Exposure mixtures
Exposure mixtures will select sets of co-occurring substances (one or more) that contribute most to the overall exposure patterns.
This module has as primary entities: Foods Substances Effects
Calculation of exposure mixtures
A multivariate decomposition method, sparse non-negative matrix underestimation (SNMU), is applied to the matrix of exposures per substance and per individual (chronic) or individual-day (acute) to find substance sets that contribute most to the cumulative exposure. Exposures per substance are preprocessed either by multiplication with relative potency factors (RPFs) to make the analysis risk-based, or by standardisation to mean 0 and variance 1 to make the analysis correlation-based.
Inputs used: Dietary exposures Exposures
Settings used