超越死亡的根本原因:研究死亡时多重发病的算法。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Francesco Grippo, Luisa Frova, Marilena Pappagallo, Magali Barbieri, Sergi Trias-Llimós, Viviana Egidi, France Meslé, Aline Désesquelles
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引用次数: 0

摘要

背景:在预期寿命高的国家,越来越多的人口患有几种疾病,这种情况被称为多重发病。除健康数据外,基于死亡证明所报告信息的死因数据也有助于监测和描述这种情况。这需要超越死亡的根本原因,并考虑到死亡证明上的所有原因,这些原因可能在病态过程中发挥了不同的作用,取决于它们之间的相互关系。方法:除了根本原因,生命登记系统中可用的死亡原因数据不能区分所有其他原因。我们根据世界卫生组织的规则开发了一种算法,为死亡证明上的每个条目分配一个“角色”。我们区分了以下角色:起源(o),当条件启动了一系列直接导致死亡的事件时;沉淀(p),当它是由原始条件或其后果之一引起时;相关的(a),当它导致死亡,但不是导致死亡的直接顺序的一部分;定义不清(i),即症状或体征等情况,或原因不明。我们将该算法应用于2017年四个国家(意大利、法国、西班牙和美国)的所有死亡记录。结果:四个国家的平均病因数量相似。死亡证明有一个以上原发原因的比例——一种典型的多重发病情况——从美国的10%到西班牙的18%不等。在所有年龄段中,意大利(41%)和美国(42%)至少有一种相关原因导致的死亡比例高于法国(29%)和西班牙(27%)。在美国所有成年年龄段,这一比例都特别高。这四个国家之间的平均原因数量的差异主要是由于突发和不明确的原因。结论:我们算法的输出揭示了死亡证明上平均原因数量的跨国差异。它还为改进用于多种死因分析的方法打开了大门。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond the underlying cause of death: an algorithm to study multi-morbidity at death.

Background: In countries with high life expectancy, a growing share of the population is living with several diseases, a situation referred to as multi-morbidity. In addition to health data, cause-of-death data, based on the information reported on death certificates, can help monitor and characterize this situation. This requires going beyond the underlying cause of death and accounting for all causes on the death certificates which may have played various roles in the morbid process, depending on how they relate to each other.

Methods: Apart from the underlying cause, the cause-of death data available in vital registration systems do not differentiate all other causes. We developed an algorithm based on the WHO rules that assigns a "role" to each entry on the death certificate. We distinguish between the following roles: originating (o), when the condition has initiated a sequence of events leading directly to death; precipitating (p), when it was caused by an originating condition or one of its consequences; associated (a), when it contributed to death but was not part of the direct sequence leading to death; ill-defined (i), i.e., conditions such as symptoms or signs or poorly informative causes. We applied this algorithm to all death records in four countries (Italy, France, Spain and the US) in 2017.

Results: The average number of originating causes is similar in the four countries. The proportion of death certificates with more than one originating cause-a situation typical of multi-morbidity-ranges from 10% in the US to 18% in Spain. All ages combined, the proportion of deaths with at least one associated cause is higher in Italy (41%) and in the US (42%) than in France (29%) and in Spain (27%). It is especially high in the US at all adult ages. Variations in the average number of causes between the four countries are mainly due to precipitating and ill-defined causes.

Conclusions: The output of our algorithm sheds light on cross-country differences in the average number of causes on death certificates. It also opens the door for improvements in the methods used for multiple cause-of-death analysis.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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