Abstract：
UNASSIGNED: For better understanding of the impact of COVID-19 pandemic on mortality in different countries, we studied the excess mortality from any cause during 2020 and 2021 in 22 European countries, and its relationship with three socioeconomic variables: life expectancy at birth in 2019, per capita income, and low education level.
UNASSIGNED: Using an ecological design, we analyzed excess mortality data between January 2020 and December 2021 in 22 European countries, obtained from the EuroMOMO surveillance system. Using weekly Z-score data for each country, we estimated the annual average deviation in mortality during 2020 and 2021 for each country. We analyzed possible relationships between the excess mortality and three independent variables: gross domestic product per capita (GDPpc) in 2020, life expectancy at birth in 2019, and proportion of the population over age 18 years with a lower than secondary education level in 2018.
UNASSIGNED: In the 22 European countries analyzed, the total number of excess deaths in 2020 and 2021 was 800,011 (11%) more than expected, with deaths among those aged 65 years and over accounting for 87.66% of these. Excess mortality was higher in 2020, especially in Spain, UK, Italy, and France. In 2021, excess mortality was highest in Hungary, the Netherlands, France, and Germany. Excess mortality during 2021 was inversely correlated with life expectancy (r =-.489, p = .021) and income level (r =-.550, p = .008).
UNASSIGNED: Reducing socioeconomic inequalities among countries not only improves conditions of most disadvantages but also will help to reduce excess of mortality from future pandemics.
UNASSIGNED: Using an ecological design, we analyzed excess mortality data between January 2020 and December 2021 in 22 European countries, obtained from the EuroMOMO surveillance system. Using weekly Z-score data for each country, we estimated the annual average deviation in mortality during 2020 and 2021 for each country. We analyzed possible relationships between the excess mortality and three independent variables: gross domestic product per capita (GDPpc) in 2020, life expectancy at birth in 2019, and proportion of the population over age 18 years with a lower than secondary education level in 2018.
UNASSIGNED: In the 22 European countries analyzed, the total number of excess deaths in 2020 and 2021 was 800,011 (11%) more than expected, with deaths among those aged 65 years and over accounting for 87.66% of these. Excess mortality was higher in 2020, especially in Spain, UK, Italy, and France. In 2021, excess mortality was highest in Hungary, the Netherlands, France, and Germany. Excess mortality during 2021 was inversely correlated with life expectancy (r =-.489, p = .021) and income level (r =-.550, p = .008).
UNASSIGNED: Reducing socioeconomic inequalities among countries not only improves conditions of most disadvantages but also will help to reduce excess of mortality from future pandemics.
摘要：
■为了更好地了解COVID-19大流行对不同国家死亡率的影响，我们研究了22个欧洲国家2020年和2021年的任何原因导致的超额死亡率，及其与三个社会经济变量的关系：2019年出生时预期寿命、人均收入、教育水平低。
■使用生态设计，我们分析了22个欧洲国家2020年1月至2021年12月的超额死亡率数据，从EuroMOMO监控系统获得。使用每个国家的每周Z得分数据，我们估计了每个国家2020年和2021年死亡率的年平均偏差。我们分析了超额死亡率与三个独立变量之间的可能关系：2020年的人均国内生产总值（GDPpc），2019年的出生时预期寿命以及2018年低于中等教育水平的18岁以上人口比例。
■在分析的22个欧洲国家中，2020年和2021年的超额死亡总数比预期多800,011人（11%），65岁及以上人群的死亡占其中的87.66%。2020年超额死亡率更高，特别是在西班牙，英国,意大利,和法国。2021年，匈牙利的超额死亡率最高，荷兰,法国,和德国。2021年的超额死亡率与预期寿命（r=-.489，p=.021）和收入水平（r=-.550，p=.008）呈负相关。
减少国家之间的社会经济不平等不仅改善了最不利的条件，而且还将有助于减少未来大流行造成的过度死亡率。
■使用生态设计，我们分析了22个欧洲国家2020年1月至2021年12月的超额死亡率数据，从EuroMOMO监控系统获得。使用每个国家的每周Z得分数据，我们估计了每个国家2020年和2021年死亡率的年平均偏差。我们分析了超额死亡率与三个独立变量之间的可能关系：2020年的人均国内生产总值（GDPpc），2019年的出生时预期寿命以及2018年低于中等教育水平的18岁以上人口比例。
■在分析的22个欧洲国家中，2020年和2021年的超额死亡总数比预期多800,011人（11%），65岁及以上人群的死亡占其中的87.66%。2020年超额死亡率更高，特别是在西班牙，英国,意大利,和法国。2021年，匈牙利的超额死亡率最高，荷兰,法国,和德国。2021年的超额死亡率与预期寿命（r=-.489，p=.021）和收入水平（r=-.550，p=.008）呈负相关。
减少国家之间的社会经济不平等不仅改善了最不利的条件，而且还将有助于减少未来大流行造成的过度死亡率。
