INEQUALITY IN THE FACE OF DEATH UNDER COVID-19 IN UKRAINE

Authors

DOI:

https://doi.org/10.15407/dse2023.02.040

Keywords:

lifespan inequality, lifespan disparity, Gini coefficient, Covid-19

Abstract

If there is a decline in mortality, it is mainly in younger age groups. As a result, more and more deaths are occurring in older age groups. In advanced societies, therefore, people are becoming “more equal in the face of death”. A sharp increase in mortality, such as that caused by the Covid-19 pandemic, affects different age groups of the population to different degrees. It is therefore relevant to study the change in inequality of life expectancy under the conditions of a sudden shock. The purpose of this paper is to analyse the inequality of lifespan variation in Ukraine in 2020—2021 and to compare it with countries with different levels of mortality.

Previous studies of lifespan variation specifically devoted to Ukraine, or those that used data for Ukraine, were conducted or related to the pre-Covid period. The novelty of this work is the study of the behaviour of indicators characterising the inequality of lifespan before and during the two years of the epidemic, for which data are available. The demographic me t hod for constructing life tables and statistical methods for calculating lifespan variation indicators were used. Those are: Gini coefficient, average inter-individual difference in length of life, lifespan disparity, entropy of the life table, standard deviation of age at death, coefficient of variation. These indicators were calculated for the period 1989—2021 for Ukraine, Poland, Sweden, Spain, Japan, and England and Wales. It was confirmed that life expectancy is generally inversely related to inequality in the life table. It was found that this rule can be violated during mortality shocks such as the Covid-19 pandemic. It is shown that male life expectancy and lifespan inequality in Ukraine decreased in 2020—2021. Average inter-individual difference in length of life and lifespan disparity have decreased by 6.6—6.9 %. On the other hand, almost all indicators of inequality for women have increased. The life expectancy elasticity indicator (entropy of the life table) turned out to be the most sensitive, increasing to 4.9 %. At the same time, it is interesting to note that the standard deviation of age at death for women in Ukraine decreased by 1.8 %. The Covid-19 pandemic has affected inequality depending on sex and the country’s pre-Covid level. Inequality indicators in Japan have hardly changed. Inequality rates rose in Spain and Sweden before returning to their previous downward trend. Available data for England and Wales suggest a continued slow trend towards greater inequality.

REFERENCES

  1. Levchuk, N. M., Luschik, L. V. (2019) . Inter-individual inequality in length of life in Ukraine. Demography and Social Economy, 2(36), 52—64. https://doi.org/10.15407/ dse2019.02.052
  2. Vigezzi, S., Aburto, J. M., Permanyer, I., & Zarulli, V. (2022). Divergent trends in lifespan variation during mortality crises. Demographic Research, 46(11), 289—336. https://doi. org/10.4054/DemRes.2022.46.11
  3. Aburto, J. M., & van Raalte, A. (2018). Lifespan Dispersion in Times of Life Expectancy Fluctuation: The Case of Central and Eastern Europe. Demography, 55, 2071—2096. https://doi.org/10.1007/s13524-018-0729-9
  4. Shkolnikov, V. M., Andreev, E. M., & Beg un, A. Z. (2003). Gini coefficient as a life table function: Computation from discrete data, decomposition of differences and empirical examples. Demographic Research, 8(11), 305—358. https://doi.org/10.4054/DemRes. 2003.8.11
  5. Tuljapurkar, S., & Edwards, R. D. (2011). Variance in death and its implications for modeling and forecasting mortality. Demographic Research, 24(21), 497—526. https://doi. org/10.4054/DemRes.2011.24.21
  6. Vaupel, J. W., & Canudas Romo, V. (2003). Decomposing change in life expectancy: A bouquet of formulas in honor of Nathan Keyfitz’s 90th birthday. Demography, 40(2), 201—216. https://doi.org/10.1353/dem.2003.0018
  7. Keyfitz, N., & Caswell, H. (2005). Applied M athematical Demography. Third edition. Springer. 555 p. https://doi.org/10.1007/b139042
  8. van Raalte, A. A., & Caswell, H. (2013). Per turbation Analysis of Indices of Lifespan Variability. Demography, 50, 1615—1640. https://doi.org/10.1007/s13524-013-0223-3
  9. Aburto, J. M., Francisco Villavicencio, F., B asellini, U., Kjærgaard, S., & Vaupel, J. W. (2020). Dynamics of life expectancy and life span equality. PNAS, 117(10), 5250—5259. https://doi.org/10.1073/pnas.1915884117
  10. Zheng, Y., Chen, M., & Yip, P. S. (2021). A dec omposition of life expectancy and life disparity: comparison between Hong Kong and Japan. International Journal of Health Policy and Management, 10(1), 5—13. https://doi.org/10.15171/ijhpm.2019.142
  11. Aburto, J. M., Kashyap, R., & Schöley, J. et al. (2021). Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis. Journal of Epidemiology and Community Health, 75, 735—40. https://doi.org/10.1136/jech-2020-215505
  12. Databank of State Statistics Service of Ukraine (0 6 March 2023). http://db.ukrcensus. gov.ua/MULT/Dialog/statfile_c.asp
  13. Human Mortality Database (2016). Berkeley: Univers ity of California; and Rostock, Germany: Max Planck Institute for Demographic Research. https://www.mortality.org/ Country/Country?cntr=UKR
  14. Life table by sex and age. Year 1960—2022. SCB Sta tistical Database (02 April 2023). https://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101I/ LivslangdEttariga/
  15. Life expectancy tables of Poland 2021. GUS (30 Marc h 2023). https://stat.gov.pl/en/ topics/population/life-expectancy/life-expectancy-tables-of-poland-2021,2,15.html
  16. Population mortality tables for Spain by year, sex, age and functions. INE (04 April 2023). https://www.ine.es/jaxiT3/Tabla.htm?t=27153
  17. Hanada, K. (1983). A formula of Gini’s concentratio n ratio and its application to life tables. Journal of Japan Statistical Society, 13(2), 95—98. https://doi.org/10.11329/jjss 1970.13.95
  18. Colchero, F. et al. (2016). The emergence of longevo us populations. PNAS, 113(48), E7681—E7690. https://doi.org/10.1073/pnas.1612191113
  19. van Raalte, A. A, Sasson, I., & Martikainen, P. (2018 ). The case for monitoring life-span inequality. Science, 362(6418), 1002—1004. https://doi.org/10.1126/science.aau5811
  20. Shevchuk, P. E. (2022). The Impact of COVID-19 on Mort ality and Life Expectancy in Ukraine in 2020—2021. Demography and Social Economy, 4(50), 23—45. https://doi. org/10.15407/dse2022.04.023
  21. Neumayer, E., & Plümper, T. (2007). The gendered nature of natural disasters: The impact of catastrophic events on the gender gap in life expectancy, 1981—2002. Annals of the Association of American Geographers, 97(3), 551—566. https://doi.org/10.1111/j.1467-8306. 2007.00563.x
  22. Meslé, F., & Vallin, J. with contributions from V. Shkolnik ov, S. Pyrozhkov, S. Adamets (2012). Mortality and Causes of Death in 20th-Century Ukraine. Springer. 279 p. https:// doi.org/10.1007/978-94-007-2433-4
  23. Rudnytskyi, O., Levchuk, N., Wolowyna, O., Shevchuk, P., & K ovbasiuk (Savchuk), A. (2015). Demography of a man-made human catastrophe: The case of massive famine in Ukraine 1932—1933. Canadian Studies in Population, 42(1—2), 53—80. https://doi. org/10.25336/P6FC7G
  24. Hiam, L. et al. (2018). Why is life expectancy in England and W ales ‘stalling’? Journal of Epidemiology and Community Health, 72, 404—408. https://doi.org/10.1136/jech2017-210401

Author Biography

Pavlo Shevchuk, Ptoukha Institute for Demography and Social Studies of the National Academy of Sciences of Ukraine

PhD (Economics), Leading scientist

Downloads

Published

2023-06-27

How to Cite

Shevchuk, P. (2023). INEQUALITY IN THE FACE OF DEATH UNDER COVID-19 IN UKRAINE. Demography and Social Economy, 52(2), 40–53. https://doi.org/10.15407/dse2023.02.040

Issue

Section

Demographic Processes