Jehu-Appiah Doreen, Obeng-Gyasi Emmanuel
Department of Built Environment, North Carolina A&T State University, Greensboro, NC 27411, USA.
Environmental Health and Disease Laboratory, North Carolina A&T State University, Greensboro, NC 27411, USA.
Toxics. 2025 Jun 5;13(6):476. doi: 10.3390/toxics13060476.
This study assessed the relationship between environmental chemical mixtures-including metals, per- and polyfluoroalkyl substances (PFAS), phthalates, and plasticizers-and key cardiovascular health markers using data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). The combined effects of these pollutants on cardiovascular markers were evaluated using Bayesian Kernel Machine Regression (BKMR), a flexible, non-parametric modeling approach that accommodates nonlinear and interactive relationships among exposures. BKMR was applied to assess both the joint and individual associations of the chemical mixture with systolic blood pressure (SBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), diastolic blood pressure (DBP), total cholesterol, and triglycerides. As part of the BKMR analysis, posterior inclusion probabilities (PIPs) were estimated to identify the relative importance of each exposure within the mixture. These results highlighted phthalates as major contributors to LDL, SBP, total cholesterol, HDL, and triglycerides while plasticizers were associated with LDL, SBP, HDL, and triglycerides. Metals and PFAS were most strongly linked to LDL, DBP, total cholesterol, and SBP. The overall mixture effect indicated that cumulative exposures were associated with lower LDL and SBP and elevated DBP, suggesting an increased cardiovascular risk. Triglycerides exhibited a complex quantile-dependent trend, with higher exposures associated with reduced levels. These findings underscore the importance of mixture-based risk assessments that reflect real-world exposure scenarios.
本研究利用2013 - 2014年美国国家健康与营养检查调查(NHANES)的数据,评估了环境化学混合物(包括金属、全氟和多氟烷基物质(PFAS)、邻苯二甲酸盐和增塑剂)与关键心血管健康指标之间的关系。使用贝叶斯核机器回归(BKMR)评估了这些污染物对心血管指标的综合影响,BKMR是一种灵活的非参数建模方法,可适应暴露之间的非线性和交互关系。应用BKMR评估化学混合物与收缩压(SBP)、高密度脂蛋白(HDL)、低密度脂蛋白(LDL)、舒张压(DBP)、总胆固醇和甘油三酯的联合及个体关联。作为BKMR分析的一部分,估计了后验包含概率(PIPs),以确定混合物中每种暴露的相对重要性。这些结果突出了邻苯二甲酸盐是LDL、SBP、总胆固醇、HDL和甘油三酯的主要贡献因素,而增塑剂与LDL、SBP、HDL和甘油三酯有关。金属和PFAS与LDL、DBP、总胆固醇和SBP的联系最为紧密。总体混合物效应表明,累积暴露与较低的LDL和SBP以及升高的DBP相关,提示心血管风险增加。甘油三酯呈现出复杂的分位数依赖性趋势,较高的暴露与较低水平相关。这些发现强调了基于混合物的风险评估的重要性,这种评估反映了现实世界的暴露情况。