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.

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.

[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.

[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.

[Regional differences and trends in healthy life expectancy in Germany]. / Regionale Unterschiede und Trends in gesunder Lebenserwartung in Deutschland.

BACKGROUND: Against the background of increasing life expectancy, the question arises in which state of health the additional years of life are spent. The aim of this study is to assess for the first time regional differences in healthy life expectancy for Germany. METHODS: The concept of healthy life expectancy allows for the combination of regional differences in health status and mortality in a single measure. This article uses the concept of partial healthy life expectancy. We use official data on deaths and population numbers to calculate abridged life tables. Data from the Socio-Economic Panel (SOEP) are used to determine the age- and sex-specific prevalences of health status. Regional differences are analyzed from 2002 to 2019 by dividing Germany into four regions (North, South, East, West). RESULTS: The regional differences in healthy life expectancy in Germany are greater than differences in life expectancy, and trends in healthy life expectancy partly differ from the corresponding trends in mortality. These differences over time also vary according to age: while healthy life expectancy has tended to stagnate and, in some cases, decline among the population aged between 20 and 64, the number and proportion of years in good health has increased among older adults up to the age of 79. CONCLUSION: There are striking regional differences and trends in the distribution of expected years in good health in Germany. The timely identification of regionally divergent developments could facilitate the implementation of targeted health-promoting measures.

[Healthier at work for longer? Trends in life years free of cardiovascular and musculoskeletal diseases in the employed and general population based on health insurance claims data]. / Länger gesund im Beruf? Trends in den Lebensjahren frei von Herz-Kreislauf- und Muskel-Skelett-Erkrankungen in GKV-Daten für die Erwerbstätigen- und Allgemeinbevölkerung.

BACKGROUND: Our study focuses on the development of disease-free life years of two disease groups with high public health relevance: musculoskeletal diseases (MSD) and cardiovascular diseases (CVD). Against the backdrop of prolonged working lives, the development of disease-free life years in the working-age population is compared with the trend in the employed population. Differences between occupational groups are also examined. METHODS: The study is based on data from the statutory health insurance provider AOK Lower Saxony (N = 2,001,225). Incident cases were identified based on the diagnosis data. The expected years free of MSD and CVD were calculated using multistate life table analysis for three periods between 2006 and 2018. The occupational group is identified via the occupational key. Three groups are distinguished: unskilled and semi-skilled workers, skilled workers and specialists, and highly skilled workers. RESULTS: Life years free of MSD clearly decreased in the general population and among the employed population. The decrease was strongest in the higher-skilled occupational groups. Life years free of CVD increased in the general population. The increase was weaker among the employed population. The only occupational group showing increases were men in unskilled and semi-skilled occupations. DISCUSSION: The study shows that disease-free life years among employed persons developed in some cases worse than in the general population. For the analysed disease groups MSD and CVD, there are clear inequalities between occupational groups, which decreased somewhat over time. The inequalities and the decrease in years free of MSD highlight the high public health relevance and the need for effective prevention strategies to prevent CVD and MSD in working age.

[Family reconstitution and online genealogies to analyze the sex-specific differential mortality in the historical context]. / Familienrekonstitution und Online-Genealogien zur Analyse der geschlechtsspezifischen differenziellen Sterblichkeit im historischen Kontext.

BACKGROUND: Family reconstitution and data from online genealogies, such as FamiLinx, are two potential sources for investigating mortality dynamics for the period before official lifetables became available. In this paper, we use two of them, the family reconstitution of Imhof and the FamiLinx dataset based on geni.com, to estimate dynamics in life expectancy and discuss the sex-specific differential mortality in the German Empire. METHOD: Sex-specific lifetables are estimated for the territory of the German Empire from the individual data of the family reconstitution and the online genealogies. On the basis of these lifetables, we estimate the conditional life expectancy and derive the corresponding sex-specific differential mortality. Findings are compared with the official lifetable of the German Empire in 1871-1910. The contribution of each age group to the differential mortality is determined using the stepwise-replacement algorithm. RESULTS: The family reconstitution overestimates conditional life expectancy less than FamiLinx after 1871, when official lifetables are available in the German Empire. However, both sources fail to capture the sex-specific mortality differentials of the official lifetables at the end of the nineteenth century and show a higher life expectancy for males instead of females. The bias in sex-specific mortality rates is particularly pronounced in the age groups 15 to 45. DISCUSSION: Finally, we discuss possible explanations for the biased findings. Notability bias, the patriarchal approach to family trees, and maternal mortality are important mechanisms in the FamiLinx dataset. Censoring due to mobility serves as a potential reason for the bias in the family reconstitution.

[Mortality trends in Germany in an international context]. / Sterblichkeitsentwicklung in Deutschland im internationalen Kontext.

BACKGROUND AND AIM: Due to its strong economy and a well-developed healthcare system, Germany is well positioned to achieve above-average reductions in mortality. Nevertheless, in terms of life expectancy, Germany is increasingly falling behind Western Europe. We compare mortality trends in Germany with other Western European countries, covering the period from 1960 to 2019. The focus is on long-term trends in Germany's ranking in international mortality trends. In addition, we conduct a detailed mortality analysis by age. METHODS: Our analysis is mostly based on mortality data from the Human Mortality Database (HMD). Cause-specific mortality data originate from the database of the World Health Organization (WHO). For the international comparison of mortality trends, we use conventional mortality indicators (age-standardized mortality rate, period life expectancy). RESULTS: Compared to other Western European countries, Germany has higher mortality in the middle and older age groups. Germany's life expectancy gap compared to Western Europe has grown during the past 20 years. In 2000, Germany was 0.73 years behind for men and 0.74 years behind for women. By 2019, these figures had risen to 1.43 and 1.34 years, respectively. This is mainly due to mortality from non-communicable diseases. CONCLUSION: For Germany to catch up with other Western European countries, a stronger focus on further reducing mortality at ages 50+ is crucial. This also requires further research to understand the factors behind Germany's disadvantageous position.

[How has life expectancy without functional limitations developed in Germany? An analysis with data from the German Ageing Survey (DEAS)]. / Wie hat sich die Lebenserwartung ohne funktionelle Einschränkungen in Deutschland entwickelt? Eine Analyse mit Daten des Deutschen Alterssurveys (DEAS).

INTRODUCTION: The long-term increase in life expectancy raises the question of whether the increased life expectancy is accompanied by an extension of years without health limitations. The study analyzes how life expectancy without functional and mobility limitations from the ages of 46 and 65 and their proportions of remaining life expectancy have changed since 2008. METHODS: We analyze data from the German Ageing Survey of the 2008, 2014, and 2020/21 waves. Life expectancy without functional limitations (disability-free life expectancy-DFLE) was calculated using the Sullivan method. Severe functional limitations (using the Global Activity Limitation Indicator-GALI) and mobility limitations (climbing stairs, walking more than 1 km) were examined. RESULTS: Compression of morbidity in the GALI has been observed in 46- and 65-year-old men since 2014, but not in women of the same age. In terms of mobility, 46- and 65-year-old men show trends towards compression when climbing stairs and 46-year-old men when walking more than 1 km since 2014. The values for women have stagnated for the first two indicators mentioned, but not for 46-year-old women since 2014 when walking more than 1 km. DISCUSSION: Our analyses show different trends in DFLE depending on the indicator, age, and gender and do not allow a clear answer to the question of morbidity compression or expansion. We tend to see morbidity compression in men, whereas trends of stagnation or expansion tend to be seen in women. These results signal challenges in maintaining functional health, especially in women, and point to the need for targeted interventions to improve quality of life and healthy life expectancy.

[Healthy life expectancy: a critical look at the benefits and potential of the demographic health indicator]. / Gesunde Lebenserwartung: Ein kritischer Blick auf Nutzen und Potenziale des demographischen Gesundheitsindikators.

Demographic ageing yields many societal consequences that depend strongly on the health status of the population. Special indicators have been developed for tracking and assessing population health, which are referred to with the overarching term healthy life expectancy (HLE). The derivation of HLE is intuitive and easily comprehensible. However, an overly simplistic interpretation hides the extreme complexity inherent in adding the health dimension to the life table. This makes HLE compared to classic life expectancy (LE) extremely sensitive to certain conceptual and methodological features. In the article, this is presented in more detail for three aspects: the underlying definition of health, the choice of survey data as a basis for estimating health status, and the reporting behavior of survey participants. It is shown that the impact on HLE can be enormous, leading to considerable bias in the interpretation of levels and trends, but also in the analysis of differences between populations. Nevertheless, the extension of classical LE to HLE is an important achievement that must not be abandoned. Therefore, the article also discusses ways in which the HLE indicator could be made more robust and reliable. Until this is achieved, however, the high methodological sensitivity of HLE must not be ignored if it is used to assess the health status of populations and as a basis for health policy measures.

[The gender paradox in health-impaired lifetime-end of a myth?] / Das Geschlechterparadoxon in der gesundheitlich beeinträchtigten Lebenszeit ­ Ende eines Mythos?

BACKGROUND: Women live longer than men, but they spend more life years with health-impairment. This article examines the extent to which this gender paradox can be explained by two factors: the "mortality effect," which results from the higher life expectancy of women, and "differential item functioning" (DIF), which refers to gender differences in reporting behavior. METHODS: Impaired life expectancy at age 50 is calculated for the health indicators general health, limitations, and chronic morbidity using the Sullivan method. Data on health prevalence are obtained from the 2012 survey "Gesundheit in Deutschland aktuell" (GEDA), data on mortality is taken from the Human Mortality Database. The gender difference in impaired life expectancy is decomposed into the mortality effect and the health effect. The latter is finally adjusted for DIF effects on the basis of vignettes from the 2004 SHARE survey. RESULTS: The gender paradox can be resolved not only partially but completely for all three health indicators considered by the mortality effect and DIF. After taking these two factors into account, the gender difference in impaired life expectancy reverses from higher values for women to higher values for men. DISCUSSION: The causes of the gender paradox are highly complex and the differences between women and men in total and impaired life expectancy are not necessarily going into contradictory directions. The extent of women's higher impaired life expectancy depends decisively on the underlying health indicator and is largely explained by the mortality effect.

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.

The Global Road Traffic Death Rate and Human Development Index from 2000 to 2019: A Trend Analysis.

BACKGROUND: Numerous studies on the association between the human development index (HDI) and road traffic death rate (RTDR) merely focus on developed countries, not reflecting the relationship between the HDI components and RTDR in a time-trend analysis. Accordingly, this study analyzes the trends of RTDR and their association with the HDI and its components from 2000 to 2019. METHODS: The RTDR data of 154 countries were imported into the unconditional latent growth model (LGM) to assess the RTDR trends. The impact of the HDI and its components (viz., education, income, and life expectancy [LE viz]) on the trajectory of RTDR was also evaluated using the conditional LGM. RESULTS: The results of the unconditional LGM indicated an overall decreasing trend in RTDR. The conditional LGM results revealed the negative effect of the HDI and its components on the model parameters. The findings of random forests indicated that education and LE were the most crucial variables. CONCLUSION: Overall, this study emphasizes the significance of HDI and its components, particularly education and LE, in lowering the number of traffic fatalities. In this sense, improving formal education and LE could be one of the main policies that policymakers could consider to reduce RTDR.

Primary Care Access in Areas of the United States With Aging Populations.

The percentage of U.S. residents 65 years and older was 17% in 2020, and this number is expected to rise due to the aging of the baby boomer generation.1Although life expectancy fell between 2020 and 2021, the proportion of U.S. residents older than 65 years continues to increase.2This age group often has more medical comorbidities and prescription medications, increasing the demand for primary care access. Domestic migration (U.S. residents moving within the country) of this retirement-aged population further strains the primary care workforce in underserved areas.

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.