Department of Pathology, Stavanger University Hospital, PO Box 8100, N-4068, Stavanger, Norway.
Department of Global Public Health and Primary Care, University of Bergen, PO Box 7804, N-5020, Bergen, Norway.
BMC Public Health. 2022 Jul 7;22(1):1301. doi: 10.1186/s12889-022-13693-w.
Reliable statistics on the underlying cause of death are essential for monitoring the health in a population. When there is insufficient information to identify the true underlying cause of death, the death will be classified using less informative codes, garbage codes. If many deaths are assigned a garbage code, the information value of the cause-of-death statistics is reduced. The aim of this study was to analyse the use of garbage codes in the Norwegian Cause of Death Registry (NCoDR).
Data from NCoDR on all deaths among Norwegian residents in the years 1996-2019 were used to describe the occurrence of garbage codes. We used logistic regression analyses to identify determinants for the use of garbage codes. Possible explanatory factors were year of death, sex, age of death, place of death and whether an autopsy was performed.
A total of 29.0% (290,469/1,000,128) of the deaths were coded with a garbage code; 14.1% (140,804/1,000,128) with a major and 15.0% (149,665/1,000,128) with a minor garbage code. The five most common major garbage codes overall were ICD-10 codes I50 (heart failure), R96 (sudden death), R54 (senility), X59 (exposure to unspecified factor), and A41 (other sepsis). The most prevalent minor garbage codes were I64 (unspecified stroke), J18 (unspecified pneumonia), C80 (malignant neoplasm with unknown primary site), E14 (unspecified diabetes mellitus), and I69 (sequelae of cerebrovascular disease). The most important determinants for the use of garbage codes were the age of the deceased (OR 17.4 for age ≥ 90 vs age < 1) and death outside hospital (OR 2.08 for unknown place of death vs hospital).
Over a 24-year period, garbage codes were used in 29.0% of all deaths. The most important determinants of a death to be assigned a garbage code were advanced age and place of death outside hospital. Knowledge of the national epidemiological situation, as well as the rules and guidelines for mortality coding, is essential for understanding the prevalence and distribution of garbage codes, in order to rely on vital statistics.
可靠的死因统计数据对于监测人群健康至关重要。当没有足够的信息来确定死亡的真正根本原因时，死亡将使用信息量较少的代码（垃圾代码）进行分类。如果许多死亡被分配了垃圾代码，死因统计数据的信息价值就会降低。本研究旨在分析挪威死因登记处（NCoDR）中垃圾代码的使用情况。
使用 NCoDR 中 1996-2019 年所有挪威居民的死亡数据，描述垃圾代码的发生情况。我们使用逻辑回归分析来确定使用垃圾代码的决定因素。可能的解释因素包括死亡年份、性别、死亡年龄、死亡地点以及是否进行尸检。
共有 29.0%（290469/1000128）的死亡被编码为垃圾代码；14.1%（140804/1000128）为主要垃圾代码，15.0%（149665/1000128）为次要垃圾代码。总体而言，最常见的五个主要垃圾代码是 ICD-10 代码 I50（心力衰竭）、R96（猝死）、R54（老年痴呆）、X59（暴露于未特指因素）和 A41（其他败血症）。最常见的次要垃圾代码是 I64（未特指的中风）、J18（未特指的肺炎）、C80（恶性肿瘤，原发部位不明）、E14（未特指的糖尿病）和 I69（脑血管病后遗症）。使用垃圾代码的最重要决定因素是死者的年龄（年龄≥90 岁与年龄<1 岁的比值比为 17.4）和医院外死亡（死因不明与医院的比值比为 2.08）。
在 24 年期间，29.0%的死亡被分配了垃圾代码。死亡被分配垃圾代码的最重要决定因素是年龄较大和医院外死亡地点。了解国家流行病学情况以及死因编码规则和指南对于理解垃圾代码的流行程度和分布至关重要，以便依赖于生命统计数据。
