Multiple causes of death data to track trends of mortality from chronic diseases: Insights from the COVID-19 pandemic in Switzerland

IF 3.6 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology Pub Date : 2026-01-01 Epub Date: 2025-12-04 DOI:10.1016/j.annepidem.2025.12.002

D. Durán N MSc. , J.S. Kaufman PhD , A. Chiolero MD. PhD , C. Carmeli PhD

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引用次数: 0

Abstract

Purpose

With the rising prevalence of multi-morbidity among aging populations and disruptive events as new infectious disease threats, the traditional focus on the underlying cause of death (UCOD) can obscure the contribution of chronic diseases to mortality trends. The multiple cause of death (MCOD) approach addresses this limitation by considering all causes recorded on a death certificate. We aimed to quantify the effect of the COVID-19 pandemic on trends of chronic disease mortality by comparing the UCOD and MCOD approaches.

Methods

We conducted a population-based time series analysis using all deaths occurred 2011–2022 in Switzerland. We modelled pre-pandemic (2011–2019) trends to predict the expected chronic disease deaths during 2020–2022 had the pandemic not occurred. We quantified the monthly effect of the pandemic as the observed minus expected chronic disease deaths and estimated these effects by sex and age using (1) the UCOD and (2) the MCOD.

Results

Both approaches revealed similar overall trends of effects. However, a marked discrepancy occurred at the end of 2020, when Switzerland experienced the highest COVID-19 mortality, with MCOD quantifying a substantially higher excess of chronic disease deaths compared to UCOD.

Conclusion

MCOD complements UCOD in quantifying cause-specific mortality trends and may improve population health monitoring.

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利用多种死亡原因数据跟踪慢性病死亡率趋势：来自瑞士COVID-19大流行的见解

目的：随着老龄化人口中多病发病率的上升和破坏性事件作为新的传染病威胁，传统上对潜在死亡原因（UCOD）的关注可能会掩盖慢性病对死亡率趋势的贡献。多种死亡原因（MCOD）方法通过考虑死亡证明上记录的所有原因来解决这一限制。我们旨在通过比较UCOD和MCOD方法来量化COVID-19大流行对慢性病死亡率趋势的影响。方法：我们对瑞士2011-2022年发生的所有死亡进行了基于人群的时间序列分析。我们模拟了大流行前（2011-2019年）的趋势，以预测2020-2022年期间未发生大流行的预期慢性病死亡人数。我们将大流行的每月影响量化为观察到的减去预期的慢性病死亡人数，并使用(1)UCOD和(2)MCOD按性别和年龄估计这些影响。结果：两种方法显示出相似的总体效果趋势。然而，2020年底出现了明显差异，当时瑞士的COVID-19死亡率最高，与UCOD相比，MCOD量化的慢性病死亡人数要高得多。结论：MCOD可作为UCOD的补充，用于量化死因特异性死亡率趋势，并可改善人群健康监测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Annals of Epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

7.40

自引率

1.80%

发文量

207

审稿时长

59 days

期刊介绍： The journal emphasizes the application of epidemiologic methods to issues that affect the distribution and determinants of human illness in diverse contexts. Its primary focus is on chronic and acute conditions of diverse etiologies and of major importance to clinical medicine, public health, and health care delivery.