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.

[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.

[Socioeconomic deprivation and premature mortality in Germany, 1998-2021 : An ecological study with what-if scenarios of inequality reduction]. / Sozioökonomische Deprivation und vorzeitige Sterblichkeit in Deutschland 1998­2021 : Eine ökologische Studie mit What-if-Szenarien der Ungleichheitsreduktion.

BACKGROUND: Earlier mortality in socioeconomically disadvantaged population groups represents an extreme manifestation of health inequity. This study examines the extent, time trends, and mitigation potentials of area-level socioeconomic inequalities in premature mortality in Germany. METHODS: Nationwide data from official cause-of-death statistics were linked at the district level with official population data and the German Index of Socioeconomic Deprivation (GISD). Age-standardized mortality rates before the age of 75 were calculated stratified by sex and deprivation quintile. A what-if analysis with counterfactual scenarios was applied to calculate how much lower premature mortality would be overall if socioeconomic mortality inequalities were reduced. RESULTS: Men and women in the highest deprivation quintile had a 43% and 33% higher risk of premature death, respectively, than those in the lowest deprivation quintile of the same age. Higher mortality rates with increasing deprivation were found for cardiovascular and cancer mortality, but also for other causes of death. Socioeconomic mortality inequalities had started to increase before the COVID-19 pandemic and further exacerbated in the first years of the pandemic. If all regions had the same mortality rate as those in the lowest deprivation quintile, premature mortality would be 13% lower overall. DISCUSSION: The widening gap in premature mortality between deprived and affluent regions emphasizes that creating equivalent living conditions across Germany is also an important field of action for reducing health inequity.

Widening area-based socioeconomic inequalities in cancer mortality in Germany between 2003 and 2019.

Cancer mortality has declined in recent decades, but-due to a lack of national individual-level data-it remains unclear whether this applies equally to all socioeconomic groups in Germany. Using an area-based approach, this study investigated socioeconomic inequalities in cancer mortality and their secular trends on a German nationwide scale for the first time. Official cause-of-death data from 2003 to 2019 were linked to the district-level German Index of Socioeconomic Deprivation. Age-standardised mortality rates for all cancers combined and the most common site-specific cancers were calculated according to the level of regional socioeconomic deprivation. To quantify the extent of area-based socioeconomic inequalities in cancer mortality, absolute (SII) and relative (RII) indices of inequality were estimated using multilevel Poisson models. On average, cancer mortality was 50% (women) and 80% (men) higher in Germany's most deprived than least deprived districts (absolute difference: 84 deaths per 100,000 in women and 185 deaths per 100,000 in men). As declines in cancer mortality were larger in less deprived districts, the socioeconomic gap in cancer mortality widened over time. This trend was observed for various common cancers. Exceptions were cancers of the lung in women and of the pancreas in both sexes, for which mortality rates increased over time, especially in highly deprived districts. Our study provides first evidence on increasing socioeconomic inequalities in cancer mortality on a nationwide scale for Germany. Area-based linkage allows to examine socioeconomic inequalities in cancer mortality across Germany and identify regions with high needs for cancer prevention and control.

Trends in cancer-free working life expectancy based on health insurance data from Germany-Is the increase as strong as in working life expectancy?

BACKGROUND: Against the backdrop of population ageing, governments are facing the need to raise the statutory retirement age. In this context, the question arises whether these extra years added to working life would be spent in good health. As cancer represents a main contributor to premature retirement this study focuses on time trends and educational inequalities in cancer-free working life expectancy (WLE). METHODS: The analyses are based on the data of a large German health insurer covering annually about 2 million individuals. Cancer-free WLE is calculated based on multistate life tables and reported for three periods: 2006-2008, 2011-2013, and 2016-2018. Educational inequalities in 2011-2013 were assessed by two educational levels (8 to 11 years and 12 to 13 years of schooling). RESULTS: While labour force participation increased, cancer incidence rates decreased over time. Cancer-free WLE at age 18 increased by 2.5 years in men and 6.3 years in women (age 50: 1.3 years in men, 2.4 years in women) between the first and third period while increases in WLE after a cancer diagnosis remained limited. Furthermore, educational inequalities are substantial, with lower groups having lower cancer-free WLE. The proportion of cancer-free WLE in total WLE remained constant in women and younger men, while it decreased in men at higher working age. CONCLUSION: The increase in WLE is accompanied by an increase in cancer-free WLE. However, the subgroups considered have not benefitted equally from this positive development. Among men at higher working age, WLE increased at a faster pace than cancer-free WLE. Particular attention should be paid to individuals with lower education and older men, as the general level and time trends in cancer-free WLE are less favourable.

[Evidence syntheses in public health: An overview]. / Evidenzsynthesen in Public Health: ein Überblick.

BACKGROUND: Since the beginning of the COVID-19 pandemic, there has been a high demand for rapid evidence syntheses to answer urgent public health questions. This article provides an overview of different types of reviews for public health questions and a synthesis of existing recommendations for the preparation of reviews. The aim is to support the planning of one's own review and the critical evaluation of published reviews. METHODS: The basis of this summary is an extensive search for guidelines and recommendations for different review types. Furthermore, internal journal clubs were held to determine knowledge needs and to critically discuss the various review types. Relating to the dissemination of results, fact sheets were developed for the individual review types including the most important information, prerequisites and work steps, as well as a decision tree for identifying the appropriate review type for the respective question. RESULTS: Of the review types identified, Systematic, Rapid, Scoping, Umbrella, and Narrative Reviews were considered in more detail because they are particularly relevant to public health issues. Together with scoping and umbrella reviews, systematic reviews have the highest resource requirements due to the demands for extensive, systematic evidence synthesis and reproducibility. Rapid methods can accelerate the review process, for example by a very narrowly formulated question, a limited literature search, or the execution of certain steps by one instead of two persons. DISCUSSION: Systematic Reviews may be considered as the gold standard, but they were developed primarily for clinical questions relating to interventions. This article, however, focusses on review types that consider the diversity of questions as well as the predominant use of quantitative methods in the field of public health. The fact sheets developed and the decision tree should enable low-threshold access to reviews while linking the perspectives of research and resource planning. They complement existing guidelines and recommendations. CONCLUSION: To answer the diverse spectrum of public health questions, various types of reviews with various requirements and approaches are available. Given this diversity, a systematic introduction can be helpful for researchers planning or assessing a review.

[Personal Resources of Adolescents in Eastern and Western Germany - Results of the KiGGS Study 15 and 25 years after the German Reunification]. / Personale Ressourcen von Jugendlichen in Ost- und Westdeutschland ­ Ergebnisse der KiGGS-Studie 15 und 25 Jahre nach der Wende.

QUESTIONS: More than 15 years after the German reunification, were there differences in the personal resources among adolescents born around 1989 between East and West? How did the differences of this generation develop? METHODS: Data from the study on the health of children, adolescents and young adults in Germany (KiGGS study) from the years 2003-2006 and 2014-2017 are used to determine the prevalence of low personal resources in 14-17-year-old adolescents in Eastern and Western Germany. Cross-sectional data at both time periods are compared between East and West, and longitudinal data are used to follow the cohort over the course of age RESULTS: Around 15 years after the German reunification, 14- to 17-year-olds from East Germany more frequently show fewer personal resources and have lower self-efficacy expectations than adolescents of the same age in West Germany. 10 years later, these differences are barely visible and have partially reversed. The east-west differences found cannot be explained by the different socio-economic situations of the families in East and West. DISCUSSION: The results show that in the 2000s, adolescents born around 1989 from families living in Eastern Germany, showed a higher risk of having fewer personal resources than adolescents from families living in Western Germany. 25 years after the German reunification this is no longer recognizable. While the differences between East and West decrease over time, the importance of the socio-economic situation of the family for the personal resources of adolescents as a whole increases, to the detriment of those with a lower socioeconomic status. The results indicate the need for targeted interventions to strengthen psychosocial resources especially for children and adolescents in phases of transformation and biographical breaks.

German Index of Socioeconomic Deprivation (GISD): Revision, update and applications.

Background: Regional deprivation indices enable researchers to analyse associations between socioeconomic disadvantages and health outcomes even if the health data of interest does not include information on the individuals' socioeconomic position. This article introduces the recent revision of the German Index of Socioeconomic Deprivation (GISD) and presents associations with life expectancy as well as age-standardised cardiovascular mortality rates and cancer incidences as applications. Methods: The GISD measures the level of socioeconomic deprivation using administrative data of education, employment, and income situations at the district and municipality level from the INKAR database. The indicators are weighted via principal component analyses. The regional distribution is depicted cartographically, regional level associations with health outcomes are presented. Results: The principal component analysis indicates medium to high correlations of the indicators with the index subdimensions. Correlation analyses show that in districts with the lowest deprivation, the average life expectancy of men is approximately six years longer (up to three years longer for women) than for those from districts with the highest deprivation. A similar social gradient is observed for cardiovascular mortality and lung cancer incidence. Conclusions: The GISD provides a valuable tool to analyse socioeconomic inequalities in health conditions, diseases, and their determinants at the regional level.

Emerging socio-economic disparities in COVID-19-related deaths during the second pandemic wave in Germany.

Over the course of the second pandemic wave in late 2020, new infections with severe acute respiratory syndrome coronavirus-2 shifted from the most affluent to the most deprived regions of Germany. This study investigated how this trend in infections played out for deaths due to coronavirus disease 2019 (COVID-19) by examining area-level socio-economic disparities in COVID-19-related mortality during the second pandemic wave in Germany. The analysis was based on nationwide data on notified deaths, which were linked to an area-based index of socio-economic deprivation. In the autumn and winter of 2020/2021, COVID-19-related deaths increased faster among residents in Germany's more deprived districts. From late 2020 onwards, the mortality risks of men and women in the most deprived districts were 1.52 (95% confidence interval [CI] 1.27-1.82] and 1.44 (95% CI 1.19-1.73) times higher than among those in the most affluent districts, respectively, after adjustment for age, urbanization and population density. To promote health equity in the pandemic and beyond, deprived populations should receive increased attention in pandemic planning, infection control and disease prevention.

Population change and the burden of hospitalization in Germany 2000-2040: Decomposition analysis and projection.

Demographic factors, such as population aging and shrinkage, and non-demographic factors, such as hospitalization rate and length of hospital stay, generate challenges for inpatient care. This paper used decomposition analysis to assess how changes in these factors affected the number of hospital treatment days from 2000 to 2015 in Germany. Demographic aging was linked to increases in the number of treatment days for women (+10.0%) and men (+19.2%) and in hospitalization rates for women +6.0% and men +5.4%. However, these increases were offset by decreases in the number of hospital days (women: 16.5%; men: 7.3%) and length of stay (women: -27.4%; men -26.3%). For the projection up to 2040, 12 scenarios were developed (six for women and six for men) using three variants for future population demographics and two variants for future length of stay and hospitalization rates. One of the two variants for future length of stay and hospitalization rates provides for a constant value for the year 2015. For the second of these two variants variant, a logarithmic model was estimated on the basis of values from 2000 to 2015. and the trends were extrapolated using this model until 2040. The strongest overall predicted increase was 18.4% between 2015 and 2040, including a 22.4% increase for men. In two scenarios for women, only slight declines were predicted. All results, both for the decomposition analysis and projection, indicated a moderate but sustained effect of demographic aging on the number of hospital treatment days, leading to a significant increase in hospital treatment days over the study period. Non-demographic factors also had strong influences, especially in shorter time periods, but these effects offset each other over time. The change in the population size in the period under study had very little effect on the number of hospital treatment days.

Demographics of the female population aged 50 years and older in Germany's north east region - Selected aspects.

Considerable demographic differences characterise the Berlin, Brandenburg and Mecklenburg-Western Pomerania region (the north east region), for example, regarding settlement patterns and age structures. These differences are also observed among women in the age group 50 years and older. The most conspicuous difference is population density. While Berlin is one of the most densely populated cities in Germany, Brandenburg and Mecklenburg-Western Pomerania are the two most sparsely populated federal states. In these two states, the female population is on average older than in Berlin, a fact particularly true of rural areas. Continuing migration is a contributing factor not only to a rise in average age but also to further decreasing population density. An essential consideration for rural area health care provision are the distances people need to travel to reach services. Having (access to) a car is a key factor. Yet, as older women are less likely than men of the same age to have (access to) a car, public transport and other modern forms of mobility (dial-a-bus services, shared taxis) are gaining in importance.

Socioeconomic inequalities and COVID-19 - A review of the current international literature.

Social epidemiological research describes correlations between socioeconomic status and the population's risk to become diseased or die. Little research of such correlations for SARS-CoV-2 and COVID-19 has so far been conducted. This scoping review provides an overview of the international research literature. Out of the 138 publications found, 46 were later included in the analysis. For the US and the UK, the reported findings indicate the presence of socioeconomic inequalities in infection risks as well as the severity of the course of the disease, with socioeconomically less privileged populations being hit harder. There are far fewer findings for Germany to date, as is the case for most other European countries. However, the scant evidence available so far already indicates that social inequalities are a factor in COVID-19. Most of these analyses have been ecological studies with only few studies considering socioeconomic inequalities at the individual level. Such studies at the individual level are particularly desirable as they could help to increase our understanding of the underlying pathways that lead to the development of inequalities in infection risks and the severity of disease and thereby could provide a basis to counteract the further exacerbation of health inequalities.

Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany.

Experiences with acute respiratory diseases which caused virus epidemics in the past and initial findings in the research literature on the current COVID-19 pandemic suggest a higher SARS-CoV-2 infection risk for socioeconomically disadvantaged populations. Nevertheless, further research on such a potential association between socioeconomic status and SARS-CoV-2 incidence in Germany is required. This article reports on the results of a first Germany-wide analysis of COVID-19 surveillance data to which an area-level index of socioeconomic deprivation was linked. The analysis included 186,839 laboratory-confirmed COVID-19 cases, the data of which was transferred to the Robert Koch Institute by 16 June 2020, 00:00. During the early stage of the epidemic up to mid-April, the data show a socioeconomic gradient with higher incidence in less deprived regions of Germany. Over the course of the epidemic, however, this gradient becomes less measurable and finally reverses in south Germany, the region hardest hit by the epidemic, to the greater detriment of the more deprived regions. These results highlight the need to continue monitoring social epidemiological patterns in COVID-19 and analysing the underlying causes to detect dynamics and trends early on and countering a potential exacerbation of health inequalities.

Mortality of the elderly population during the COVID-19 pandemic. Are there north-south differences?

COVID-19 disease courses are dynamic and in some cases, fatal. In this article, we aim to identify the periods where overall mortality is higher, and therefore to more precisely measure excess mortality. We analysed mortality rate development for the population aged 65 years and older in Germany as a whole, a south Germany region (comprising the federal states of Baden-Wuerttemberg and Bavaria) and a north Germany region (comprising the federal states of Schleswig Holstein, Mecklenburg Western-Pomerania and Brandenburg). The article analyses the mortality rates per calendar week that have been published by Germany's Federal Statistical Office (Destatis) for the first 23 calendar weeks of 2020. We compare these figures with those for the same period 2016, the last year in which there was no influenza-related excess mortality. In calendar weeks ten to 15, mortality rates for the elder population rose exceptionally in the south compared to the north Germany region as well as compared to the 2016 figures. A peak was reached in calendar weeks 14 and 15. Mortality rates peaked around two to three weeks after incidence. Since this peak, mortality rates have decreased again, but up to calendar week 18 have remained above the 2016 rates. Overall the rise in mortality rates observed appears to be related to the COVID-19 pandemic and not the annual influenza wave.

Developments in life expectancy in Germany. Current trends.

Since the beginning of the 1990s, life expectancy in Germany has increased by 4.2 years among women (to 83.2 years), and by 5.9 years among men (to 78.4 years). This rise is related to the increasing convergence of life expectancy in Germany's new and old federal states. Recently, life expectancy among women in the new federal states has even risen slightly above the level found in the old federal states. In addition, differences between socioeconomic groups continue to be observed in Germany. Women in the highest income group have a 4.4-year longer life expectancy than women in the lowest income group. Similarly, an 8.6-year difference exists between men in the highest income group and men in the lowest income group. Influenza waves can adversely affect the development of life expectancy in certain calendar years. In comparison to other European countries, Germany has a mid-range life expectancy: the current difference between life expectancy in Germany and Switzerland (the European country with the highest life expectancy) is 2.7 years.

30 years after the fall of the Berlin Wall: Regional health differences in Germany.

Following the fall of the Berlin Wall in November 1989, considerable effort was made to bring the living conditions and levels of social participation in the former East German federal states into line with the former West German federal states. As a result, differences in health between the East and the West diminished significantly, in many cases as early as the 1990s, examples being life expectancy and cardiovascular mortality. In regard to health behaviour, the overall tendency has also clearly been one of convergence. Thus, only very small differences can be observed today, for example in the use of tobacco or in the prevalence of obesity. Yet the results also highlight the insufficiency of regarding the remaining differences as a simple comparison between East and West. Instead, the focus should shift towards smaller-scale approaches that take regional differences in living conditions into account.

[Impact of Population Aging on Utilization of Medical Rehabilitation in Germany Till 2040]. / Einfluss der demografischen Alterung auf die Inanspruchnahme der medizinischen Rehabilitation in Deutschland bis 2040.

BACKGROUND: The paper analyzes the influence of population aging on the future number of medical rehabilitation cases. Implications for the most important providers of rehabilitation services (Deutsche Rentenversicherung (DRV) (German Pension Insurance) and Gesetzliche Krankenversicherung (GKV) (Statutory Health Insurance)) are discussed. METHODS: Data provided by the DRV and the GKV were used. A third database is the Hospital Statistics of the Federal Statistical Office. Each database contains data of rehabilitation cases of certain subpopulations. Based on the 13th coordinated population projection a forecast up to 2040 with each of these databases was undertaken. RESULTS: Population aging will decrease case numbers for the DRV from 961 thousand (2015) to 911 thousand in 2040 (- 5.2%). Cases of GKV will rise from 742 thousand (2015) to 934 thousand in 2040 (+25.9%). Because of population aging, the case numbers of older people (65 years or older) in rehabilitation will increase by about a third until 2040. CONCLUSIONS: The expected increase in the number of elderly rehabilitants concerns especially the GKV. There are a number of problems arising from this, concerning financing of rehabilitation and the aspect of growing importance of multimorbidity and geriatric rehabilitation. Furthermore, there is a growing gap between the demographic development of rehabilitation in working age and the demographic component of the budgets for this rehabilitation in the DRV.

[Regional differences in the development of hospitalizations : An effect of different demographic trends?] / Regionale Unterschiede der Entwicklung der Krankenhausbehandlungen : Effekt unterschiedlicher demografischer Trends?

Population aging and population decline in many regions of the Federal Republic of Germany are key elements of demographic change. In the regions concerned there is a rising number of older people and, simultaneously, a declining population. So far, the consequences of regional shrinkage and growth for inpatient care don't seem to have been analysed very well. This paper analyses the influence of population aging and declining/increasing population (demographic factors) as well as other, non-demographic factors on the number of hospitalizations in Germany and the Federal States since 2000.One result of the analysis is that there are major differences between the Federal States. The analysis shows, for example, an increase of hospitalizations in Berlin while in Saxony-Anhalt the number of hospitalizations declines. The increase in Berlin was the result of population aging and, to a lower extent, an increase in population. In Saxony-Anhalt the declining population resulted in a decreasing number of hospitalizations. Population aging and non-demographic factors were not able to compensate this trend.Overall, the effect of demographic factors on the number of hospitalizations remains constant over time. Short-term changes of hospitalizations are due to non-demographic factors, such as epidemiological trends, (for example trends of incidence or prevalence), or structural changes of health care service (for example patients shifting between different sectors of health care or the introduction of new reimbursement systems).