Literature DB >> 20495951

The scientific assessment of combined effects of risk factors: different approaches in experimental biosciences and epidemiology.

Wolfgang Boedeker1, Thomas Backhaus.   

Abstract

The analysis of combined effects of substances or risk factors has been a subject to science for more than a century. With different goals, combined effect analysis was addressed in almost all experimental biosciences. The major theoretical foundation can be traced back to two distinct origins. First, to the work by the pharmacologist Loewe on the concept of concentration additivity and second to the biometrician Bliss and the concept of independent action. In the search for a general solution and a unified terminology the interrelations of the concepts have extensively been studied and experimental findings reviewed. Meanwhile there seems to be consensus in experimental sciences that each concept has its role in predicting combined effect of agents and both are used for hazard und risk management. In contrast, epidemiologists describe combined effects mainly in terms of interactions in regression models. Although this approach started from a probabilistic model equivalent to the concept of independent action this origin is rarely acknowledged and effect summation is usually the preferred concept nowadays. Obscure biological meaning, the scale dependency of interaction terms as well as unavoidable residual confounding are taken as reasons why no new insights in combined effect analysis are likely to occur from epidemiology. In this paper we sketch the history of ideas and the state of the arts in combined effect analysis. We point to differences and common grounds in experimental biosciences and epidemiology.

Mesh:

Year:  2010        PMID: 20495951     DOI: 10.1007/s10654-010-9464-2

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  30 in total

1.  A general best-fit method for concentration-response curves and the estimation of low-effect concentrations.

Authors:  M Scholze; W Boedeker; M Faust; T Backhaus; R Altenburger; L H Grimme
Journal:  Environ Toxicol Chem       Date:  2001-02       Impact factor: 3.742

2.  Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures.

Authors:  Marion Junghans; Thomas Backhaus; Michael Faust; Martin Scholze; L H Grimme
Journal:  Aquat Toxicol       Date:  2005-11-28       Impact factor: 4.964

3.  When one depends on the other: reporting of interaction in case-control and cohort studies.

Authors:  Mirjam J Knol; Matthias Egger; Pippa Scott; Mirjam I Geerlings; Jan P Vandenbroucke
Journal:  Epidemiology       Date:  2009-03       Impact factor: 4.822

4.  Sufficient cause interactions and statistical interactions.

Authors:  Tyler J VanderWeele
Journal:  Epidemiology       Date:  2009-01       Impact factor: 4.822

5.  The estimation of synergy or antagonism.

Authors:  K J Rothman
Journal:  Am J Epidemiol       Date:  1976-05       Impact factor: 4.897

6.  Statistical aspects of the independent joint action of poisons, particularly insecticides; the toxicity of a mixture of poisons.

Authors:  R L PLACKETT; P S HEWLETT
Journal:  Ann Appl Biol       Date:  1948-09       Impact factor: 2.750

7.  Invariants and noninvariants in the concept of interdependent effects.

Authors:  S Greenland; C Poole
Journal:  Scand J Work Environ Health       Date:  1988-04       Impact factor: 5.024

8.  The expected effect of a combination of agents: the general solution.

Authors:  M C Berenbaum
Journal:  J Theor Biol       Date:  1985-06-07       Impact factor: 2.691

9.  Interaction in epidemiologic studies.

Authors:  L L Kupper; M D Hogan
Journal:  Am J Epidemiol       Date:  1978-12       Impact factor: 4.897

Review 10.  Regulations for combined effects of pollutants: consequences from risk assessment in aquatic toxicology.

Authors:  R Altenburger; W Boedeker; M Faust; L H Grimme
Journal:  Food Chem Toxicol       Date:  1996 Nov-Dec       Impact factor: 6.023

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