■慢性疾病的全球负担一直在增加,有证据表明饮食和暴露于环境污染物,如全氟和多氟烷基物质(PFAS)和重金属,可能有助于他们的发展。饮食炎症指数(DII)评估个体饮食的炎症潜能。然而,PFAS之间复杂的相互作用,重金属,和DII基本上仍未开发。
■这项横断面研究的目的是调查作为DII操作的饮食与个体和联合铅之间的关联,镉,水银,全氟辛酸(PFOA),和全氟辛烷磺酸(PFOS)暴露使用国家健康和营养检查调查(NHANES)2017-2018的数据。
■描述性统计,相关分析,和线性回归最初用于评估感兴趣的变量之间的关系。随后,我们采用贝叶斯核机回归(BKMR)来分析数据,以评估非线性、非添加剂,PFAS和金属与DII的暴露-反应关系和相互作用。
■多变量线性回归揭示了DII与镉和汞之间的显着关联。我们的BKMR分析揭示了PFAS之间的复杂关系,金属暴露,还有DII.在我们的单变量暴露-响应函数图中,镉和汞呈正负线性关系,分别,这表明与DII的曝光光谱之间存在正负关系。此外,在混合物中两次暴露之间的双变量暴露响应函数表明,对于不同的铅分位数,镉与DII具有稳健的正相关关系,水银,PFOA,和全氟辛烷磺酸,表明镉含量的增加与DII有关。汞的双变量图显示出所有污染物的所有分位数之间的负相关关系。此外,后验包涵概率(PIP)结果强调了镉和汞与个体饮食的潜在炎症的一致性重要性,在我们的研究中作为DII操作,两者的PIP均为1.000。其次是PFOS,PIP为0.8524,PFOA为0.5924,铅,在五种环境污染物中影响最小,PIP为0.5596。
■我们的研究表明,暴露于环境金属和PFAS,特别是汞和镉,与DII有关。这些发现还提供了PFAS之间复杂关系的证据,重金属,还有DII.研究结果强调了考虑多污染物暴露累积效应的重要性。未来的研究应该集中在阐明机制途径和剂量反应关系的基础上,这些关联在一项研究中,检查因果关系,这将使人们更深入地了解与环境污染物相关的饮食风险。
UNASSIGNED: The global burden of chronic diseases has been increasing, with evidence suggesting that diet and exposure to environmental pollutants, such as per- and polyfluoroalkyl substances (
PFAS) and heavy metals, may contribute to their development. The Dietary Inflammatory Index (DII) assesses the inflammatory potential of an individual\'s diet. However, the complex interplay between
PFAS, heavy metals, and DII remains largely unexplored.
UNASSIGNED: The goal of this cross-sectional study was to investigate the associations between diet operationalized as the DII with individual and combined lead, cadmium, mercury, perfluorooctanoic acid (PFOA), and perfluorooctanesulfonic acid (PFOS) exposures using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018.
UNASSIGNED: Descriptive statistics, a correlational analysis, and linear regression were initially used to assess the relationship between the variables of interest. We subsequently employed Bayesian kernel Machine regression (BKMR) to analyze the data to assess the non-linear, non-additive, exposure-response relationships and interactions between
PFAS and metals with the DII.
UNASSIGNED: The multi-variable linear regression revealed significant associations between the DII and cadmium and mercury. Our BKMR analysis revealed a complex relationship between
PFAS, metal exposures, and the DII. In our univariate exposure-response function plot, cadmium and mercury exhibited a positive and negative linear relationship, respectively, which indicated a positive and negative relationship across the spectrum of exposures with the DII. In addition, the bivariate exposure-response function between two exposures in a mixture revealed that cadmium had a robust positive relationship with the DII for different quantiles of lead, mercury, PFOA, and PFOS, indicating that increasing levels of cadmium are associated with the DII. Mercury\'s bivariate plot demonstrated a negative relationship across all quantiles for all pollutants. Furthermore, the posterior inclusion probability (PIP) results highlighted the consistent importance of cadmium and mercury with the inflammatory potential of an individual\'s diet, operationalized as the DII in our study, with both showing a PIP of 1.000. This was followed by PFOS with a PIP of 0.8524, PFOA at 0.5924, and lead, which had the lowest impact among the five environmental pollutants, with a PIP of 0.5596.
UNASSIGNED: Our study suggests that exposures to environmental metals and
PFAS, particularly mercury and cadmium, are associated with DII. These findings also provide evidence of the intricate relationships between PFAS, heavy metals, and the DII. The findings underscore the importance of considering the cumulative effects of multi-pollutant exposures. Future research should focus on elucidating the mechanistic pathways and dose-response relationships underlying these associations in a study that examines causality, which will enable a deeper understanding of the dietary risks associated with environmental pollutants.