OBJECTIVE Metal and metalloid exposures (hereafter "metals") are associated with adverse health outcomes, including type 2 diabetes; however, previous studies were largely cross- sectional or underpowered. Furthermore, underserved racial/ethnic groups are underrepresented in environmental health research despite having higher rates of type 2 diabetes and a greater risk of metal exposures. Consequently, we evaluated continuous glycemic traits in relation to baseline urinary toxic metal, essential metal, and metal mixtures in a cohort of Mexican American adults. RESEARCH DESIGN AND METHODS A total of 510 participants were selected based upon self-reported diabetes status and followed over 3 years. Urinary metals were assessed at baseline. Linear mixed-effects models were used to estimate per-month changes in hemoglobin A1c, fasting plasma glucose, and postload glucose in relation to urinary metal levels. Multiple statistical approaches were used to assess the associations between glycemic traits and metal mixtures. RESULTS After adjustment, higher urinary levels of arsenic, selenium, copper, molybdenum, nickel, and tin were associated with faster increases in measures of glycemia. The toxic metal mixture composed of arsenic, lead, cadmium, nickel, and tin was associated with faster increases in postload glucose. Using postload glucose criteria, highest versus lowest arsenic was predicted to accelerate conversion of normoglycemia to prediabetes and diabetes by 23 and 65 months, respectively. CONCLUSIONS In this underrepresented, high-risk Mexican American population, exposure to toxic metals and alterations in essential metal homeostasis were associated with faster increases in glycemia over time that may accelerate type 2 diabetes development.

中文翻译：

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居住在德克萨斯州斯塔尔县的墨西哥裔美国人与尿液毒性/必需金属和金属混合物相关的纵向血糖变化加速


目的 金属和准金属暴露（以下简称“金属”）与不良健康结果相关，包括 2 型糖尿病;然而，以前的研究主要是横断面的或把握度不足。此外，尽管 2 型糖尿病的发病率较高且金属暴露风险较高，但服务不足的种族/族裔群体在环境健康研究中代表性不足。因此，我们评估了一组墨西哥裔美国成年人与基线尿毒性金属、必需金属和金属混合物相关的连续血糖特征。研究设计和方法 根据自我报告的糖尿病状况共选择了 510 名参与者，并进行了 3 年以上的随访。在基线时评估尿金属。线性混合效应模型用于估计血红蛋白 A1c 、空腹血糖和负荷后血糖与尿金属水平相关的每月变化。使用多种统计方法来评估血糖特征与金属混合物之间的关联。结果 调整后，尿液中砷、硒、铜、钼、镍和锡水平升高与血糖指标的快速升高有关。由砷、铅、镉、镍和锡组成的有毒金属混合物与负荷后葡萄糖的快速增加有关。使用负荷后血糖标准，预计最高砷与最低砷分别会加速正常血糖向糖尿病前期和糖尿病的转化 23 个月和 65 个月。结论 在这个代表性不足的高危墨西哥裔美国人群体中，暴露于有毒金属和必需金属稳态的改变与随着时间的推移血糖的快速增加有关，这可能会加速 2 型糖尿病的发展。