Forthcoming Articles
Peer Reviewed Articles

A Comparison of Mortality Transition in China and India, 1950–2021

PDF
  • Aalok Chaurasia
Aalok Chaurasia
MLC Foundation and 'Shyam' Institute
DOI: https://doi.org/10.3197/JPS.63799977346494

Published 2024-06-27

Keywords

  • Mortality transition, China, India, Geometric Mean, Life expectancy, Decomposition

How to Cite

Chaurasia, Aalok. 2024. “A Comparison of Mortality Transition in China and India, 1950–2021”. The Journal of Population and Sustainability, June. https://doi.org/10.3197/JPS.63799977346494.

Copyright (c) 2022 Aalok Chaurasia

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Crossref
Scopus
Google Scholar
Europe PMC

Abstract

This paper compares mortality transition in China and India in the period 1950–2021, highlighting similarities and differences. Mortality transition has been inconsistent in both countries, but differences remain. In China, the transition has been spread evenly across the age range, while in India, it has primarily been confined to younger ages, being markedly slow in ages 35–90. This difference in the older ages appears to explain the main difference between the respective mortality transition in the two countries. To address its ongoing mortality transition, the paper concludes, India needs to reinvigorate its health-care delivery system to meet the health care needs of the old people. The paper also emphasises using geometric mean of the age-specific probabilities of death as an appropriate measure to analyse mortality transition.

PDF

Downloads

Download data is not yet available.

References

  1. Adlakha, A. and J. Banister. 1995. ‘Demographic perspectives on China and India’. Journal of Biosocial Science 27 (2): 163–78. https://doi.org/10.1017/S0021932000022677
  2. Andreev, E.M., V.M. Shkolnikov and A.Z. Begun. 2002. ‘Algorithm for decomposition of differences between aggregate demographic measures and its application to life expectancies, healthy life expectancies, parity-progression ratios and total fertility rates’. Demographic Research 7 (14): 499–522. https://doi.org/10.4054/DemRes.2002.7.14
  3. Ang, B.W. 2004. ‘Decomposition analysis for policymaking in energy: Which is the preferred method?’. Energy Policy 32 (9): 1131–39. https://doi.org/10.1016/S0301-4215(03)00076-4
  4. Ang, B.W. 2005. ‘The LMDI approach to decomposition analysis: A practical guide’. Energy Policy 33: 867–71. https://doi.org/10.1016/j.enpol.2003.10.010
  5. Ang, B.W. and F.L. Liu. 2001. ‘A new energy decomposition method: Perfect in decomposition and consistent in aggregation’. Energy 26 (6): 537–48. https://doi.org/10.1016/S0360-5442(01)00022-6
  6. Bhatia, R. 2008. ‘The logarithmic mean’. Resonance, June 2008: 583–94. https://doi.org/10.1007/s12045-008-0063-4
  7. Canudas-Romo, V. 2008. ‘The modal age at death and the shifting mortality hypothesis’. Demographic Research 19 (30): 1179–204. https://doi.org/10.4054/DemRes.2008.19.30
  8. Chaurasia, A.R. 2017. ‘Fertility, mortality and age composition effects of population transition in China and India: 1950–2015’. Comparative Population Studies 42. https://doi.org/10.12765/CPoS-2017-12
  9. Chaurasia, A.R. 2020. ‘Economic growth and population transition in China and India, 1990–2018’. China Population and Development Studies 4 (3): 229–61. https://doi.org/10.1007/s42379-020-00067-1
  10. Chaurasia, A.R. 2023. ‘Seventy years of mortality transition in India, 1950–2021’. Indian Journal of Population and Development 3 (1): 1–34. https://doi.org/10.1101/2023.03.24.23287189
  11. Carlson, B.C. 1966. ’Some inequalities for hypergeometric functions’. Proceedings of American Mathematical Society 17: 32–39. https://doi.org/10.2307/2035056
  12. Carlson, B.C. 1972. ‘The logarithmic mean’. American Mathematical Monthly 79: 615–618. https://doi.org/10.1080/00029890.1972.11993095
  13. Chen J., H. Zheng, J.X. Bei, L. Sun, W.H. Jia, T. Li, F. Zhang, M. Seielstad, Y.X. Zeng, X. Zhang and J. Liu. 2009. ‘Genetic structure of the Han Chinese population revealed by genome-wide SNP variation’. American Journal of Human Genetics 85 (6): 775–85. https://doi.org/10.1016/j.ajhg.2009.10.016
  14. Clegg, L.X., Hankey, B.F., Tiwari, R., Feuer, E.J., Edwards and B.K. 2009. ‘Estimating average annual per cent change in trend analysis’. Statistics in Medicine 28 (29): 3670–82. https://doi.org/10.1002/sim.3733
  15. Coale, A.J. 1983. ‘Population trends in China and India’. Proceedings of National Academy of Sciences 80: 1757–63. https://doi.org/10.1073/pnas.80.6.1757
  16. de Beer, J. 2012. ‘Smoothing and projecting age-specific probabilities of death by TOPALS’.Demographic Research 27 (20): 543–92. https://doi.org/10.4054/DemRes.2012.27.20
  17. Dummer, T.J.B. and I.G. Cook. 2008. ‘Health in China and India: A cross-country comparison in a context of rapid globalisation’. Social Science & Medicine 67: 590–605. https://doi.org/10.1016/j.socscimed.2008.04.019
  18. Ghislandi, S., W.C. Sanderson and S. Scherbov. 2019. ‘A simple measure of human development: The Human Life Indicator’. Population and Development Review 45: 219–33. https://doi.org/10.1111/padr.12205
  19. Goerlich Gisbert, F.J. 2020. ‘Distributionally adjusted life expectancy as a life table function’. Demographic Research 43 (14): 365–400. https://doi.org/10.4054/DemRes.2020.43.14
  20. Golley, J. and R. Tyres. 2013. ‘Contrasting giants: Demographic change and economic performance in China and India’. Procedia – Social and Behavioral Sciences 77: 353–83. https://doi.org/10.1016/j.sbspro.2013.03.093
  21. He, H. and R.J. Myers. 2021. ‘Log Mean Divisia Index decomposition analysis of the demand for building materials: Application to concrete, dwellings, and the UK’. Environmental Science & Technology 55 (5): 2767–78. https://doi.org/10.1021/acs.est.0c02387
  22. INE (Instituto Nacional de Estadística). 1952. Tablas de mortalidad de la población española: Años 1900 a 1940. Madrid, Instituto Nacional de Estadística.
  23. INE (Instituto Nacional de Estadística). 1958. Tablas de mortalidad de la población española: Año 1950. Madrid, Instituto Nacional de Estadística.
  24. Jdanov, D.A., V.M. Shkolnikov, A.A. van Raalte and E.M. Andreev. 2017. ‘Decomposing current mortality differences into initial differences and differences in trends: The contour decomposition method’. Demography 54: 1579–602. https://doi.org/10.1007/s13524-017-0599-6
  25. Joe, W., A.K. Dash and P. Agrawal. 2015. ‘Demographic transition, savings, and economic growth in China and India’. Working paper no. 351. Delhi: Institute of Economic Growth.
  26. Keyfitz, N. 1977. Applied Mathematical Demography. New York: Wiley.
  27. King, G. and S. Soneji. 2011: ‘The future of death in America’. Demographic Research 25 (1): 1–38. https://doi.org/10.4054/DemRes.2011.25.1
  28. Lin, T-P. 1974. ‘The power mean and the logarithmic mean’. The American Mathematical Monthly 81 (8): 879–883. https://doi.org/10.1080/00029890.1974.11993684
  29. Lisaba, E.B. and N.S. Lopez. 2020. ‘Using Logarithmic Mean Divisia Index method (LMDI) to estimate drivers to final energy consumption and emissions in ASEAN’. IOP Conference Series: Materials Science and Engineering: 1109. https://doi.org/10.1088/1757-899X/1109/1/012070
  30. Makutėnienė, D., D. Perkumienė and V. Makutėnas. 2022. ‘Logarithmic Mean Divisia Index decomposition based on Kaya Identity of GHG emissions from agricultural sector in Baltic States’. Energies 15 (3): 1195. https://doi.org/10.3390/en15031195
  31. National Cancer Institute 2023. Joinpoint Regression Program, Version 5.02. May, 2023. Statistical Research and Applications Branch.
  32. Ostle, B., and H.L. Terwilliger. 1957. ‘A comparison of two means’. Proceedings of Montana Academy of Science 17: 69–70
  33. Tu, M., Y. Li, L. Bao, Y. Wei, O. Orfila, W. Li and D. Gruyer. 2019. ‘Logarithmic Mean Divisia Index decomposition of CO2 emissions from urban passenger transport: An empirical study of global cities from 1960–2001’. Sustainability 11: 4310. https://doi.org/10.3390/su11164310
  34. Schoen, R. 1970. The geometric mean of age-specific death rates as a summary index of mortality. Demography 7(3): 318–324. https://doi.org/10.2307/2060150
  35. Sen, A. 1998. ‘Mortality as an indicator of economic success and failure’. The Economic Journal 108 (446): 1–25. https://doi.org/10.1111/1468-0297.00270
  36. Singh, G.K., and J. Liu. 2012. ‘Health improvements have been more rapid and widespread in China than in India: A comparative analysis of health and socioeconomic trends from 1960 to 2011’. International Journal of Maternal and Child Health and AIDS 1 (1): 31–48. https://doi.org/10.21106/ijma.11
  37. Tukey, J.W. 1977. Exploratory Data Analysis. Reading, Massachusetts: Addison-Wesley Publising Company.
  38. United Nations .2022. World Population Prospects 2022. Online Edition. New York, Department of Economic and Social Affairs, Population Division.
  39. Vaupel, J.W. 1986. ‘How change in age-specific mortality affects life expectancy’. Population Studies 40: 147–157. https://doi.org/10.1080/0032472031000141896