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INTRODUCTION: Information on years of life lost (YLL) due to premature mortality is instrumental to assess the fatal impact of disease and necessary for the calculation of Belgian disability-adjusted life years (DALYs). This study presents a novel method to reallocate causes of death data. MATERIALS AND METHODS: Causes of death data are provided by Statistics Belgium (Statbel). First, the specific ICD-10 codes that define the underlying cause of death are mapped to the GBD cause list. Second, ill-defined deaths (IDDs) are redistributed to specific ICD-10 codes. A four-step probabilistic redistribution was developed to fit the Belgian context: redistribution using predefined ICD codes, redistribution using multiple causes of death data, internal redistribution, and redistribution to all causes. Finally, we used the GBD 2019 reference life table to calculate Standard Expected Years of Life Lost (SEYLL). RESULTS: In Belgium, between 2004 and 2019, IDDs increased from 31 to 34% of all deaths. The majority was redistributed using predefined ICD codes (14-15%), followed by the redistribution using multiple causes of death data (10-12%). The total number of SEYLL decreased from 1.83 to 1.73 million per year. In 2019, the top cause of SEYLL was lung cancer with a share of 8.5%, followed by ischemic heart disease (8.1%) and Alzheimer's disease and other dementias (5.7%). All results are available in an online tool https://burden.sciensano.be/shiny/mortality2019/ . CONCLUSION: The redistribution process assigned a specific cause of death to all deaths in Belgium, making it possible to investigate the full mortality burden for the first time. A large number of estimates were produced to estimate SEYLL by age, sex, and region for a large number of causes of death and every year between 2004 and 2019. These estimates are important stepping stones for future investigations on Disability-Adjusted Life Years (DALYs) in Belgium.
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The place where people die is not only considered an indicator of quality of death, but also has implications for health care costs and the organization of end-of-life care. Advancing urbanization, combined with social fragmentation, poor social conditions, and concentration of inpatient care in large cities make it relevant to study the place of death in a metropolitan context. The objective of this article is to examine determinants of place of death (home, care home, hospital) in a Belgian metropolitan region (Brussels) for patients suffering from chronic diseases eligible for palliative care. Using death certificate data, we describe place of death and associated factors for all deaths after chronic diseases in 2003 in Brussels (n=3672). Of all chronically ill patients, 15.1% died at home, 63.0% in hospital, and 21.6% in a care home. Of those residing in care homes, 23.8% died in hospital. Noncancer patients and residents of districts with higher socioeconomic status had a higher chance of dying at home or in a care home if they resided in one. Home death was also more likely for patients not living alone. Care home death was more likely with increasing age. Compared with other parts of Belgium and other big cities worldwide, few patients eligible for palliative care in Brussels died at home. Both the overall low proportion of people dying in familiar surroundings and the inequality between different districts in Brussels imply that a health policy aiming at facilitating dying in the place of choice might also need to develop specific approaches for metropolitan cities.
