Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang 050017, PR China.
Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China.
Ecotoxicol Environ Saf. 2024 Oct 1;284:116981. doi: 10.1016/j.ecoenv.2024.116981. Epub 2024 Sep 3.
Metal exposure has been reported to be associated with metabolic syndrome (MetS), however, the evidence remains inconclusive, particularly in elderly individuals. From May to July 2016, serum levels of 16 metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) in 852 elderly individuals (≥65 years) residing in Wuhan, China. Biological detection and disease recognition were based on individual surveys conducted during health check-ups. Spearman's rank correlation analysis was performed to identify the correlation among serum metals. The data were Ln-transformed to fit a normal distribution for further analyses. Linear and logistic regression were applied to explore the associations between metals and diseases. Restricted cubic spline (RCS) analysis was utilized to examine dose-response relationships. The Weighted Quantile Sum (WQS) score was applied to determine the empirical weights of each heavy metal in the context of their combined effect on metabolic diseases. The prevalence of MetS, hypertension, diabetes, and hyperlipidemia were 46.36 %, 68.90 %, 24.65 %, and 21.60 %, respectively. Serum metal mixture was positively associated with the prevalence of MetS (OR = 1.92, 95 % CI: 1.30-2.82), hypertension (OR = 1.50, 95 % CI: 1.01-2.23), and diabetes (OR = 2.18, 95 % CI: 1.48-3.22). In single metal models, we found that serum zinc levels were associated with an increased risk of MetS, while rubidium had a protective effect against MetS. Interestingly, different metals had distinct effects on specific diseases in this study: lithium and barium were more likely to influence blood pressure, while selenium had a more significant effect on blood glucose. Lipids were more susceptible to the effects of zinc, selenium, and strontium. Platelet count (PLT) and lymphocyte count (LYM) mediated the association between selenium exposure and hyperlipidemia, while neutrophil count (NEU) mediated the relationship between serum rubidium exposure and MetS. Our findings offer valuable etiological insights into the relationship between serum heavy metals and the prevalence of MetS, suggesting that peripheral blood cells may play a mediating role in this association.
金属暴露与代谢综合征(MetS)有关,然而,证据仍然不确定,特别是在老年人中。2016 年 5 月至 7 月,采用电感耦合等离子体质谱法(ICP-MS)对居住在中国武汉的 852 名老年人(≥65 岁)的血清 16 种金属水平进行了测量。生物检测和疾病识别是基于健康检查期间进行的个体调查。采用 Spearman 秩相关分析来确定血清金属之间的相关性。对数据进行 Ln 转换以适应正态分布,以便进一步分析。线性和逻辑回归用于探索金属与疾病之间的关系。限制性立方样条(RCS)分析用于检查剂量-反应关系。加权数量和总和(WQS)评分用于确定在代谢疾病方面,每种重金属的综合效应的经验权重。MetS、高血压、糖尿病和高脂血症的患病率分别为 46.36%、68.90%、24.65%和 21.60%。血清金属混合物与 MetS 的患病率呈正相关(OR=1.92,95%CI:1.30-2.82)、高血压(OR=1.50,95%CI:1.01-2.23)和糖尿病(OR=2.18,95%CI:1.48-3.22)。在单一金属模型中,我们发现血清锌水平与 MetS 风险增加有关,而铷则对 MetS 有保护作用。有趣的是,在这项研究中,不同的金属对特定疾病有不同的影响:锂和钡更容易影响血压,而硒对血糖的影响更为显著。脂质更容易受到锌、硒和锶的影响。血小板计数(PLT)和淋巴细胞计数(LYM)介导了硒暴露与高脂血症之间的关联,而中性粒细胞计数(NEU)介导了血清铷暴露与 MetS 之间的关系。我们的研究结果为血清重金属与 MetS 患病率之间的关系提供了有价值的病因学见解,表明外周血细胞可能在这种关联中发挥中介作用。