Yadav Pawan Kumar, Yadav Suryakant
Department of Bio-Statistics and Epidemiology, International Institute for Population Sciences (IIPS), Mumbai, 400088, India.
Department of Community Medicine, Sikkim Manipal Institute of Medical Sciences, Sikkim Manipal University, Gangtok, Sikkim, 737102, India.
Arch Public Health. 2023 Sep 4;81(1):165. doi: 10.1186/s13690-023-01170-8.
Measuring life expectancy and life disparity can assist in comprehending how the COVID-19 pandemic has affected the mortality estimates in the Indian population. The present study aims to study the life expectancy and life disparity at birth at the national and subnational levels before and during the COVID-19 pandemic using the NFHS and SRS data.
The measures Life expectancy at birth ([Formula: see text]) and Life disparity at birth ([Formula: see text]) were computed for the non-pandemic and pandemic years from NFHS (2015-16), SRS (2015) and NFHS (2019-21), SRS (2020) respectively at the national and Subnational level in India. Using NFHS data for the 36 states and SRS data for the 22 states, the study calculates [Formula: see text] and [Formula: see text] by total, male and female population.
The [Formula: see text] for male and female decline from 64.3 years and 69.2 years in 2015-16 to 62.9 years and 68.9 years in 2019-21. The [Formula: see text] shows a drop of approximately 1.4 years for males and 0.3 years for females in the pandemic year 2019-21 when compared to the non-pandemic year 2015-16. At the subnational level [Formula: see text] shows a decline for 22 states in person, 23 states in males and 21 states in females in the pandemic year 2019-21 as compared to the non-pandemic years 2015-16. The [Formula: see text] shows a increase for 21 states in person, 24 states in females and 17 states in males in the pandemic year than non-pandemic year. The findings shows a significant losses in [Formula: see text] and gains in [Formula: see text] for males than females in the pandemic year as compared to the non-pandemic year at the subnational level in India.
COVID-19 pandemic has decreased [Formula: see text] and increased [Formula: see text] in the pandemic year 2019-21 at the national and subnational level in India. COVID-19 had a significant impact on the age pattern of mortality for many states and male, female population and delayed the mortality transition in India.
衡量预期寿命和寿命差异有助于理解新冠疫情如何影响印度人口的死亡率估计。本研究旨在利用全国家庭健康调查（NFHS）和抽样登记系统（SRS）数据，研究新冠疫情之前和期间印度全国及各邦层面的出生时预期寿命和寿命差异。
分别根据印度全国及各邦层面的NFHS（2015 - 16年）、SRS（2015年）以及NFHS（2019 - 21年）、SRS（2020年）数据，计算非疫情年份和疫情年份的出生时预期寿命（[公式：见正文]）和出生时寿命差异（[公式：见正文]）。利用36个邦的NFHS数据和22个邦的SRS数据，该研究按总人口、男性人口和女性人口计算[公式：见正文]和[公式：见正文]。
男性和女性的[公式：见正文]从2015 - 16年的64.3岁和69.2岁降至2019 - 21年的62.9岁和68.9岁。与非疫情年份2015 - 16年相比，2019 - 21年疫情期间男性的[公式：见正文]下降了约1.4岁，女性下降了0.3岁。在各邦层面，与2015 - 16年非疫情年份相比，2019 - 21年疫情期间有22个邦的[公式：见正文]下降，23个邦男性的[公式：见正文]下降，21个邦女性的[公式：见正文]下降。与非疫情年份相比，2019 - 21年疫情期间有21个邦的[公式：见正文]上升，24个邦女性的[公式：见正文]上升，17个邦男性的[公式：见正文]上升。研究结果表明，在印度各邦层面，与非疫情年份相比，2019 - 21年疫情期间男性的[公式：见正文]显著下降，[公式：见正文]上升幅度大于女性。
2019 - 21年疫情期间，新冠疫情在印度全国及各邦层面降低了[公式：见正文]，增加了[公式：见正文]。新冠疫情对许多邦以及男性、女性人口的死亡年龄模式产生了重大影响，并延缓了印度的死亡率转变。
