Marques Chloé, Frenoy Pauline, Fiolet Thibault, Crépet Amélie, Severi Gianluca, Mancini Francesca Romana
Paris-Saclay University, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP U1018, 94805 Villejuif, France.
French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Risk Assessment Department, Methodology and Survey Unit, 94701 Maisons-Alfort, France.
Sci Total Environ. 2023 Sep 20;892:164350. doi: 10.1016/j.scitotenv.2023.164350. Epub 2023 May 24.
Food is contaminated by many chemicals which interact with each other, resulting in additive, synergistic or antagonistic effects. It is thus necessary to study the health effects of dietary exposure to chemical mixtures rather than single contaminants. We aimed to investigate the association between dietary exposure to chemical mixtures and mortality risk in the E3N French prospective cohort. We included 72,585 women from the E3N cohort who completed a food frequency questionnaire in 1993. From 197 chemicals, and using sparse non-negative matrix under-approximation (SNMU), we identified six main chemical mixtures to which these women were chronically exposed through the diet. We estimated the associations between dietary exposure to these mixtures and all-cause or cause-specific mortality using Cox proportional hazard models. During the follow-up (1993-2014), 6441 deaths occurred. We observed no association between dietary exposure to three mixtures and all-cause mortality, and a non-monotonic inverse association for the three other mixtures. These results could be explained by the fact that, despite the different dietary adjustment strategies tested, we did not fully succeed in excluding the residual confounding from the overall effect of the diet. We also questioned the number of chemicals to include in mixtures' studies, as a balance needs to be reached between including a large number of chemicals and the interpretability of the results. Integrating a priori knowledge, such as toxicological data, could lead to the identification of more parsimonious mixtures, thus to more interpretable results. Moreover, as the SNMU is a non-supervised method, which identifies the mixtures only on the basis of the correlations between the exposure variables, and not in relation to the outcome, it would be interesting to test supervised methods. Finally, further studies are needed to identify the most adequate approach to investigate the health effects of dietary exposure to chemical mixtures in observational studies.
食物会被许多相互作用的化学物质污染,从而产生相加、协同或拮抗作用。因此,有必要研究饮食中接触化学混合物而非单一污染物对健康的影响。我们旨在调查法国E3N前瞻性队列中饮食接触化学混合物与死亡风险之间的关联。我们纳入了E3N队列中在1993年完成食物频率问卷的72585名女性。从197种化学物质中,我们使用稀疏非负矩阵下近似法(SNMU)确定了六种主要化学混合物,这些女性通过饮食长期接触这些混合物。我们使用Cox比例风险模型估计了饮食接触这些混合物与全因死亡率或特定原因死亡率之间的关联。在随访期间(1993 - 2014年),发生了6441例死亡。我们观察到饮食接触三种混合物与全因死亡率之间无关联,而对其他三种混合物则观察到非单调的负相关。这些结果可以解释为,尽管测试了不同的饮食调整策略,但我们并未完全成功排除饮食总体效应中的残余混杂因素。我们还对混合物研究中应纳入的化学物质数量提出质疑,因为在纳入大量化学物质与结果的可解释性之间需要取得平衡。整合先验知识,如毒理学数据,可能会导致识别出更简约的混合物,从而得到更具可解释性的结果。此外,由于SNMU是一种无监督方法,它仅根据暴露变量之间的相关性来识别混合物,而与结果无关,因此测试有监督方法会很有趣。最后,需要进一步研究以确定在观察性研究中调查饮食接触化学混合物对健康影响的最适当方法。