A decomposition method based on a model of continuous change

Estimation of cause-specific mortality in Rakai, Uganda, using verbal autopsy 1999-2019

BACKGROUND

There are scant data on the causes of adult deaths in sub-Saharan Africa. We estimated the level and trends in adult mortality, overall and by different causes, in rural Rakai, Uganda, by age, sex, and HIV status.

OBJECTIVES

To estimate and analyse adult cause-specific mortality trends in Rakai, Uganda.

METHODOLOGY

Mortality information by cause, age, sex, and HIV status was recorded in the Rakai Community Cohort study using verbal autopsy interviews, HIV serosurveys, and residency data. We estimated the average number of years lived in adulthood. Using demographic decomposition methods, we estimated the contribution of each cause of death to adult mortality based on the average number of years lived in adulthood.

RESULTS

Between 1999 and 2019, 63082 adults (15-60 years) were censused, with 1670 deaths registered. Of these, 1656 (99.2%) had completed cause of death data from verbal autopsy. The crude adult death rate was 5.60 (95% confidence interval (CI): 5.33-5.87) per 1000 person-years of observation (pyo). The crude death rate decreased from 11.41 (95% CI: 10.61-12.28) to 3.27 (95% CI: 2.89-3.68) per 1000 pyo between 1999-2004 and 2015-2019. The average number of years lived in adulthood increased in people living with HIV and decreased in HIV-negative individuals between 2000 and 2019. Communicable diseases, primarily HIV and Malaria, had the biggest decreases, which improved the average number of years lived by approximately extra 12 years of life in females and 6 years in males. There were increases in deaths due to non-communicable diseases and external causes, which reduced the average number of years lived in adulthood by 2.0 years and 1.5 years in females and males, respectively.

CONCLUSION

There has been a significant decline in overall mortality from 1999 to 2019, with the greatest decline seen in people living with HIV since the availability of antiretroviral therapy in 2004. By 2020, the predominant causes of death among females were non-communicable diseases, with external causes of death dominating in males.

The contribution of avoidable mortality to life expectancy differences and lifespan disparities in the European Union: a population-based study

Background

Twenty years after the 2004 European Union (EU) enlargement, life expectancy differences between established (EMS) and new member states (NMS) remain large. Contributing to this gap are deaths that can be avoided through preventive services or adequate medical treatment. We estimate the impact of reducing avoidable mortality on life expectancy and lifespan disparities in the enlarged EU.

Methods

Using World Health Organization mortality database data, we analysed the potential of reducing avoidable mortality, as defined by Eurostat and the Organisation for Economic Cooperation and Development, to close the mortality gap between NMS and EMS. We decomposed the changes in life expectancy and lifespan disparity by age and cause using linear integral decomposition.

Findings

Averting all avoidable deaths across the EU from 2005 to 2019 would decrease the average life expectancy gap from 5.8 to 2.4 years in men and 3.3-2 years in women and eliminate the lifespan disparity gap. Had NMS achieved the average EMS avoidable mortality rates during the same period, the average life expectancy gap would have been reduced to 1.8 years in men and 1.6 years in women, and the lifespan disparities gap would have been reversed. Avoidable circulatory and injury-related deaths in middle and older age drove the observed mortality changes.

Interpretation

Our results suggest that the gap in life expectancy and lifespan disparity across the EU could be reduced by strengthening health systems and investing in averting circulatory and injury-related deaths in middle and older age in NMS.

Funding

None.

Contributions of injury deaths to the changes in sex gaps in life expectancy and life disparity in the Nordic countries in the 21st century

OBJECTIVE

The objective of this study was to provide novel comparative insights on the contributions of injury deaths to the changes in sex gaps in life expectancy (SGLE) and sex gaps in life disparity (SGLD) across Nordic countries.

STUDY DESIGN

Retrospective demographic analysis of aggregated mortality data.

METHODS

To compute life expectancy (LE)/life disparity (LD), annual data on age- and sex-specific causes of death from the World Health Organization mortality database were used to construct abridged life tables for two periods: 2000-2002 and 2016-2018 (2014-2016 for Norway). The contributions of injury deaths to the changes in the SGLE and SGLD between these two periods were decomposed by age and cause using a continuous-change model.

RESULTS

Females' LE and LD advantages due to injury deaths narrowed by 0.16-0.44 (0.06-0.35) years for LE (LD) over time. While self-inflicted injuries consistently played a predominant role in contributing to the SGLE/SGLD in all countries in both periods, in all countries but Finland, transport accidents had the greatest contributions to the narrowing SGLE/SGLD. Widening SGLE due to self-inflicted injuries in Iceland and due to falls in Sweden were unique to these countries. Accounting for >20% of total contributions of injury deaths, the age group of 20-24 years had the greatest contributions to the narrowing SGLE/SGLD. Deaths due to falls in older ages and assault in younger ages generally contributed to the widening SGLE/SGLD.

CONCLUSIONS

Injury deaths, particularly transport accidents, contributed significantly to the narrowing SGLE and SGLD across Nordic countries, with cross-country variations in age- and cause-specific patterns. The results suggest the need for injury prevention policies targeting self-inflicted injuries in younger and falls in older males.

Can pre-visit exposure to virtual tours of healthcare facilities help reduce child and parent anxiety during outpatient surgical procedures?

AIM

The study aims to evaluate the impact of exposure to a highly realistic virtual facility tour prior to the on-site visit on patients and their parent/care partner's self-reported anxiety and physiological measures on the day of the procedure.

BACKGROUND

Preoperative anxiety impacts pediatric surgical outcomes; therefore, it is important for healthcare providers to address and manage preoperative anxiety in pediatric patients to promote better outcomes and overall wellbeing. Providing patients with a preview of the care setting before the actual procedure can be highly beneficial in mitigating preoperative anxiety.

METHODOLOGY

In this pilot randomized experimental study, sixteen patient-care partner dyads scheduled to undergo a gastrointestinal procedure either received a virtual tour identical to the places experienced on the day of the procedure (experimental group) or received no virtual tour (control group). Self-reported measures of anxiety were collected from participants before and on the day of the procedure. Physiological measures of heart rate variability and skin conductance were collected on the day of the procedure from both groups.

RESULTS

There were no significant differences between the self-reported and physiological measures of anxiety between the child groups. However, parents in the control group reported lower levels of anxiety and demonstrated lower levels of stress based on their physiological measures.

CONCLUSION

Exposure to virtual facility tours days before the surgery was not helpful in positively impacting the psychological measures related to preoperative anxiety levels for the participants.

The contributions of avoidable causes of death to gender gap in life expectancy and life disparity in the US and Canada: 2001-2019

OBJECTIVES

This study measures public health policies' and healthcare system's influence, by assessing the contributions of avoidable deaths, on the gender gaps in life expectancy and disparity (GGLD and GGLD, respectively) in the United States (US) and Canada from 2001 to 2019.

METHODS

To estimate the GGLE and GGLD, we retrieved age- and sex-specific causes of death from the World Health Organization's mortality database. By employing the continuous-change model, we decomposed the GGLE and GGLD by age and cause of death for each year and over time using females as the reference group.

RESULTS

In Canada and the US, the GGLE (GGLD) narrowed (increased) by 0.9 (0.2) and 0.2 (0.3) years, respectively. Largest contributor to the GGLE was non-avoidable deaths in Canada and preventable deaths in the US. Preventable deaths had the largest contributions to the GGLD in both countries. Ischemic heart disease contributed to the narrowing GGLE/GGLD in both countries. Conversely, treatable causes of death increased the GGLE/GGLD in both countries. In Canada, "treatable & preventable" as well as preventable causes of death narrowed the GGLE while opposite was seen in the US. While lung cancer contributed to the narrowing GGLE/GGLD, drug-related death contributed to the widening GGLE/GGLD in both countries. Injury-related deaths contributed to the narrowing GGLE/GGLD in Canada but not in the US. The contributions of avoidable causes of death to the GGLE declined in the age groups 55-74 in Canada and 70-74 in the US, whereas the GGLE widened for ages 25-34 in the US.

CONCLUSION

Canada experienced larger reduction in the GGLE compared to the US attributed mainly to preventable causes of death. To narrow the GGLE and GGLD, the US needs to address injury deaths. Urgent interventions are required for drug-related death in both countries, particularly among males aged 15-44 years.

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the "Inequality" component), (2) the total share of deaths attributable to each cause (the "Proportion" component), or (3) the cause-specific mean age at death (the "Mean" component). This so-called Inequality-Proportion-Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, "circulatory system" and "neoplasms") do not necessarily contribute the most to overall levels of lifespan inequality. In fact, "perinatal and congenital" causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark

BACKGROUND

Denmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014-2019).

METHODS

We used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category.

RESULTS

We observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups.

CONCLUSIONS

COVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries.

Factors Contributing to the Change in Overweight/Obesity Prevalence Among Indian Adults: A multivariate decomposition analysis of data from the National Family Health Surveys

INTRODUCTION

Concerns over the escalating burden of non-communicable diseases call for the redressal of behavioral risk factors like increased body mass index. Most studies have failed to quantify the contribution of socio-demographic characteristics in a linear trend. The present study aims to estimate the current prevalence of overweight and obesity in Indian adults and the contribution of different socio-demographic factors to the increasing prevalence.

METHODS

We carried out a secondary data analysis of two National Family Health Survey (NFHS) rounds. The final sample includes 558,122 women and 84,477 men from round 4, and 574,099 women and 74,761 men were included from round 5, using a multi-stage stratified random sampling approach. Overweight/obesity was our primary dependent variable. Weighted bivariate analysis was used to ascertain the prevalence, and the adjusted odds ratios were computed to ascertain the potential predictors. The contribution of different factors towards rising burden over two time points was estimated using multivariate decomposition analysis for non-linear response models.

RESULTS

Overall weighted prevalence of overweight and obesity in males and females per NFHS-5 was 44.02% and 41.16%, respectively, compared to 37.71% and 36.14% in NFHS-4. Decomposition analyses depict that the proportion of obesity increased by 6.37% and 5.10% points among men and women, respectively, over the two rounds. Compositional differences of participants (endowment) attributed to 16.54 and 49.90% differences, and the difference in coefficient or effect accounted for 83.46 and 50.10%, respectively, of the increase in the prevalence. The most significant factors contributing to increased prevalence were age, improving socio-economic status, smoking, unclean cooking fuel, and diabetes.

CONCLUSIONS

The incremental rise in such a short period, mainly attributed to the effect of socio-demographic variables, is concerning. Policy interventions should prioritize health advocacy programs and aggressively target behavioral modifications while preparing the health systems to manage the people living with obesity.

Gains in life expectancy from decreasing cardiovascular disease and cancer mortality - an analysis of 28 European countries 1995-2019

BACKGROUND

Life expectancy (LE) is an indicator of societal progress among rapidly aging populations. In recent decades, the displacement of deaths from cardiovascular disease (CVD) and cancer have been key drivers in further extending LE on the continent, though improvements vary markedly by country, sex, and over time. This study provides a comparative overview of the age-specific contributions of CVD and cancer to increasing LE in the 27 European Union member states, plus the U.K.

METHODS

Cause-by-age decompositions of national changes in LE were conducted for the years 1995-1999 and 2015-2019 based on the standard approach of multiple decrement life tables to quantify the relative impact over time. The contributions of CVD and cancer mortality changes to differences in LE were computed by sex and age for each of the 28 countries. We examine the difference between the member states before 2004 ("founding countries") and those which accessed the EU after 2004 ("A10 countries").

RESULTS

Among men, declines in CVD mortality in the founding countries of the EU were larger contributors to increasing LE over the last decades than malignant neoplasms: 2.26 years were gained by CVD declines versus 1.07 years for cancer, with 2.23 and 0.84 years gained in A10 countries, respectively. Among women in founding countries, 1.81 and 0.54 additional life years were attributable to CVD and cancer mortality declines, respectively, while in A10 countries, the corresponding values were 2.33 and 0.37 years. Lung and stomach cancer in men, and breast cancer in women were key drivers of gains in LE due to cancer overall, though rising mortality rates from lung cancer diminished the potential impact of increasing female LE in both EU founding (e.g., France, Spain, and Sweden) and A10 countries (e.g., Croatia, Hungary, and Slovenia), notably among cohorts aged 55-70 years. Over the 25 years, the LE gap between the two sets of countries narrowed from 6.22 to 5.59 years in men, and from 4.03 to 3.12 years for women, with diminishing female mortality from CVD as a determinative contributor.

CONCLUSION

This study underscores the continued existence of an East-West divide in life expectancy across the EU27 + 1, evident on benchmarking the founding vs. A10 countries. In EU founding countries, continuous economic growth alongside improved health care, health promotion and protection policies have contributed to steady declines in mortality from chronic diseases, leading to increases in life expectancy. In contrast, less favourable mortality trends in the EU A10 countries indicate greater economic and health care challenges, and a failure to implement effective health policies.

Decomposition of disparities in life expectancy with applications to administrative health claims and registry data

Research shows that geographic disparities in life expectancy between leading and lagging states are increasing over time while racial disparities between Black and White Americans have been going down. In the 65+ age strata morbidity is the most common cause of death, making differences in morbidity and associated adverse health-related outcomes between advantaged and disadvantaged groups an important aspect of disparities in life expectancy at age 65 (LE65). In this study, we used Pollard's decomposition to evaluate the disease-related contributions to disparities in LE65 for two types of data with distinctly differing structures: population/registry and administrative claims. To do so, we analyzed Pollard's integral, which is exact by construction, and developed exact analytic solutions for both types of data without the need for numerical integration. The solutions are broadly applicable and easily implemented. Applying these solutions, we found that the largest relative contributions to geographic disparities in LE65 were chronic lower respiratory diseases, circulatory diseases, and lung cancer; and, to racial disparities: arterial hypertension, diabetes mellitus, and cerebrovascular diseases. Overall, the increase in LE65 observed over 1998-2005 and 2010-2017 was primarily due to a reduction in the contributions of acute and chronic ischemic diseases; this was partially offset by increased contributions of diseases of the nervous system including dementia and Alzheimer's disease.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Levels, trends, and determinants of cause-of-death diversity in a global perspective: 1990-2019

BACKGROUND

While much is known about the leading causes of death (CoD) and how they have evolved over time, much less is known about the diversity of such causes of death. CoD diversity is an important marker of population health heterogeneity that has been largely overlooked in the study of contemporary health dynamics.

METHODS

We provide regional and national estimates of CoD diversity from 1990 to 2019. We rely on data from the Global Burden of Disease project, using information on 21 CoD. Results are presented for 204 countries and territories, for women and men separately. CoD diversity is measured with the index of Fractionalization. Results are disaggregated by age and cause of death.

RESULTS

CoD diversity has declined across world regions, except for Latin America and the Caribbean, the region of High-income countries and women in Central Europe, Eastern Europe, and Central Asia. Changes in mortality at adult and older ages have been mostly responsible for CoD diversity dynamics, except for the regions of South Asia and Sub-Saharan Africa, where infant and child mortality still play a non-negligible role. The relationship between CoD diversity, life expectancy, and lifespan inequality is strongly non-monotonic, with turning points differing by sex and indicator. Among longevity vanguard countries, further increases in life expectancy are associated with decreasing lifespan inequality but increasing CoD diversity.

CONCLUSION

As mortality declines, there is no universal pathway toward low CoD diversity, thus casting doubts on the ability of Epidemiological Transition Theory to predict prospective CoD dynamics among high- and middle-mortality countries. Despite the postponement and increasing predictability of the ages at which individuals die, low-mortality populations are composed of an increasingly heterogenous mix of robust and frail individuals, thus increasing the diversity of health profiles among older persons - an issue that could potentially complicate further improvements in longevity.

A global assessment of the impact of violence on lifetime uncertainty

Uncertainty around age at death, or lifetime uncertainty, is a key public health indicator and a marker of inequality in survival. How does the extent of violence affect lifetime uncertainty? We address this question by quantifying the impact of violence on dispersion in the ages at death, the metric most used to measure lifetime uncertainty. Using mortality data from the Global Burden of Disease Study and the Internal Peace Index between 2008 and 2017, we find that the most violent countries are also those with the highest lifetime uncertainty. In the Middle East, conflict-related deaths are the largest contributor to lifetime uncertainty. In Latin America, a similar pattern is attributable to homicides. The effects are larger in magnitude for men, but the consequences remain considerable for women. Our study points to a double burden of violence on longevity: Not only does violence shorten individual lives, but it also makes the length of life less predictable.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

CO2 emissions in the Middle East: Decoupling and decomposition analysis of carbon emissions, and projection of its future trajectory

Despite their acute climatic susceptibility, the hot, arid Middle Eastern countries are among the world's largest energy consumers and emitters of greenhouse gases, particularly carbon dioxide (CO₂). Nonetheless, no study has been conducted to decompose regionally the influential primary factors of the Middle East's carbon emissions. This study utilized the logarithmic mean Divisia index (LMDI) method to fill this knowledge gap and investigate the driving forces of CO₂ emissions in 12 Middle Eastern countries, namely, Bahrain, Iran, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, the United Arab Emirates, and Yemen (1990-2020). The research confirmed that, with a contribution rate of 53.89 %, population growth is the primary driver of CO₂ emissions in the Middle East, followed by energy intensity (31.97 %) and economic growth (18.42 %); and the most straightforward approach to reduce emissions, are boosting energy efficiency and reforming energy subsidies. It also concluded that the West Asian economy is gradually decoupling from CO₂ due to the effective decarbonization of countries, such as Saudi Arabia and Kuwait, based on the Tapio decoupling model results. Furthermore, each country's future emissions (2020-2026) were projected using a novel group method of data handling (GMDH) approach based on the main identified factors. The countries' decoupling status confirms the accuracy of the projected data on CO₂ emissions growth. The region's CO₂ emissions are expected to rise 13.28 % by 2026, with Syria and Yemen experiencing the most significant increases (129.45 % and 112.14 %, respectively) due to post-civil war economic growth. Other aspects of regional conflicts and migration impacts on the CO₂ emission influencing factors were also explored. Indeed, besides providing a comprehensive analysis of the current and future status of CO₂ emissions in the Middle East, the effects of military conflicts on CO₂ emissions have been investigated using this regional case study for global application.

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.

Alcohol-Attributable Deaths Help Drive Growing Socioeconomic Inequalities In US Life Expectancy, 2000-18

Socioeconomic gaps in life expectancy have widened substantially in the United States since 2000. Yet the contribution of specific causes to these growing disparities remains unknown. We used death records from the National Vital Statistics System and population data from Current Population Surveys to quantify the contribution of alcohol-attributable causes of death to changes in US life expectancy between 2000 and 2018 by sex and socioeconomic status (as measured by educational attainment). During the study period, the gap in life expectancy between people with low (high school diploma or less) compared with high (college degree) levels of education increased by three years among men and five years among women. Between 2000 and 2010 declines in cardiovascular disease mortality among people with high education made major contributions to growing inequalities. In contrast, between 2010 and 2018 deaths from a cause with an alcohol-attributable fraction of 20 percent or more were a dominant driver of socioeconomic divergence. Increased efforts to implement cost-effective alcohol control policies will be essential for reducing health disparities.

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

Background

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

Methods

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

Results

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

Conclusions

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

Supplementary Information

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

Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries

BACKGROUND

Variations in the age patterns and magnitudes of excess deaths, as well as differences in population sizes and age structures, make cross-national comparisons of the cumulative mortality impacts of the COVID-19 pandemic challenging. Life expectancy is a widely used indicator that provides a clear and cross-nationally comparable picture of the population-level impacts of the pandemic on mortality.

METHODS

Life tables by sex were calculated for 29 countries, including most European countries, Chile and the USA, for 2015-2020. Life expectancy at birth and at age 60 years for 2020 were contextualized against recent trends between 2015 and 2019. Using decomposition techniques, we examined which specific age groups contributed to reductions in life expectancy in 2020 and to what extent reductions were attributable to official COVID-19 deaths.

RESULTS

Life expectancy at birth declined from 2019 to 2020 in 27 out of 29 countries. Males in the USA and Lithuania experienced the largest losses in life expectancy at birth during 2020 (2.2 and 1.7 years, respectively), but reductions of more than an entire year were documented in 11 countries for males and 8 among females. Reductions were mostly attributable to increased mortality above age 60 years and to official COVID-19 deaths.

CONCLUSIONS

The COVID-19 pandemic triggered significant mortality increases in 2020 of a magnitude not witnessed since World War II in Western Europe or the breakup of the Soviet Union in Eastern Europe. Females from 15 countries and males from 10 ended up with lower life expectancy at birth in 2020 than in 2015.

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

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

Normalized lifespan inequality: disentangling the longevity-lifespan variability nexus

Previous studies have documented a historically strong and negative association between countries’ life expectancy (i.e., average longevity) and length-of-life inequality (i.e., variability in ages at death). The relationship between both variables might be partially explained by life expectancy increasing at a faster pace than maximal length of life, a phenomenon that mechanically compresses the age-at-death distribution and has not been taken into consideration in previous studies. In this paper, we propose a new approach to lifespan inequality measurement that accounts for the (uncertainly) bounded nature of length-of-life. Applying the new approach to the countries of the Human Mortality Database, we observe that the decline in overall lifespan variability typically associated with increases in longevity seems to stop and even reverse at higher levels of life expectancy. This suggests the emergence of worrying ethical dilemmas, whereby higher achievements in longevity would only be possible at the expense of higher lifespan variability.

Educational note: causal decomposition of population health differences using Monte Carlo integration and the g-formula

One key objective of the population health sciences is to understand why one social group has different levels of health and well-being compared with another. Whereas several methods have been developed in economics, sociology, demography, and epidemiology to answer these types of questions, a recent method introduced by Jackson and VanderWeele (2018) provided an update to decompositions by anchoring them within causal inference theory. In this paper, we demonstrate how to implement the causal decomposition using Monte Carlo integration and the parametric g-formula. Causal decomposition can help to identify the sources of differences across populations and provide researchers with a way to move beyond estimating inequalities to explaining them and determining what can be done to reduce health disparities. Our implementation approach can easily and flexibly be applied for different types of outcome and explanatory variables without having to derive decomposition equations. We describe the concepts of the approach and the practical steps and considerations needed to implement it. We then walk through a worked example in which we investigate the contribution of smoking to sex differences in mortality in South Korea. For this example, we provide both pseudocode and R code using our package, cfdecomp. Ultimately, we outline how to implement a very general decomposition algorithm that is grounded in counterfactual theory but still easy to apply to a wide range of situations.

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.

Gender differences in time to first hospital admission at age 60 in Denmark, 1995-2014

Women have consistently lower mortality rates than men at all ages and with respect to most causes. However, gender differences regarding hospital admission rates are more mixed, varying across ages and causes. A number of intuitive metrics have previously been used to explore changes in hospital admissions over time, but have not explicitly quantified the gender gap or estimated the cumulative contribution from cause-specific admission rates. Using register data for the total Danish population between 1995 and 2014, we estimated the time to first hospital admission for Danish men and women aged 60. This is an intuitive population-level metric with the same interpretive and mathematical properties as period life expectancy. Using a decomposition approach, we were able to quantify the cumulative contributions from eight causes of hospital admission to the gender gap in time to first hospital admission. Between 1995 and 2014, time to first admission increased for both, men (7.6 to 9.4 years) and women (8.3 to 10.3 years). However, the magnitude of gender differences in time to first admission remained relatively stable within this time period (0.7 years in 1995, 0.9 years in 2014). After age 60, Danish men had consistently higher rates of admission for cardiovascular conditions and neoplasms, but lower rates of admission for injuries, musculoskeletal disorders, and sex-specific causes. Although admission rates for both genders have generally declined over the last decades, the same major causes of admission accounted for the gender gap. Persistent gender differences in causes of admission are, therefore, important to consider when planning the delivery of health care in times of population ageing.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10433-021-00614-w.

Use of Counterfactual Population Projections for Assessing the Demographic Determinants of Population Ageing

Counterfactual population projections have been used to estimate the contributions of fertility and mortality to population ageing, a method recently designated as the gold standard for this purpose. We analyse projections with base years between 1850 and 1950 for 11 European countries with long-run demographic data series to estimate the robustness of this approach. We link this approach with stable population theory to derive quantitative indicators of the role of fertility and mortality; consider ways of incorporating net migration; and examine the effect of using alternative indicators of population ageing. A number of substantive and technical weaknesses in the counterfactual projection approach are identified: (1) the conclusions are very sensitive to the choice of base year. Specifically, the level of base year fertility has a major influence on whether fertility or mortality is considered the main driver of population ageing. (2) The method is not transitive: results for two adjacent intervals are unrelated to results for the combined period. Therefore, overall results cannot be usefully allocated between different sub-intervals. (3) Different ageing indices tend to produce similar qualitative conclusions, but quantitative results may differ markedly. (4) Comparisons of alternative models should be with a fixed fertility and mortality projection model rather than with the baseline values as usually done. (5) The standard counterfactual projections approach concatenates the effects of initial age structure and subsequent fertility and mortality rates: methods to separate these components are derived.

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.

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.

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 rise in the number of long-term survivors from different diseases can slow the increase in life expectancy of the total population

Background

Recent improvements in life expectancy in many countries stem from reduced mortality from cardiovascular disease and cancer above the age of 60. This is the combined result of decreased incidence and improved survival among those with disease. The latter has led to a higher proportion in the population of people with a past history of disease. This is a group with higher mortality than the general population. How growing shares of persons with past history of disease and improved survival with disease have affected changes in life expectancy of the total population is the objective of this paper.

Methods

Using register data for the total Swedish population, we stratified the population based on whether individuals have been diagnosed with myocardial infarction, stroke, hip fracture, colon cancer, or breast cancer. Using a novel decomposition approach, we decomposed the changes in life expectancy at age 60 between 1994 and 2016 into contributions from improved survival with disease and from changes in proportion of people with past history of disease.

Results

Improvements in survival from disease resulted in gains of life expectancy for the total population. However, while the contributions to life expectancy improvements from myocardial infarction, stroke and breast cancer were substantial, the contributions from the other diseases were minor. These gains were counteracted, to various degrees, by the increasing proportion of people with raised mortality due to a past history of disease. For instance, the impact on life expectancy by improved survival from breast cancer was almost halved by the increasing share of females with a past history of breast cancer.

Conclusion

Rising numbers of survivors of different diseases can slow the increase in life expectancy. This dynamic may represent the costs associated with successful treatment of diseases, and thus, a potential “failure of success.” This dynamic should be considered when assessing mortality and life expectancy trends. As populations are aging and disease survival continues to improve, this issue is likely to become even more important in the future.

Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality

The population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries at any given time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy, Germany, Spain, and New York City over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late June 2020, CFRs varied from 2.2% in South Korea to 14.0% in Italy. The age-structure of detected cases often explains more than two-thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 14.0% between March 9 and June 30, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well-designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.

The impact of violence on Venezuelan life expectancy and lifespan inequality

BACKGROUND

Venezuela is one of the most violent countries in the world. According to the United Nations, homicide rates in the country increased from 32.9 to 61.9 per 100 000 people between 2000 and 2014. This upsurge coincided with a slowdown in life expectancy improvements. We estimate mortality trends and quantify the impact of violence-related deaths and other causes of death on life expectancy and lifespan inequality in Venezuela.

METHODS

Life tables were computed with corrected age-specific mortality rates from 1996 to 2013. From these, changes in life expectancy and lifespan inequality were decomposed by age and cause of death using a continuous-change model. Lifespan inequality, or variation in age at death, is measured by the standard deviation of the age-at-death distribution.

RESULTS

From 1996 to 2013 in Venezuela, female life expectancy rose 3.57 [95% confidence interval (CI): 3.08-4.09] years [from 75.79 (75.98-76.10) to 79.36 (78.97-79.68)], and lifespan inequality fell 1.03 (-2.96 to 1.26) years [from 18.44 (18.01-19.00) to 17.41 (17.30-18.27)]. Male life expectancy increased 1.64 (1.09-2.25) years [from 69.36 (68.89-59.70) to 71.00 (70.53-71.39)], but lifespan inequality increased 0.95 (-0.80 to 2.89) years [from 20.70 (20.24-21.08) to 21.65 (21.34-22.12)]. If violence-related death rates had not risen over this period, male life expectancy would have increased an additional 1.55 years, and lifespan inequality would have declined slightly (-0.31 years).

CONCLUSIONS

As increases in violence-related deaths among young men (ages 15-39) have slowed gains in male life expectancy and increased lifespan inequality, Venezuelan males face more uncertainty about their age at death. There is an urgent need for more accurate mortality estimates in Venezuela.

Dynamics of life expectancy and life span equality

As people live longer, ages at death are becoming more similar. This dual advance over the last two centuries, a central aim of public health policies, is a major achievement of modern civilization. Some recent exceptions to the joint rise of life expectancy and life span equality, however, make it difficult to determine the underlying causes of this relationship. Here, we develop a unifying framework to study life expectancy and life span equality over time, relying on concepts about the pace and shape of aging. We study the dynamic relationship between life expectancy and life span equality with reliable data from the Human Mortality Database for 49 countries and regions with emphasis on the long time series from Sweden. Our results demonstrate that both changes in life expectancy and life span equality are weighted totals of rates of progress in reducing mortality. This finding holds for three different measures of the variability of life spans. The weights evolve over time and indicate the ages at which reductions in mortality increase life expectancy and life span equality: the more progress at the youngest ages, the tighter the relationship. The link between life expectancy and life span equality is especially strong when life expectancy is less than 70 y. In recent decades, life expectancy and life span equality have occasionally moved in opposite directions due to larger improvements in mortality at older ages or a slowdown in declines in midlife mortality. Saving lives at ages below life expectancy is the key to increasing both life expectancy and life span equality.

Monitoring trends and differences in COVID-19 case-fatality rates using decomposition methods: Contributions of age structure and age-specific fatality

The population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries at any given time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy, Germany, Spain, and New York City over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late June 2020, CFRs varied from 2.2% in South Korea to 14.0% in Italy. The age-structure of detected cases often explains more than two-thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 14.0% between March 9 and June 30, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well-designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.

The Mechanism Underlying Change in the Sex Gap in Life Expectancy at Birth: An Extended Decomposition

The relationship between differential mortality rates and differences in life expectancy is well understood, but how changing differential rates translate into changing differences in life expectancy has not been fully explained. To elucidate the mechanism involved, this study extends existing decomposition methods. The extended method decomposes change in the sex gap in life expectancy at birth into three components capturing the effects of the sex difference in mortality improvement (ρ-effect), life table deaths density by age (f-effect), and remaining life expectancy by age (e-effect). These three effects oppose and augment each other, depending on relative change in sex-differential mortality rates. The new method is applied to period data for 35 countries and cohort data for 25 countries. The results demonstrate how the mechanism, involving the three effects, operates to determine change in the sex difference in life expectancy. We observe the pivotal importance of the f-effect, which is predominantly negative because of lower female mortality, in favoring narrowing rather than widening of the sex gap, in shifting the overall effect to younger ages, and in exaggerating fluctuations due to crisis mortality. The new decomposition provides a more detailed basis for substantive analyses examining change in differences in life expectancy.

Impact of Coming Demographic Changes on the Number of Adults in Need of Care for Hypertension in Brazil, China, India, Indonesia, Mexico, and South Africa

Over the coming decades, middle-income countries are expected to undergo substantial demographic changes. We estimated the consequences of these changes on the number of adults in need of hypertension care between 2015 and 2050 using nationally representative household-survey data collected in Brazil, China, India, Indonesia, Mexico, and South Africa (N=770 121). To reflect unmet need for healthcare, we defined hypertension as systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg regardless of treatment status. Using a mathematical disease projection equation, we calculated the change in the number of individuals in need of hypertension care in each country that was due to changes in population size, age composition, and age-specific prevalence under various epidemiological scenarios. If the current age-specific prevalence schedule of hypertension remains unchanged until 2050, demographic changes alone will increase the number of adults in need of hypertension care by 319.7 million individuals, ranging from a relative growth of 55% in China to 151% in Mexico. Even if the age-specific prevalence of hypertension is reduced by 25% by 2050 among adults aged ≥40 years, the number of individuals in need of hypertension care will still increase by 145.9 million individuals, with relative increases ranging from 16% in China to 88% in Mexico. Overall, our results suggest that coming demographic changes in middle-income countries will overpower even ideal prevention efforts. Middle-income countries will need to massively expand healthcare services for aging-related diseases, such as hypertension, if they are to meet the virtually inevitable future increase in care needs for these conditions.

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

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

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

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

Partitioning of time trends in prevalence and mortality of lung cancer

BACKGROUND

Time trends of lung cancer prevalence and mortality are the result of three competing processes: changes in the incidence rate, stage-specific survival, and ascertainment at early stages. Improvements in these measures act concordantly to improve disease-related mortality, but push the prevalence rate in opposite directions making a qualitative interpretation difficult. The goal of this paper is to evaluate the relative contributions of these components to changes in lung cancer prevalence and mortality.

METHODS

Partitioning of prevalence and mortality trends into their components using SEER data for 1973-2013.

RESULTS

The prevalence of lung cancer increases for females and decreases for males. In 1998, the former was due to increased incidence (45%-50% of total trend), improved survival (40%-45%), and increased ascertainment at early stages (10%-15%). In males, a rapidly declining incidence rate overpowered the effects of survival and ascertainment resulting in an overall decrease in prevalence over time. Trends in lung cancer mortality are determined by incidence during 1993-2002 with noticeable contribution of survival after 2002.

CONCLUSION

Lung cancer incidence was the main driving force behind trends in prevalence and mortality. Improved survival played essential role from 2000 onwards. Trends in stage ascertainment played a small but adverse role. Our results suggest that further improvement in lung cancer mortality can be achieved through advances in early stage ascertainment, especially for males, and that in spite of success in treatment, adenocarcinoma continues to exhibit adverse trends (especially in female incidence) and its role among other histology-specific lung cancers will increase in the near future.

The contribution of urbanization to changes in life expectancy in Scotland, 1861-1910

During the nineteenth and early twentieth centuries, urban populations in Europe and North America continued to be afflicted by very high mortality as rapid urbanization and industrialization processes got underway. Here we measure the effect of population redistribution from (low-mortality) rural to (high-mortality) urban areas on changes in Scottish life expectancy at birth from 1861 to 1910. Using vital registration data for that period, we apply a new decomposition method that decomposes changes in life expectancy into the contributions of two main components: (1) changes in mortality; and (2) compositional changes in the population. We find that, besides an urban penalty (higher mortality in urban areas), an urbanization penalty (negative effect of population redistribution to urban areas on survival) existed in Scotland during the study period. In the absence of the urbanization penalty, Scottish life expectancy at birth could have attained higher values by the beginning of the twentieth century.

Upsurge of Homicides and Its Impact on Life Expectancy and Life Span Inequality in Mexico, 2005-2015

OBJECTIVES

To quantify the effect of the upsurge of violence on life expectancy and life span inequality in Mexico after 2005.

METHODS

We calculated age- and cause-specific contributions to changes in life expectancy and life span inequality conditional on surviving to age 15 years between 1995 and 2015. We analyzed homicides, medically amenable conditions, diabetes, ischemic heart diseases, and traffic accidents by state and sex.

RESULTS

Male life expectancy at age 15 years increased by more than twice in 1995 to 2005 (1.17 years) than in 2005 to 2015 (0.55 years). Life span inequality decreased by more than half a year for males in 1995 to 2005, whereas in 2005 to 2015 the reduction was about 4 times smaller. Homicides for those aged between 15 and 49 years had the largest effect in slowing down male life expectancy and life span inequality. Between 2005 and 2015, three states in the north experienced life expectancy losses while 5 states experienced increased life span inequality.

CONCLUSIONS

Ten years into the upsurge of violence, Mexico has not been able to reduce the homicide levels to those before 2005. Life expectancy and life span inequality stagnated since 2005 for young men at the national level. In some states, males live shorter lives than in 2005, on average, and experience higher uncertainty in their eventual death.

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.

Trends in the Quantiles of the Life Table Survivorship Function

We offer a new approach for modeling past trends in the quantiles of the life table survivorship function. Trends in the quantiles are estimated, and the extent to which the observed patterns fit the unit root hypothesis or, alternatively, an innovative outlier model, are conducted. Then a factor model is applied to the detrended data, and it is used to construct quantile cycles. We enrich the ongoing discussion about human longevity extension by calculating specific improvements in the distribution of the survivorship function, across its full range, and not only at the central-age ranges. To illustrate our proposal, we use data for the UK from 1922 to 2013. We find that there is no sign in the data of any reduction in the pace of longevity extension during the last decades.