Identification of chemical mixtures to which women are exposed through the diet: Results from the French E3N cohort

Due to the large number of chemical food contaminants, consumers are exposed simultaneously to a wide range of chemicals which can interact and have a negative impact on health. Nevertheless, due to the multitude of possible chemical combinations it is unrealistic to test all combined toxicological effects. It is therefore essential to identify the most relevant mixtures to which the population is exposed through the diet and investigate their impact on heath. The present study aims to identify and describe the main chemical mixtures to which women enrolled in the E3N study, a large French prospective cohort, are chronically exposed through the diet. 74 522 women who had answered a validated semi-quantitative food frequency questionnaire in 1993, were included in the present study. Dietary exposure to chemical contaminates was estimated based on the food contamination measured in 186 core food in France collected between 2007 and 2009 by the French agency for food, environment and occupational health, and safety (ANSES) in the framework of the second French total diet study (2TDS). The sparse non-negative matrix under-approximation (SNMU) was used to identify mixtures of chemical substances. A k-means clustering classification of the whole study population was then performed to define clusters with similar co-exposure profiles. Overall, 8 mixtures which explained 83% of the total variance, were retained. The first mixture, entitled “Minerals, inorganic contaminants, and furans”, explained the highest proportion of the total variance (38%), and was correlated in particular with the consumption of “Offal” (rho = 0.22), “Vegetables except roots” (rho = 0.20), and “Eggs” (rho = 0.19). The other seven mixtures explained between 17% and 1% of the variance. Finally, 5 clusters were identified based on the adherence to the 8 mixtures. This study, being the largest ever conducted to identify dietary exposure to chemical mixtures, represents a concrete attempt to prioritize mixtures for which it is essential to investigate combined health effects based on exposure.