Department of Development Studies, International Institute for Population Sciences (IIPS), Mumbai, 400088, India.
Centre of Social Medicine and Community Health, Jawaharlal Nehru University (JNU), New Delhi, 110067, India.
BMC Public Health. 2021 Oct 21;21(1):1906. doi: 10.1186/s12889-021-11690-z.
Quantifying excess deaths and their impact on life expectancy at birth (e) provide a more comprehensive understanding of the burden of coronavirus disease of 2019 (COVID-19) on mortality. The study aims to comprehend the repercussions of the burden of COVID-19 disease on the life expectancy at birth and inequality in age at death in India.
The mortality schedule of COVID-19 disease in the pandemic year 2020 was considered one of the causes of death in the category of other infectious diseases in addition to other 21 causes of death in the non-pandemic year 2019 in the Global Burden of Disease (GBD) data. The measures e and Gini coefficient at age zero (G) and then sex differences in e and G over time were analysed by assessing the age-specific contributions based on the application of decomposition analyses in the entire period of 2010-2020.
The e for men and women decline from 69.5 and 72.0 years in 2019 to 67.5 and 69.8 years, respectively, in 2020. The e shows a drop of approximately 2.0 years in 2020 when compared to 2019. The sex differences in e and G are negatively skewed towards men. The trends in e and G value reveal that its value in 2020 is comparable to that in the early 2010s. The age group of 35-79 years showed a remarkable negative contribution to Δe and ΔG. By causes of death, the COVID-19 disease has contributed - 1.5 and - 9.5%, respectively, whereas cardiovascular diseases contributed the largest value of was 44.6 and 45.9%, respectively, to sex differences in e and G in 2020. The outcomes reveal a significant impact of excess deaths caused by the COVID-19 disease on mortality patterns.
The COVID-19 pandemic has negative repercussions on e and G in the pandemic year 2020. It has severely affected the distribution of age at death in India, resulting in widening the sex differences in e and G. The COVID-19 disease demonstrates its potential to cancel the gains of six to eight years in e and five years in G and has slowed the mortality transition in India.
量化超额死亡人数及其对出生时预期寿命 (e) 的影响,可以更全面地了解 2019 年冠状病毒病 (COVID-19) 对死亡率的影响。本研究旨在了解 COVID-19 疾病负担对印度出生时预期寿命和死亡年龄不平等的影响。
在全球疾病负担 (GBD) 数据中,2020 年大流行年份 COVID-19 疾病的死亡率被视为除其他 21 种非大流行年份 2019 年的其他传染病类别中的一个死因。根据应用于整个 2010-2020 年期间的分解分析,基于年龄特异性贡献的评估,分析 e 和零岁基尼系数 (G) 以及 e 和 G 随时间的性别差异。
男性和女性的 e 分别从 2019 年的 69.5 岁和 72.0 岁下降到 2020 年的 67.5 岁和 69.8 岁。与 2019 年相比,2020 年 e 下降了约 2.0 年。e 和 G 的性别差异向男性倾斜呈负偏态。e 和 G 值的趋势表明,其在 2020 年的值与 2010 年代早期相当。35-79 岁年龄组对Δe 和ΔG 有显著的负贡献。按死因划分,COVID-19 疾病分别贡献了-1.5%和-9.5%,而心血管疾病对 2020 年 e 和 G 的性别差异的贡献最大,分别为 44.6%和 45.9%。结果表明,COVID-19 疾病导致的超额死亡对死亡率模式有重大影响。
COVID-19 大流行对 2020 年大流行年的 e 和 G 产生了负面影响。它严重影响了印度的死亡年龄分布,导致 e 和 G 的性别差异扩大。COVID-19 疾病表明它有可能使 e 增加 6 到 8 年和 G 增加 5 年的成果化为乌有,并减缓了印度的死亡率转型。