Zusammenfassung Hintergrund Durch die deutsche Teilung wurden 2 kulturell sehr ähnliche Bevölkerungen sehr unterschiedlichen sozioökonomischen Bedingungen ausgesetzt, die sich nach 1989 wieder anglichen. Der Einfluss von Gesundheitsversorgung und Lebensumständen auf Sterblichkeitsunterschiede kann besser erfasst werden, wenn kulturelle Erklärungen weitgehend ausgeblendet werden können. Ziel der Arbeit Die Arbeit wertet harmonisierte Todesursachendaten erstmals detailliert nach Alter aus. Hierdurch kann aufgezeigt werden, welche Alter bzw. Geburtsjahrgänge besonders stark durch die deutsche Teilung und Wiedervereinigung in ihrer Mortalität beeinflusst wurden und auf welche Todesursachen dies zurückzuführen ist. Material und Methoden Die deutschen Todesursachenstatistiken wurden einem international standardisierten Harmonisierungsverfahren unterzogen, um Unterschieden und Brüchen in der Todesursachencodierung Rechnung zu tragen. Die Daten wurden mit Dekompositionsmethoden analysiert. Ergebnisse In den 1980er-Jahren stiegen die Ost-West-Unterschiede stark an, da Westdeutschland gerade in höheren Altern deutlich höhere Rückgänge bei der kardiovaskulären Mortalität erzielen konnte. Nach 1989 konnte Ostdeutschland in vielen Bereichen zum Westen aufholen. Dies gilt besonders für ältere Personen und Frauen, während gerade bei den stark von der ostdeutschen Transformationskrise betroffenen männlichen Geburtsjahrgängen (1950–1970) noch heute Ost-West-Unterschiede sichtbar sind. Diskussion Die geringere Lebenserwartung der ostdeutschen Bevölkerung Ende der 1980er-Jahre war primär durch Rückstände bei der kardiovaskulären Revolution bedingt. Die noch heute bestehenden Unterschiede sind eher Spätfolgen der ostdeutschen Transformationskrise als direkte Spätfolgen der Teilung.
Background: Regional comparisons of cancer-related mortality in Germany are traditionally focused on disparities between East and West Germany. Recent improvements in all-cause and cancer-related mortality show a diverse regional pattern beyond the known East-West mortality divide. A generalized approach of the avoidable/amenable cancer mortality definition is applied for suitable regional comparisons of long-term trends. Methods: Standardized death rates of preventable and amenable cancer mortality for men and women were computed for the period 1990–2014 to observe sex-specific excess mortality due to specific cancers after the German reunification. For regional comparison, three German super regions were defined in Eastern, Northwestern, and Southwestern Germany to account for similarities in long-term regional premature and cancer-related mortality patterns, socioeconomic characteristics, and age structure. Results: Since preventable and amenable cancer mortality rates typically have driven the recent trends in premature mortality, our findings underline the current regional pattern of preventable cancer mortality for males with disadvantages for Eastern Germany, and advantages for Southwestern Germany. Among women, the preventable cancer mortality has increased in Northwestern and Southwestern Germany after the German reunification but has decreased in Eastern Germany and converged to the pattern of Southwestern Germany. Similar patterns can be observed for females in amenable cancer mortality. Conclusions: Although the “traditional” East-West gap in preventable cancer mortality was still evident in males, our study provides some hints for more regional diversity in avoidable cancer mortality in women. An establishing north-south divide in avoidable cancer mortality could alter the future trends in regional cancer-related mortality in Germany.
The consequences of political reunification for health and mortality have the unique character of a 'natural experiment'. This is particularly true for the formerly divided German Baltic Sea region due to its cultural and geographic commonalities. This paper ascertains the changes and differences in premature mortality at ages 0-74 in urban and rural areas of the German states of Mecklenburg-Vorpommern (MV) and Schleswig-Holstein (SH) since reunification and the contribution made by 'avoidable' mortality. Using official cause-of-death data, the effectiveness of health care and health policies was measured based on the concept of avoidable mortality in terms of both amenable and preventable conditions. Methods of decomposition and standardisation were employed in order to erase the compositional effect from the mortality trend. As a result, mortality differences relate primarily to men and the rural areas of the German Baltic Sea region. Whereas the mortality levels in the urban areas of MV and SH have converged, the rural areas of MV still show higher levels of preventable and amenable mortality. The results show that the accessibility and quality of medical care in the thinly populated areas of MV and the effectiveness of inter-sectoral health policies through primary prevention, particularly with regard to men, have room for improvement.
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. Design: Statistical and demographic analyses of regional all-cause mortality data. Setting: The vital statistics systems of 21 European countries. Participants: The entire population of 561 spatial units in 21 European countries. Main Outcome Measures: Losses of life expectancy at ages 0 and 60 for males and females. Results: Evidence was found of a loss in life expectancy in 391 regions, while 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. Geographic clusters of high mortality were found in Northern Italia, Spain and Poland, while 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.
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