London School of Hygiene & Tropical Medicine, London, United Kingdom.
University College London, London, United Kingdom.
PLoS Med. 2022 Jan 6;19(1):e1003870. doi: 10.1371/journal.pmed.1003870. eCollection 2022 Jan.
Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic.
We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception.
The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.
超额死亡率反映了 2019 年冠状病毒病（COVID-19）大流行对死亡率的总影响，不受死因指定不当的影响。我们旨在描述在大流行期间与大流行之前相比，健康和人口统计学因素与超额死亡率之间的关联。
我们分析了一个时间序列数据集，其中包括来自参与临床实践研究数据链接的英国普通实践的 9635613 名（≥40 岁）成年人。我们按个体因素对 2015 年 3 月至 2020 年 7 月之间每周的死亡人数和风险人数进行了提取。使用季节性调整的负二项式回归模型来估计英国大流行第一波（2020 年 5 月 5 日至 27 日）期间与大流行前相比的超额死亡率。通过包含交互项，我们在第一波之前和期间估计了一系列因素的死亡相对风险（RR）。我们发现，与大流行前相比，第一波期间全因死亡率增加了 43%（95%CI 40%至 47%）。与大流行前相比，第一波期间与大多数社会人口学和临床特征相关的死亡 RR 变化较小。然而，痴呆症相关的死亡率 RR 明显增加（痴呆症与无痴呆症大流行前：3.5，95%CI 3.4 至 3.5；第一波期间：5.1，4.9 至 5.3）；学习障碍的情况类似（大流行前：3.6，3.4 至 3.5；第一波期间：4.8，4.4 至 5.3），与白种人相比，黑人或南亚人以及伦敦与其他地区相比。在多次敏感性分析中，病态 RR 保持稳定。然而，该研究的一个局限性是，由于人口行为、病毒传播和风险认知的变化，我们不能假设在第一波期间观察到的风险会适用于其他波次。
英国 COVID-19 大流行的第一波似乎将大多数人群亚组的基本死亡率风险放大到大致相同的相对程度。然而，痴呆症、学习障碍、非白种人或居住在伦敦的人群的死亡率不成比例地增加。
