Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China.
Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China; Global Health Institute, Wuhan University, 185# Donghu Road, Wuhan 430072, China.
Sci Total Environ. 2022 Dec 10;851(Pt 2):158218. doi: 10.1016/j.scitotenv.2022.158218. Epub 2022 Aug 24.
The effects of environmental chemicals on insulin resistance have attracted extensive attention. Previous studies typically focused on the single chemical effects. This study adopted three different models to analyze the mixed effects of nine common chemicals (one phenol, two parabens, two chlorophenols and four phthalates) on insulin resistance.
Urinary concentrations of chemicals were extracted from National Health and Nutrition Examination Survey (NHANES) 2009-2016. Insulin resistance was assessed using homeostatic model assessment (HOMA) and defined as HOMA-IR >2.6. The generalized linear regression (GLM), weighted quantile sum regression (WQS) and Bayesian kernel machine regression models (BKMR) were applied to assess the relationship between chemical mixture and HOMA-IR or insulin resistance.
Of the 2067 participants included, 872 (42.19 %) were identified as insulin resistant. In single-chemical GLM model, di-2-ethylhexyl phthalate (DEHP) had the highest parameter (β/OR, 95 % CIs) of 0.21 (quartile 4, 0.12- 0.29) and 1.95 (quartile 4, 1.39- 2.74). Similar results were observed in the multi-chemical models, with DEHP (quartile 4) showing the positive relationship with HOMA-IR (0.18, 0.08- 0.28) and insulin resistance (1.76, 1.17- 2.64). According to WQS models, the WQS indices were significantly positively correlated with both HOMA-IR (β: 0.07, 95 % CI: 0.03- 0.12) and insulin resistance (OR: 1.25, 95 % CI: 1.03- 1.53). DEHP was the top-weighted chemical positively correlated with both HOMA-IR and insulin resistance. In the BKMR model, the joint effect was also positively correlated with both outcomes. DEHP remained the main contributor to the joint effect, consistent with WQS analysis.
Our findings suggested that these chemical mixtures had the positive joint effects on both HOMA-IR and insulin resistance, with DEHP being the potentially predominant driver. The inter-validation of the three models may indicate that reducing the DEHP concentration could improve glucose homeostasis and reduce the risk of insulin resistance. However, further studies are recommended to deepen our findings and elucidate the mechanisms of insulin resistance and chemical mixture.
环境化学物质对胰岛素抵抗的影响引起了广泛关注。先前的研究通常集中于单一化学物质的影响。本研究采用三种不同模型分析了九种常见化学物质(一种酚、两种对羟基苯甲酸酯、两种氯酚和四种邻苯二甲酸酯)对胰岛素抵抗的混合效应。
从 2009-2016 年国家健康和营养检查调查(NHANES)中提取化学物质的尿浓度。采用稳态模型评估(HOMA)评估胰岛素抵抗,将 HOMA-IR>2.6 定义为胰岛素抵抗。应用广义线性回归(GLM)、加权分位数总和回归(WQS)和贝叶斯核机器回归模型(BKMR)评估化学混合物与 HOMA-IR 或胰岛素抵抗之间的关系。
在纳入的 2067 名参与者中,872 名(42.19%)被确定为胰岛素抵抗。在单化学 GLM 模型中,邻苯二甲酸二(2-乙基己基)酯(DEHP)的参数(β/OR,95%置信区间)最高,为 0.21(四分位数 4,0.12-0.29)和 1.95(四分位数 4,1.39-2.74)。在多化学物质模型中也观察到了类似的结果,DEHP(四分位数 4)与 HOMA-IR(0.18,0.08-0.28)和胰岛素抵抗(1.76,1.17-2.64)呈正相关。根据 WQS 模型,WQS 指数与 HOMA-IR(β:0.07,95%CI:0.03-0.12)和胰岛素抵抗(OR:1.25,95%CI:1.03-1.53)均呈显著正相关。DEHP 是与 HOMA-IR 和胰岛素抵抗均呈正相关的最重要的加权化学物质。在 BKMR 模型中,联合效应也与两种结果呈正相关。DEHP 仍然是联合效应的主要贡献者,与 WQS 分析一致。
我们的研究结果表明,这些化学混合物对 HOMA-IR 和胰岛素抵抗均有正向的联合效应,其中 DEHP 可能是主要驱动因素。三种模型的相互验证可能表明,降低 DEHP 浓度可以改善葡萄糖稳态并降低胰岛素抵抗的风险。但是,建议进行进一步的研究以深化我们的发现并阐明胰岛素抵抗和化学混合物的机制。