Scohy Aline, Lesnik Tina, Devleesschauwer Brecht, Haneef Romana
Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
National Institute of Public Health, Ljubljana, Slovenia.
Arch Public Health. 2025 Jul 11;83(1):185. doi: 10.1186/s13690-025-01652-x.
Causes of death (CoDs) statistics are an important source of information for epidemiological research. Some causes of death (CoDs) are not regarded as sufficiently specific causes of death for public health purposes, they are named "ill-defined deaths" (IDDs) or "garbage codes". Redistribution is the process of reallocating IDDs to plausible underlying causes (i.e., target cause) as defined in the Global Burden of Disease (GBD) study. The main objectives of this commentary were to describe the various steps taken for the redistribution of IDDs by applying the Belgium redistribution approach to national mortality data sets and to underline key challenges with potential solutions.A four-step probabilistic redistribution method was developed in the context of the Belgian national Burden of Disease (BeBOD) study including followings: (1) predefined ICD codes, (2) package redistribution using multiple causes of death data (MCOD), (3) internal redistribution, and (4) redistribution to all causes. The Belgian, French and Slovenian mortality databases included a share of 34%, 36% and 20% of IDDs in 2017, respectively. The majority of the IDDs were redistributed using predefined ICD-10 codes (14%), followed by package redistribution using MCOD data (11%) in Belgium and French database, whereas this redistribution was 7% and 10% for Slovenia database, respectively. The main challenges encountered were lack of computational capacity to run 100 simulations and lack of MCOD.This commentary highlighted the importance of the harmonized approach of redistribution that allowed us to get an in-depth knowledge of various steps applied for the redistribution process transparently and allowed comparing these results with other European countries. Further research is recommended considering creating a common/standardized consensus list of IDDs based on a comprehensive definition and aligned with the context of national mortality databases in European countries.
死亡原因（CoDs）统计数据是流行病学研究的重要信息来源。某些死亡原因（CoDs）在公共卫生目的方面未被视为足够具体的死亡原因，它们被称为“死因不明死亡”（IDDs）或“垃圾代码”。重新分配是将死因不明死亡重新分配到全球疾病负担（GBD）研究中定义的合理潜在原因（即目标原因）的过程。本评论的主要目的是描述通过将比利时重新分配方法应用于国家死亡率数据集来重新分配死因不明死亡所采取的各个步骤，并强调关键挑战及潜在解决方案。在比利时国家疾病负担（BeBOD）研究的背景下开发了一种四步概率重新分配方法，包括以下内容：（1）预定义的国际疾病分类（ICD）代码，（2）使用多种死因数据（MCOD）进行包重新分配，（3）内部重新分配，以及（4）重新分配到所有原因。2017年，比利时、法国和斯洛文尼亚的死亡率数据库中，死因不明死亡的占比分别为34%、36%和20%。在比利时和法国数据库中，大多数死因不明死亡是使用预定义的ICD - 10代码重新分配的（14%），其次是使用MCOD数据进行包重新分配（11%），而在斯洛文尼亚数据库中，这种重新分配分别为7%和10%。遇到的主要挑战是缺乏运行100次模拟的计算能力以及缺乏MCOD。本评论强调了统一重新分配方法的重要性，该方法使我们能够深入了解透明应用于重新分配过程的各个步骤，并能够将这些结果与其他欧洲国家进行比较。建议进一步开展研究，考虑基于全面定义并与欧洲国家国家死亡率数据库的背景相一致，创建一份通用/标准化的死因不明死亡共识清单。
