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Decelerating Mortality Rates in Older Ages and its Prospects through Lee-Carter Approach

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  • Awdhesh Yadav
  • Suryakant Yadav
  • Ranjana Kesarwani

Abstract

The present study attempts to study the age pattern mortality and prospects through Lee-Carter approach. The objectives of the study are to examine the trend of mortality decline and life expectancy. Contemporaneously, we have projected life expectancy up to 2025, projecting ASDR using Lee-Carter method. Life table aging rate (LAR) used to estimate the rate of mortality deceleration. Overtime, LAR increased and during recent decade it remained more or less unchanged. By age, LAR significant increased in the oldest of old. The slope is steepest in the oldest of old in the recent decade. The rates of mortality increased in oldest of old as the age group is more vulnerable to chronic disease and vulnerable to identifiable risk factors for virtually every disease, marked by senility. The analysis revealed that the level of mortality is not declining but rate of acceleration is declining and is further expected to decline. By the year 2025, the age specific death rates for the age group 5–9 and 10–14 will go below one per thousand.Life expectancy will attained as high as 73 and 79 years for male and female and is further expected to increase linearly. 71 percent of total female birth and 57 percent of total male birth will survive up to age 70+. Also the findings revealed that mortality rate is declining with constant rate up to age 70 and thereafter, the mortality rate accelerates and this holds true for both sexes.

Suggested Citation

  • Awdhesh Yadav & Suryakant Yadav & Ranjana Kesarwani, 2012. "Decelerating Mortality Rates in Older Ages and its Prospects through Lee-Carter Approach," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-9, December.
    • Handle: RePEc:plo:pone00:0050941
    DOI: 10.1371/journal.pone.0050941
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    References listed on IDEAS

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    1. Ansley Coale & Shaomin Li, 1991. "The Effect of Age Misreporting in China on the Calculation of Mortality Rates at Very High Ages," Demography, Springer;Population Association of America (PAA), vol. 28(2), pages 293-301, May.
    2. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    3. Shiro Horiuchi & John Wilmoth, 1998. "Deceleration in the age pattern of mortality at olderages," Demography, Springer;Population Association of America (PAA), vol. 35(4), pages 391-412, November.
    4. Kenneth Manton & Eric Stallard & Larry Corder, 1997. "Changes in the age dependence of mortality and disability: Cohort and other determinants," Demography, Springer;Population Association of America (PAA), vol. 34(1), pages 135-157, February.
    5. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
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    Cited by:

    1. Suryakant Yadav, 2021. "Progress of Inequality in Age at Death in India: Role of Adult Mortality," European Journal of Population, Springer;European Association for Population Studies, vol. 37(3), pages 523-550, July.

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