Guo Xianwei, Wu Birong, Hu Wenjing, Wang Xingyue, Su Wenqi, Meng Jia, Lowe Scott, Zhao Dongdong, Huang Christy, Liang Mingming, Qu Guangbo, Zhou Xiaoqin, Sun Yehuan
Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China.
College of Osteopathic Medicine, Kansas City University, Kansas City, MO 64106, USA.
Sci Total Environ. 2023 Jun 25;879:163083. doi: 10.1016/j.scitotenv.2023.163083. Epub 2023 Mar 25.
Perchlorate, nitrate and thiocyanate are common endocrine disruptors. Herein, this study was undertaken to evaluate the associations between perchlorate, nitrate, and thiocyanate exposures (alone or in combination) and risk of metabolic syndrome (MetS) among adults, which has not been explored so far. Analytical data were extracted from different datasets in the National Health and Nutrition Examination Survey (NHANES) database. Multivariate logistic regression models were constructed to investigate the associations between perchlorate, nitrate, and thiocyanate exposures, and the prevalence of MetS. Subsequently, odds ratios (OR) and their corresponding 95 % confidence intervals (CIs) were adopted to represent the magnitude of the effect size. We performed a series of subgroup analyses and sensitivity analyses as well. Moreover, three commonly used mixture modeling strategies [Weighted quantile sum (WQS) regression, quantile-based g-computation (Qgcomp), and Bayesian kernel machine regression (BKMR)] were utilized to evaluate the joint mixture effect on MetS. This study included 12,007 participants in the subsequent analyses. After adjustment for confounding factors, higher levels of perchlorate, and thiocyanate concentrations were significantly associated with the risk of MetS (OR = 1.15, 95%CI:1.00, 1.32; OR = 1.21, 95%CI:1.04, 1.41, respectively). Analyses of WQS and Qgcomp showed that a quartile increase in chemical mixture was correlated with the occurrence of MetS with ORs of 1.07 (95%CI: 0.99, 1.16) and 1.07 (95%CI: 1.00, 1.14), respectively. This positive association was mainly driven by perchlorate and thiocyanate. Analysis of BKMR revealed that perchlorate, nitrate, and thiocyanate mixture was positively associated with the risk of MetS while perchlorate, and thiocyanate were major predictors in the mixture. In summary, our study reveals positive relationships between perchlorate, thiocyanate and MetS. Co-exposure to perchlorate, nitrate and thiocyanate is positively associated with the risk of MetS, with perchlorate and thiocyanate contributing the most to the overall mixture effect.
高氯酸盐、硝酸盐和硫氰酸盐是常见的内分泌干扰物。在此，本研究旨在评估高氯酸盐、硝酸盐和硫氰酸盐暴露（单独或联合）与成年人代谢综合征（MetS）风险之间的关联，这一关联迄今尚未得到探索。分析数据取自国家健康与营养检查调查（NHANES）数据库中的不同数据集。构建多变量逻辑回归模型，以研究高氯酸盐、硝酸盐和硫氰酸盐暴露与代谢综合征患病率之间的关联。随后，采用优势比（OR）及其相应的95%置信区间（CI）来表示效应大小的幅度。我们还进行了一系列亚组分析和敏感性分析。此外，使用了三种常用的混合建模策略[加权分位数和（WQS）回归、基于分位数的g计算（Qgcomp）和贝叶斯核机器回归（BKMR）]来评估对代谢综合征的联合混合效应。本研究在后续分析中纳入了12,007名参与者。在对混杂因素进行调整后，较高水平的高氯酸盐和硫氰酸盐浓度与代谢综合征风险显著相关（OR分别为1.15，95%CI：1.00，1.32；OR为1.21，95%CI：1.04，1.41）。WQS和Qgcomp分析表明，化学混合物增加一个四分位数与代谢综合征的发生相关，OR分别为1.07（95%CI：0.99，1.16）和1.07（95%CI：1.00，1.14）。这种正相关主要由高氯酸盐和硫氰酸盐驱动。BKMR分析显示，高氯酸盐、硝酸盐和硫氰酸盐混合物与代谢综合征风险呈正相关，而高氯酸盐和硫氰酸盐是混合物中的主要预测因素。总之，我们的研究揭示了高氯酸盐、硫氰酸盐与代谢综合征之间的正相关关系。高氯酸盐、硝酸盐和硫氰酸盐的共同暴露与代谢综合征风险呈正相关，高氯酸盐和硫氰酸盐对总体混合效应的贡献最大。
