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Background Male excess mortality is mostly related to non-biological factors, and is thus of high social- and health-policy concern. Previous research has mainly focused on national patterns, while subnational disparities have been less in the focus. This study takes a spatial perspective on subnational patterns, covering seven European countries at the crossroad between Eastern and Western Europe. Methods We analyze a newly gathered spatially detailed data resource comprising 228 regions with well-established demographic methods to assess the contribution of specific causes of death to the evolution of sex mortality differentials (SMDs) since the mid-1990s. Results Our results show that declines in SMDs were mostly driven by a reduction of male excess mortality from cardiovascular diseases and neoplasms (about 50–60% and 20–30%, respectively). In Western Europe, trends in deaths from neoplasms contributed more to the reduction of SMDs, while among regions located in Eastern-Central Europe narrowing SMDs were mostly driven by changes in cardiovascular disease-related deaths. Moreover, men show up to three times higher mortality levels from external causes as compared to women in several analyzed regions. But in absolute terms, external deaths play only a minor role in explaining SMDs due to their small contribution to overall mortality. Conclusions We conclude that examining the regional development of SMDs is useful for introducing targeted social and health policies in order to reduce and prevent mortality inequalities between women and men. [ABSTRACT FROM AUTHOR]

Background: Over the past half century the global tendency for improvements in longevity has been uneven across countries. This has resulted in widening of inter-country disparities in life expectancy. Moreover, the pattern of divergence appears to be driven in part by processes at the level of country groupings defined in geopolitical terms. A systematic quantitative analysis of this phenomenon has not been possible using demographic decomposition approaches as these have not been suitably adapted for this purpose. In this paper we present an elaboration of conventional decomposition techniques to provide a toolkit for analysis of the inter-country variance, and illustrate its use by analyzing trends in life expectancy in developed countries over a 40-year period. Methods: We analyze trends in the population-weighted variance of life expectancy at birth across 36 developed countries and three country groups over the period 1970-2010. We have modified existing decomposition approaches using the stepwise replacement algorithm to compute age components of changes in the total variance as well as variance between and within groups of Established Market Economies (EME), Central and Eastern Europe (CEE), and the Former Soviet Union (FSU). The method is generally applicable to the decomposition of temporal changes in any aggregate index based on a set of populations. Results: The divergence in life expectancy between developed countries has generally increased over the study period. This tendency dominated from the beginning of 1970s to the early 2000s, and reversed only after 2005. From 1970 to 2010, the total standard deviation of life expectancy increased from 2.0 to 5.6 years among men and from 1.0 to 3.6 years among women. This was determined by the between-group effects due to polarization between the EME and the FSU. The latter contrast was largely fueled by the long-term health crisis in Russia. With respect to age, the increase in the overall divergence was attributable to between-country differences in mortality changes at ages 15-64 years compared to those aged 65 and older. The within-group variance increased, especially among women. This change was mostly produced by growing mortality differences at ages 65 and older. Conclusions: From the early 1970s to the mid-2000s, the strong divergence in life expectancy across developed countries was largely determined by the between-group variance and mortality polarization linked to the East--West geopolitical division. [ABSTRACT FROM AUTHOR]

The conventional approach to gauging mortality convergence in Europe relies on life expectancy estimates (e0${{e}^0}$) at the national level. However, mortality can differ within countries significantly. To better apprehend whether Europe's mortality patterns have been converging or diverging over recent decades, we must shift our focus to regional mortality data. Using data from statistical offices, we present annual e0${{e}^0}$ estimates for 420 regions in 16 EU countries from 1995 to 2019. In our empirical analysis, we examined whether regions with initially high mortality levels caught up with low‐mortality regions, and we investigated changes in the standard deviation of Europe's regional e0${{e}^0}$ distribution over time. Indeed, mortality variation has generally decreased from 1995 to 2019 due to larger gains in e0${{e}^0}$ for regions with initially high mortality levels. The convergence phase took place mostly during the first half of the entire time period analyzed. Over more recent periods, however, we observe more heterogeneity in the development of e0${{e}^0}$. Some advantaged regions realized further gains in e0${{e}^0}$, even as e0${{e}^0}$ improvements slowed for more disadvantaged regions. In conclusion, our analysis underscores the importance of addressing widening health inequalities. Policies should target disadvantaged regions to retard mortality divergence across Europe. [ABSTRACT FROM AUTHOR]

Evaluating the impact of health systems on premature mortality across different countries is a very challenging task, as it is hardly possible to disentangle it from the influence of contextual factors such as cultural differences. In this respect, the German-speaking area in Central Europe (Austria, Germany, South Tyrol and large parts of Switzerland) represents a unique 'natural experiment' setting: While being exposed to different health policies, they share a similar culture and language. To assess the impact of different health systems on mortality differentials across the German-speaking area, we relied on the concept of avoidable mortality. Based on official mortality statistics, we aggregated causes of death below age 75 that are either 1) amenable to health care or 2) avoidable through primary prevention. We calculated standardised death rates and constructed cause-deleted life tables for 9 Austrian, 96 German, 1 Italian and 5 Swiss regions from 1992 to 2019, harmonised according to the current territorial borders. There are strong north-south and east-west gradients in amenable and preventable mortality across the studied regions to the advantage of the southwest. However, the Swiss regions still show significantly lower mortality levels than the neighbouring regions in southern Germany. Eliminating avoidable deaths from the life tables reduces spatial inequality in life expectancy in 2017/2019 by 30% for men and 28% for women. The efficiency of health policies in assuring timely and adequate health care and in preventing risk-relevant behaviour has room for improvement in all German regions, especially in the north, west and east, and in eastern Austria as well. • Strong north-south and east-west gradients across the studied area. • Swiss regions and South Tyrol show the lowest outcomes of avoidable mortality. • Even best-performing regions of Germany and Austria are above Swiss level. • Spatial pattern related to varying effectiveness of health care and health policies. • Avoidable deaths explain approx. 30% of regional variation in life expectancy. [ABSTRACT FROM AUTHOR]

Objective: To measure the burden of the COVID-19 pandemic in 2020 at the subnational level by estimating excess mortality, defined as the increase in all-cause mortality relative to an expected baseline mortality level., Methods: Statistical and demographic analyses of regional all-cause mortality data provided by the vital statistics systems of 21 European countries for 561 regions in Central and Western Europe. Life expectancy losses at ages 0 and 60 for males and females were estimated., Results: We found evidence of a loss in life expectancy in 391 regions, whilst only three regions exhibit notable gains in life expectancy in 2020. For 12 regions, losses of life expectancy amounted to more than 2 years and three regions showed losses greater than 3 years. We highlight geographical clusters of high mortality in Northern Italy, Spain and Poland, whilst clusters of low mortality were found in Western France, Germany/Denmark and Norway/Sweden., Conclusions: Regional differences of loss of life expectancy are impressive, ranging from a loss of more than 4 years to a gain of 8 months. These findings provide a strong rationale for regional analysis, as national estimates hide significant regional disparities., (© 2024. The Author(s).)

Since its emergence in December 2019, the COVID-19 pandemic has resulted in a significant increase in deaths worldwide. This article presents a detailed analysis of the mortality burden of the COVID-19 pandemic across 569 regions in 25 European countries. We produce age and sex-specific excess mortality and present our results using Age-Standardised Years of Life Lost in 2020 and 2021, as well as the cumulative impact over the two pandemic years. Employing a forecasting approach based on CP-splines that considers regional diversity and provides confidence intervals, we find notable losses in 362 regions in 2020 (440 regions in 2021). Conversely, only seven regions experienced gains in 2020 (four regions in 2021). We also estimate that eight regions suffered losses exceeding 20 years of life per 1000 population in 2020, whereas this number increased to 75 regions in 2021. The contiguity of the regions investigated in our study also reveals the changing geographical patterns of the pandemic. While the highest excess mortality values were concentrated in the early COVID-19 outbreak areas during the initial pandemic year, a clear East-West gradient appeared in 2021, with regions of Slovakia, Hungary, and Latvia experiencing the highest losses. This research underscores the importance of regional analyses for a nuanced comprehension of the pandemic's impact., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)