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丹麦 2000 至 2018 年各种疾病死亡率指标分析:基于人群的队列研究。

Analysis of mortality metrics associated with a comprehensive range of disorders in Denmark, 2000 to 2018: A population-based cohort study.

机构信息

National Centre for Register-based Research, Aarhus University, Aarhus, Denmark.

Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.

出版信息

PLoS Med. 2022 Jun 16;19(6):e1004023. doi: 10.1371/journal.pmed.1004023. eCollection 2022 Jun.

Abstract

BACKGROUND

The provision of different types of mortality metrics (e.g., mortality rate ratios [MRRs] and life expectancy) allows the research community to access a more informative set of health metrics. The aim of this study was to provide a panel of mortality metrics associated with a comprehensive range of disorders and to design a web page to visualize all results.

METHODS AND FINDINGS

In a population-based cohort of all 7,378,598 persons living in Denmark at some point between 2000 and 2018, we identified individuals diagnosed at hospitals with 1,803 specific categories of disorders through the International Classification of Diseases-10th Revision (ICD-10) in the National Patient Register. Information on date and cause of death was obtained from the Registry of Causes of Death. For each of the disorders, a panel of epidemiological and mortality metrics was estimated, including incidence rates, age-of-onset distributions, MRRs, and differences in life expectancy (estimated as life years lost [LYLs]). Additionally, we examined models that adjusted for measures of air pollution to explore potential associations with MRRs. We focus on 39 general medical conditions to simplify the presentation of results, which cover 10 broad categories: circulatory, endocrine, pulmonary, gastrointestinal, urogenital, musculoskeletal, hematologic, mental, and neurologic conditions and cancer. A total of 3,676,694 males and 3,701,904 females were followed up for 101.7 million person-years. During the 19-year follow-up period, 1,034,273 persons (14.0%) died. For 37 of the 39 selected medical conditions, mortality rates were larger and life expectancy shorter compared to the Danish general population. For these 37 disorders, MRRs ranged from 1.09 (95% confidence interval [CI]: 1.09 to 1.10) for vision problems to 7.85 (7.77 to 7.93) for chronic liver disease, while LYLs ranged from 0.31 (0.14 to 0.47) years (approximately 16 weeks) for allergy to 17.05 (16.95 to 17.15) years for chronic liver disease. Adjustment for air pollution had very little impact on the estimates; however, a limitation of the study is the possibility that the association between the different disorders and mortality could be explained by other underlying factors associated with both the disorder and mortality.

CONCLUSIONS

In this study, we show estimates of incidence, age of onset, age of death, and mortality metrics (both MRRs and LYLs) for a comprehensive range of disorders. The interactive data visualization site (https://nbepi.com/atlas) allows more fine-grained analysis of the link between a range of disorders and key mortality estimates.

摘要

背景

提供不同类型的死亡率指标(例如,死亡率比率[MRR]和预期寿命)可以使研究界获得更具信息量的一组健康指标。本研究的目的是提供与各种疾病相关的一组死亡率指标,并设计一个网页来可视化所有结果。

方法和发现

在丹麦 2000 年至 2018 年间的某个时间居住的所有 7378598 人中,我们通过国家患者登记处的国际疾病分类第 10 版(ICD-10),在全国患者登记处中识别出患有 1803 种特定疾病类别的个体。有关死亡日期和原因的信息是从死因登记处获得的。对于每种疾病,我们估计了一组流行病学和死亡率指标,包括发病率、发病年龄分布、MRR 和预期寿命差异(估计为生命年损失[LYL])。此外,我们还检查了调整空气污染措施的模型,以探讨与 MRR 之间的潜在关联。我们专注于 39 种一般医疗状况,以简化结果的呈现,这些状况涵盖 10 个广泛的类别:循环、内分泌、肺部、胃肠道、泌尿生殖、肌肉骨骼、血液、精神和神经系统疾病以及癌症。共有 3676694 名男性和 3701904 名女性接受了 1.017 亿人年的随访。在 19 年的随访期间,有 1034273 人(14.0%)死亡。与丹麦一般人群相比,39 种选定医疗状况中的 37 种状况的死亡率更高,预期寿命更短。对于这 37 种疾病,MRR 的范围从 1.09(95%置信区间[CI]:1.09 至 1.10)到慢性肝病的 7.85(7.77 至 7.93),而 LYL 的范围从过敏的 0.31(0.14 至 0.47)年(约 16 周)到慢性肝病的 17.05(16.95 至 17.15)年。对空气污染的调整对估计值影响很小;然而,本研究的一个局限性是,不同疾病与死亡率之间的关联可能可以通过与疾病和死亡率都相关的其他潜在因素来解释。

结论

在这项研究中,我们展示了一系列广泛疾病的发病率、发病年龄、死亡年龄和死亡率指标(MRR 和 LYL)的估计值。交互式数据可视化网站(https://nbepi.com/atlas)允许对一系列疾病与关键死亡率估计值之间的联系进行更细粒度的分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b86f/9202944/89045d33da82/pmed.1004023.g001.jpg

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