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Objective: The objective of the present study was to examine if the change in the suicide rate is associated with individuals' use of antidepressants as has been suggested by ecological studies.Design: Decomposition of suicide rates by antidepressant treatment group.Setting: Population-based record linkage.Participants: All individuals aged 50 years and older living in Denmark between 1 January 1996 and 31 December 2000 (N = 2 100 808).Main outcome measures: Suicide rates are calculated according to current antidepressant treatment status (no treatment, tricyclic antidepressants (TCA), selective serotonin reuptake inhibitors (SSRI), other antidepressants). The change in the suicide rate during 1996-2000 was decomposed by treatment group.Results: Only one in five older adults dying by suicide was in treatment at the time of death. Whereas the male suicide rate declined by 9.7 suicides per 100 000, recipients of antidepressants contributed to the decline by 0.9 suicides. Women redeeming antidepressant prescriptions accounted for 0.4 suicides of the observed reduction of 3.3 per 100 000. The average suicide rates for men receiving TCA and SSRI were 153.3 and 169.0 per 100 000 person-years, respectively. Among older women, both TCA and SSRI users had an average suicide rate of 68.8 per 100 000 over the period examined.Conclusions: Just a small proportion of older adults dying by suicide were found to be in treatment with antidepressants at the time of death. Individuals in active treatment with antidepressants seem to account for 10% of the decline in the suicide rate. Nevertheless, suicides might be prevented by more effective treatment. [ABSTRACT FROM AUTHOR]

Background: The percentage of the world's population with disabilities is estimated to be 16%, although its distribution and intensity varies within nations. We aim to disentangle the degree and types of disabilities, estimate the years spent with more severe disabilities, and analyze their distribution across states and between sexes in Mexico., Methods: The Mexican Census of 2020 includes information on disabilities, which allows the study of its national distribution. We used life tables and the Sullivan method to calculate the number of years spent with disability (NYSD) and its percentage with respect to life expectancy for each state and each sex., Results: In Mexico, the population with disabilities is estimated to be 16.5%. Of this total, 69% have milder disabilities, while the remaining 31% have more severe disabilities. At age eighteen, there is a higher NYSD from more severe disabilities for females with 5.67 years (95% CI 5.66 to 5.69) as opposed to males with 3.66 years (95% CI 3.65 to 3.67). Across states, a more homogeneous distribution with lower NYSD is observed for men (between 2.44 and 5.69 years) than for women (4.14 and 8.08 years). A north-south division can also be observed, with particularly notorious disadvantages among coastal states, which is more distinctive among women., Conclusions: This study shows that comparing the number of years spent with disability and the total life expectancy between subpopulations is essential for monitoring the well-being of aging populations, guiding policy decisions, and promoting a society that values and supports all individuals, regardless of their abilities., (© 2024. The Author(s).)

Air pollution in India is a foremost environmental risk factor that affects human health. This study first investigates the geographical distribution of ambient and household air pollution (HAP) and then examines the associated mortality risk. Data on fine particulate matter (PM 2.5 ) concentration has been extracted from the Greenhouse Gas Air Pollution Interactions and Synergies (GAINS) model. HAP, mortality and socio-demographic data were extracted from the National Family and Health Survey-5, India, 2019-2021. Regression models were applied to see the difference in age-group mortality by different pollution parameters. The districts with PM 2.5 concentration above the National Ambient Air Quality Standard (NAAQS) level of 40 μg/m 3 show a higher risk of neonatal (OR-1.86, CI 1.418-2.433), postneonatal (OR-2.04, CI 1.399-2.971), child (OR-2.19, CI 0.999-4.803) and adult death (OR-1.13, CI 1.060-1.208). The absence of a separate kitchen shows a higher probability of neonatal (OR: 1.18, CI 1.074-1.306) and adult death (OR-1.06, CI 1.027-1.088). The interaction between PM 2.5 levels above NAAQS and HAP leads to a substantial rise in mortality observed for neonatal (OR 1.19 CI 1.051-1.337), child (OR 1.17 CI 1.054-1.289), and adult (OR 1.13 CI 1.096-1.168) age groups. This study advocates that there is a strong positive association between ambient and HAP and mortality risk. PM 2.5 pollution significantly contributes to the mortality risk in all age groups. Children are more vulnerable to HAP than adults. In India, policymakers should focus on reducing the anthropogenic PM 2.5 emission at least to reach the NAAQS, which can substantially reduce disease burden and, more precisely, mortality., Competing Interests: The authors declare no conflicts of interest relevant to this study., (© 2024 The Author(s). GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union.)

Background: Before the COVID-19 pandemic, stagnating life expectancy trends were reported in some high-income countries (HICs). Despite previous evidence from country-specific studies, there is a lack of comparative research that provides a broader perspective and challenges existing assumptions. This study aims to examine longevity trends and patterns in six English-speaking countries (Australia, Canada, Ireland, New Zealand, United Kingdom, United States) by combining period and cohort perspectives and to compare them with other HICs., Methods: Using data from the Human Mortality and World Health Organization Mortality Databases, we estimated partial life expectancy, lifespan inequality and cohort survival differences for 1970-2021, as well as the contribution of causes of death to the gap in life expectancy between English-speaking countries and the average for other HICs in 2017-19., Results: In the pre-pandemic period, the increase in life expectancy slowed in all English-speaking countries, except Ireland, mainly due to stagnating or rising mortality at young-middle ages. Relative to other HICs, those born in Anglophone countries since the 1970s experienced relative survival disadvantage, largely attributable to injuries (mainly suicides) and substance-related mortality (mainly poisonings). In contrast, older cohorts enjoyed advantages for females in Australia and Canada and for males in all English-speaking countries except the United States., Conclusions: Although future gains in life expectancy in wealthy societies will increasingly depend on reducing mortality at older ages, adverse health trends at younger ages are a cause for concern. This emerging and avoidable threat to health equity in English-speaking countries should be the focus of further research and policy action., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Population aging is an important and increasingly relevant area of study for demographers. A growing body of research seeks to determine how long-term changes in births, mortality, and migration-the three drivers of any demographic process-have shaped the present aging situation. Using variable-r decomposition and cohort data, this research note presents a formula for the change in the old-age dependency ratio to determine the extent to which relative changes in births, as well as in mortality and migration rates, contribute to aging. This perspective provides a careful and in-depth picture of aging and contributes to the debate concerning whether changes in births or mortality have had the strongest effect on population aging. When applied to Australia, the United States, and several European populations, the decomposition of the old-age dependency ratio shows that aging occurred in all populations and that changes in both births and mortality contributed to this aging. Analysis of these populations demonstrates that although they differed regarding which of these factors contributed more, changes in births prevailed as the more significant factor. In nearly all populations, migration decreased the rate of population aging., (Copyright © 2024 The Authors.)

Keyfitz and Leser's life table entropy was proposed to serve as a relative inequality in mortality measure. Entropy considers the variation around the age at death relative to the length of lifespan in a population, allowing comparisons across time and populations. It is used widely in period and cohort applications. Here, we propose extending this measure and present an index that incorporates the history of survival of all cohorts present at a given time, namely the cross-sectional average length of life entropy, or CAL-entropy ( H CAL ). We decompose cross-population differences of CAL-entropy into the contribution of longevity and lifespan variation, and the change of those differences across time. Our illustrations show that populations are converging regarding lifespan inequality. Lifespan variation holds a noticeable share in the CAL-entropy gap among selected European populations. Longevity held once a pronounced share in CAL-entropy differences and their change, but its influence has receded over the years. The US demonstrates a unique trend where it performs worse across time compared to the selected European populations, and lifespan variation has played a major role in this process. This study signals the importance of lifespan variation in reducing inequality in mortality among developed and longevous populations., (© 2024. The Author(s).)

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

A population's current growth rate is determined jointly by changes in fertility, mortality, and migration. This overall growth rate is also the average of age-specific growth rates, which can be decomposed into the result of historical changes in fertility, mortality, and migration. However, doing so requires more than 100 years of historical data, meaning that such analyses are possible only in a select few populations. In this research note, we propose an adapted version of the variable-r model to measure contributions to the population growth rate for countries with shorter demographic series. In addition, we extend this model to explore the contribution of subnational changes to the national population growth rate. Our results demonstrate that the age-specific growth rates obtained from short historical series, say 25 years, closely match those of the longer series. These abbreviated age-specific growth rates closely resemble the growth rate at birth of their respective cohorts, which is the major determinant of population growth, except at older ages where mortality becomes the main explanatory element. Exploring subnational populations, we find considerable heterogeneity in the age profile of the components of growth and find that the most populous regions tend to have an outsized impact on national-level growth., (Copyright © 2024 The Authors.)

Introduction: Understanding mortality variability by age and cause is critical to identifying intervention and prevention actions to support disadvantaged populations. We assessed mortality changes in two rural South African populations over 25 years covering pre-AIDS and peak AIDS epidemic and subsequent antiretroviral therapy (ART) availability., Methods: Using population surveillance data from the Agincourt Health and Socio-Demographic Surveillance System (AHDSS; 1994-2018) and Africa Health Research Institute (AHRI; 2000-2018) for 5-year periods, we calculated life expectancy from birth to age 85, mortality age distributions and variation, and life-years lost (LYL) decomposed into four cause-of-death groups., Results: The AIDS epidemic shifted the age-at-death distribution to younger ages and increased LYL. For AHDSS, between 1994-1998 and 1999-2003 LYL increased for females from 13.6 years (95% CI 12.7 to 14.4) to 22.1 (95% CI 21.2 to 23.0) and for males from 19.9 (95% CI 18.8 to 20.8) to 27.1 (95% CI 26.2 to 28.0). AHRI LYL in 2000-2003 was extremely high (females=40.7 years (95% CI 39.8 to 41.5), males=44.8 years (95% CI 44.1 to 45.5)). Subsequent widespread ART availability reduced LYL (2014-2018) for women (AHDSS=15.7 (95% CI 15.0 to 16.3); AHRI=22.4 (95% CI 21.7 to 23.1)) and men (AHDSS=21.2 (95% CI 20.5 to 22.0); AHRI=27.4 (95% CI 26.7 to 28.2)), primarily due to reduced HIV/AIDS/TB deaths in mid-life and other communicable disease deaths in children. External causes increased as a proportion of LYL for men (2014-2018: AHRI=25%, AHDSS=17%). The share of AHDSS LYL 2014-2018 due to non-communicable diseases exceeded pre-HIV levels: females=43%; males=40%., Conclusions: Our findings highlight shifting burdens in cause-specific LYL and persistent mortality differentials in two populations experiencing complex epidemiological transitions. Results show high contributions of child deaths to LYL at the height of the AIDS epidemic. Reductions in LYL were primarily driven by lowered HIV/AIDS/TB and other communicable disease mortality during the ART periods. LYL differentials persist despite widespread ART availability, highlighting the contributions of other communicable diseases in children, HIV/AIDS/TB and external causes in mid-life and non-communicable diseases in older ages., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Background: Alongside average health measures, namely, life expectancy (LE) and healthy life expectancy (HLE), we sought to investigate the inequality in lifespan and healthy lifespan at the worldwide level with an alternative indicator., Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, we evaluated the global distribution of life disparity (LD) and healthy life disparity (HLD) for 204 countries and territories in 2019 by sex and socio-demographic index (SDI), and also explored the relationships between average and variation health indicators., Results: Substantial gaps in all observed health indicators were found across SDI quintiles. For instance, in 2019, for low SDI, female LE and HLE were 67.3 years (95% confidence interval 66.8, 67.6) and 57.4 years (56.6, 57.9), and their LD and HLD were 16.7 years (16.5, 17.0) and 14.4 years (14.1, 14.7). For high SDI, female LE and HLE were greater [83.7 years (83.6, 83.7) and 70.2 years (69.3, 70.7)], but their LD and HLD were smaller [10.4 years (10.3, 10.4) and 7.9 years (7.7, 8.0)]. Besides, all estimates varied across populations within each SDI quintile. There were also gaps in LD and HLD between males and females, as those found in LE and HLE., Conclusion: In addition to the disadvantaged LE and HLE, greater LD and HLD were also found in low SDI countries and territories. This reveals the serious challenge in achieving global health equality. Targeted policies are thus necessary for improving health performance among these populations., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Public Health Association.)

Background: Australia provides a valuable international case study of life expectancy during the pandemic. In contrast to many other countries, it experienced relatively stringent restrictions and low COVID-19 mortality during 2020-21, followed by relaxation of these restrictions when high vaccination rates were achieved. This study measures Australia's life expectancy trends and the contributions of age group and causes of death, during the pandemic., Methods: Trends in life expectancy at birth in Australia and its states and territories were measured from 2020 to 2022. The contributions of age group and cause of death to these trends were measured using decomposition methods. Life expectancy was compared with other high-income countries., Results: Australia's life expectancy fell by more than half a year in 2022, following a sharp increase in 2020 and moderate decline in 2021. For the 3 years 2020 to 2022, life expectancy was 0.13 years (95% confidence interval 0.07-0.19) higher for males and 0.09 years (0.03-0.14) higher for females versus 2017-19. Australia's life expectancy increase in 2020 was larger than that in the vast majority of other high-income countries, but its decline in 2022 was greater than in other countries whose life expectancy rose in the first year of the pandemic. The small negative contribution of COVID-19 deaths to life expectancy in Australia was more than offset by lower non-communicable disease mortality. There were only small differences in life expectancy change between the states with the most stringent restrictions (Victoria and New South Wales) and the rest of Australia., Conclusions: Australia's life expectancy trends during 2020-22 were relatively favourable compared with other high-income countries, with the exception of its sharp decline in 2022 once restrictions were loosened., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Multistate modeling is a commonly used method to compute healthy life expectancy. However, there is currently no analytical method to decompose the components of differentials in summary measures calculated from multistate models. In this research note, we propose a derivative-based method to decompose the differentials in population-based health expectancies estimated via a multistate model into two main components: the proportion resulting from differences in initial health structure and the proportion resulting from differences in health transitions. We illustrate the method using data on activities of daily living from the U.S. Health and Retirement Study to decompose the sex differential in disability-free life expectancy (HLE) among older Americans. Our results suggest that the sex gap in HLE results primarily from differences in transition rates between disability states rather than from the initial health distribution of female and male populations. The methods introduced here will enable researchers, including those working in fields other than health, to decompose the relative contribution of initial population structure and transition probabilities to differences in state-specific life expectancies from multistate models., (Copyright © 2023 The Authors.)

Air particulate matter (PM) and its harmful effects on human health are of great concern globally due to all-cause and cause-specific mortality impacts across different population groups. While Europe has made significant progress in reducing particulate air pollution-related mortality through innovative technologies and policies, many countries in Asia-Pacific region still rely on high-polluting technologies and have yet to implement effective policies to address this issue, resulting in higher levels of mortality due to air pollution in the region. This study has three aims related to quantifying life-years lost (LYL) attributable to PM, and further separated into ambient PM and household air pollution (HAP): (1) to investigate LYL by causes of death; (2) to compare LYL between Asia-Pacific (APAC) and Europe; and (3) to assess LYL across different socio-demographic index (SDI) countries. The data used come from the Institute for Health Metrics and Evaluation (IHME) and Health Effects Institute (HEI). Our results show that average LYL due to PM in APAC was greater than in Europe, with some Pacific island countries particularly affected by the exposure to HAP. Three quarters of LYL came from premature deaths by ischemic heart disease and stroke, in both continents. There were significant differences between SDI groups for causes of death due to ambient PM and HAP. Our findings call for urgent improvement of clean air to reduce indoor and outdoor air pollution-related mortality in the APAC region., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

In addition to fundamental mortality metrics such as mortality rates and mortality rate ratios, life expectancy is also commonly used to investigate excess mortality among a group of individuals diagnosed with specific diseases or conditions. However, as an average measure, life expectancy ignores the heterogeneity in lifespan. Interestingly, the variation in lifespan-a measure commonly used in the field of demography-has not been estimated for people with a specific condition. Based on recent advances in methodology in research within epidemiology and demography, we discuss two metrics, namely, the average life disparity and average lifetable entropy after diagnosis, which estimate the variation in lifespan for time-varying conditions in both absolute and relative aspects. These metrics are further decomposed into early and late components, separated by their threshold ages. We use mortality data for women with mental disorders from Danish registers to design a population-based study and measure such metrics. Compared with women from the general population, women with a mental disorder had a shorter average remaining life expectancy after diagnosis (37.6 years vs. 44.9 years). In addition, women with mental disorders also experienced a larger average lifespan variation, illustrated by larger average life disparity (9.5 years vs 9.1 years) and larger average lifetable entropy (0.33 vs 0.27). More specifically, we found that women with a mental disorder had a larger early average life disparity but a smaller late average life disparity. Unlike the average life disparity, both early and late average lifetable entropy were higher for women with mental disorders compared to the general population. In conclusion, the metric proposed in our study complements the current research focusing merely on life expectancy and further provides a new perspective into the assessment of people's health associated with time-varying conditions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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

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

We introduce a method for decomposing differences in healthy cross-sectional average length of life (HCAL). HCAL provides an alternative to the health expectancy (HE) indicator by including the health and mortality history of all cohorts present at a given time. While decompositions of HE differences account for contributions made by health and mortality, differences in HCAL are further disentangled into cohort-specific contributions. In this research note we illustrate the technique by analyzing the sex gap in health and mortality for the United States. We use the harmonized version of the Health and Retirement Survey data and define the health status in terms of activities of daily living. Our results suggest that the female advantage in cohort survival is partly compensated by women's lower cohort-specific health levels. At older ages, however, the sex differences in health are not large enough to compensate men's disadvantage in cohort survival., (Copyright © 2022 The Authors.)

The demographic balance equation relates the population growth rate with crude rates of fertility, mortality, and net migration. All these rates refer to changes occurring between two time points, say, t and t + h. However, this fundamental balance equation overlooks the contribution of historical fertility, mortality, and migration in explaining these population counts. Because of this, the balance equation only partially explains a change in growth rate between time t and t + h as it does not include the contribution of historical population trends in shaping the population at time t. The overall population growth rate can also be expressed as the weighted average of age-specific growth rates. In this article, we develop a method to decompose the historical drivers of current population growth by recursively employing the variable-r method on the population's average age-specific growth rates. We illustrate our method by identifying the unique contributions of survival progress, migration change, and fertility decline for current population growth in Denmark, England and Wales, France, and the United States. Our results show that survival progress is mainly having an effect on population growth at older ages, although accounting for indirect historical effects illuminates additional contributions at younger ages. Migration is particularly important in Denmark and England and Wales. Finally, we find that across all populations studied, historical fertility decline plays the largest role in shaping recent reductions in population growth rates., (Copyright © 2022 The Authors.)

Objectives: To examine the length and dispersion level of lifespan for the subnational populations in China, identify the urban-rural gap and sex differences, and analyse the contribution made by causes of death., Setting: Cause-specific mortality data extracted from the Chinese Disease Surveillance Points system, grouped by sex and urban/rural residence., Primary Outcome Measures: Life expectancy and lifespan disparity are used to measure the length and dispersion level of lifespan, respectively. Cause-specific contributions are obtained by contrasting cause-deleted life expectancy and lifespan disparities with observed values., Participants: Aggregated national data gathered from over 605 surveillance points across China, covering over 264 million people by 2016 (about 19.14% of the total Chinese population)., Results: In the decade under observation, all subpopulations in China, by area and sex, experienced increases in life expectancy and decreases in lifespan disparity, while causes of deaths contributed differently. For example, based on the 2016 data, if cardiovascular diseases were deleted, there would be an increase in life expectancy that ranges from 5.59 years for urban males to 6.69 years for rural females. However, also lifespan disparity would increase, ranging from 0.81 years for urban females to 1.37 years for rural males., Conclusions: In China, the urban-rural gaps in both life expectancy and lifespan disparity are shrinking as the rural residents are catching up fast, while the gender gaps remain large, and even widening. Causes of death with different age distribution patterns contribute differently to the level and direction of the urban-rural and sex differentials in life expectancy and lifespan disparity. Sex differentials were observed in cardiovascular diseases, respiratory diseases, lung and liver cancers, and external causes, while urban-rural differences were found in lung and breast cancers, and external causes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Lifespan variation is a key metric of mortality that describes both individual uncertainty about the length of life and heterogeneity in population health. We propose a novel and timely lifespan variation measure, which we call the cross-sectional average inequality in lifespan, or CAL†. This new index provides an alternative perspective on the analysis of lifespan inequality by combining the mortality histories of all cohorts present in a cross-sectional approach. We demonstrate how differences in the CAL† measure can be decomposed between populations by age and cohort to explore the compression or expansion of mortality in a cohort perspective. We apply these new methods using data from 10 low-mortality countries or regions from 1879 to 2013. CAL† reveals greater uncertainty in the timing of death than the period life table-based indices of variation indicate. Also, country rankings of lifespan inequality vary considerably between period and cross-sectional measures. These differences raise intriguing questions as to which temporal dimension is the most relevant to individuals when considering the uncertainty in the timing of death in planning their life courses., (Copyright © 2021 The Authors.)

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

Objectives: To investigate the effect that particulate matter with a diameter of 2.5 μg (PM 2.5 ) had on mortality in Asian populations in years 2000-2015., Setting: Mortality and level of PM 2.5 data from the United Nations, Global Burden of Disease and University of Chicago were used., Outcome Measures: Age pattern of mortality and the number of life-years lost (LYL) attributable to PM 2.5 in years 2000-2015. LYL were further separated into causes of death to quantify the contribution of each cause., Results: Ischaemic heart disease (IHD) mortality increased to represent over 31% of the LYL attributable to PM 2.5 between 2005-2010 and 2010-2015 in Asia (females 31% and males 35%). However, great diversity in LYL attributable to PM 2.5 by causes-of-death were found across the region, with IHD proportions of LYL ranging from 25% to 63% for males from Eastern and Central Asia, respectively. Similar diversity was observed for mortality attributable to PM 2.5 for other causes of death across Asia: chronic obstructive pulmonary disease (LYL ranging from 6% to 28%), lung cancer (4% to 20%) and stroke (11% to 22%)., Conclusion: PM 2.5 is a crucial component in the rising health effects in Asia. The diverse trends in cause-specific mortality attributable to PM 2.5 creates a further challenge for health systems in the region. These findings highlight that immediate interventions are needed to mitigate the increasing levels of air pollution and with that reduce its detrimental effect on the health and mortality of Asian populations., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

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., (Copyright © 2021 The Authors.)

Life expectancy is most commonly measured for a period (corresponding to mortality within a given year) or for a specific birth cohort. Although widely used, period and cohort life expectancy have limitations as their time-trends often show disparities and can mask the historical mortality experience of all cohorts present at a given time. The truncated cross-sectional average length of life, or TCAL, is a period measure including all available cohort mortality information, irrespective of whether all cohort members have died. It is particularly useful for comparing cohort mortality between populations. This study extends TCAL by disentangling causes of death contributions. The strength of the approach is that it allows identification of mortality differences in cohorts with members still alive, as well as identification of which ages and causes of death contribute to mortality differentials between populations. Application of the method to Japan shows that over the period 1950-2014 a major contributor to TCAL differences with other high-longevity countries was its lower cardiovascular disease mortality., (© The Author(s) 2020; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Premature mortality is often a neglected component of overall deaths, and the most difficult to identify. However, it is important to estimate its prevalence. Following Pearson's theory about mortality components, a definition of premature deaths and a parametric model to study its transformations are introduced. The model is a mixture of three distributions: a Half Normal for the first part of the death curve and two Skew Normals to fit the remaining pieces. One advantage of the model is the possibility of obtaining an explicit equation to compute life expectancy at birth and to break it down into mortality components. We estimated the mixture model for Sweden, France, East Germany and Czech Republic. In addition, to the well-known reduction in infant deaths, and compression and shifting trend of adult mortality, we were able to study the trend of the central part of the distribution of deaths in detail. In general, a right shift of the modal age at death for young adults is observed; in some cases, it is also accompanied by an increase in the number of deaths at these ages: in particular for France, in the last twenty years, premature mortality increases., (© The Author(s) 2020.)

Life expectancy at a given age is a summary measure of mortality rates present in a population (estimated as the area under the survival curve), and represents the average number of years an individual at that age is expected to live if current age-specific mortality rates apply now and in the future. A complementary metric is the number of Life Years Lost, which is used to measure the reduction in life expectancy for a specific group of persons, for example those diagnosed with a specific disease or condition (e.g. smoking). However, calculation of life expectancy among those with a specific disease is not straightforward for diseases that are not present at birth, and previous studies have considered a fixed age at onset of the disease, e.g. at age 15 or 20 years. In this paper, we present the R package lillies (freely available through the Comprehensive R Archive Network; CRAN) to guide the reader on how to implement a recently-introduced method to estimate excess Life Years Lost associated with a disease or condition that overcomes these limitations. In addition, we show how to decompose the total number of Life Years Lost into specific causes of death through a competing risks model, and how to calculate confidence intervals for the estimates using non-parametric bootstrap. We provide a description on how to use the method when the researcher has access to individual-level data (e.g. electronic healthcare and mortality records) and when only aggregated-level data are available., Competing Interests: The authors have declared that no competing interests exist.

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.

Despite an overall downward trend in child sex ratios in India, some of the most imbalanced districts in 2001 (fewer girls than boys) showed signs of becoming more balanced in 2011. This analysis looked in depth at these districts to better understand the nature of the improvement in the child sex ratio using two rounds of data from the Census of India from 2001 and 2011. Data were used from the 153 districts that showed improvement in their child sex ratio between 2001 and 2011. The improvement was decomposed into: (1) less sex-selective abortion and (2) improved girl compared with boy mortality. Most of the improvement in child sex ratios were shown to be due to reductions in sex-selective abortion, although this still made up the majority of the cause of imbalanced sex ratios in 2011. Child sex ratio improvement has been happening in both rural and urban areas of India, and there is evidence of stagnation in mortality decline for urban girls.

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.

Background: Systematic reviews have consistently shown that individuals with mental disorders have an increased risk of premature mortality. Traditionally, this evidence has been based on relative risks or crude estimates of reduced life expectancy. The aim of this study was to compile a comprehensive analysis of mortality-related health metrics associated with mental disorders, including sex-specific and age-specific mortality rate ratios (MRRs) and life-years lost (LYLs), a measure that takes into account age of onset of the disorder., Methods: In this population-based cohort study, we included all people younger than 95 years of age who lived in Denmark at some point between Jan 1, 1995, and Dec 31, 2015. Information on mental disorders was obtained from the Danish Psychiatric Central Research Register and the date and cause of death was obtained from the Danish Register of Causes of Death. We classified mental disorders into ten groups and causes of death into 11 groups, which were further categorised into natural causes (deaths from diseases and medical conditions) and external causes (suicide, homicide, and accidents). For each specific mental disorder, we estimated MRRs using Poisson regression models, adjusting for sex, age, and calendar time, and excess LYLs (ie, difference in LYLs between people with a mental disorder and the general population) for all-cause mortality and for each specific cause of death., Findings: 7 369 926 people were included in our analysis. We found that mortality rates were higher for people with a diagnosis of a mental disorder than for the general Danish population (28·70 deaths [95% CI 28·57-28·82] vs 12·95 deaths [12·93-12·98] per 1000 person-years). Additionally, all types of disorders were associated with higher mortality rates, with MRRs ranging from 1·92 (95% CI 1·91-1·94) for mood disorders to 3·91 (3·87-3·94) for substance use disorders. All types of mental disorders were associated with shorter life expectancies, with excess LYLs ranging from 5·42 years (95% CI 5·36-5·48) for organic disorders in females to 14·84 years (14·70-14·99) for substance use disorders in males. When we examined specific causes of death, we found that males with any type of mental disorder lost fewer years due to neoplasm-related deaths compared with the general population, although their cancer mortality rates were higher., Interpretation: Mental disorders are associated with premature mortality. We provide a comprehensive analysis of mortality by different types of disorders, presenting both MRRs and premature mortality based on LYLs, displayed by age, sex, and cause of death. By providing accurate estimates of premature mortality, we reveal previously underappreciated features related to competing risks and specific causes of death., Funding: Danish National Research Foundation., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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.