[Ethics of a long life]. / Ethik des langen Lebens.

The increase in average life expectancy that has taken place since 1850 and is continuing globally to the present day can be seen as a major achievement of civilization. However, many are skeptical about demographic change and the continuing trend of increasing life expectancy beyond current limits. The reasons for this lie in deeply rooted cultural attitudes towards old age and the elderly.This article counters these attitudes with principles for a long life that emphasize the benefits of the first revolution of life extension. Research should be promoted that can ensure this gain and holds out the prospect of a further extension of the human lifespan as a result of a second revolution.

The impact of devolution on local health systems: Evidence from Greater Manchester, England.

Devolution and decentralisation policies involving health and other government sectors have been promoted with a view to improve efficiency and equity in local service provision. Evaluations of these reforms have focused on specific health or care measures, but little is known about their full impact on local health systems. We evaluated the impact of devolution in Greater Manchester (England) on multiple outcomes using a whole system approach. We estimated the impact of devolution until February 2020 on 98 measures of health system performance, using the generalised synthetic control method and adjusting for multiple hypothesis testing. We selected measures from existing monitoring frameworks to populate the WHO Health System Performance Assessment framework. The included measures captured information on health system functions, intermediatory objectives, final goals, and social determinants of health. We identified which indicators were targeted in response to devolution from an analysis of 170 health policy intervention documents. Life expectancy (0.233 years, S.E. 0.012) and healthy life expectancy (0.603 years, S.E. 0.391) increased more in GM than in the estimated synthetic control group following devolution. These increases were driven by improvements in public health, primary care, hospital, and adult social care services as well as factors associated with social determinants of health, including a reduction in alcohol-related admissions (-110.1 admission per 100,000, S.E. 9.07). In contrast, the impact on outpatient, mental health, maternity, and dental services was mixed. Devolution was associated with improved population health, driven by improvements in health services and wider social determinants of health. These changes occurred despite limited devolved powers over health service resources suggesting that other mechanisms played an important role, including the allocation of sustainability and transformation funding and the alignment of decision-making across health, social care, and wider public services in the region.

Civil service organization as a political determinant of health: Analyzing relationships between merit-based hiring, corruption, and population health.

A growing literature finds that the way governments are organized can impact the societies they serve in important ways. The same is apparent with respect to civil service organizations. Numerous studies show that the recruitment of civil servants based on their credentials rather than on nepotism or patronage reduces corruption in government. Political corruption in turn appears to harm population health. Up to this time, however, civil service organization is not a recognized determinant of health and is little discussed outside of political science disciplines. To provoke a broader conversation on this subject, the following study proposes that meritocratic recruitment of civil servants improves population health. To test this proposition, a series of regression models examines comparative data for 118 countries. Consistent with study hypotheses, meritocratic recruitment of civil servants corresponds longitudinally with both lower rates of corruption and lower rates of infant mortality. Results are similar after robustness checks. Findings with regard to life expectancy are more mixed. However, additional tests suggest meritocratic recruitment contributes to life expectancy over a longer span of time. Findings also offer more support for a direct pathway from meritocratic recruitment to population health rather than via changes in corruption levels per se, although this may depend on a country's level of economic development. Overall, this study offers first evidence that civil service organization, particularly the recruitment of civil servants based on the merits of their applications rather than on whom they happen to know in government, is a positive determinant of health. More research in this area is needed.

Gentrification Yields Racial And Ethnic Disparities In Exposure To Contextual Determinants Of Health.

This article examines racial and ethnic disparities in the relationship between gentrification and exposure to contextual determinants of health. In our study, we focused on changes in selected contextual determinants of health (health care access, social deprivation, air pollution, and walkability) and life expectancy during the period 2006-21 among residents of gentrifying census tracts in six large US cities that have experienced different gentrification patterns and have different levels of segregation: Chicago, Illinois; Los Angeles, California; New York, New York; Philadelphia, Pennsylvania; San Francisco, California; and Seattle, Washington. We found that gentrification was associated with overall improvements in the likelihood of living in Medically Underserved Areas across racial and ethnic groups, but it was also associated with increased social deprivation and reduced life expectancy among Black people, Hispanic people, and people of another or undetermined race or ethnicity. In contrast, we found that gentrification was related to better (or unchanged) contextual determinants of health for Asian people and White people. Our findings can inform policies that target communities identified to be particularly at risk for worsening contextual determinants of health as a result of gentrification.

Excess Mortality and Years of Potential Life Lost Among the Black Population in the US, 1999-2020.

Importance: Amid efforts in the US to promote health equity, there is a need to assess recent progress in reducing excess deaths and years of potential life lost among the Black population compared with the White population. Objective: To evaluate trends in excess mortality and years of potential life lost among the Black population compared with the White population. Design, setting, and participants: Serial cross-sectional study using US national data from the Centers for Disease Control and Prevention from 1999 through 2020. We included data from non-Hispanic White and non-Hispanic Black populations across all age groups. Exposures: Race as documented in the death certificates. Main outcomes and measures: Excess age-adjusted all-cause mortality, cause-specific mortality, age-specific mortality, and years of potential life lost rates (per 100 000 individuals) among the Black population compared with the White population. Results: From 1999 to 2011, the age-adjusted excess mortality rate declined from 404 to 211 excess deaths per 100 000 individuals among Black males (P for trend <.001). However, the rate plateaued from 2011 through 2019 (P for trend = .98) and increased in 2020 to 395-rates not seen since 2000. Among Black females, the rate declined from 224 excess deaths per 100 000 individuals in 1999 to 87 in 2015 (P for trend <.001). There was no significant change between 2016 and 2019 (P for trend = .71) and in 2020 rates increased to 192-levels not seen since 2005. The trends in rates of excess years of potential life lost followed a similar pattern. From 1999 to 2020, the disproportionately higher mortality rates in Black males and females resulted in 997 623 and 628 464 excess deaths, respectively, representing a loss of more than 80 million years of life. Heart disease had the highest excess mortality rates, and the excess years of potential life lost rates were largest among infants and middle-aged adults. Conclusions and relevance: Over a recent 22-year period, the Black population in the US experienced more than 1.63 million excess deaths and more than 80 million excess years of life lost when compared with the White population. After a period of progress in reducing disparities, improvements stalled, and differences between the Black population and the White population worsened in 2020.

Changes in the Relationship Between Income and Life Expectancy Before and During the COVID-19 Pandemic, California, 2015-2021.

Importance: The COVID-19 pandemic caused a large decrease in US life expectancy in 2020, but whether a similar decrease occurred in 2021 and whether the relationship between income and life expectancy intensified during the pandemic are unclear. Objective: To measure changes in life expectancy in 2020 and 2021 and the relationship between income and life expectancy by race and ethnicity. Design, Setting, and Participants: Retrospective ecological analysis of deaths in California in 2015 to 2021 to calculate state- and census tract-level life expectancy. Tracts were grouped by median household income (MHI), obtained from the American Community Survey, and the slope of the life expectancy-income gradient was compared by year and by racial and ethnic composition. Exposures: California in 2015 to 2019 (before the COVID-19 pandemic) and 2020 to 2021 (during the COVID-19 pandemic). Main Outcomes and Measures: Life expectancy at birth. Results: California experienced 1 988 606 deaths during 2015 to 2021, including 654 887 in 2020 to 2021. State life expectancy declined from 81.40 years in 2019 to 79.20 years in 2020 and 78.37 years in 2021. MHI data were available for 7962 of 8057 census tracts (98.8%; n = 1 899 065 deaths). Mean MHI ranged from $21 279 to $232 261 between the lowest and highest percentiles. The slope of the relationship between life expectancy and MHI increased significantly, from 0.075 (95% CI, 0.07-0.08) years per percentile in 2019 to 0.103 (95% CI, 0.098-0.108; P < .001) years per percentile in 2020 and 0.107 (95% CI, 0.102-0.112; P < .001) years per percentile in 2021. The gap in life expectancy between the richest and poorest percentiles increased from 11.52 years in 2019 to 14.67 years in 2020 and 15.51 years in 2021. Among Hispanic and non-Hispanic Asian, Black, and White populations, life expectancy declined 5.74 years among the Hispanic population, 3.04 years among the non-Hispanic Asian population, 3.84 years among the non-Hispanic Black population, and 1.90 years among the non-Hispanic White population between 2019 and 2021. The income-life expectancy gradient in these groups increased significantly between 2019 and 2020 (0.038 [95% CI, 0.030-0.045; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI: 0.005-0.044; P = .02] years per percentile among Asian individuals; 0.015 [95% CI, 0.010-0.020; P < .001] years per percentile among Black individuals; and 0.011 [95% CI, 0.007-0.015; P < .001] years per percentile among White individuals) and between 2019 and 2021 (0.033 [95% CI, 0.026-0.040; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI, 0.010-0.038; P = .002] years among Asian individuals; 0.024 [95% CI, 0.011-0.037; P = .003] years per percentile among Black individuals; and 0.013 [95% CI, 0.008-0.018; P < .001] years per percentile among White individuals). The increase in the gradient was significantly greater among Hispanic vs White populations in 2020 and 2021 (P < .001 in both years) and among Black vs White populations in 2021 (P = .04). Conclusions and Relevance: This retrospective analysis of census tract-level income and mortality data in California from 2015 to 2021 demonstrated a decrease in life expectancy in both 2020 and 2021 and an increase in the life expectancy gap by income level relative to the prepandemic period that disproportionately affected some racial and ethnic minority populations. Inferences at the individual level are limited by the ecological nature of the study, and the generalizability of the findings outside of California are unknown.

Research on the prediction of longevity from both individual and family perspectives.

Increasing human longevity is of global interest. The present study explored the prediction of longevity from both individual perspective and family perspective based on demographic and psychosocial factors. A total of 186 longevous family members and 237 ordinary elderly family members participated in a cross-sectional study, and a sample of 62 longevous elderly and 57 ordinary elderly were selected for comparative research. The results showed that it was three times more female than male in longevous elderly group. Up to 71.2% of longevous elderly had no experience in education, which was significantly lower than that of ordinary elderly. Due to such extreme age, more widowed (81.4%) elderly than those in married (18.6%). Less than one-seventh of the longevous elderly maintained the habit of smoking, and about one-third of them liked drinking, both were significantly lower than that of ordinary elderly. In terms of psychosocial factors, longevous elderly showed lower neuroticism and social support, while higher extraversion, compared with the ordinary elderly. However, there were no significant differences between the two family groups in demographic and psychosocial variables, except longevous families showing lower scores in neuroticism. Regression analysis found that neuroticism, social support and smoking habit had significant impact on individuals' life span, then, neuroticism and psychoticism were the key factor to predict families' longevity. We conclude that good emotional management, benign interpersonal support, and moderation of habits are important factors for individual longevity, and the intergenerational influence of personality is closely related to family longevity.

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.

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

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

Life expectancy and risk of death in 6791 communities in England from 2002 to 2019: high-resolution spatiotemporal analysis of civil registration data.

BACKGROUND: High-resolution data for how mortality and longevity have changed in England, UK are scarce. We aimed to estimate trends from 2002 to 2019 in life expectancy and probabilities of death at different ages for all 6791 middle-layer super output areas (MSOAs) in England. METHODS: We performed a high-resolution spatiotemporal analysis of civil registration data from the UK Small Area Health Statistics Unit research database using de-identified data for all deaths in England from 2002 to 2019, with information on age, sex, and MSOA of residence, and population counts by age, sex, and MSOA. We used a Bayesian hierarchical model to obtain estimates of age-specific death rates by sharing information across age groups, MSOAs, and years. We used life table methods to calculate life expectancy at birth and probabilities of death in different ages by sex and MSOA. FINDINGS: In 2002-06 and 2006-10, all but a few (0-1%) MSOAs had a life expectancy increase for female and male sexes. In 2010-14, female life expectancy decreased in 351 (5·2%) of 6791 MSOAs. By 2014-19, the number of MSOAs with declining life expectancy was 1270 (18·7%) for women and 784 (11·5%) for men. The life expectancy increase from 2002 to 2019 was smaller in MSOAs where life expectancy had been lower in 2002 (mostly northern urban MSOAs), and larger in MSOAs where life expectancy had been higher in 2002 (mostly MSOAs in and around London). As a result of these trends, the gap between the first and 99th percentiles of MSOA life expectancy for women increased from 10·7 years (95% credible interval 10·4-10·9) in 2002 to reach 14·2 years (13·9-14·5) in 2019, and for men increased from 11·5 years (11·3-11·7) in 2002 to 13·6 years (13·4-13·9) in 2019. INTERPRETATION: In the decade before the COVID-19 pandemic, life expectancy declined in increasing numbers of communities in England. To ensure that this trend does not continue or worsen, there is a need for pro-equity economic and social policies, and greater investment in public health and health care throughout the entire country. FUNDING: Wellcome Trust, Imperial College London, Medical Research Council, Health Data Research UK, and National Institutes of Health Research.

Inequality in mortality between Black and White Americans by age, place, and cause and in comparison to Europe, 1990 to 2018.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans' mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

The effects on mortality and the associated financial costs of wood heater pollution in a regional Australian city.

OBJECTIVES: To estimate the annual burden of mortality and the associated health costs attributable to air pollution from wood heaters in Armidale. DESIGN: Health impact assessment (excess annual mortality and financial costs) based upon atmospheric PM2.5 measurements. SETTING: Armidale, a regional Australian city (population, 24 504) with high levels of air pollution in winter caused by domestic wood heaters, 1 May 2018 - 30 April 2019. MAIN OUTCOME MEASURES: Estimated population exposure to PM2.5 from wood heaters; estimated numbers of premature deaths and years of life lost. RESULTS: Fourteen premature deaths (95% CI, 12-17 deaths) per year, corresponding to 210 (95% CI, 172-249) years of life lost, are attributable to long term exposure to wood heater PM2.5 pollution in Armidale. The estimated financial cost is $32.8 million (95% CI, $27.0-38.5 million), or $10 930 (95% CI, $9004-12 822) per wood heater per year. CONCLUSIONS: The substantial mortality and financial cost attributable to wood heating in Armidale indicates that effective policies are needed to reduce wood heater pollution, including public education about the effects of wood smoke on health, subsidies that encourage residents to switch to less polluting home heating (perhaps as part of an economic recovery package), assistance for those affected by wood smoke from other people, and regulations that reduce wood heater use (eg, by not permitting new wood heaters and requiring existing units to be removed when houses are sold).

Inequalities in life expectancy in Australia according to education level: a whole-of-population record linkage study.

BACKGROUND: Life expectancy in Australia is amongst the highest globally, but national estimates mask within-country inequalities. To monitor socioeconomic inequalities in health, many high-income countries routinely report life expectancy by education level. However in Australia, education-related gaps in life expectancy are not routinely reported because, until recently, the data required to produce these estimates have not been available. Using newly linked, whole-of-population data, we estimated education-related inequalities in adult life expectancy in Australia. METHODS: Using data from 2016 Australian Census linked to 2016-17 Death Registrations, we estimated age-sex-education-specific mortality rates and used standard life table methodology to calculate life expectancy. For men and women separately, we estimated absolute (in years) and relative (ratios) differences in life expectancy at ages 25, 45, 65 and 85 years according to education level (measured in five categories, from university qualification [highest] to no formal qualifications [lowest]). RESULTS: Data came from 14,565,910 Australian residents aged 25 years and older. At each age, those with lower levels of education had lower life expectancies. For men, the gap (highest vs. lowest level of education) was 9.1 (95 %CI: 8.8, 9.4) years at age 25, 7.3 (7.1, 7.5) years at age 45, 4.9 (4.7, 5.1) years at age 65 and 1.9 (1.8, 2.1) years at age 85. For women, the gap was 5.5 (5.1, 5.9) years at age 25, 4.7 (4.4, 5.0) years at age 45, 3.3 (3.1, 3.5) years at 65 and 1.6 (1.4, 1.8) years at age 85. Relative differences (comparing highest education level with each of the other levels) were larger for men than women and increased with age, but overall, revealed a 10-25 % reduction in life expectancy for those with the lowest compared to the highest education level. CONCLUSIONS: Education-related inequalities in life expectancy from age 25 years in Australia are substantial, particularly for men. Those with the lowest education level have a life expectancy equivalent to the national average 15-20 years ago. These vast gaps indicate large potential for further gains in life expectancy at the national level and continuing opportunities to improve health equity.

The triple burden of communicable and non-communicable diseases and injuries on sex differences in life expectancy in Ethiopia.

BACKGROUND: Ethiopia has experienced great improvements in life expectancy (LE) at birth over the last three decades. Despite consistent increases in LE for both males and females in Ethiopia, the country has simultaneously witnessed an increasing discrepancy in LE between males and females. METHODS: This study used Pollard's actuarial method of decomposing LE to compare age- and cause- specific contributions to changes in sex differences in LE between 1995 and 2015 in Ethiopia. RESULTS: Life expectancy at birth in Ethiopia increased for both males and females from 48.28 years and 50.12 years in 1995 to 65.59 years and 69.11 years in 2015, respectively. However, the sex differences in LE at birth also increased from 1.85 years in 1995 to 3.51 years in 2015. Decomposition analysis shows that the higher male mortality was consistently due to injuries and respiratory infections, which contributed to 1.57 out of 1.85 years in 1995 and 1.62 out of 3.51 years in 2015 of the sex differences in LE. Increased male mortality from non-communicable diseases (NCDs) also contributed to the increased difference in LE between males and females over the period, accounting for 0.21 out of 1.85 years and 1.05 out of 3.51 years in 1995 and 2015, respectively. CONCLUSIONS: While injuries and respiratory infections causing male mortality were the most consistent causes of the sex differences in LE in Ethiopia, morality from NCDs is the main cause of the recent increasing differences in LE between males and females. However, unlike the higher exposure of males to death from injuries due to road traffic injuries or interpersonal violence, to what extent sex differences are caused by the higher male mortality compared to female mortality from respiratory infection diseases is unclear. Similarly, despite Ethiopia's weak social security system, an explanation for the increased sex differences after the age of 40 years due to either longer female LE or reduced male LE should be further investigated.

Future life expectancy in Europe taking into account the impact of smoking, obesity, and alcohol.

Introduction: In Europe, women can expect to live on average 82 years and men 75 years. Forecasting how life expectancy will develop in the future is essential for society. Most forecasts rely on a mechanical extrapolation of past mortality trends, which leads to unreliable outcomes because of temporal fluctuations in the past trends due to lifestyle 'epidemics'. Methods: We project life expectancy for 18 European countries by taking into account the impact of smoking, obesity, and alcohol on mortality, and the mortality experiences of forerunner populations. Results: We project that life expectancy in these 18 countries will increase from, on average, 83.4 years for women and 78.3 years for men in 2014 to 92.8 years for women and 90.5 years for men in 2065. Compared to others (Lee-Carter, Eurostat, United Nations), we project higher future life expectancy values and more realistic differences between countries and sexes. Conclusions: Our results imply longer individual lifespans, and more elderly in society. Funding: Netherlands Organisation for Scientific Research (NWO) (grant no. 452-13-001).

On average, in Europe, men can currently expect to live till the age of 75 and women until they are 82. But what will their lifespans be in the next decades? Reliable answers to this question are essential to help governments plan for future health care and social security costs. While medical improvements are likely to further extend lifespans, lifestyle factors can result in temporal distortions of this trend. Yet, most estimates of future life expectancy fail to consider changing lifestyles, as they only use past mortality trends in their calculations. This can make these projections unreliable: for example, increases in smoking rates among Northern and Western European men led to stagnating male life expectancies in the 1950s and 1960s, but these picked up again after smoking declined. The same pattern is showing for women, except it is lagging as they took up smoking later than men. Based simply on the extrapolation of past mortality trends, current projection models fail to consider the past and predicted modifications of life expectancy trends prompted by changing rates of health behaviours ­ such as increases followed by (anticipated) declines in alcohol consumption and obesity rates, similar to what was observed with smoking. To produce a more reliable forecast, Janssen et al. incorporated trends in smoking, obesity, and alcohol use into life expectancy projections for 18 European countries. The predictions suggest that life expectancy for women in these countries will increase from 83.4 years in 2014 to 92.8 years in 2065. For men, it will also go up, from 78.3 to 90.5 years. In the future, this integrative approach may help to track the effects of health-behaviour related prevention policies on life expectancy, and allow scientists to account for changes caused by the COVID-19 pandemic. In the meantime, these estimates are higher than those obtained using more traditional methods; they suggest that communities should start to adjust to the possibility of longer individual lifespans, and of larger numbers of elderly people in society.

Planning for tomorrow: global cancer incidence and the role of prevention 2020-2070.

Cancer is currently the first or second most common contributor to premature mortality in most countries of the world. The global number of patients with cancer is expected to rise over the next 50 years owing to the strong influence of demographic changes, such as population ageing and growth, on the diverging trends in cancer incidence in different regions. Assuming that the latest incidence trends continue for the major cancer types, we predict a doubling of the incidence of all cancers combined by 2070 relative to 2020. The greatest increases are predicted in lower-resource settings, in countries currently assigned a low Human Development Index (HDI), whereas the predicted increases in national burden diminish with increasing levels of national HDI. Herein, we assess studies modelling the future burden of cancer that underscore how comprehensive cancer prevention strategies can markedly reduce the prevalence of major risk factors and, in so doing, the number of future cancer cases. Focusing on an in-depth assessment of prevention strategies that target tobacco smoking, overweight and obesity, and human papillomavirus infection, we discuss how stepwise, population-level approaches with amenable goals can avert millions of future cancer diagnoses worldwide. In the absence of a step-change in cancer prevention delivery, tobacco smoking will remain the leading preventable cause of cancer, and overweight and obesity might well present a comparable opportunity for prevention, given its increasing prevalence globally in the past few decades. Countries must therefore instigate national cancer control programmes aimed at preventing cancer, and with some urgency, if such programmes are to yield the desired public health and economic benefits in this century.

Minimizing Population Health Loss in Times of Scarce Surgical Capacity During the Coronavirus Disease 2019 Crisis and Beyond: A Modeling Study.

OBJECTIVES: Coronavirus disease 2019 has put unprecedented pressure on healthcare systems worldwide, leading to a reduction of the available healthcare capacity. Our objective was to develop a decision model to estimate the impact of postponing semielective surgical procedures on health, to support prioritization of care from a utilitarian perspective. METHODS: A cohort state-transition model was developed and applied to 43 semielective nonpediatric surgical procedures commonly performed in academic hospitals. Scenarios of delaying surgery from 2 weeks were compared with delaying up to 1 year and no surgery at all. Model parameters were based on registries, scientific literature, and the World Health Organization Global Burden of Disease study. For each surgical procedure, the model estimated the average expected disability-adjusted life-years (DALYs) per month of delay. RESULTS: Given the best available evidence, the 2 surgical procedures associated with most DALYs owing to delay were bypass surgery for Fontaine III/IV peripheral arterial disease (0.23 DALY/month, 95% confidence interval [CI]: 0.13-0.36) and transaortic valve implantation (0.15 DALY/month, 95% CI: 0.09-0.24). The 2 surgical procedures with the least DALYs were placing a shunt for dialysis (0.01, 95% CI: 0.005-0.01) and thyroid carcinoma resection (0.01, 95% CI: 0.01-0.02). CONCLUSION: Expected health loss owing to surgical delay can be objectively calculated with our decision model based on best available evidence, which can guide prioritization of surgical procedures to minimize population health loss in times of scarcity. The model results should be placed in the context of different ethical perspectives and combined with capacity management tools to facilitate large-scale implementation.

The life expectancy of older couples and surviving spouses.

Individual life expectancies provide information for individuals making retirement decisions and for policy makers. For couples, analogous measures are the expected years both spouses will be alive (joint life expectancy) and the expected years the surviving spouse will be a widow or widower (survivor life expectancy). Using individual life expectancies to calculate summary measures for couples is intuitively appealing but yield misleading results, overstating joint life expectancy and dramatically understating survivor life expectancies. This implies that standard "individual life cycle models" are misleading for couples and that "couple life cycle models" must be substantially more complex. Using the CDC life tables for 2010, we construct joint and survivor life expectancy measures for randomly formed couples. The couples we form are defined by age, race and ethnicity, and education. Due to assortative marriage, inequalities in individual life expectancies are compounded into inequalities in joint and survivor life expectancies. We also calculate life expectancy measures for randomly formed couples for the 1930-2010 decennial years. Trends over time show how the relative rate of decrease in the mortality rates of men and women affect joint and survivor life expectancies. Because our couple life expectancy measures are based on randomly formed couples, they do not capture the effects of differences in spouses' premarital characteristics (apart from sex, age, race and ethnicity, and, in some cases, education) or of correlations in spouses' experiences or behaviors during marriage. However, they provide benchmarks which have been sorely lacking in the public discourse.