Evidence map›Paper›PMID 22260322›Full record

ReviewEnvironmental science & technology2012

Predictive environmental risk assessment of chemical mixtures: a conceptual framework.

Thomas Backhaus, Michael Faust

Abstract readReview
PubMed Publisher
In one paragraph

Review in Environmental science & technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

126 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Toxicity-informed control of global PMNational science review · 2026
    Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. The Freshwater CiliateJournal of xenobiotics · 2026
    Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

66 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Thomas BackhausDepartment of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden. thomas.backhaus@gu.se
Michael Faust

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental risks of chemicals are still often assessed substance-by-substance, neglecting mixture effects. This may result in risk underestimations, as the typical exposure is toward multicomponent chemical "cocktails". We use the two well established mixture toxicity concepts (Concentration Addition (CA) and Independent Action (IA)) for providing a tiered outline for environmental hazard and risk assessments of mixtures, focusing on general industrial chemicals and assuming that the "base set" of data (EC50s for algae, crustaceans, fish) is available. As mixture toxicities higher than predicted by CA are rare findings, we suggest applying CA as a precautious first tier, irrespective of the modes/mechanisms of action of the mixture components. In particular, we prove that summing up PEC/PNEC ratios might serve as a justifiable CA-approximation, in order to estimate in a first tier assessment whether there is a potential risk for an exposed ecosystem if only base-set data are available. This makes optimum use of existing single substance assessments as more demanding mixture investigations are requested only if there are first indications of an environmental risk. Finally we suggest to call for mode-of-action driven analyses only if error estimations indicate the possibility for substantial differences between CA- and IA-based assessments.

Indexed as

EnvironmentModels, TheoreticalComplex MixturesEcotoxicologyRisk AssessmentComplex Mixtures

Identifiers

PMID22260322

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.