Per和多氟烷基物质与腹部脂肪分布的关系:特征谱暴露模式和基于结构的研究。

Zhi Li, Shi Lin Shan, Chen Yang Song, Cheng Zhe Tao, Hong Qian, Qin Yuan, Yan Zhang, Qiao Qiao Xu, Yu Feng Qin, Yun Fan, Chun Cheng Lu
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引用次数: 0

摘要

目的:分析2011-2018年全国健康与营养检查调查(NHANES)数据,探讨8种血清全氟和多氟烷基物质(PFASs)与区域脂肪库的关系。方法:建立多元线性回归模型,探讨血清PFAS浓度与六种脂肪成分之间的关系,并通过将六种脂肪成分的浓度相加得出脂肪分布评分。研究人员评估了PFAS结构分组与脂肪分布之间的关系,并建立了一个预测模型来估计PFAS暴露预测肥胖风险的能力。结果:在39-59岁的女性中,躯干脂肪量与全氟辛烷磺酸(PFOS)呈正相关。更高浓度的全氟辛烷磺酸、全氟己烷磺酸(PFHxS)、全氟癸酸(PFDeA)、全氟壬酸(PFNA)和正全氟辛酸(n-PFOA)与这一组中内脏脂肪组织的增加有关。在男性中,接触全氟烷烃磺酸盐(pfsa)和长链pfsa与腹部脂肪减少有关,而在39-59岁的女性中,腹部脂肪增加与短链pfsa有关。预测模型具有较高的准确度,预测肥胖风险的曲线下面积(AUC)为0.9925。结论:PFAS暴露与区域脂肪分布有关,其影响因年龄、性别和PFAS结构而异。研究结果强调了PFAS暴露在影响脂肪储存和肥胖风险方面的潜在作用,对公众健康具有重要意义。该预测模型为评估PFAS暴露相关的肥胖风险提供了高度准确的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association between Per and Polyfluoroalkyl Substance and Abdominal Fat Distribution: A Trait Spectrum Exposure Pattern and Structure-Based Investigation.

Objective: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles.

Methods: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk.

Results: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk.

Conclusion: PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.

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