Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Incorporating regulatory guideline values in analysis of epidemiology data
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry.
Show others and affiliations
Number of Authors: 72018 (English)In: Environment International, ISSN 0160-4120, E-ISSN 1873-6750, Vol. 120, p. 535-543Article in journal (Refereed) Published
Abstract [en]

Fundamental to regulatory guidelines is to identify chemicals that are implicated with adverse human health effects and inform public health risk assessors about acceptable ranges of such environmental exposures (e.g., from consumer products and pesticides). The process is made more difficult when accounting for complex human exposures to multiple environmental chemicals. Herein we propose a new class of nonlinear statistical models for human data that incorporate and evaluate regulatory guideline values into analyses of health effects of exposure to chemical mixtures using so-called 'desirability functions' (DFs). The DFs are incorporated into nonlinear regression models to allow for the simultaneous estimation of points of departure for risk assessment of combinations of individual substances that are parts of chemical mixtures detected in humans. These are, in contrast to published so-called biomonitoring equivalent (BE) values and human biomonitoring (HBM) values that link regulatory guideline values from in vivo studies of single chemicals to internal concentrations monitored in humans. We illustrate the strategy through the analysis of prenatal concentrations of mixtures of 11 chemicals with suspected endocrine disrupting properties and two health effects: birth weight and language delay at 2.5 years. The strategy allows for the creation of a Mixture Desirability Function i.e., MDF, which is a uni-dimensional construct of the set of single chemical DFs; thus, it focuses the resulting inference to a single dimension for a more powerful one degree-of-freedom test of significance. Based on the application of this new method we conclude that the guideline values need to be lower than those for single chemicals when the chemicals are observed in combination to achieve a similar level of protection as was aimed for the individual chemicals. The proposed modeling may thus suggest data-driven uncertainty factors for single chemical risk assessment that takes environmental mixtures into account.

Place, publisher, year, edition, pages
2018. Vol. 120, p. 535-543
Keywords [en]
Environmental chemicals, Mixtures, Cumulative risk assessment
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-162888DOI: 10.1016/j.envint.2018.08.039ISI: 000448688500055PubMedID: 30170308OAI: oai:DiVA.org:su-162888DiVA, id: diva2:1273483
Available from: 2018-12-21 Created: 2018-12-21 Last updated: 2018-12-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Gennings, ChrisShu, HuanRudén, ChristinaLindh, ChristianKiviranta, HannuBornehag, Carl-Gustaf
By organisation
Department of Environmental Science and Analytical Chemistry
In the same journal
Environment International
Earth and Related Environmental Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 18 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf