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The Impact of Multifactorial Genetic Disorders on Critical Illness Insurance: A Simulation Study Based on UK Biobank

Published online by Cambridge University Press:  17 April 2015

Angus Macdonald
Affiliation:
Maxwell Institute for Mathematical Sciences and Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh EH14 4AS, U.K., Tel: +44(0)131-451-3209, Fax: +44(0)131-451-3249, E-mail: A.S.Macdonald@ma.hw.ac.uk
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Abstract

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The UK Biobank project is a proposed large-scale investigation of the combined effects of genotype and environmental exposures on the risk of common diseases. It is intended to recruit 500,000 subjects aged 40-69, to obtain medical histories and blood samples at outset, and to follow them up for at least 10 years. This will have a major impact on our knowledge of multifactorial genetic disorders, rather than the rare but severe single-gene disorders that have been studied to date. What use may insurance companies make of this knowledge, particularly if genetic tests can identify persons at different risk? We describe here a simulation study of the UK Biobank project. We specify a simple hypothetical model of genetic and environmental influences on the risk of heart attack. A single simulation of UK Biobank consists of 500,000 life histories over 10 years; we suppose that case-control studies are carried out to estimate age-specific odds ratios, and that an actuary uses these odds ratios to parameterise a model of critical illness insurance. From a large number of such simulations we obtain sampling distributions of premium rates in different strata defined by genotype and environmental exposure. We conclude that the ability of such a study reliably to discriminate between different underwriting classes is limited, and depends on large numbers of cases being analysed.

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Articles
Copyright
Copyright © ASTIN Bulletin 2006

References

Breslow, N.E. and Day, N.E. (1980) Statistical Methods in Cancer Research: Volume 1 – The analysis of case-control studies. International Agency for Research on Cancer.Google Scholar
Capewell, S., Livingston, B.M., Macintyre, K., Chalmers, J.W.T., Boyd, J., Finlayson, A., Redpath, A., Pell, J.P., Evans, C.J. and McMurray, J.J.V. (2000) Trends in case-fatality in 117,718 patients admitted with acute myocardial infarction in Scotland. European Heart Journal, 21, 18331840.CrossRefGoogle ScholarPubMed
Daykin, CD., Akers, D.A., Macdonald, A.S., McGleenan, T., Paul, D. and Turvey, P.J. (2003) Genetics and insurance - some social policy issues (with discussions). British Actuarial Journal, 9, 787874.CrossRefGoogle Scholar
Gutiérrez, C. and Macdonald, A.S. (2003) Adult polycystic kidney disease and critical illness insurance. North American Actuarial Journal, 7(2), 93115.CrossRefGoogle Scholar
MacDonald, A.S. (2004) Genetics and insurance management, in The Swedish Society of Actuaries: One Hundred Years, ed. Sandström, A., Svenska Aktuarieföreningen, Stockholm.Google Scholar
MacDonald, A.S. and Pritchard, D.J. (2000) A mathematical model of Alzheimer’s disease and the ApoE gene. ASTIN Bulletin, 30, 69110.CrossRefGoogle Scholar
Norberg, R. (1995) Differential equations for moments of present values in life insurance. Insurance: Mathematics and Economics, 17, 171180.Google Scholar
Woodward, M. (1999) Epidemiology: Study Design and Data Analysis. Chapman & Hall.Google Scholar
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