Reporting and Modeling of Results Below the Limit of Detection

Abstract

Conducting dietary exposure assessment (E) consists in combining deterministically or probabilistically food consumption figures (Q) with concentrations (C) of a given chemical substance in a number of foods or food categories. Occurrence data can be obtained either from control and monitoring programs or from a total diet Study (TDS). In both cases, data reported to be below the limit of detection (LOD), called “non-detects” or “left-censored data”, are likely to have a critical influence on the results of the assessment. Both the LOD and the limit of quantification (LOQ) are of special importance for exposure estimations in risk assessments as they determine the minimum value that can be detected and quantified, respectively.

The objective of TDS is to provide concentration data for dietary exposure assessment, which are analyzed in food as consumed and issued from composite samples expected to represent an average value for a food, food group of interest or even the whole diet. In theory, the dietary exposure to a chemical could, therefore, be based on a unique sample including a weighted mix of all food of the diet in which the chemical is expected to occur. At the other end of the spectrum of possibilities, a TDS can be based on each relevant food item, such as fish, or on a composite of various species available on the market. Finally composite samples can be prepared locally and repeated in various areas of a country or region and in various seasons to capture the variability of the contamination regarding these parameters.

This chapter covers the handling of non-detects in TDS studies. It is based on a review of the literature included in a recent report of the European Food Safety Authority dedicated to this topic. While none of these works were specific to the TDS, many were based on realistic datasets in the field of chemical occurrence in food.