Skip to main content

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

Macdonald, Angus S., Pritchard, Delme J., Tapadar, Pradip (2006) The Impact of Multifactorial Genetic Disorders on Critical Illness Insurance: A Simulation Study Based on UK Biobank. ASTIN Bulletin, 36 (2). pp. 311-346. ISSN 0515-0361. (doi:10.2143/AST.36.2.2017924) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.2143/AST.36.2.2017924

Abstract

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.

Item Type: Article
DOI/Identification number: 10.2143/AST.36.2.2017924
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Actuarial Science
Depositing User: Pradip Tapadar
Date Deposited: 01 Sep 2008 13:59 UTC
Last Modified: 01 Aug 2019 10:30 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/4753 (The current URI for this page, for reference purposes)
Tapadar, Pradip: https://orcid.org/0000-0003-0435-0860
  • Depositors only (login required):