A Model for Coronary Heart Disease and Stroke with Applications to Critical Illness Insurance Underwriting I: The Model

Macdonald, Angus S.; Waters, Howard R.; Wekwete, Chessman T

doi:10.1080/10920277.2005.10596182

Cited by 19 publications

(10 citation statements)

References 24 publications

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“…Law, Wald & Rudnicka (2003) state that: "... cohort studies showed no association between serum cholesterol concentrations and stroke.'' This is consistent with the findings of Macdonald et al (2003), based on data from the Framingham Heart Study. However, Law, Wald & Rudnicka (2003) also report what they refer to as a 'paradox', in that earlier studies "... showed that statins reduced the incidence of stroke by about 30%.''…”

Section: Drug Treatments For Cardiovascular Diseasesupporting

confidence: 92%

Longevity in the 21st Century

Willets¹,

Gallop²,

Leandro³

et al. 2004

Br. Actuar. J.

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The main objective of this paper is to offer a detailed analysis of mortality change in the United Kingdom at the beginning the 21st century. Starting from an exploration of 20th century mortality trends, focusing in particular on the 1990s, underlying forces driving trends in longevity are discussed. These include the 'cohort effect' and the 'ageing of mortality improvement'. International mortality statistics and trends are also analysed. The pace of medical advances is discussed, with specific focus on research into the ageing process and a potential treatment for cardiovascular disease. The paper also discusses the potential threat from infectious diseases.The analysis of underlying trends suggests that life expectancy in retirement in the U.K. is likely to increase rapidly in the early part of the 21st century. Some scientists are also claiming that we will be seeing the fruits of anti-ageing research within just a few decades.A core theme of the paper is that future projections should be grounded in as good an understanding of the past as possible. Different methods for projecting future rates of mortality are discussed, and it is noted that emphasis should be placed on the uncertainty surrounding projections.The financial impact of using different assumptions for future mortality is explored. Significant differences in the cost of an annuity or pension arise from the use of the various projection bases.Life assurance companies have already declared significant losses as a result of strengthening reserves on annuity portfolios. Taken together, future increases in life expectancy, increasing awareness of the risk of providing longevity insurance, changes in legislation and shortages in market capacity and capital, may well lead to worsening annuity rates.It is difficult to assess the precise impact of future changes in life expectancy on final salary pension schemes. There is a lack of readily available information on the mortality assumptions being used in practice. It is therefore suggested that more disclosure in this area would be helpful. Employers sponsoring final salary schemes are making promises to their employees that extend up to 70 or 80 years into the future. Actuaries should be clear in spelling out to employers and trustees the nature of the risks behind the promises they are making. Future scheme design should reflect the possibility of substantial increases in life expectancy.An over-riding implication of the anticipated increases in life expectancy is that people will remain in work for longer in the future. The age at which people retire will inevitably have to increase, and this trend will necessarily drive changes in all aspects of our society. As actuaries we have a vital role in helping to inform the wider debate. keywords Mortality; Longevity; Ageing; Annuities; Cohort Effect B.A.

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Section: Drug Treatments For Cardiovascular Diseasesupporting

confidence: 92%

Longevity in the 21st Century

Willets¹,

Gallop²,

Leandro³

et al. 2004

Br. Actuar. J.

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“…To date, no gene or set of genes has been shown to cause illnesses such as heart disease and diabetes, and the pathways to those diseases are complicated. However, there is evidence that common chronic diseases tend to aggregate within a family (Macdonald, Waters, & Wekwete, 2005), suggesting that certain conditions tend to “run” within families. The economic model suggests that one's genetic endowment is part of one's available resources.…”

mentioning

confidence: 99%

Stages of Change in Physical Exercise and Social Support: An Integrated Socio‐Psycho‐Economic Approach

Gibbison

Johnson

2011

J Applied Social Pyschol

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The present research attempts to integrate behavioral and social science theories (e.g., theory of reasoned action, social cognitive theory, transtheoretical model) in assessing the effect and sources of social support of persons in various stages of physical exercise. Using multinomial regression to analyze the data collected via interviews from a sample of over 1,500 working adults in Jamaica, strong statistical support was found for the role of social support in initiating and maintaining exercise. The importance of various providers depends on the individual's stage of behavioral change. Health workers, relatives, and friends are important during early stages; while friends and physical trainers are important during later stages. Other results, limitations, and suggestions for future research are discussed.

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“…Macdonald et al (2005a;2005b) modelled CHD using three risk factors assumed to be static (sex, smoking status and body mass index) and three assumed to be dynamic (i.e. Macdonald et al (2005a;2005b) modelled CHD using three risk factors assumed to be static (sex, smoking status and body mass index) and three assumed to be dynamic (i.e.…”

Section: Multifactorial Disordersmentioning

confidence: 99%

Insurance

Macdonald¹

2007

Handbook of Statistical Genetics

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As soon as DNA-based genetic testing became available, questions were asked about its use by insurers to discriminate against carriers of deleterious alleles. The statistical interest in these questions lies mainly in the application of genetic epidemiology to the actuarial models used to price life and health insurance. This chapter surveys the relevant research, including early work mostly focussed on single-gene disorders, and more recent attempts to predict the relevance of multifactorial genetics to insurance practice.Insurance is an unusual branch of commerce because the basis of its sound operation is mathematical in nature. Just as airlines (say) must take the mathematics of aerodynamics as they find it, insurance companies may be in peril if they ignore the actuarial mathematics and statistics that govern their businesses. But actuaries do not deal with precise and impersonal qualities like airflow over a wing; they deal with people and their personal attributes, that lead to an assessment of the risk of making a claim under an insurance contract. Some personal attributes (sex, race, disability) give rise to stronger sensitivities than others (age, weight, smoking habits) and the experience of the last 10 years suggests that any kind of personal genetic information falls in the first group.The mathematical nature of insurance, and life insurance in particular, is straightforward. The simplest contract, called whole-of-life insurance, pays an agreed sum (the sum assured) immediately on the death of the insured person. Suppose a person wishes to buy whole-of-life insurance with sum assured S. The problem is to determine the premium P to be paid at outset (in practice, premiums are usually payable monthly but we ignore this complication). Death being certain, so the insurer will pay out S at some future time with certainty. Intuitively the 'fair' premium before allowing for expenses, profit, etc. appears 1346 Handbook of Statistical Genetics, Third Edition . E dited by D . J. Balding, M . Bishop and C. Cannings.

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A Model for Coronary Heart Disease and Stroke with Applications to Critical Illness Insurance Underwriting I: The Model

Cited by 19 publications

References 24 publications

Longevity in the 21st Century

Longevity in the 21st Century

Stages of Change in Physical Exercise and Social Support: An Integrated Socio‐Psycho‐Economic Approach

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