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

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.

Genetic discrimination in private insurance: global perspectives

“…They have claimed that these measures would result in "adverse selection," i.e. the phenomenon whereby individuals having learned of heightened health risks would be more likely than the average individual to seek insurance coverage, or seek larger quantities of insurance without disclosing their risks to insurers (Macdonald 2003, Macdonald et al 2006, Viswanathan 2007). Yet, several authors dismiss exclusively actuarial-based arguments, emphasizing the need for political, rather than actuarial solutions to the insurance and genetics dilemma (Van Hoyweghen et al 2005).…”

Multifactorial Genetic Disorders and Adverse Selection: Epidemiology Meets Economics

“… Gutiérrez and Macdonald (2003) parameterized the CI model shown in Figure 2, using medical studies and population data. Therefore, in particular, λ 12 ( x ) denotes the rate of onset of heart attacks in the general population (different for males and females). Macdonald, Pritchard, and Tapadar (2006) assumed that a 2 × 2 gene–environment interaction affected heart attack risk, with genotypes G and g , and environmental exposures E and e , upper case representing higher risk. So there are four strata for each sex— ge , gE , Ge , and GE .…”

“…Macdonald, Pritchard, and Tapadar (2006) assumed that a 2 × 2 gene–environment interaction affected heart attack risk, with genotypes G and g , and environmental exposures E and e , upper case representing higher risk. So there are four strata for each sex— ge , gE , Ge , and GE .…”

“…Their epidemiology is not very advanced but should make progress in the next 5-10 years through the very large prospective studies now beginning in several countries. One of the largest is the Biobank project in the United Kingdom, with 500,000 subjects, described in Macdonald, Pritchard, and Tapadar (2006). UK Biobank will recruit 500,000 people aged 40 to 69 from the general population of the United Kingdom, and follow them for up for 10 years.…”

“…(2) Macdonald, Pritchard, and Tapadar (2006) assumed that a 2 × 2 gene-environment interaction affected heart attack risk, with genotypes G and g, and environmental exposures E and e, upper case representing higher risk. So there are four strata for each sex-ge, gE, Ge, and G E. The authors showed that it is possible to hypothecate assumptions on strata-specific relative risks in a way that is consistent with the rate of onset in the general population.…”