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

Increased homicide played a key role in driving Black-White disparities in life expectancy among men during the COVID-19 pandemic

Disparities in life expectancy between Black and White Americans increased substantially during the COVID-19 pandemic. During the same period, the US experienced the largest increase in homicide on record. Yet, little research has examined the contribution of homicide to Black-White disparities in longevity in recent years. Using mortality data and population estimates, we conduct a comprehensive decomposition of the drivers of Black-White inequality in life expectancy and lifespan variability between 2019 and 2021 among men. We find that homicide is one of the principal reasons why lifespans have become shorter for Black men than White men in recent years. In 2020 and 2021, homicide was the leading contributor to inequality in both life expectancy and lifespan variability between Black and White men, accounting for far more of the racial gap in longevity and variability than deaths from COVID-19. Addressing homicides should be at the forefront of any public health discussion aimed at promoting racial health equity.

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.

Black and white differences in subjective survival expectations: An evaluation of competing mechanisms

While black-white inequality in longevity is well documented in the United States, little is known about how individuals from different race/ethnic groups form their own personal survival expectations. Prior research has found that despite having higher mortality, blacks on average report higher survival expectations relative to whites. Using data from the Health and Retirement Study, we examined racial differences in subjective survival expectations across birth cohorts and provide explanatory mechanisms. We find that blacks-men in particular-were overly optimistic about their survival, but this effect had waned with successive birth cohorts. Furthermore, whereas subjective survival expectations and actual survival were correlated among white men, among black men the most optimistic fared worst. Blacks and whites differed not only in their response patterns, but also in how they weighed the different factors (socioeconomic, psychosocial, health, parental longevity) associated with expected survival. Importantly, those who estimated their survival probability with certainty had positive psychosocial characteristics, irrespective of race, but only whites had better health. These findings underscore the importance of group differences in subjective survival expectations as another potential form of inequality. Racial differences in how long individual expect to live may account for differences in social and economic behavior and outcomes, irrespective of actual longevity differentials.

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.

Racial-ethnic inequities in age at death among adults with/without intellectual and developmental disability in the United States

To identify potential differences in racial-ethnic inequities in mortality between adults with/without intellectual and developmental disability, we compared patterns in age at death by race-ethnic status among adults who did/did not have intellectual and developmental disability reported on their death certificate in the United States. Data were from the 2005-2017 U.S. Multiple Cause-of-Death Mortality files. Average age at death by racial-ethnic status was compared between adults, age 18 and older, with/without different types of intellectual and developmental disability reported on their death certificate (N = 32,760,741). A multiple descent pattern was observed among adults without intellectual or developmental disability, with age at death highest among Whites, followed by Asians, Hispanics and Blacks, then American Indians. In contrast, a bifurcated pattern was observed among adults with intellectual disability, with age at death highest among Whites, but lower and similar among all racial-ethnic minority groups. The severity of racial-ethnic inequities in age at death was most pronounced among adults with cerebral palsy. Policy makers and public health experts should be aware that racial-ethnic inequities are different for adults with intellectual and developmental disability - all minorities with intellectual and developmental disability are at greater risk of premature death than their White counterparts.

Mortality disparities between Black and White Americans mediated by income and health behaviors

Background

Race disparities in health outcomes including mortality risk are well known, but mediating mechanisms that link race to mortality risk have rarely been formally tested.

Methods

We analyzed public NHANES III data from 1988 to 1994 linked to mortality outcomes prospectively through 2015. Participants included 10,460 non-Hispanic Black (40.5%, n = 4233) and non-Hispanic White (59.5%, n = 6227) adults. Proportional hazards regression models examined mortality risk in association with race, demographics, income, and an index of risky health behaviors including smoking, poor diet and low physical activity. A mediation approach under the counterfactual framework was used to test effects of income and risky health behaviors as mediators between race and mortality risk.

Results

Considering only race, age and sex, Black participants had significantly higher mortality risk than Whites (HR = 1.46, 95% CI 1.35–1.58). When income and education were added, the race effect was lower but remained significant (HR = 1.15, 95% CI 1.02–1.30). In the subsequent model that also included risky behaviors the association between race and mortality was no longer significant (HR = 1.05, 95% CI 0.92–1.20); both higher income and healthier behaviors contributed to lower mortality risk. There was a significant indirect effect of race on mortality mediated through income, and the direct effect of race on mortality was not significant when the mediating effect of income was considered. Likewise, the risky behavior score significantly mediated the association between race with mortality, and the direct effect of race was not significant. In the separate models, income mediated 62% of the association between race and mortality and lifestyle mediated 61% of the relationship.

Conclusions

Efforts to reduce race-based mortality disparities may focus on policies to reduce income-based disparities and promote positive health behaviors that consider variations in socioeconomic resources and personal preferences.

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Racial mortality disparities are mediated by lower income and poorer health behaviors.

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Direct race effects are not present when formally accounting for mediators.

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Interventions to reduce disparities may focus on income policies and behavior change.

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.

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

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

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.

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

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

The color of death: race, observed skin tone, and all-cause mortality in the United States

Objective: This paper examines how mortality covaries with observed skin tone among blacks and in relation to whites. Additionally, the study analyzes the extent to which social factors such as socioeconomic status affect this relationship. Design: This study uses data from the 1982 General Social Survey (N = 1,689) data linked to the National Death Index until 2008. We use this data to examine the links between race, observed skin tone among blacks, and all-cause mortality. Piecewise exponential hazard modeling was used to estimate disparities in skin tone mortality among blacks, and relative to whites. The multivariate models control for age, education, gender, region, metropolitan statistical area, marital status, labor force status, and household income. Results: Observed skin tone is a significant determinant of mortality among blacks and in relation to whites. Light skinned blacks had the lowest mortality hazards among blacks, while respondents with medium and dark brown skin experienced significantly higher mortality. The observed skin tone mortality disparities covaried with education; there are significant mortality disparities across observed skin tone groups among black respondents with high school or more education, and nonsignificant disparities among those with less education. Conclusion: It is crucial to identify the social processes driving racial disparities in health and mortality. The findings reveal that the nuanced social experiences of blacks with different observed skin tones markedly change the experience of racial inequality. Research on the nuanced social processes and biological mechanisms that connect differences in observed skin tone to mortality outcomes promises to better illuminate the experience of racial inequality and policy mechanisms we can use to undermine it.

Black and White Differences in Life Expectancy in 4 US States, 1969-2013

OBJECTIVES

Racial differences in mortality in the United States have narrowed and vary by time and place. The objectives of our study were to (1) examine the gap in life expectancy between white and black persons (hereinafter, racial gap in life expectancy) in 4 states (California, Georgia, Illinois, and New York) and (2) estimate trends in the contribution of major causes of death (CODs) to the racial gap in life expectancy by age group.

METHODS

We extracted data on the number of deaths and population sizes for 1969-2013 by state, sex, race, age group, and 6 major CODs. We used a Bayesian time-series model to smooth and impute mortality rates and decomposition methods to estimate trends in sex- and age-specific contributions of CODs to the racial gap in life expectancy.

RESULTS

The racial gap in life expectancy at birth decreased in all 4 states, especially among men in New York (from 8.8 to 1.1 years) and women in Georgia (from 8.0 to 1.7 years). Although few deaths occurred among persons aged 1-39, racial differences in mortality at these ages (mostly from injuries and infant mortality) contributed to the racial gap in life expectancy, especially among men in California (1.0 year of the 4.3-year difference in 2013) and Illinois (1.9 years of the 6.7-year difference in 2013). Cardiovascular deaths contributed most to the racial gap in life expectancy for adults aged 40-64, but contributions decreased among women aged 40-64, especially in Georgia (from 2.8 to 0.5 years). The contribution of cancer deaths to inequality increased in California and Illinois, whereas New York had the greatest reductions in inequality attributable to cancer deaths (from 0.6 to 0.2 years among men and from 0.2 to 0 years among women).

CONCLUSIONS

Future research should identify policy innovations and economic changes at the state level to better understand New York's success, which may help other states emulate its performance.

Twin consequences of rising U.S. death rates among young adults: Lower life expectancy and greater lifespan variability

The current study is an original investigation of the U.S. mortality pattern from 2000 to 2017. Previous research has shown that the unusual post-2014 decline in life expectancy is related to the increase in death rates for ages 25-44, mostly due to rising prevalence in drug poisoning and suicide deaths. Our investigation reveals that such increase in younger-age mortality has had an impact not only on life expectancy (or mean age at death), but also, and to a larger extent, on lifespan variability (the dispersion around the mean age at death). Even though lifespan variability is a key component of mortality change, as well as a measure of human well-being, with social, economic, and psychological implications, it has received much less attention than life expectancy has.

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.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Equity and length of lifespan are not the same

Efforts to understand the dramatic declines in mortality over the past century have focused on life expectancy. However, understanding changes in disparity in age of death is important to understanding mechanisms of mortality improvement and devising policy to promote health equity. We derive a novel decomposition of variance in age of death, a measure of inequality, and apply it to cause-specific contributions to the change in variance among the G7 countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) from 1950 to 2010. We find that the causes of death that contributed most to declines in the variance are different from those that contributed most to increase in life expectancy; in particular, they affect mortality at younger ages. We also find that, for two leading causes of death [cancers and cardiovascular disease (CVD)], there are no consistent relationships between changes in life expectancy and variance either within countries over time or between countries. These results show that promoting health at younger ages is critical for health equity and that policies to control cancer and CVD may have differing implications for equity.

Trends in Life Expectancy and Lifespan Variation by Educational Attainment: United States, 1990-2010

The educational gradient in life expectancy is well documented in the United States and in other low-mortality countries. Highly educated Americans, on average, live longer than their low-educated counterparts, who have recently seen declines in adult life expectancy. However, limiting the discussion on lifespan inequality to mean differences alone overlooks other dimensions of inequality and particularly disparities in lifespan variation. The latter represents a unique form of inequality, with higher variation translating into greater uncertainty in the time of death from an individual standpoint, and higher group heterogeneity from a population perspective. Using data from the National Vital Statistics System from 1990 to 2010, this is the first study to document trends in both life expectancy and S25--the standard deviation of age at death above 25--by educational attainment. Among low-educated whites, adult life expectancy declined by 3.1 years for women and by 0.6 years for men. At the same time, S25 increased by about 1.5 years among high school-educated whites of both genders, becoming an increasingly important component of total lifespan inequality. By contrast, college-educated whites benefited from rising life expectancy and record low variation in age at death, consistent with the shifting mortality scenario. Among blacks, adult life expectancy increased, and S25 plateaued or declined in nearly all educational attainment groups, although blacks generally lagged behind whites of the same gender on both measures. Documenting trends in lifespan variation can therefore improve our understanding of lifespan inequality and point to diverging trajectories in adult mortality across socioeconomic strata.

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.