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Journal of Population Ageing

, Volume 7, Issue 4, pp 301–322 | Cite as

Understanding the Growth of Australia’s Very Elderly Population, 1976 to 2012

  • Wilma TerblancheEmail author
  • Tom Wilson
Article

Abstract

The very elderly population in Australia has grown significantly over the last forty years but knowledge about its changing age-sex composition and the demographic drivers of its increase is limited. Official population data on the very elderly suffer from a number of shortcomings and the ABS has recently changed its method of estimating population, resulting in major revisions of numbers from 1991 to 2011. The aims of this paper are to present new estimates of the very elderly population of Australia, and investigate the proximate demographic drivers of its growth. We compare our new estimates with official population estimates and those of the Human Mortality Database and assess the impact of recent revisions to official population estimates made by the Australian Bureau of Statistics. The extinct-cohort and survivor ratio methods were used to create new population estimates from 31 December 1976 to 31 December 2012. A decomposition of the growth in numbers of nonagenarians and centenarians from 1976 to 2012 into the demographic drivers of births, survival ratios and net migration was undertaken. The very elderly population in Australia increased five-fold from 1976 to 2012, from 86,000 to 430,000, or from 0.6 to 1.9 % of the total population. Accompanying the significant absolute and proportional growth was an ageing of this group itself, with gradually increasing proportions of nonagenarians and centenarians. From the 1990s, the growth rate in numbers of very elderly males accelerated and exceeded that of females, resulting in increasing sex ratios which are strongly cohort-related. Improvements in survival beyond age 65 and survival beyond age 85 were the main drivers of growth in numbers of nonagenarians and centenarians.

Keywords

Very elderly Australia Decomposition Centenarians Survivor ratio method 

Notes

Acknowledgments

This paper was completed while the first author was a PhD student at the University of Queensland. She gratefully acknowledges receipt of a UQ scholarship.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Queensland Centre for Population Research, School of Geography, Planning and Environmental Management, Chamberlain BuildingThe University of QueenslandBrisbaneAustralia

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