Decomposition Of Life Expectancy Research Articles

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Age- and cause-specific contributions to increase in life expectancy at birth in Korea, 2000–2019: a descriptive study

BackgroundKorea’s life expectancy at birth has consistently increased in the 21st century. This study compared the age and cause-specific contribution to the increase in life expectancy at birth in Korea before and after 2010.MethodsThe population and death numbers by year, sex, 5-year age group, and cause of death from 2000 to 2019 were acquired. Life expectancy at birth was calculated using an abridged life table by sex and year. The annual age-standardized and age-specific mortality by cause of death was also estimated. Lastly, the age and cause-specific contribution to the increase in life expectancy at birth in the two periods were compared using a stepwise replacement algorithm.ResultsLife expectancy at birth in Korea increased consistently from 2010 to 2019, though slightly slower than from 2000 to 2009. The cause-specific mortality and life expectancy decomposition analysis showed a significant decrease in mortality in chronic diseases, such as neoplasms and diseases of the circulatory system, in the middle and old-aged groups. External causes, such as transport injuries and suicide, mortality in younger age groups also increased life expectancy. However, mortality from diseases of the respiratory system increased in the very old age group during 2010–2019.ConclusionsLife expectancy at birth in Korea continued to increase mainly due to decreased mortality from chronic diseases and external causes during the study period. However, the aging of the population structure increased vulnerability to respiratory diseases. The factors behind the higher death rate from respiratory disease should be studied in the future.

Fuzzy clustering of the healthy life expectancy decomposition: A multi-population analysis

This work analyses healthy life expectancy, which combines information on the period life table with the age-specific disability prevalence data in a single indicator. We quantify how much mortality and disability contributed to changes in healthy life expectancy over a fixed time horizon by age group and population to understand if life expectancy is increasing faster than the decline of disability. The prominent heterogeneity in mortality and health worldwide calls for a cross-country comparative analysis. The methodology used is decomposition, which splits the difference between two times of an aggregate index by assigning the difference to its components. Besides, through a cluster analysis, we categorize countries according to the age-specific contributions of mortality and disability simultaneously, using the healthy life expectancy decomposition results. This allows us to ease the interpretation and better outline the outcomes. Since health is increasingly considered a crucial aspect of economic growth, monitoring health expectancies is essential to assess the financial sustainability of the health and social security system. Some policy implications are finally discussed.

Impacts of COVID-19 pandemic through decomposition of life expectancy according to leading causes and place of death in Czechia

While the direct effects of the pandemic are well documented, less is known about the indirect ones, including changes in healthcare provision or human behavior. This paper aims to study the impact of indirect consequences on mortality, focusing on two leading causes (cardiovascular diseases, COVID-19) and places of death in Czechia, during the COVID-19 pandemic, one of the most severely affected European countries. The analysis was performed using data from the Czech Statistical Office and the Institute of Health Information and Statistics. The study compares annual mortality changes during three time periods: pre-pandemic (2018–2019), pandemic beginning and peaking (2020–2021), and pandemic fading (2022). Pandemic years were covered by the WHO public health emergency of international concern. Abridged life tables were computed, and Pollard's decomposition was used to calculate the contributions of causes and places of death on annual differences in life expectancy. Seasonal decomposition of monthly time series revealed an increase in cardiovascular mortality at home or in social care facilities corresponding to limitations in healthcare. While COVID-19 had a systemic negative effect on life expectancy during the pandemic, the impact of cardiovascular mortality according to place of death changed over time. This study contributes to the evidence base of systemic risks during health crises and emergency response.

Effects of cancer mortality on life expectancy in European high-income countries between 1950 and 2019

This article aims to analyze the effects of cancer mortality on life expectancy at birth in 15 European high-income countries between 1950 and 2019. To establish the 1950–2019 time series of deaths from cancer, mortality data were harmonized from the available datasets of the World Health Organization Mortality database, coded according to the International Classification of Diseases of the 7th, 8th, 9th, and 10th editions. The estimation of the cancer mortality effect on the life expectancy at birth was performed using the algorithm of stepwise replacement for the life expectancy decomposition. The increase in cancer mortality contributed to a decline in overall life expectancy growth until the mid-1990s, coinciding with the aging cohorts of heavy smokers and a long-term reduction in mortality from other non-communicable diseases. Subsequently, since the 1990s, the reduction in cancer mortality has contributed to a significant increase in life expectancy at birth, especially in males. Reduction in cancer mortality was the outcome of various factors, such as alcohol and tobacco control policies, advances in cancer prevention and its treatment, general increase in population well-being, and reduction in risk-factors.

Key Drivers of Long-Term Rates of Mortality Improvements in the United States: Period, Cohort, and Cause of Death Analysis, 1959–2016

The main objective of this article is to identify significant mortality drivers in the U.S. population that have a high likelihood of being linked to the historical improvement or deterioration of mortality over the 1959 to 2016 period. To achieve this objective, we integrate cause of death modeling with epidemiological evidence to explain the underlying drivers. In particular, we analyze cause of death data for six broad groups of causes including circulatory diseases, neoplasms, respiratory diseases, digestive system diseases, external causes, and other causes. We also identify and analyze some key causes that serve as markers of trends in behavioral risk factors that could drive mortality change. These risk factors are AIDS and tuberculosis, alcohol abuse, dementia and Alzheimer’s disease, diabetes and obesity, drug dependency, homicide, hypertensive disease, self-harm, and smoking. We analyze these different groupings of causes of death using life expectancy decomposition techniques and formal age–period–cohort decomposition of both mortality rates and mortality improvement rates. We find that the story of mortality evolution in the United States in the second half of the 20th century, which continued into the first decade of the 21st century, has been mainly a story of mortality improvements from circulatory diseases. Nevertheless, despite the clear dominance of circulatory diseases as a leading cause of death and as the main contributor to mortality improvements between 1959 and 2016, the decline in mortality has been more complex. The trajectories of other major causes have ebbed and flowed, and the patterns of behavioral risk factors that contribute to overall mortality change have seen changes between generations.

The effect of avoidable mortality on life expectancy in Serbia, 2010-2019

Avoidable mortality is defined as death that could have been avoided by adequate and timely healthcare and public health and prevention measures. The method measures the efficiency of the health system by quantifying premature deaths (0-74) from certain causes. The analysis of avoidable mortality in Serbia, including both amenable and preventable mortality, covers the period from 2010 to 2019. The results for Serbia have shown that the contribution of specific mortality rates by age is mostly positive and that in the second decade of the 21st century, we can see a trend of increasing life expectancy (LE). The decomposition of life expectancy by age groups, sex, and cause of death showed that most positive contributions relate to the reduction of avoidable mortality (about 70%). Observed by gender, the reduction in avoidable mortality rates is higher in men, especially in middle-aged people, where gains in LE are over 80%. In women, the share of avoidable mortality by age in changes in LE is usually around 70%. Avoidable mortality rates in Serbia remain relatively high compared to the rest of Europe, but there is a positive shift. The fact that the probability of avoidable mortality in the male population at birth in Serbia is about 30% (18% for women) shows that there is much room for improvement. With the hypothetical elimination of avoidable mortality, the increase in LE in men could be 6.3 years, and in women 3.9. Amenable and preventable mortality rates are always higher in the male population, but the reduction in standardised values is more intense in men in Serbia. Standardised preventable mortality rates have been declining faster than standardised amenable mortality rates in Serbia. Since the male population is significantly more burdened with preventable causes of death, the possibility of reduction is higher. Diseases and conditions that can be amenable by adequate healthcare showed a steady decrease in mortality rates by sex in the observed period, while the main difference observed in avoidable mortality is the result of a greater shift in preventable mortality in men. The most significant positive trend in the reduction of avoidable mortality is in cardiovascular diseases and violent deaths. At the beginning of the observed period, cardiovascular diseases had a higher share than cancer, but 10 years later the situation changed, and cancer became the most significant cause of avoidable mortality in Serbia, with an increasing trend. Malignant neoplasm of the trachea, bronchi, and lungs is the most common disease that can be avoided, while ischemic heart disease is in second place. Data from the 10-year period (2010 to 2019) show that respiratory diseases, infectious and contagious diseases, and addiction have a clear growth trend, as does cancer. The most significant positive trend in the reduction of avoidable mortality is in cardiovascular diseases and violent death. Diseases that can be treated and prevented by lifestyle changes and regular check-ups can significantly extend life expectancy in Serbia. Investing in the healthcare system pays off many times over because the costs of treating an individual are reduced in the long run, and that person can potentially contribute more to the community in good health over the years.

Contribution of avoidable causes of death to premature mortality in Poland and selected European countries

Our study, availing the new, agreed by the OECD and Eurostat, lists of preventable and treatable causes of death, seeks to quantify the contribution of avoidable causes to premature mortality and its dynamics in Poland and Central European countries – Czechia, Hungary, Lithuania and Slovenia, in comparison with Sweden serving as a benchmark country in 1999–2017. We calculated age standardised death rates for the broad groups of avoidable causes and more specific ones, which comprised preventable and treatable cancer and diseases of the circulatory system (DCS), preventable injuries and alcohol-related diseases. Deaths from not avoidable causes were also analysed. The analysis of time trends in the death rates and calculation of the Average Annual Percent Change (AAPC) for the overall trend were performed with joint-point models. The contribution of changes in mortality from avoidable causes to increase life expectancy during 1999–2017 and contribution of the difference in mortality from these causes to the difference in life expectancy between five countries and Sweden were based on the decomposition of temporary life expectancy between birth and age 75 [e(0-75)]. For the calculation of life expectancy, we used the classic Chiang method and the decomposition of life expectancy by the death causes and age was conducted with the Arriaga method. The AAPC of death rates from avoidable causes in 1999–2017 was similar in all the countries but Lithuania, where the decline started later. The decline in the death rates from not avoidable causes is much slower than the rates from avoidable causes. Mortality from treatable causes was decreasing faster than from preventable causes in most populations. In 1999–2017, the average rate of mortality decline for preventable cancer was greater among men than among women, while for treatable cancer the sex-related differences were much smaller and in favour of women. As for preventable and treatable death from DCS, their decrease was faster among women than men in all the countries but Sweden. Improvements in mortality from causes that could be avoided through prevention or treatment made substantial positive contributions to the overall change in life expectancy in all the countries. The differences in temporary life expectancy e(0-75) between the analysed Central European countries and Sweden were much smaller in 2017 than in 1999, due to the reduction of the gap in mortality from avoidable causes. Our results show that among men, and to a lesser extent among women, mortality from preventable causes contributes more than mortality from causes that can be effectively treated to shorter life expectancy in the countries of Central Europe than in Sweden.
 This indicates that in reducing the health gap between the inhabitants of Central Europe and Western Europe, the healthcare system should consider disease prevention even to a greater extent than just treating them.

Age- and cause-specific contributions to the life expectancy gap between Medical Aid recipients and National Health Insurance beneficiaries in Korea, 2008-2017.

Recipients of Medical Aid, a government-funded social assistance program for the poor, have a shorter life expectancy than National Health Insurance beneficiaries in Korea. This study aims to explore the contributions of age and major causes of death to the life expectancy difference between the two groups. We used the National Health Information Database provided by the National Health Insurance Service individually linked to mortality registration data of Statistics Korea between 2008 and 2017. Annual abridged life tables were constructed and Arriaga’s life expectancy decomposition method was employed to estimate age- and cause-specific contributions to the life expectancy gap between National Health Insurance beneficiaries and Medical Aid recipients. The life expectancy difference between National Health Insurance beneficiaries and Medical Aid recipients was 14.5 years during the period of 2008–2017. The age groups between 30 and 64 years accounted for 78.7% and 67.5% of the total life expectancy gap in men and women, respectively. Cancer was the leading cause of death contributing to excess mortality among Medical Aid recipients compared to National Health Insurance beneficiaries. More specifically, alcohol-attributable deaths (such as alcoholic liver disease, liver cancer, liver cirrhosis, and alcohol/substance abuse), suicide, and cardiometabolic risk factor–related deaths (such as cerebrovascular disease, ischemic heart disease, and diabetes) were the leading contributors to the life expectancy gap. To decrease excess deaths in Medical Aid recipients and reduce health inequalities, effective policies for tobacco and alcohol regulation, suicide prevention, and interventions to address cardiometabolic risk factors are needed.

How have changes in death by cause and age group contributed to the recent stalling of life expectancy gains in Scotland? Comparative decomposition analysis of mortality data, 2000–2002 to 2015–2017

ObjectiveAnnual gains in life expectancy in Scotland were slower in recent years than in the previous two decades. This analysis investigates how deaths in different age groups and from different...

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

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

A Decomposition of Life Expectancy and Life Disparity: Comparison Between Hong Kong and Japan.

Background: Life expectancy and life disparity are 2 useful indicators to assess the health condition of a society. Both Hong Kong and Japan have one of the longest life expectancies in the world. Recently, Hong Kong has overtaken Japan and topped the life expectancy rankings. However, whether Hong Kong has also outperformed Japan in life disparity is still unknown. Methods: Decomposition analyses have been conducted to evaluate age-specific contributions to the changes in life expectancy and life disparity for each of the populations. Furthermore, the differences between the 2 populations were examined over the period 1977-2016. Results: Reduction in mortality of the adult and the old age groups contributes most to the increase in life expectancy for the study period. Hong Kong has a higher life disparity than Japan, and due to the great improvement in reducing premature deaths, the Hong Kong-Japan gap has been narrowing. However, in recent years, further reduction in mortality of the oldest elderly in Hong Kong has actually contributed to the increase in its disparity, thus widening its gap with Japan again. Conclusion: Increasing dominant influence of "saving lives at late ages" is very likely to cause the reemergence of increasing life disparity in these 2 long-lived populations.

Recent decline in life expectancy at birth in Slovenia

For many decades, life expectancy at birth (e0) in Slovenia has been increasing at a very rapid pace. However, in 2015, e0 declined slightly; it recovered in 2016, but fell again in 2017 for women. In the same period, a pause in declining mortality was observed in numerous developed countries worldwide. It is too early to provide a thorough analysis and firm conclusions, but we shed some light on the topic by decomposing the observed decline in Slovenia by age and cause of death. In particular, using a life table model and life expectancy decomposition technique, we analyse what cause of death for what age group contributed the most to this decline in life expectancy at birth. We show that the main reason for the recent drop in life expectancy at birth in Slovenia was higher mortality due to external causes for men of all ages and due to neoplasms for women above 60 years and men above 50 years.

The decomposition of life expectancy for age and cause of death in Tuscany, Italy

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

Violencia y accidentes mortales: análisis de la mortalidad por causas externas en Colombia y México, 1998-2015

The main objective was to analyze the level, trend and impact of mortality by external causes in Colombia and Mexico between 1998 and 2015. The years of life lost were calculated for people younger than 85 years of age and their trend was estimated using a joinpoint regression analysis. The decomposition of life expectancy by cause of death and age groups was also calculated. In Colombia a significant decrease was observed in all the analyzed external causes of death; in Mexico, the increase of mortality by homicides and the continued rise in suicides reversed their declining trend. Mexico presented a higher mortality due to external causes than Colombia, which clearly shows the divergent trends in both countries.

Decomposition of Ethiopian life expectancy by age and cause of mortality; 1990-2015.

Ethiopia’s average life expectancy has improved by more than 18 years from 1990 to 2015. This initiated interest to study the gain in life expectancy with respect to age structure and cause of death. Applying a life expectancy decomposition technique on secondary data obtained from the Institute of Health Metrics and Evaluation, the study found that the burden of disease in Ethiopia has declined from 626.18 in 1990 to 225.69 in 2015 per 1000 population measured in age-standardized rate of life years lost. The major causes of burden in 1990; namely lower respiratory tract infections, neonatal disorders, diarrheal diseases and neglected tropical diseases at rates of 89.2, 63.2, 61.2, and 42.2 age-standardized years of life lost per 1000 population respectively; have shown a fast decline in 2015. Deaths from neglected tropical disease showed 94.95% reduction, contributing to 5.71(27.30%) years gain in life expectancy followed by lower respiratory tract infection and diarrheal disease contributing about 4.65 years (22.23%) and 1.48 years (7.10%) respectively. On the other hand, about 3.3 (15.73%) years and 6.4 (30.71%) years of increase in life expectancy are achieved through improved longevity in infants and children aged 1–4 years respectively. In conclusion, the study found that reductions in under-five child mortality and decline in burden of major communicable diseases could explain the major gain in life expectancy. However, findings also revealed that the prevalence of non-communicable diseases and injuries are on the rise calling for the need to be addressed by the public health system.

On the decomposition of life expectancy and limits to life

Life expectancy is a measure of how long people are expected to live and is widely used as a measure of human development. Variations in the measure reflect not only the process of ageing but also the impacts of such events as epidemics, wars, and economic recessions. Since 1950, the influence of these events in the most developed countries has waned and life expectancy continues to lengthen unabated. As a result, it has become more difficult to forecast long-run trends accurately, or identify possible upper limits. We present new methods for comparing past improvements in life expectancy and also future prospects, using data from five developed, low-mortality countries. We consider life expectancy in 10-year age intervals rather than over the remaining lifetime, and show how natural limits to life expectancy can be used to extrapolate trends. We discuss the implications and compare our approach with other commonly used methods.Supplementary material for this article is available at: http://dx.doi.org/10.1080/00324728.2014.972433

Racial Disparities in Life Expectancy in Brazil: Challenges From a Multiracial Society

We calculated life expectancy at birth for Whites, Blacks, and mixed races in Brazil, and decomposed the differences by causes of death. We used Ministry of Health death records and 2010 Census population data (190,755,799 residents and 1,136,947 deaths). We applied the Arriaga methodology to calculate decomposition of life expectancy by cause of death. We performed sensitivity analyses for underreporting of deaths, missing data, and numerator-denominator bias. Using standard life table methods, female life expectancy was highest for mixed races (78.80 years), followed by Whites (77.54 years), then Blacks (76.32 years). Male life expectancy was highest for Whites (71.10 years) followed closely by mixed races (71.08 years), and lower for Blacks (70.11 years). Homicides contributed the most to the relative life expectancy increase for Whites, and cancer decreased the gap. After adjustment for underreporting, missing data, and numerator-denominator bias, life expectancy was higher for Whites than for Blacks and mixed races. Despite wide socioeconomic differences between Whites and mixed races, standard life table methods showed that mixed races had higher life expectancy than Whites for women, and similar for men. With the increase of multiracial populations, measuring racial disparities in life expectancy will be a fast-growing challenge.

¿Por qué vivimos más? Descomposición por causa de la esperanza de vida española 1980 a 2009

Este trabajo describe y explica de forma interdisciplinar las tendenciasrecientes de la esperanza de vida al nacimiento en España. Se utilizandos metodologías: regresión lineal segmentada y descomposición de laesperanza de vida. El estudio consta de tres partes. Primero, sedescriben los factores demográficos que se encuentran tras el aumentode más de 40 años en la esperanza de vida al nacimiento de 1910 a2009. Segundo, se analiza el efecto que el cambio de la mortalidad, porcausa de muerte, en mayores de 65 años ha tenido en esa esperanzade vida en 1980-2009. Y tercero, se aportan las causas socioepidemiológicasque hay detrás de dicho incremento. Se concluye queese aumento se debe principalmente a la reducción de la mortalidad enlas edades avanzadas y a la disminución de la mortalidad porenfermedades cardiovasculares.

Decomposition of life expectancy among permanent residents of Beijing, 2000 - 2010

To analyze the change of life expectancy and the impact of mortality by age and causes of death on this issue among permanent residents of Beijing. Abridged Life Table and Arriaga method were used to calculate and to decompose the changes on life expectancy by age and causes of death in 2000 - 2010. From 2000 - 2010, life expectancy under this studied population had an increase of 3.35 years. Most part of the increases (44.27%, 1.48 years) within the last 10 years could be explained by the decrease of mortality in the population at age ≥ 80. Both cerebrovascular and heart diseases were contributing the most to the increment of life expectancy while mortality of malignant tumors appeared a negative contributor to this increment. From 2000 to 2010, increment in life expectancy contributed to the decrease of mortality in the elderly and the decrease of mortalities on both cardio- and cerebro-vascular diseases. The decrease of life expectancy was mainly due to the increase of mortality related to malignant tumors.