Improving food additive exposure assessment using FoodEx2-based sub-categorisation and food labelling information: a...

Precise estimates of food additive exposure levels are critical for scientific evaluations of associated health risks. However, a lack of data on additive concentrations and usage levels in foods can result in excessively conservative estimates. To address this issue, we propose an approach that first subdivides food categories authorised to contain a given food additive according to the European FoodEx2 classification system and food labelling information, which are objective and comprehensive. By identifying food categories and products that do not use the given additive using information from food labels, these items can be excluded from the food consumption datasets used for exposure estimates. The proposed method was applied to estimate dietary exposure to sucrose esters of fatty acids (E 473) in selected fine bakery wares and favoured drinks that permit the use of E 473. The refined model yielded substantially lower exposure estimates, with a 98.9% reduction in the 95^th percentile for favoured drinks among very elderly consumers. These findings demonstrate that evidence-based classification and the exclusion of non-relevant food categories can markedly enhance the accuracy and reproducibility of food additive exposure assessments.