient of the life table is a concentration index that provides information on lifespan variation. Originally proposed by economists to measure income and wealth inequalities, it has been widely used in population studies to investigate variation in ages at death. We focus on the complement of the Gini coefficient, Drewnowski's index, which is a measure of equality. We study its mathematical properties and analyze how changes over time relate to changes in life expectancy. Further, we identify the threshold age below which mortality improvements are translated into decreasing lifespan variation and above which these improvements translate into increasing lifespan inequality. We illustrate our theoretical findings simulating scenarios of mortality improvement in the Gompertz model, and showing an example of application to Swedish life table data. Our experiments demonstrate how Drewnowski's index can serve as an indicator of the shape of mortality patterns. These properties, along with our analytical findings, support studying lifespan variation alongside life expectancy trends in multiple species.

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.

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.

Significant impacts of the COVID-19 pandemic on race/ethnic differences in US mortality

The coronavirus 2019 (COVID-19) pandemic triggered global declines in life expectancy. The United States was hit particularly hard among high-income countries. Early data from the United States showed that these losses varied greatly by race/ethnicity in 2020, with Hispanic and Black Americans suffering much larger losses in life expectancy compared with White people. We add to this research by examining trends in lifespan inequality, average years of life lost, and the contribution of specific causes of death and ages to race/ethnic life-expectancy disparities in the United States from 2010 to 2020. We find that life expectancy in 2020 fell more for Hispanic and Black males (4.5 and 3.6 y, respectively) compared with White males (1.5 y). These drops nearly eliminated the previous life-expectancy advantage for the Hispanic compared with the White population, while dramatically increasing the already large gap in life expectancy between Black and White people. While the drops in life expectancy for the Hispanic population were largely attributable to official COVID-19 deaths, Black Americans saw increases in cardiovascular diseases and "deaths of despair" over this period. In 2020, lifespan inequality increased slightly for Hispanic and White populations but decreased for Black people, reflecting the younger age pattern of COVID-19 deaths for Hispanic people. Overall, the mortality burden of the COVID-19 pandemic hit race/ethnic minorities particularly hard in the United States, underscoring the importance of the social determinants of health during a public health crisis.

Probability of males to outlive females: an international comparison from 1751 to 2020

OBJECTIVE

To measure sex differences in lifespan based on the probability of males to outlive females.

DESIGN

International comparison of national and regional sex-specific life tables from the Human Mortality Database and the World Population Prospects.

SETTING

199 populations spanning all continents, between 1751 and 2020.

PRIMARY OUTCOME MEASURE

We used the outsurvival statistic ( φ ) to measure inequality in lifespan between sexes, which is interpreted here as the probability of males to outlive females.

RESULTS

In random pairs of one male and one female at age 0, the probability of the male outliving the female varies between 25% and 50% for life tables in almost all years since 1751 and across almost all populations. We show that φ is negatively correlated with sex differences in life expectancy and positively correlated with the level of lifespan variation. The important reduction of lifespan inequality observed in recent years has made it less likely for a male to outlive a female.

CONCLUSIONS

Although male life expectancy is generally lower than female life expectancy, and male death rates are usually higher at all ages, males have a substantial chance of outliving females. These findings challenge the general impression that 'men do not live as long as women' and reveal a more nuanced inequality in lifespans between females and males.

The gap in life expectancy and lifespan inequality between Iran and neighbour countries: the contributions of avoidable causes of death

Background

Healthcare system and intersectoral public health policies play a crucial role in improving population health and reducing health inequalities. This study aimed to quantify their impact, operationalized as avoidable deaths, on the gap in life expectancy (LE) and lifespan inequality (LI) between Iran and three neighbour countries viz., Turkey, Qatar, and Kuwait in 2015–2016.

Methods

Annual data on population and causes of deaths by age and sex for Iran and three neighbour countries were obtained from the World Health Organization mortality database for the period 2015–2016. A recently developed list by the OECD/Eurostat was used to identify avoidable causes of death (with an upper age limit of 75). The cross-country gaps in LE and LI (measured by standard deviation) were decomposed by age and cause of death using a continuous-change model.

Results

Iranian males and females had the second lowest and lowest LE, respectively, compared with their counterparts in the neighbour countries. On the other hand, the highest LIs in both sexes (by 2.3 to 4.5 years in males and 1.1 to 3.3 years in females) were observed in Iran. Avoidable causes contributed substantially to the LE and LI gap in both sexes with injuries and maternal/infant mortality represented the greatest contributions to the disadvantages in Iranian males and females, respectively.

Conclusions

Higher mortality rates in young Iranians led to a double burden of inequality –shorter LE and greater uncertainty at timing of death. Strengthening intersectoral public health policies and healthcare quality targeted at averting premature deaths, especially from injuries among younger people, can mitigate this double burden.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-022-01683-8.

Why we should monitor disparities in old-age mortality with the modal age at death

Indicators based a fixed “old” age threshold have been widely used for assessing socioeconomic disparities in mortality at older ages. Interpretation of long-term trends and determinants of these indicators is challenging because mortality above a fixed age that in the past would have reflected old age deaths is today mixing premature and old-age mortality. We propose the modal (i.e., most frequent) age at death, M, an indicator increasingly recognized in aging research, but which has been infrequently used for monitoring mortality disparities at older ages. We use mortality and population exposure data by occupational class over the 1971-2017 period from Finnish register data. The modal age and life expectancy indicators are estimated from mortality rates smoothed with penalized B-splines. Over the 1971-2017 period, occupational class disparities in life expectancy at 65 and 75 widened while disparities in M remained relatively stable. The proportion of the group surviving to the modal age was constant across time and occupational class. In contrast, the proportion surviving to age 65 and 75 has roughly doubled since 1971 and showed strong occupational class differences. Increasing socioeconomic disparities in mortality based on fixed old age thresholds may be a feature of changing selection dynamics in a context of overall declining mortality. Unlike life expectancy at a selected fixed old age, M compares individuals with similar survival chances over time and across occupational classes. This property makes trends and differentials in M easier to interpret in countries where old-age survival has improved significantly.

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.

Linking Pensions to Life Expectancy: Tackling Conceptual Uncertainty through Bayesian Model Averaging

Linking pensions to longevity developments at retirement age has been one of the most common policy responses of pension schemes to aging populations. The introduction of automatic stabilizers is primarily motivated by cost containment objectives, but there are other dimensions of welfare restructuring in the politics of pension reforms, including recalibration, rationalization, and blame avoidance for unpopular policies that involve retrenchments. This paper examines the policy designs and implications of linking entry pensions to life expectancy developments through sustainability factors or life expectancy coefficients in Finland, Portugal, and Spain. To address conceptual and specification uncertainty in policymaking, we propose and apply a Bayesian model averaging approach to stochastic mortality modeling and life expectancy computation. The results show that: (i) sustainability factors will generate substantial pension entitlement reductions in the three countries analyzed; (ii) the magnitude of the pension losses depends on the factor design; (iii) to offset pension cuts and safeguard pension adequacy, individuals will have to prolong their working lives significantly; (iv) factor designs considering cohort longevity markers would have generated higher pension cuts in countries with increasing life expectancy gap.

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.

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.

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.