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.

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

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

Decomposition of Differentials in Health Expectancies From Multistate Life Tables: A Research Note.

Multistate modeling is a commonly used method to compute healthy life expectancy. However, there is currently no analytical method to decompose the components of differentials in summary measures calculated from multistate models. In this research note, we propose a derivative-based method to decompose the differentials in population-based health expectancies estimated via a multistate model into two main components: the proportion resulting from differences in initial health structure and the proportion resulting from differences in health transitions. We illustrate the method using data on activities of daily living from the U.S. Health and Retirement Study to decompose the sex differential in disability-free life expectancy (HLE) among older Americans. Our results suggest that the sex gap in HLE results primarily from differences in transition rates between disability states rather than from the initial health distribution of female and male populations. The methods introduced here will enable researchers, including those working in fields other than health, to decompose the relative contribution of initial population structure and transition probabilities to differences in state-specific life expectancies from multistate models.

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.

Effect of the COVID-19 pandemic on life expectancy in Australia, 2020-22.

BACKGROUND: Australia provides a valuable international case study of life expectancy during the pandemic. In contrast to many other countries, it experienced relatively stringent restrictions and low COVID-19 mortality during 2020-21, followed by relaxation of these restrictions when high vaccination rates were achieved. This study measures Australia's life expectancy trends and the contributions of age group and causes of death, during the pandemic. METHODS: Trends in life expectancy at birth in Australia and its states and territories were measured from 2020 to 2022. The contributions of age group and cause of death to these trends were measured using decomposition methods. Life expectancy was compared with other high-income countries. RESULTS: Australia's life expectancy fell by more than half a year in 2022, following a sharp increase in 2020 and moderate decline in 2021. For the 3 years 2020 to 2022, life expectancy was 0.13 years (95% confidence interval 0.07-0.19) higher for males and 0.09 years (0.03-0.14) higher for females versus 2017-19. Australia's life expectancy increase in 2020 was larger than that in the vast majority of other high-income countries, but its decline in 2022 was greater than in other countries whose life expectancy rose in the first year of the pandemic. The small negative contribution of COVID-19 deaths to life expectancy in Australia was more than offset by lower non-communicable disease mortality. There were only small differences in life expectancy change between the states with the most stringent restrictions (Victoria and New South Wales) and the rest of Australia. CONCLUSIONS: Australia's life expectancy trends during 2020-22 were relatively favourable compared with other high-income countries, with the exception of its sharp decline in 2022 once restrictions were loosened.

A comparative study of life-years lost attributable to air particulate matter in Asia-Pacific and European countries.

Air particulate matter (PM) and its harmful effects on human health are of great concern globally due to all-cause and cause-specific mortality impacts across different population groups. While Europe has made significant progress in reducing particulate air pollution-related mortality through innovative technologies and policies, many countries in Asia-Pacific region still rely on high-polluting technologies and have yet to implement effective policies to address this issue, resulting in higher levels of mortality due to air pollution in the region. This study has three aims related to quantifying life-years lost (LYL) attributable to PM, and further separated into ambient PM and household air pollution (HAP): (1) to investigate LYL by causes of death; (2) to compare LYL between Asia-Pacific (APAC) and Europe; and (3) to assess LYL across different socio-demographic index (SDI) countries. The data used come from the Institute for Health Metrics and Evaluation (IHME) and Health Effects Institute (HEI). Our results show that average LYL due to PM in APAC was greater than in Europe, with some Pacific island countries particularly affected by the exposure to HAP. Three quarters of LYL came from premature deaths by ischemic heart disease and stroke, in both continents. There were significant differences between SDI groups for causes of death due to ambient PM and HAP. Our findings call for urgent improvement of clean air to reduce indoor and outdoor air pollution-related mortality in the APAC region.

The contribution of survival to changes in the net reproduction rate.

The net reproduction rate (NRR) is an alternative fertility measure to the more common total fertility rate (TFR) and accounts for the mortality context of the population studied. This study is the first to compare NRR trends in high- and low-income countries and to decompose NRR changes over time into fertility and survival components. The results show that changes in the NRR have been driven mostly by changes in fertility. Yet improvements in survival have also played an important role in explaining changes in the NRR over the last century and represent a substantial component of change in some low-income countries today. Furthermore, the decomposition of the survival component by age indicates that the survival effect on population reproduction is concentrated mostly in infancy, although the HIV/AIDS epidemic altered this age profile in some populations. The findings highlight the importance of mortality's effect on reproduction in specific periods and contexts.

Cross-sectional average length of life by parity: Country comparisons.

This study aims to present an alternative measure of fertility-cross-sectional average length of life by parity (CALP)-which: (1) is a period fertility indicator using all available cohort information; (2) captures the dynamics of parity transitions; and (3) links information on fertility quantum and timing together as part of a single phenomenon. Using data from the Human Fertility Database, we calculate CALP for 12 countries in the Global North. Our results show that women spend the longest time at parity zero on average, and in countries where women spend comparatively longer time at parity zero, they spend fewer years at parities one and two. The analysis is extended by decomposing the differences in CALPs between Sweden and the United States, revealing age- and cohort-specific contributions to population-level differences in parity-specific fertility patterns. The decomposition illustrates how high teenage fertility in the United States dominates the differences between these two countries in the time spent at different parities.

Comparing Cohort Survival in Good Health: A Research Note on Decomposing Sex Differentials in the United States.

We introduce a method for decomposing differences in healthy cross-sectional average length of life (HCAL). HCAL provides an alternative to the health expectancy (HE) indicator by including the health and mortality history of all cohorts present at a given time. While decompositions of HE differences account for contributions made by health and mortality, differences in HCAL are further disentangled into cohort-specific contributions. In this research note we illustrate the technique by analyzing the sex gap in health and mortality for the United States. We use the harmonized version of the Health and Retirement Survey data and define the health status in terms of activities of daily living. Our results suggest that the female advantage in cohort survival is partly compensated by women's lower cohort-specific health levels. At older ages, however, the sex differences in health are not large enough to compensate men's disadvantage in cohort survival.

Urban-rural lifespan disparities and cause-deleted analysis: evidence from China.

OBJECTIVES: To examine the length and dispersion level of lifespan for the subnational populations in China, identify the urban-rural gap and sex differences, and analyse the contribution made by causes of death. SETTING: Cause-specific mortality data extracted from the Chinese Disease Surveillance Points system, grouped by sex and urban/rural residence. PRIMARY OUTCOME MEASURES: Life expectancy and lifespan disparity are used to measure the length and dispersion level of lifespan, respectively. Cause-specific contributions are obtained by contrasting cause-deleted life expectancy and lifespan disparities with observed values. PARTICIPANTS: Aggregated national data gathered from over 605 surveillance points across China, covering over 264 million people by 2016 (about 19.14% of the total Chinese population). RESULTS: In the decade under observation, all subpopulations in China, by area and sex, experienced increases in life expectancy and decreases in lifespan disparity, while causes of deaths contributed differently. For example, based on the 2016 data, if cardiovascular diseases were deleted, there would be an increase in life expectancy that ranges from 5.59 years for urban males to 6.69 years for rural females. However, also lifespan disparity would increase, ranging from 0.81 years for urban females to 1.37 years for rural males. CONCLUSIONS: In China, the urban-rural gaps in both life expectancy and lifespan disparity are shrinking as the rural residents are catching up fast, while the gender gaps remain large, and even widening. Causes of death with different age distribution patterns contribute differently to the level and direction of the urban-rural and sex differentials in life expectancy and lifespan disparity. Sex differentials were observed in cardiovascular diseases, respiratory diseases, lung and liver cancers, and external causes, while urban-rural differences were found in lung and breast cancers, and external causes.

The Components of Change in Population Growth Rates.

The demographic balance equation relates the population growth rate with crude rates of fertility, mortality, and net migration. All these rates refer to changes occurring between two time points, say, t and t + h. However, this fundamental balance equation overlooks the contribution of historical fertility, mortality, and migration in explaining these population counts. Because of this, the balance equation only partially explains a change in growth rate between time t and t + h as it does not include the contribution of historical population trends in shaping the population at time t. The overall population growth rate can also be expressed as the weighted average of age-specific growth rates. In this article, we develop a method to decompose the historical drivers of current population growth by recursively employing the variable-r method on the population's average age-specific growth rates. We illustrate our method by identifying the unique contributions of survival progress, migration change, and fertility decline for current population growth in Denmark, England and Wales, France, and the United States. Our results show that survival progress is mainly having an effect on population growth at older ages, although accounting for indirect historical effects illuminates additional contributions at younger ages. Migration is particularly important in Denmark and England and Wales. Finally, we find that across all populations studied, historical fertility decline plays the largest role in shaping recent reductions in population growth rates.

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.

Understanding longevity in Hong Kong: a comparative study with long-living, high-income countries.

BACKGROUND: Since 2013, Hong Kong has sustained the world's highest life expectancy at birth-a key indicator of population health. The reasons behind this achievement remain poorly understood but are of great relevance to both rapidly developing and high-income regions. Here, we aim to compare factors behind Hong Kong's survival advantage over long-living, high-income countries. METHODS: Life expectancy data from 1960-2020 were obtained for 18 high-income countries in the Organisation for Economic Co-operation and Development from the Human Mortality Database and for Hong Kong from Hong Kong's Census and Statistics Department. Causes of death data from 1950-2016 were obtained from WHO's Mortality Database. We used truncated cross-sectional average length of life (TCAL) to identify the contributions to survival differences based on 263 million deaths overall. As smoking is the leading cause of premature death, we also compared smoking-attributable mortality between Hong Kong and the high-income countries. FINDINGS: From 1979-2016, Hong Kong accumulated a substantial survival advantage over high-income countries, with a difference of 1·86 years (95% CI 1·83-1·89) for males and 2·50 years (2·47-2·53) for females. As mortality from infectious diseases declined, the main contributors to Hong Kong's survival advantage were lower mortality from cardiovascular diseases for both males (TCAL difference 1·22 years, 95% CI 1·21-1·23) and females (1·19 years, 1·18-1·21), cancer for females (0·47 years, 0·45-0·48), and transport accidents for males (0·27 years, 0·27-0·28). Among high-income populations, Hong Kong recorded the lowest cardiovascular mortality and one of the lowest cancer mortalities in women. These findings were underpinned by the lowest absolute smoking-attributable mortality in high-income regions (39·7 per 100 000 in 2016, 95% CI 34·4-45·0). Reduced smoking-attributable mortality contributed to 50·5% (0·94 years, 0·93-0·95) of Hong Kong's survival advantage over males in high-income countries and 34·8% (0·87 years, 0·87-0·88) of it in females. INTERPRETATION: Hong Kong's leading longevity is the result of fewer diseases of poverty while suppressing the diseases of affluence. A unique combination of economic prosperity and low levels of smoking with development contributed to this achievement. As such, it offers a framework that could be replicated through deliberate policies in developing and developed populations globally. FUNDING: Early Career Scheme (RGC ECS Grant #27602415), Research Grants Council, University Grants Committee of Hong Kong.

Mortality attributable to fine particulate matter in Asia, 2000-2015: a cross-sectional cause-of-death analysis.

OBJECTIVES: To investigate the effect that particulate matter with a diameter of 2.5 µg (PM2.5) had on mortality in Asian populations in years 2000-2015. SETTING: Mortality and level of PM2.5 data from the United Nations, Global Burden of Disease and University of Chicago were used. OUTCOME MEASURES: Age pattern of mortality and the number of life-years lost (LYL) attributable to PM2.5 in years 2000-2015. LYL were further separated into causes of death to quantify the contribution of each cause. RESULTS: Ischaemic heart disease (IHD) mortality increased to represent over 31% of the LYL attributable to PM2.5 between 2005-2010 and 2010-2015 in Asia (females 31% and males 35%). However, great diversity in LYL attributable to PM2.5 by causes-of-death were found across the region, with IHD proportions of LYL ranging from 25% to 63% for males from Eastern and Central Asia, respectively. Similar diversity was observed for mortality attributable to PM2.5 for other causes of death across Asia: chronic obstructive pulmonary disease (LYL ranging from 6% to 28%), lung cancer (4% to 20%) and stroke (11% to 22%). CONCLUSION: PM2.5 is a crucial component in the rising health effects in Asia. The diverse trends in cause-specific mortality attributable to PM2.5 creates a further challenge for health systems in the region. These findings highlight that immediate interventions are needed to mitigate the increasing levels of air pollution and with that reduce its detrimental effect on the health and mortality of Asian populations.

Cross-Sectional Average Length of Life Childless.

Increases in the average age at first birth and in the proportion of women remaining childless have extended the total number of years that women spend childless during their reproductive lifetime in several countries. To quantify the number of years that reproductive-age women live without children, we introduce the cross-sectional average length of life childless (CALC). This measure includes all the age-specific first-birth information available for the cohorts present at time t; it is a period measure based on cohort data. Using the Human Fertility Database, CALC is calculated for the year 2015 for all countries with long enough histories of fertility available. Results show that women in the majority of the studied countries spend, on average, more than half of their reproductive lives childless. Furthermore, the difference between CALCs in two countries can be decomposed to give a clear visualization of how each cohort contributes to the difference in the duration of the length of childless life in those populations. Our illustration of the decomposition shows that (1) in recent years, female cohorts in Japan and Spain at increasingly younger ages have been contributing to more years of childless life compared with those in Sweden, (2) the United States continues to represent an exception among the high-income countries with a low expectation for childless life of women, and (3) Hungary experienced a strong period effect of the recent Great Recession. These examples show that CALC and its decomposition can provide insights into first-birth patterns.

Educational composition and parity contribution to completed cohort fertility change in low-fertility settings.

Extensive literature has documented the contribution of rising women's education to decreases in completed cohort fertility (CCF). A key question related to the education-fertility relationship is to what extent the decrease in fertility is the result of changes in educational composition vs changes in fertility behaviours within educational categories. This study quantified the effect of educational expansion on fertility levels by decomposing the overall change in CCF into educational composition and education-specific fertility, and explored the changes in parity-specific components of CCF by education for cohorts born between 1940 and 1970. The results show that, despite the decline in CCF being caused mostly by changes in fertility behaviours, educational composition had a considerable impact for some cohorts. The decline in third and higher-order births played a central role in the fall in CCF across educational groups, while the effects of transitions to first and second births varied substantially.

Uneven state distribution of homicides in Brazil and their effect on life expectancy, 2000-2015: a cross-sectional mortality study.

OBJECTIVE: To determine cause-specific and age-specific contributions to life expectancy changes between 2000 and 2015, separately by state and sex in Brazil, with a focus on homicides. DESIGN: Retrospective cross-sectional demographic analysis of mortality. SETTING AND POPULATION: Brazilian population by age, sex and state from 2000 to 2015. MAIN OUTCOME MEASURE: Using mortality data from the Brazilian Mortality Information System and population estimates from the National Statistics Office, we used death distribution methods and the linear integral decomposition model to estimate levels and changes in life expectancy. We also examine how multiple causes of death, including those attributable to homicides and amenable/avoidable mortality, contributed to these changes from 2000 to 2015. RESULTS: Between 2000 and 2015, life expectancy in Brazil increased from 71.5 to 75.1 years. Despite state-level variation in gains, life expectancy increased in almost all states over this period. However across Brazil, homicide mortality contributed, to varying degrees, to either attenuated or decreased male life expectancy gains. In Alagoas in 2000-2007 and Sergipe in 2007-2015, homicides contributed to a reduction in life expectancy of 1.5 years, offsetting gains achieved through improvements due to medically amenable causes. In the period 2007-2015, male life expectancy could have been improved by more than half a year in 12 of Brazil's states if homicide mortality had remained at the levels of 2007. CONCLUSIONS: Homicide mortality appears to offset life expectancy gains made through recent improvements to mortality amenable to medical services and public health interventions, with considerable subnational heterogeneity in the extent of this phenomenon. Efforts combating the causes of homicides can increase life expectancy beyond what has been achieved in recent decades.

A Mixture-Function Mortality Model: Illustration of the Evolution of Premature Mortality.

Premature mortality is often a neglected component of overall deaths, and the most difficult to identify. However, it is important to estimate its prevalence. Following Pearson's theory about mortality components, a definition of premature deaths and a parametric model to study its transformations are introduced. The model is a mixture of three distributions: a Half Normal for the first part of the death curve and two Skew Normals to fit the remaining pieces. One advantage of the model is the possibility of obtaining an explicit equation to compute life expectancy at birth and to break it down into mortality components. We estimated the mixture model for Sweden, France, East Germany and Czech Republic. In addition, to the well-known reduction in infant deaths, and compression and shifting trend of adult mortality, we were able to study the trend of the central part of the distribution of deaths in detail. In general, a right shift of the modal age at death for young adults is observed; in some cases, it is also accompanied by an increase in the number of deaths at these ages: in particular for France, in the last twenty years, premature mortality increases.