Literature DB >> 7156935

Causal and preventive interdependence. Elementary principles.

O S Miettinen.   

Abstract

"Synergism" of two factors in the causation or prevention of an all-or-none event means the existence of instances in which both factors are needed for the effect, while "antagonism" means that at least one can block the solo effect of the other. The manifestation of such interdependences--or of their complement, independence--in terms of event rates is complicated by the correlation of the susceptibilities to the two factors. Thus, given the risk difference (RD) values representing the solo effects, the RD corresponding to the joint exposure has a range consistent with independence so that independence cannot be inferred even from very ample data without knowledge of the degree of correlatedness of the susceptibilities. The definition of this range is closely analogous for causal and preventive factors, respectively. However, when knowledge about interdependence is used in inference about the factors' interrelation in the mechanisms for the effect, sharp distinctions may have to be made between causal and preventive factors. In each case, the interdependence is a result of the interrelation of the actions of the two factors and/or interaction between them. Operational decisions, having to do with the wisdom of the joint exposure, can be guided by knowledge about the interdependence of the factors; however, knowledge of the risks corresponding to the various exposures is a sufficient guide, without any need for inferences about causal or preventive interdependence.

Mesh:

Year:  1982        PMID: 7156935     DOI: 10.5271/sjweh.2479

Source DB:  PubMed          Journal:  Scand J Work Environ Health        ISSN: 0355-3140            Impact factor:   5.024


  13 in total

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

Authors:  Wolfgang Boedeker; Thomas Backhaus
Journal:  Eur J Epidemiol       Date:  2010-05-22       Impact factor: 8.082

2.  Commentary: reporting and assessing evidence for interaction: why, when and how?

Authors:  David Clayton
Journal:  Int J Epidemiol       Date:  2012-05-16       Impact factor: 7.196

3.  A sufficient cause based approach to the assessment of mediation.

Authors:  Danella M Hafeman
Journal:  Eur J Epidemiol       Date:  2008-09-17       Impact factor: 8.082

Review 4.  Identification of operating mediation and mechanism in the sufficient-component cause framework.

Authors:  Etsuji Suzuki; Eiji Yamamoto; Toshihide Tsuda
Journal:  Eur J Epidemiol       Date:  2011-03-30       Impact factor: 8.082

Review 5.  The quest for interaction: studies on combined exposure.

Authors:  M van Dormolen; C A Hertog; F J van Dijk; M A Kompier; R Fortuin
Journal:  Int Arch Occup Environ Health       Date:  1990       Impact factor: 3.015

6.  Gene-environment interaction: definitions and study designs.

Authors:  R Ottman
Journal:  Prev Med       Date:  1996 Nov-Dec       Impact factor: 4.018

7.  From exposures to population interventions: pregnancy and response to HIV therapy.

Authors:  Daniel Westreich
Journal:  Am J Epidemiol       Date:  2014-02-25       Impact factor: 4.897

8.  Multiply robust inference for statistical interactions.

Authors:  Stijn Vansteelandt; Tyler J Vanderweele; James M Robins
Journal:  J Am Stat Assoc       Date:  2008-12-01       Impact factor: 5.033

Review 9.  Considerations when assessing heterogeneity of treatment effect in patient-centered outcomes research.

Authors:  Catherine R Lesko; Nicholas C Henderson; Ravi Varadhan
Journal:  J Clin Epidemiol       Date:  2018-04-11       Impact factor: 6.437

10.  Contrasting theories of interaction in epidemiology and toxicology.

Authors:  Gregory J Howard; Thomas F Webster
Journal:  Environ Health Perspect       Date:  2012-09-26       Impact factor: 9.031

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.