Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-26T06:37:30.470Z Has data issue: false hasContentIssue false
  • English
  • Français

Selected Issues in Modelling Mortality by Cause and in Small Populations

Published online by Cambridge University Press:  10 June 2011

S. J. Richards
S. J. Richards
Affiliation:
4 Caledonian Place, Edinburgh, EH11 2AS, U.K. Telephone: +44 (0)131 315 4470; E-mail: stephen@richardsconsulting.co.uk; Web: www.richardsconsulting.co.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

Actuarial practice as regards mortality analysis and projection is changing rapidly. This paper provides a short introduction to some of the limitations and risks in using trends in cause of death as a means for projecting future mortality rates. It also covers recent developments in analysing the mortality of smaller populations, including survival models and “piggyback” models.

Keywords

Cause of DeathForecastingSurvival ModelsMortality Laws
Type
Sessional meetings: papers and abstracts of discussions
Information
British Actuarial Journal , Volume 15 , Issue S1 , 2009 , pp. 267 - 283
Copyright
Copyright © Institute and Faculty of Actuaries 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Aylin, P. (1997). Background note on twentieth century mortality files. Office for National Statistics.Google Scholar
Azambuja, M.I. & Levins, R. (2007). Coronary heart disease — one or several diseases? Perspectives in Biology and Medicine, 50(2), 228–242.CrossRefGoogle ScholarPubMed
Azambuja, M.I. (2009). Connections between causes of diseases: influenza and Sutherland's “epidemiology of constitutions”. Presentation to Joining Forces on Mortality and Longevity, 22 October 2009, Edinburgh. http://www.actuaries.org.uk/research-and-resources/documents/connections-between-causes-diseases-influenza-and-sutherlands-epide [Accessed 7 October 2010]Google Scholar
Beard, R.E. (1959). Note on some mathematical mortality models. In: Wolstenholme, G.E.W. & O'Connor, M. (eds.). The Lifespan of Animals. Little, Brown, Boston, 302–311.Google Scholar
Beard, R.E. (1971). Some aspects of theories of mortality, cause of death analysis, forecasting and stochastic processes. In: Brass, W. (ed.). Biological Aspects of Demography, Taylor and Francis Ltd., London.Google Scholar
Booth, H. & Tickle, L. (2008). Mortality modelling and forecasting: a review of methods. Annals of Actuarial Science, 3(Parts 1 and 2), 8.CrossRefGoogle Scholar
Cairns, A. (2009). Modelling multi-population mortality with cohort effects, Presentation to Joining Forces on Mortality and Longevity, 22 October 2009, Edinburgh. http://www.actuaries.org.uk/research-and-resources/documents/modelling-multi-population-mortality-cohort-effects-slides [Accessed 7 October 2010]Google Scholar
CMI (2004). Projecting future mortality. A discussion paper, Continuous Mortality Investigation Mortality sub-committee Working Paper 3.Google Scholar
Currie, I.D. (2009). Adjusting for bias in mortality forecasts, Presentation to Joining Forces on Mortality and Longevity, 22 October 2009, Edinburgh. http://www.actuaries.org.uk/research-and-resources/documents/adjusting-bias-mortality-forecasts-slides [Accessed 7 October 2010]Google Scholar
Di Cesare, M. & Murphy, M. (2009). Forecasting mortality, different approaches for different cause of deaths? The cases of lung cancer; influenza, pneumonia, and bronchitis; and motor vehicle accidents, Presentation to Joining Forces on Mortality and Longevity, 22 October 2009, Edinburgh. http://www.actuaries.org.uk/research-and-resources/documents/forecasting-mortality-different-approaches-different-cause-deaths-s [Accessed 7 October 2010]CrossRefGoogle Scholar
Diez-Roux, A.V. (2003). A glossary for multilevel analysis. Epidemiological Bulletin, 24(3), Pan American Health Organization.Google Scholar
Fletcher, G. (2009). Uncovering scheme-specific mortality. Presentation to Joining Forces on Mortality and Longevity, 22 October 2009, Edinburgh. http://www.actuaries.org.uk/research-and-resources/documents/uncovering-scheme-specific-mortality-slides [Accessed 7 October 2010]Google Scholar
Gavrilov, L.A. & Gavrilova, N.S. (2001). The reliability theory of aging and longevity. Journal of Theoretical Biology (2001), 213, 527–545.CrossRefGoogle ScholarPubMed
Gompertz, B. (1825). The nature of the function expressive of the law of human mortality. Philosophical Transactions of the Royal Society, 115, 513–585.Google Scholar
Government Actuary's Department (2001). National Population Projections: Review of Methodology for Projecting Mortality. Government Actuary's Department, NSQR No. 8, pages 18–21.Google Scholar
Horiuchi, S. & Coale, A.J. (1990). Age patterns of mortality for older women: an analysis using the age-specific rate of mortality change with age. Mathematical Population Studies, 2(4), 245–267.CrossRefGoogle ScholarPubMed
Jordan, K., Porcheret, M. & Croft, P. (2004). Quality of morbidity coding in general practice computerized medical records: a systematic review. Family Practice, 21, 396–412.CrossRefGoogle ScholarPubMed
Makeham, W.M. (1859). On the law of mortality and the construction of annuity tables, Journal of the Institute of Actuaries, 8, 301–310.Google Scholar
Martin, C. (2010). For the record. http://www.longevitas.co.uk/site/informationmatrix/fortherecord.htmlGoogle Scholar
Milne, E. (2009). A new model of ageing and mortality. Presentation to Joining Forces on Mortality and Longevity, 22 October 2009, Edinburgh. http://www.actuaries.org.uk/research-and-resources/documents/new-model-ageing-and-mortality-slides [Accessed 7 October 2010]CrossRefGoogle Scholar
R Development Core Team (2004). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.r-project.orgGoogle Scholar
Richards, S.J. (2008). Applying survival models to pensioner mortality data. British Actuarial Journal. 14(11), 257–326.CrossRefGoogle Scholar
Richards, S.J. & Currie, I.D. (2009). Longevity risk and annuity pricing with the Lee–Carter model. British Actuarial Journal (to appear).CrossRefGoogle Scholar
Richards, S.J. (2010). A handbook of parametric survival models for actuarial use. Scandinavian Actuarial Journal (to appear).Google Scholar
Robinson, W.S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15, 351–357.CrossRefGoogle Scholar
Romeri, E., Baker, A. & Griffiths, C. (2006). Mortality by deprivation and cause of death in England and Wales, 1999–2003. Health Statistics Quarterly 32, National Statistics.Google Scholar
van Ginneken, A.M., van der Lei, J. & Moorman, P.W. (1993). Towards unambiguous representation of patient data, Proceedings of the Sixteenth Annual Symposium on Computer Applications in Medical Care (SCAMC), Baltimore, MD, 1992; McGraw-Hill, New York, 1993 pp. 69–73.Google Scholar
van der Lei, J. (1991). Use and abuse of computer-stored medical records. Methods of Information in Medicine 1991, 30(2): 79–80.Google ScholarPubMed
Vanfleteren, J.R., De Vreese, A. & Braeckman, B.P. (1998). Two-parameter logistic and Weibull equations provide better fits to survival data from isogenic populations of caenorhabiditis elegans in axenic culture than does the Gompertz model. Journal of Gerontology Series A, 53, B393-B403.CrossRefGoogle Scholar
Vaupel, J.W. & Yashin, A.I. (1985). Heterogeneity's ruses: some surprising effects of selection on population dynamics. The American Statistician, 39(3), 176–185.Google ScholarPubMed
Wong-Fupuy, C. & Haberman, S. (2004). Projecting mortality trends: recent developments in the United Kingdom and the United States. North American Actuarial Journal, 8(2), 56–83.CrossRefGoogle Scholar