Life tables of annual life expectancy and risk factors for mortality in cats in the UK.

OBJECTIVES: The aims of the present study were to generate the first life tables for the UK companion cat population overall as well as broken down by sex and breed status, and to quantify associations between mortality and traits such as sex, neuter status, breed status and body weight in relation to mortality. METHODS: Life table construction and modelling included data on 7936 confirmed deaths in cats under primary veterinary care at clinics participating in the VetCompass Programme in 2019. The life tables were built for cats overall, female and male cats, and crossbred and purebred cats. Multivariable generalised linear regression models were generated to explore the risk factors for a shortened lifespan. RESULTS: Life expectancy at age 0 for UK companion cats overall was 11.74 years (95% confidence interval [CI] 11.61-11.87). The probability of death at each year interval increased with age from year interval 3-4, with the probability value not exceeding 0.05 before year 9. Female cats (12.51 years; 95% CI 12.32-12.69) had a 1.33-year longer life expectancy than male cats (11.18 years; 95% CI 11.01-11.38) at age 0. Among the 12 breeds (including crossbred) analysed, Burmese and Birman had the longest life expectancy at year 0, showing 14.42 years (95% CI 12.91-15.93) and 14.39 years (95% CI 12.87-15.91), respectively. Sphynx had the shortest life expectancy at year 0 among the analysed breeds at 6.68 years (95% CI 4.53-8.83). Being entire, purebred and with a non-ideal body weight were significantly linked to a decreased lifespan. CONCLUSIONS AND RELEVANCE: The life tables presented here for companion cats in the UK overall, by sex, and by crossbred and purebred cats can contribute to a better understanding of the life trajectory of cats, helping with evidence-based decision-making for cat owners and the veterinary profession. We have also provided an updated life expectancy at age 0 for various cat breeds for 2019 and showed evidence of the association between non-ideal weight and a decreased lifespan.

Measuring population health using health expectancy estimates from morbidity and mortality databases.

The progressive incorporation of quality of life indicators in health planning meets a critical need: The evaluation of the performance of health services, which are under stress by multiple causes, but in particular by an ageing population. In general, national health plans rely on health expectancies obtained using the Sullivan method. The Sullivan health expectancy index combines age-specific mortality rates and age-specific prevalence of healthy life, obtained from health surveys. The objective of this work is to investigate an equivalent estimation, using available information from morbidity and mortality datasets. Mortality and morbidity information, corresponding to years 2016 and 2017, was obtained for the population of the county of Baix Empordà (Catalonia), N = 91,130. Anonymized individual information on diagnoses, procedures and pharmacy consumption contained in the individual clinical record (ICD and ATC codes), were classified into health states. Based on the observed health transitions and mortality, life expectancies by health state were obtained from a multistate microsimulation model. Healthy life expectancies at birth and 65 years for females and males were respectively HLE0female = 39.94, HLE0male = 42.87, HLE65female = 2.43, HLE65male = 2.17. These results differed considerably from the Sullivan equivalents, e.g., 8.25 years less for HLE65female, 9.26 less for HLE65male. Point estimates for global life expectancies at birth and 65 years of age: LE0female = 85.82, LE0male = 80.58, LE65female = 22.31, LE65male = 18.86. Health indicators can be efficiently obtained from multistate models based on mortality and morbidity information, without the use of health surveys. This alternative method could be used for monitoring populations in the context of health planning. Life Expectancy results were consistent with the standard government reports. Due to the different approximation to the concept of health (data-based versus self-perception), healthy life expectancies obtained from multistate micro simulation are consistently lower than those calculated with the standard Sullivan method.

[Direct and indirect impact of COVID-19 on life expectancy at birth in Chile in 2020]. / Impacto directo e indirecto del COVID-19 en la esperanza de vida al nacer de Chile en el año 2020.

This article shows the direct and indirect impacts of COVID-19 on life expectancy in Chile in 2020, based on mortality statistics published in March 2023. To this end, a counterfactual mortality was estimated for 2020 without COVID-19; based on the pattern of mortality by cause of death from 1997 to 2019, mortality charts were created to calculate life expectancy from 2015 to 2020 and an estimation for 2020, and the difference between expected and observed life expectancy in 2020 was then separated by age group and cause of death. Life expectancy in 2020 interrupted the upward trend from 2015 to 2019, showing a decline of 1.32 years in men and 0.75 years in women compared to 2019. Compared to the estimated 2020, life expectancy was 1.51 years lower in men and 0.92 years lower in women, but the direct impact of COVID-19 on the decrease in life expectancy was greater (1.89 for men and 1.5 for women) in the 60-84 age group in men and the 60-89 age group in women. The direct negative impact of COVID-19 on life expectancy was partially mitigated by significant positive indirect impacts on two groups of causes of death: diseases of the respiratory system and infectious and parasitic diseases. This study shows the need to differentiate direct and indirect impacts of COVID-19, due to the implications for public health when the intensity of COVID-19 decreases and mobility restrictions are suspended.

El artículo muestra el impacto directo e indirecto del COVID-19 en la esperanza de vida de Chile durante el año 2020, utilizando las estadísticas de defunciones definitivas publicadas en marzo del año 2023. Para ello, se estimó una mortalidad contrafactual para año 2020 sin el COVID-19, siguiendo el patrón de mortalidad según causas de muerte desde 1997 a 2019, se elaboraron tablas de mortalidad para calcular la esperanza de vida para los años 2015 a 2020 y para el año 2020 estimado, y luego se descompuso la diferencia entre la esperanza de vida esperada y observada del año 2020 según grupos de edad y causas de muerte. La esperanza de vida del año 2020 quiebra la tendencia a su aumento entre 2015 y 2019, mostrando un retroceso, en hombres y en mujeres, con respecto al año 2019, de 1,32 y 0,75 años respectivamente. Con respecto al año 2020 estimado, la esperanza de vida del 2020 observado es 1,51 años menor en hombres y 0,92 en mujeres, pero el impacto directo del COVID-19 en pérdida de esperanza de vida fue mayor, 1,89 para los hombres y 1,5 para las mujeres, concentrándose en las edades entre los 60 y 84 años en hombres y entre 60 y 89 años en mujeres. El impacto directo negativo del COVID-19 a la esperanza de vida en parte fue contrarrestado por impactos indirectos positivos significativos en dos grupos de causas de muerte, las enfermedades del sistema respiratorio y las enfermedades infecciosas y parasitarias. El estudio muestra la necesidad de distinguir los impactos directos e indirectos del COVID-19, por la incidencia que pueden tener en la salud pública cuando el COVID-19 baje su intensidad y se eliminen las restricciones de movilidad.

Este artigo apresenta os impactos direto e indireto da COVID-19 na expectativa de vida no Chile em 2020 a partir de estatísticas de mortalidade publicadas em março de 2023. Para tanto, foi estimada uma mortalidade contrafactual para 2020 sem a COVID-19; a partir do padrão de mortalidade por causa de morte de 1997 a 2019, foram criadas tabelas de mortalidade para calcular a expectativa de vida para o período de 2015 a 2020 e para o ano estimado de 2020 e, em seguida, a diferença entre a expectativa de vida esperada e observada em 2020 foi separada por faixa etária e causa de morte. A expectativa de vida em 2020 interrompe a tendência de aumento entre 2015 e 2019, mostrando um declínio com relação a 2019 de 1,32 ano nos homens e 0,75 ano nas mulheres. Com relação ao ano estimado de 2020, a expectativa de vida observada é 1,51 ano menor nos homens e 0,92 nas mulheres, mas o impacto direto da COVID-19 na diminuição da expectativa de vida foi maior (1,89 para homens e 1,5 para mulheres), concentrando-se nas idades entre 60 e 84 anos nos homens e entre 60 e 89 anos nas mulheres. O impacto direto negativo da COVID-19 na expectativa de vida foi parcialmente atenuado por impactos indiretos positivos significativos em dois grupos de causas de morte: doenças do sistema respiratório e doenças infecciosas e parasitárias. Este estudo mostra a necessidade de diferenciar impactos diretos e indiretos da COVID-19, devido às implicações para a saúde pública quando a intensidade da COVID-19 diminuir e as restrições de mobilidade forem suspensas.

The state of health in the European Union (EU-27) in 2019: a systematic analysis for the Global Burden of Disease study 2019.

BACKGROUND: The European Union (EU) faces many health-related challenges. Burden of diseases information and the resulting trends over time are essential for health planning. This paper reports estimates of disease burden in the EU and individual 27 EU countries in 2019, and compares them with those in 2010. METHODS: We used the Global Burden of Disease 2019 study estimates and 95% uncertainty intervals for the whole EU and each country to evaluate age-standardised death, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) rates for Level 2 causes, as well as life expectancy and healthy life expectancy (HALE). RESULTS: In 2019, the age-standardised death and DALY rates in the EU were 465.8 deaths and 20,251.0 DALYs per 100,000 inhabitants, respectively. Between 2010 and 2019, there were significant decreases in age-standardised death and YLL rates across EU countries. However, YLD rates remained mainly unchanged. The largest decreases in age-standardised DALY rates were observed for "HIV/AIDS and sexually transmitted diseases" and "transport injuries" (each -19%). "Diabetes and kidney diseases" showed a significant increase for age-standardised DALY rates across the EU (3.5%). In addition, "mental disorders" showed an increasing age-standardised YLL rate (14.5%). CONCLUSIONS: There was a clear trend towards improvement in the overall health status of the EU but with differences between countries. EU health policymakers need to address the burden of diseases, paying specific attention to causes such as mental disorders. There are many opportunities for mutual learning among otherwise similar countries with different patterns of disease.

Premature mortality for patients after completely resected early adenocarcinoma of the esophagus or stomach.

OBJECTIVE: To establish the life expectancy burden of esophago-gastric cancer by analyzing years of life lost (YLL) for a Western patient population after treatment of early esophageal (EAC) or early gastric (GAC) adenocarcinoma. BACKGROUND: For patients with early EAC or GAC, the short-term prognosis after surgical resection is very good. Little data is available regarding long-term prognosis when compared to the general population. METHODS: Two hundred and fourteen patients with pT1 EAC (n = 112) or GAC (n = 102) were included in the study. Patients with EAC underwent transthoracic en-bloc esophagectomy; those with GAC had total or subtotal gastrectomy with D2-lymphadenectomy. Surviving patients had a median follow-up of approximately 14 years. YLL was calculated using average life expectancy data from Germany. RESULTS: Patients with EAC were younger (median age 61 years) than those with GAC (66 years) (p = 0.031). The male:female ratio was 10:1 for EAC and 3:2 for GAC (p < 0.001). Multivariate survival analysis showed the age of the patients ≥60 years and the existence of lymph node metastasis was associated with poor prognosis. The median YLL for all patients who died over follow-up was 8.0 years. For patients under 60 years, it was approximately 20 years, and for older patients, approximately 5 years (p < 0.001) without difference in tumor stage between these age cohorts. YLL did not differ for GAC vs. EAC. CONCLUSION: After surgical resection, the prognostic burden as measured by YLL is relevant for all patients with early esophageal and gastric adenocarcinomas and especially for younger patients. Reasons for YLL need further studies.

[Is mortality an objective indicator for measuring the impact of an epidemic?: The example of Covid-19 in Switzerland]. / La mortalité est-elle un indicateur objectif pour mesurer l'impact d'une épidémie ?. L'exemple du Covid-19 en Suisse.

Measuring the health impact of an epidemic using appropriate indicators is necessarily complex. Mortality does not sum up all the issues, but at least it seems to be an objective indicator. There are, however, a number of different mortality indicators, which do not all convey the same message. During the Covid-19 epidemic in Switzerland, the mortality rate rose by 10.2% in 2020, while life expectancy fell by "only" 0.8%, or 8.3 months, a decline described as "modest" or "complete freefall" depending on when it was published. In reality, the population living in Switzerland in 2020 lost an average of "only" 2.4 days, as the epidemic did not last their entire lives. The use of such an indicator, in comparison with losses due to other factors, would enable us to better estimate the real impact of an epidemic.

Mesurer l'impact sanitaire d'une épidémie à l'aide d'indicateurs appropriés est forcément complexe. La mortalité ne résume pas tous les enjeux mais semble au moins être un indicateur objectif. Il existe cependant différents indicateurs de mortalité ne donnant pas tous le même message. Lors de l'épidémie de Covid-19 en Suisse, le taux de mortalité a augmenté de 10,2 % en 2020, alors que l'espérance de vie n'a diminué « que ¼ de 0,8 %, ou 8,3 mois, recul par ailleurs qualifié de « modeste ¼ ou de « chute libre ¼ selon quand il a été publié. En réalité, la population vivant en Suisse en 2020 n'a perdu en moyenne « que ¼ 2,4 jours car l'épidémie n'a pas duré toute sa vie. L'utilisation d'un tel indicateur, en comparaison avec les pertes dues à d'autres facteurs, permettrait une meilleure estimation de l'impact réel d'une épidémie.

Mortality and years of life lost related to adverse drug events in Brazil.

OBJECTIVE: To assess regional and national mortality and years of life lost (YLL) related to adverse drug events in Brazil. METHODS: This is an ecological study in which death records from 2009 to 2018 from the Mortality Information System were analyzed. Codes from the International Classification of Diseases 10th revision (ICD-10) that indicated drugs as the cause of death were identified. The number of deaths and the YLL due to adverse drug events were obtained. Crude, age- and gender-specific, and age-adjusted mortality rates and YLL rates per 100,000 inhabitants were formed by year, age group, gender, and Brazilian Federative Unit. Rate ratios were calculated by comparing rates from 2009 to 2018. A joinpoint regression model was applied for temporal analysis. RESULTS: For the selected ICD-10 codes, a total of 95,231 deaths and 2,843,413 YLL were recorded. Mortality rates from adverse drug events increased by a mean of 2.5% per year, and YLL rates increased by 3.7%. Increases in rates were observed in almost all age groups for both genders. Variations in rates were found between Federative Units, with the highest age-adjusted mortality and YLL rates occurring in the Distrito Federal. CONCLUSIONS: The numbers and rates of deaths and YLL increased during the study period, and variations in rates of deaths and YLL were observed between Brazilian Federative Units. Information on multiple causes of death from death certificates can be useful for quantifying adverse drug events and analyzing them geographically, by age and by gender.

[Impact of changes in malignant tumor death spectrum on life expectancy in Tianjin residents from 1999-2019].

Objective: To analyze the effects of changes in the spectrum of deaths from malignant tumors on the life expectancies of residents of different ages, sexes, and regions (urban or rural) in Tianjin from 1999 to 2019. Methods: The Abridged Life Table method and the Arriaga's decomposition method were used to calculate the effects of changes in spectrum of deaths from malignant tumors on the life expectancies of Tianjin residents of different ages, sexes, and regions. Results: During 1999-2019, the life expectancies increased by 4.96 years and 5.69 years for males and females, respectively, in Tianjin. The decreases in the mortalities from malignant neoplasms contributed 0.12 year (3.30%) and 0.03 year (0.77%) for males and females, respectively, to the increase during 1999-2007, and 0.05 year (3.13%) and 0.12 year (6.08%) for males and females, respectively, during 2007-2019. The decreases in the mortality rates of malignant tumors contributed the most to the increase among residents in the 60-69 years group, and the decreases in mortality rates of lung, gastric, esophageal, and liver cancers had relatively larger contribution. Lung cancer had a negative effect on the life expectancies of men and rural residents, but a positive effect on those of women and urban residents. The significant increases in the mortality rates of lung, colorectal, and pancreatic cancers in the ≥85 years group had a large negative effect on the overall life expectancy. Breast and ovarian cancers contributed negatively to the life expectancy of female residents. Conclusion: The overall increase in the life expectancy in Tianjin from 1999 to 2019 was mainly attributed to the elderly and the decreases in the mortality rates of gastric, esophageal, and liver cancers, among other malignancies, while the increases in the mortality rates of lung, colorectal, gallbladder, pancreatic, and breast cancers were the most significant factors hindering the increase of the life expectancy in Tianjin.

Projected Life Expectancy for Adolescents With HIV in the US.

Importance: Life expectancy is a key measure of overall population health. Life expectancy estimates for youth with HIV in the US are needed in the current HIV care and treatment context to guide health policies and resource allocation. Objective: To compare life expectancy between 18-year-old youth with perinatally acquired HIV (PHIV), youth with nonperinatally acquired HIV (NPHIV), and youth without HIV. Design, Setting, and Participants: Using a US-focused adolescent-specific Monte Carlo state-transition HIV model, we simulated individuals from age 18 years until death. We estimated probabilities of HIV treatment and care engagement, HIV progression, clinical events, and mortality from observational cohorts and clinical trials for model input parameters. The simulated individuals were 18-year-old race and ethnicity-matched youth with PHIV, youth with NPHIV, and youth without HIV; 47%, 85%, and 50% were assigned male sex at birth, respectively. Individuals were categorized by US Centers for Disease Control and Prevention-defined HIV acquisition risk: men who have sex with men, people who ever injected drugs, heterosexually active individuals at increased risk for HIV infection, or average risk for HIV infection. Distributions were 3%, 2%, 12%, and 83% for youth with PHIV and youth without HIV, and 80%, 6%, 14%, and 0% for youth with NPHIV, respectively. Among the simulated youth in this analysis, individuals were 61% Black, 24% Hispanic, and 15% White, respectively. Exposures: HIV status by timing of acquisition. Main Outcomes: Life expectancy loss for youth with PHIV and youth with NPHIV: difference between mean projected life expectancy under current and ideal HIV care scenarios compared with youth without HIV. Uncertainty intervals reflect varying adolescent HIV-related mortality inputs (95% CIs). Results: Compared with youth without HIV (life expectancy: male, 76.3 years; female, 81.7 years), male youth with PHIV and youth with NPHIV had projected life expectancy losses of 10.4 years (95% CI, 5.5-18.1) and 15.0 years (95% CI, 9.3-26.8); female youth with PHIV and youth with NPHIV had projected life expectancy losses of 11.8 years (95% CI, 6.4-20.2) and 19.5 years (95% CI, 13.8-31.6), respectively. When receiving ideal HIV care, life expectancy losses were projected to improve for youth with PHIV (male: 0.5 years [95% CI, 0.3-1.8]: female: 0.6 years [95% CI, 0.4-2.1]) but were projected to persist for youth with NPHIV (male: 6.0 years [95% CI, 5.0-9.1]; female: 10.4 years [95% CI, 9.4-13.6]). Conclusions: This adolescent-focused microsimulation modeling analysis projected that youth with HIV would have shorter life expectancy than youth without HIV. Projected differences were larger for youth with NPHIV compared with youth with PHIV. Differences in mortality by sex at birth, sexual behavior, and injection drug use contributed to lower projected life expectancy among youth with NPHIV. Interventions focused on HIV care and social factors are needed to improve life expectancy for youth with HIV in the US.

Does better than expected life expectancy in areas of disadvantage indicate health resilience? Stakeholder perspectives and possible explanations.

Some places have better than expected health trends despite being disadvantaged in other ways. Thematic analysis of qualitative data from stakeholders (N = 25) in two case studies of disadvantaged local authorities the North West and South East of England assessed explanations for the localities' apparent health resilience. Participants identified ways of working that might contribute to improved life expectancy, such as partnering with third sector, targeting and outcome driven action. Stakeholders were reluctant to assume credit for better-than-expected health outcomes. External factors such as population change, national politics and finances were considered crucial. Local public health stakeholders regard their work as important but unlikely to cause place-centred health resilience.

Piloting a Measure of Segregation at the Census Tract Level: Associations with Place and Racial/Ethnic Disparities in Life Expectancy.

This study considers residential segregation as a critical driver of racial/ethnic health disparities and introduces a proxy measure of segregation that estimates the degree of segregation at the census tract level with a metric capturing the overrepresentation of a racialized/ethnic group in a census tract in relation to that group's representation at the city level. Using Dallas, Texas as a pilot city, the measure is used to investigate mean life expectancy at birth for relatively overrepresented Hispanic, non-Hispanic white, non-Hispanic Black, and Asian census tracts and examine for significant differences between mean life expectancy in relatively overrepresented census tracts and that group's mean life expectancy at the state level. Multivariable linear regression analysis was utilized to assess how segregation measured at the census tract level associates with life expectancy across different racialized/ethnic groups, controlling for socioeconomic disparities. This study aimed to expose the need to consider the possibility of neighborhood mechanisms beyond socioeconomic characteristics as an important determinant of health and draw attention to the importance of critically engaging the experience of place in examinations of racial and ethnic health disparities. Multivariable linear regression modeling resulted in significant findings for non-Hispanic Black, non-Hispanic white, and Asian groups, indicating increased census tract-level life expectancy for Black and white residents in highly segregated census tracts and decreased life expectancy for residents of tracts in which the Asian community is overrepresented when compared to state means. Unadjusted models demonstrated socioeconomic inequities between first and fourth quartile census tracts and pointed to the importance of mixed methods in health disparities research and the importance of including the voice of community members to account for places of daily lived experience and people's relationships with them.

Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021.

BACKGROUND: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. METHODS: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. FINDINGS: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8-63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0-45·0] in 2050) and south Asia (31·7% [29·2-34·1] to 15·5% [13·7-17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4-40·3) to 41·1% (33·9-48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6-25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5-43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5-17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7-11·3) in the high-income super-region to 23·9% (20·7-27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5-6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2-26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [-0·6 to 3·6]). INTERPRETATION: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions. FUNDING: Bill & Melinda Gates Foundation.

Estimation and probabilistic projection of age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030.

BACKGROUND: Mortality rate estimation in small areas can be difficult due the low number of events/exposure (i.e. stochastic error). If the death records are not completed, it adds a systematic uncertainty on the mortality estimates. Previous studies in Brazil have combined demographic and statistical methods to partially overcome these issues. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010 and forecasted probabilistic mortality rates and life expectancy between 2010 and 2030. METHODS: We used a combination of the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS), Bayesian Model, Spatial Smoothing Model and an ad-hoc procedure to estimate age- and sex-specific mortality rates for all Brazilian municipalities for 2010. Then we adapted the Lee-Carter model to forecast mortality rates by age and sex in all municipalities between 2010 and 2030. RESULTS: The adjusted sex- and age-specific mortality rates for all Brazilian municipalities in 2010 reveal a distinct regional pattern, showcasing a decrease in life expectancy in less socioeconomically developed municipalities when compared to estimates without adjustments. The forecasted mortality rates indicate varying regional improvements, leading to a convergence in life expectancy at birth among small areas in Brazil. Consequently, a reduction in the variability of age at death across Brazil's municipalities was observed, with a persistent sex differential. CONCLUSION: Mortality rates at a small-area level were successfully estimated and forecasted, with associated uncertainty estimates also generated for future life tables. Our approach could be applied across countries with data quality issues to improve public policy planning.

Age-specific and cause-specific mortality contributions to the socioeconomic gap in life expectancy in Germany, 2003-21: an ecological study.

BACKGROUND: Earlier death among people in socioeconomically deprived circumstances has been found internationally and for various causes of death, resulting in a considerable life-expectancy gap between socioeconomic groups. We examined how age-specific and cause-specific mortality contributions to the socioeconomic gap in life expectancy have changed at the area level in Germany over time. METHODS: In this ecological study, official German population and cause-of-death statistics provided by the Federal Statistical Office of Germany for the period Jan 1, 2003, to Dec 31, 2021, were linked to district-level data of the German Index of Socioeconomic Deprivation. Life-table and decomposition methods were applied to calculate life expectancy by area-level deprivation quintile and decompose the life-expectancy gap between the most and least deprived quintiles into age-specific and cause-specific mortality contributions. FINDINGS: Over the study period, population numbers varied between 80 million and 83 million people per year, with the number of deaths ranging from 818 000 to 1 024 000, covering the entire German population. Between Jan 1, 2003, and Dec 31, 2019, the gap in life expectancy between the most and least deprived quintiles of districts increased by 0·7 years among females (from 1·1 to 1·8 years) and by 0·1 years among males (from 3·0 to 3·1 years). Thereafter, during the COVID-19 pandemic, the gap increased more rapidly to 2·2 years in females and 3·5 years in males in 2021. Between 2003 and 2021, the causes of death that contributed the most to the life-expectancy gap were cardiovascular diseases and cancer, with declining contributions of cardiovascular disease deaths among those aged 70 years and older and increasing contributions of cancer deaths among those aged 40-74 years over this period. COVID-19 mortality among individuals aged 45 years and older was the strongest contributor to the increase in life-expectancy gap after 2019. INTERPRETATION: To reduce the socioeconomic gap in life expectancy, effective efforts are needed to prevent early deaths from cardiovascular disease and cancer in socioeconomically deprived populations, with cancer prevention and control becoming an increasingly important field of action in this respect. FUNDING: German Cancer Aid and European Research Council.

The association between disability and mortality: a mixed-methods study.

BACKGROUND: Globally, 1·3 billion people have a disability and are more likely to experience poor health than the general population. However, little is known about the mortality or life expectancy gaps experienced by people with disabilities. We aimed to undertake a systematic review and meta-analysis of the association between disability and mortality, compare these findings to the evidence on the association of impairment types and mortality, and model the estimated life expectancy gap experienced by people with disabilities. METHODS: We did a mixed-methods study, which included a systematic review and meta-analysis, umbrella review, and life expectancy modelling. For the systematic review and meta-analysis, we searched MEDLINE, Global Health, PsycINFO, and Embase for studies published in English between Jan 1, 2007, and June 7, 2023, investigating the association of mortality and disability. We included prospective and retrospective cohort studies and randomised controlled trials with a baseline assessment of disability and a longitudinal assessment of all-cause mortality or cause-specific mortality. Two reviewers independently assessed study eligibility, extracted the data, and assessed risk of bias. We did a random-effects meta-analysis to calculate a pooled estimate of the mortality rate ratio for people with disabilities compared with those without disabilities. We did an umbrella review of meta-analyses examining the association between different impairment types and mortality. We used life table modelling to translate the mortality rate ratio into an estimate of the life expectancy gap between people with disabilities and the general population. The systematic review and meta-analysis is registered with PROSPERO, CRD42023433374. FINDINGS: Our search identified 3731 articles, of which 42 studies were included in the systematic review. The meta-analysis included 31 studies. Pooled estimates showed that all-cause mortality was 2·24 times (95% CI 1·84-2·72) higher in people with disabilities than among people without disabilities, although heterogeneity between the studies was high (τ2=0·28, I2=100%). Modelling indicated a median gap in life expectancy of 13·8 years (95% CI 13·1-14·5) by disability status. Cause-specific mortality was also higher for people with disabilities, including for cancer, COVID-19, cardiovascular disease, and suicide. The umbrella review identified nine meta-analyses, which showed consistently elevated mortality rates among people with different impairment types. INTERPRETATION: Mortality inequities experienced by people with disabilities necessitate health system changes and efforts to address inclusion and the social determinants of health. FUNDING: National Institute for Health and Care Research, Rhodes Scholarship, Indonesia Endowment Funds for Education, Foreign, Commonwealth and Development Office (Programme for Evidence to Inform Disability Action), and the Arts and Humanities Research Council.

Trends of Gaps Between Health-Adjusted Life Expectancy and Life Expectancy at the Regional Level in Korea Using a Group-Based Multi-Trajectory Modeling Approach (2008-2019).

BACKGROUND: Health-adjusted life expectancy (HALE) is an indicator of the average lifespan in good health. Through this study, we aimed to identify regional disparities in the gap between HALE and life expectancy, considering the trends that have changed over time in Korea. METHODS: We employed a group-based multi-trajectory modeling approach to capture trends in the gap between HALE and life expectancy at the regional level from 2008 to 2019. HALE was calculated using incidence-based "years lived with disability." This methodology was also employed in the Korean National Burden of Disease Study. RESULTS: Based on five different information criteria, the most fitted number of trajectory groups was seven, with at least 11 regions in each group. Among the seven groups, one had an exceptionally large gap between HALE and life expectancy compared to that of the others. This group was assigned to 17 regions, of which six were metropolitan cities. CONCLUSION: Based on the results of this study, we identified regions in which health levels have deteriorated over time, particularly within specific areas of metropolitan cities. These findings can be used to design comprehensive policy interventions for community health promotion and urban regeneration projects in the future.