The Burden of Disease in Germany at the National and Regional Level.

BACKGROUND: .Summary measures such as disability-adjusted life years (DALY) are becoming increasingly important for the standardized assessment of the burden of disease due to death and disability. The BURDEN 2020 pilot project was designed as an independent burden-of-disease study for Germany, which was based on nationwide data, but which also yielded regional estimates. METHODS: DALY is defined as the sum of years of life lost due to death (YLL) and years lived with disability (YLD). YLL is the difference between the age at death due to disease and the remaining life expectancy at this age, while YLD quantifies the number of years individuals have spent with health impairments. Data are derived mainly from causes of death statistics, population health surveys, and claims data from health insurers. RESULTS: In 2017, there were approximately 12 million DALY in Germany, or 14 584 DALY per 100 000 inhabitants. Conditions which caused the greatest number of DALY were coronary heart disease (2321 DALY), low back pain (1735 DALY), and lung cancer (1197 DALY). Headache and dementia accounted for a greater disease burden in women than in men, while lung cancer and alcohol use disorders accounted for a greater disease burden in men than in women. Pain disorders and alcohol use disorders were the leading causes of DALY among young adults of both sexes. The disease burden rose with age for some diseases, including cardiovascular diseases, dementia, and diabetes mellitus. For some diseases and conditions, the disease burden varied by geographical region. CONCLUSION: The results indicate a need for age- and sex-specific prevention and for differing interventions according to geographic region. Burden of disease studies yield comprehensive population health surveillance data and are a useful aid to decision-making in health policy.

Years of Life Lost to Death­A Comprehensive Analysis of Mortality in Germany Conducted as Part of the BURDEN 2020 Project

BACKGROUND: Knowing which diseases and causes of death account for most of the years of life lost (YLL) can help to better target appropriate prevention and intervention measures. The YLL in Germany for specific causes of death were estimated as part of the BURDEN 2020 project at the Robert Koch Institute. METHODS: Data from cause-of-death statistics were used for the analysis. ICD codes were grouped into causes of death categories at different levels of disaggregation. The YLL were estimated by combining each cause of death with the remaining life expectancy at the age of death. Deaths and YLL were compared by sex, age category, and regional distribution. RESULTS: Approximately 11.6 million years were estimated to be lost in Germany in 2017, of which 42.8% were lost by women and 57.2% by men. The largest number of YLL were due to (malignant) neoplasms (35.2%), followed by cardiovascular diseases (27.6%), gastrointestinal diseases (5.8%), and neurological diseases (5.7%). Deaths at younger ages had a greater impact on population health if expressed in YLL: the death share of persons under age 65 was 14.7%, but the years of life lost in this age group amounted to 38.3% of all YLL. The most common causes of death in this group include accidents, self-injury and violence, malignant neoplasms, and alcohol-related diseases. CONCLUSION: A large proportion of YLL is borne by young and middle-aged persons. These findings emphasize the need to introduce preventive strategies early in life to reduce the YLL at younger ages, as well as to prevent risk factors for diseases in older ages.

Redistributing ill-defined causes of death - a case study from the BURDEN 2020-project in Germany.

BACKGROUND: The cause of death statistics in Germany include a relatively high share (26% in 2017) of ill-defined deaths (IDD). To make use of the cause of death statistics for Burden of Disease calculations we redistribute those IDD to valid causes of death. METHODS: The process of proportional redistribution is described in detail. It makes use of the distribution of the valid ICD-codes in the cause of death data. We use examples of stroke, diabetes, and heart failure to illustrate how IDD are reallocated. RESULTS: The largest increases in the number of deaths for both women and men were found for lower respiratory infections, diabetes mellitus, and stroke. The numbers of deaths for these causes more than doubled after redistribution. CONCLUSION: This is the first comprehensive redistribution of IDD using the German cause of death statistics. Performing a redistribution is necessary for burden of disease analyses, otherwise there would be an underreporting of certain causes of death or large numbers of deaths coded to residual or unspecific codes.

[ICD coding of causes of death: challenges for calculating the burden of disease in Germany]. / ICD-Codierung von Todesursachen: Herausforderungen bei der Berechnung der Krankheitslast in Deutschland.

In the project BURDEN 2020 - "The burden of disease in Germany and its regions" - the years of life lost (YLL) due to premature mortality are calculated on the basis of official cause-of-death statistics. This requires the identification and redistribution of the so-called ill-defined ICD codes. "Ill-defined" means that an ICD code does not sufficiently reflect the cause of death, such that it is not informative for the calculation of the burden of disease.The first steps on the way to calculating cause-specific YLL are presented. Different frameworks of ill-defined codes are compared. The number of deaths with ill-defined codes that can be found in the German cause-of-death statistics in absolute and relative terms are analyzed, including how they are distributed by age, sex, and region.According to the WHO framework, 15.6% of the 925,200 deaths in Germany in 2015 can be identified as ill-defined. According to the framework of the Institute for Health Metrics and Evaluation (IHME) in the Global Burden of Disease Study (GBD), the proportion of ill-defined codes is 26.6%. The ICD-related distribution patterns hardly differ between WHO and IHME classifications. Considerable differences exist between the federal states, with shares of ill-defined codes between 16 and 35% (IHME framework).The cause-of-death statistics in Germany contain a considerable proportion of ill-defined codes. The differences between the federal states can only partially be explained by different electronic data processing. Due to further dissemination and improvement of electronic data collection, higher quality of cause-of-death statistics can be expected in the future.