# Using decomposed household food acquisitions as inputs of a Kinetic Dietary Exposure Model

## TL;DR

This paper presents a new method for assessing long-term dietary risk from food contaminants by decomposing household food acquisition data into individual consumption patterns and integrating pharmacokinetic properties.

## Contribution

It introduces a semi-parametric decomposition model of household food data as input for a kinetic dietary exposure model, enhancing chronic risk assessment accuracy.

## Key findings

- Applied to methyl mercury in seafood, demonstrating the model's practical utility.
- Provides a framework for integrating long-term consumption data with contaminant pharmacokinetics.
- Improves understanding of chronic dietary exposure risks.

## Abstract

Foods naturally contain a number of contaminants that may have different and long term toxic effects. This paper introduces a novel approach for the assessment of such chronic food risk that integrates the pharmacokinetic properties of a given contaminant. The estimation of such a Kinetic Dietary Exposure Model (KDEM) should be based on long term consumption data which, for the moment, can only be provided by Household Budget Surveys such as the SECODIP panel in France. A semi parametric model is proposed to decompose a series of household quantities into individual quantities which are then used as inputs of the KDEM. As an illustration, the risk assessment related to the presence of methyl mercury in seafood is revisited using this novel approach.