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On Summarizing Group Exposures in Risk Assessment: Is an Arithmetic Mean or a Geometric Mean More Appropriate?

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  • Kenny S. Crump

Abstract

Since substantial bias can result from assigning some type of mean exposure to a group, risk assessments based on epidemiological data should avoid the grouping of data whenever possible. However, ungrouped data are frequently unavailable, and the question arises as to whether an arithmetic or geometric mean is the most appropriate summary measure of exposure. It is argued in this paper that one should use the type of mean for which the total risk that would result if every member of the population was exposed to the mean level is as close as possible to the actual total population risk. Using this criterion an arithmetic mean is always preferred over a geometric mean whenever the dose response is convex. In each of several data sets examined in this paper for which the dose response was not convex, an arithmetic mean was still preferred based on this criterion.

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  • Kenny S. Crump, 1998. "On Summarizing Group Exposures in Risk Assessment: Is an Arithmetic Mean or a Geometric Mean More Appropriate?," Risk Analysis, John Wiley & Sons, vol. 18(3), pages 293-297, June.
    • Handle: RePEc:wly:riskan:v:18:y:1998:i:3:p:293-297
    DOI: 10.1111/j.1539-6924.1998.tb01296.x
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    References listed on IDEAS

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    1. Kenny Crump & John Viren & Abraham Silvers & Harvey Clewell III & Jeff Gearhart & Annette Shipp, 1995. "Reanalysis of Dose‐Response Data from the Iraqi Methylmercury Poisoning Episode," Risk Analysis, John Wiley & Sons, vol. 15(4), pages 523-532, August.
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    Cited by:

    1. Harvey J. Clewell & Gregory A. Lawrence & Donald B. Calne & Kenny S. Crump, 2003. "Determination of an Occupational Exposure Guideline for Manganese Using the Benchmark Method," Risk Analysis, John Wiley & Sons, vol. 23(5), pages 1031-1046, October.
    2. Sara Gustavsson & Björn Fagerberg & Gerd Sallsten & Eva M. Andersson, 2014. "Regression Models for Log-Normal Data: Comparing Different Methods for Quantifying the Association between Abdominal Adiposity and Biomarkers of Inflammation and Insulin Resistance," IJERPH, MDPI, vol. 11(4), pages 1-19, March.

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