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Perspective: Risk Apportionment and Disease Intervention Strategies

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  • Leila M. Barraj
  • Nga L. Tran
  • Michael Goodman
  • Michael E. Ginevan

Abstract

The ultimate public health objective is the ability to predict and prevent disease, and not necessarily to identify an exhaustive list of potential disease risk factors. For any important public health outcome with multiple and potentially interrelated risk factors, an improved understanding of the contribution of individual and combinations of modifiable risk factors to the disease burden is essential for formulating an appropriate public health strategy. Partitioning techniques that divide the combined impact of multiple risk factors into exposure‐specific components while taking into account the potential interrelations among those components, have been described in the epidemiological literature. In this article, we review and compare the available methods and options for such apportionment and apply them in a more general public health context as a method of selecting and prioritizing coronary heart disease (CHD) prevention strategies.

Suggested Citation

  • Leila M. Barraj & Nga L. Tran & Michael Goodman & Michael E. Ginevan, 2008. "Perspective: Risk Apportionment and Disease Intervention Strategies," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 477-486, April.
    • Handle: RePEc:wly:riskan:v:28:y:2008:i:2:p:477-486
    DOI: 10.1111/j.1539-6924.2008.01028.x
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    References listed on IDEAS

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    2. Krieger, Nancy, 1994. "Epidemiology and the web of causation: Has anyone seen the spider?," Social Science & Medicine, Elsevier, vol. 39(7), pages 887-903, October.
    3. Greenland, S., 1999. "Relation of probability of causation to relative risk and doubling dose: A methodologic error that has become a social problem," American Journal of Public Health, American Public Health Association, vol. 89(8), pages 1166-1169.
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    Cited by:

    1. Bertram Price & Michael MacNicoll, 2015. "Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 931-940, May.

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