University of Michigan School of Public Health, Department of Environmental Health Sciences, Ann Arbor, MI, United States.
University of Michigan School of Public Health, Department of Biostatistics, Ann Arbor, MI, United States.
Environ Res. 2021 Sep;200:111435. doi: 10.1016/j.envres.2021.111435. Epub 2021 Jun 10.
Studies on the health effects of metal mixtures typically utilize biomarkers measured in a single biological medium, such as blood or urine. However, the ability to evaluate mixture effects are limited by the uncertainty whether a unified medium can fully capture exposure for each metal. Therefore, it is important to compare and assess metal mixtures measured in different media in epidemiology studies.
The aim of this study was to examine the mixture predictive performance of urine and blood metal biomarkers and integrated multi-media biomarkers in association with birth outcomes.
In our analysis of 847 women from the Puerto Rico PROTECT Cohort, we measured 10 essential and non-essential metals in repeated and paired samples of urine and blood during pregnancy. For each metal, we integrated exposure estimates from paired urine and blood biomarkers into multi-media biomarkers (MMBs), using intraclass-correlation coefficient (ICC) and weighted quantile sum (WQS) approaches. Using Ridge regressions, four separate Environmental risk scores (ERSs) for metals in urine, blood, MMB, and MMB were computed as a weighted sum of the 10 metal concentrations. We then examined associations between urine, blood, and multi-media biomarker ERSs and birth outcomes using linear and logistic regressions, adjusting for maternal age, maternal education, pre-pregnancy body mass index (BMI), and second-hand smoke exposure. The performance of each ERS was evaluated with continuous and tertile estimates and 95% confidence intervals of the odds ratio of preterm birth using area under the curve (AUC).
Pb was the most important contributor of blood ERS as well as the two integrated multi-media biomarker ERSs. Individuals with high ERS (3rd tertile) showed increased odds of preterm birth compared to individuals with low ERS (1st tertile), with 2.8-fold (95% CI, 1.49 to 5.40) for urine (specific gravity corrected); 3.2- fold (95% CI, 1.68 to 6.25) for blood; 3.9-fold (95% CI, 1.72 to 8.66) for multi-media biomarkers composed using ICC; and 5.2-fold (95% CI, 2.34 to 11.42) for multi-media biomarkers composed using WQS. The four ERSs had comparable predictive performances (AUC ranging from 0.64 to 0.68) when urine is examined with specific gravity corrected concentrations.
Within a practical metal panel, measuring metals in either urine or blood may be an equally good approach to evaluate the metals as a mixture. Applications in practical study design require validation of these methods with other cohorts, larger panels of metals and within the context of other adverse health effects of interest.
研究金属混合物对健康的影响通常利用单一生物介质（如血液或尿液）中测量的生物标志物。然而，评估混合物效应的能力受到不确定性的限制，即统一的介质是否能够充分捕捉每种金属的暴露情况。因此，在流行病学研究中比较和评估不同介质中测量的金属混合物非常重要。
本研究旨在比较尿液和血液金属生物标志物以及综合多介质生物标志物在与出生结局相关方面的混合物预测性能。
在对来自波多黎各 PROTECT 队列的 847 名女性进行的分析中，我们在怀孕期间重复测量了尿液和血液中 10 种必需和非必需金属的配对样本。对于每种金属，我们使用内类相关系数（ICC）和加权分位数和（WQS）方法，将来自配对尿液和血液生物标志物的暴露估计值整合到多介质生物标志物（MMB）中。然后，我们使用线性和逻辑回归，在调整了母亲年龄、母亲教育程度、孕前体重指数（BMI）和二手烟暴露的情况下，分别使用尿液、血液、MMB 和 MMB 的环境风险评分（ERS）与出生结局进行了关联。使用曲线下面积（AUC）评估每个 ERS 的连续和三分位数估计值以及早产比值比的 95%置信区间。
Pb 是血液 ERS 以及两种综合多介质生物标志物 ERS 的最重要贡献者。与低 ERS（第 1 三分位）个体相比，高 ERS（第 3 三分位）个体的早产几率更高，尿液（比重校正）的比值比为 2.8 倍（95%置信区间，1.49 至 5.40）；血液为 3.2 倍（95%置信区间，1.68 至 6.25）；使用 ICC 组合的多介质生物标志物为 3.9 倍（95%置信区间，1.72 至 8.66）；使用 WQS 组合的多介质生物标志物为 5.2 倍（95%置信区间，2.34 至 11.42）。当使用比重校正的浓度检测尿液时，四个 ERS 具有相当的预测性能（AUC 范围为 0.64 至 0.68）。
在实际金属面板中，测量尿液或血液中的金属可能是评估金属混合物的同样好的方法。在实际研究设计中应用这些方法需要在其他队列、更大的金属面板以及其他感兴趣的不良健康影响的背景下进行验证。
