李悦, 王焕强, 张美辨, 倪春辉. 电焊工金属混合暴露与肺功能关联:基于多污染物统计模型[J]. 环境与职业医学, 2024, 41(3): 251-258. DOI: 10.11836/JEOM23322
引用本文: 李悦, 王焕强, 张美辨, 倪春辉. 电焊工金属混合暴露与肺功能关联:基于多污染物统计模型[J]. 环境与职业医学, 2024, 41(3): 251-258. DOI: 10.11836/JEOM23322
LI Yue, WANG Huanqiang, ZHANG Meibian, NI Chunhui. Association between exposure to multiple metals and lung function in welders by multi-pollutant statistical models[J]. Journal of Environmental and Occupational Medicine, 2024, 41(3): 251-258. DOI: 10.11836/JEOM23322
Citation: LI Yue, WANG Huanqiang, ZHANG Meibian, NI Chunhui. Association between exposure to multiple metals and lung function in welders by multi-pollutant statistical models[J]. Journal of Environmental and Occupational Medicine, 2024, 41(3): 251-258. DOI: 10.11836/JEOM23322

电焊工金属混合暴露与肺功能关联:基于多污染物统计模型

Association between exposure to multiple metals and lung function in welders by multi-pollutant statistical models

  • 摘要: 背景

    电焊工接触含多种金属的电焊烟尘引起肺功能下降,既往研究多集中于单一金属与肺功能间的关联,较少关注到金属混合暴露的肺功能健康损害。

    目的

    本研究旨在评估电焊工尿液和血液中多种金属浓度与肺功能指标间的关联,探讨影响肺功能的关键金属成分,为职业健康风险评估提供参考依据。

    方法

    对上海市某造船厂电焊工和对照组工人进行问卷调查、肺功能检测,并收集尿液和血液样本。采用电感耦合等离子体质谱法(ICP-MS)检测尿液和血液中钒、铬、锰等12种金属浓度。Spearman相关用于分析血液、尿液中金属间的关联性。应用多重线性回归、加权分位数之和回归(WQS)和贝叶斯核机器回归(BKMR)剖析金属混合暴露与肺功能指标用力肺活量(FVC)、用力肺活量占预计值百分比(FVC%)、第1秒用力呼气容积(FEV1)、第1秒用力呼气容积占预计值百分比(FEV1%)和一秒率(FEV1/FVC)间的关系。

    结果

    本研究共纳入445名工人,焊工组322人(72.36%),对照组123人(27.64%),总人群平均年龄为(37.64±8.80)岁,87.19%为男性。电焊工尿镉(0.88 vs 0.58 μg·L−1)以及血铬(5.86 vs 5.06 μg·L−1)、锰(24.24 vs 21.38 μg·L−1)浓度均显著高于对照组(P<0.05)。Spearman相关结果显示尿液和血液中金属元素间相关系数范围为−0.46~0.68。在校正混杂因素后,多重线性回归结果提示电焊工尿钼与FVC、FEV1间呈负相关;血钼与FVC、FVC%、FEV1、FEV1%以及血铜与FEV1/FVC间呈负相关。WQS结果表明电焊工血液、尿液金属混合浓度每增加1个四分位数水平,FEV1、FVC分别平均下降0.112 L、0.353 L,铜、锌、钒、锑等金属贡献较大。BKMR显示电焊工血液、尿液中金属浓度与FVC、FVC%、FEV1、FEV1%间呈下降趋势,单变量暴露反应-关系中血液、尿液钼浓度与FVC、FVC%、FEV1、FEV1大致呈线性下降趋势;电焊工尿液中不同金属作用于FEV1%时,镉与锰、镍、钒间,钒与铁、钼、锌、铜间可能具有交互作用。

    结论

    多金属混合暴露引起电焊工肺功能下降,贡献较大的金属有钼、锑、铜和锌等。

     

    Abstract: Background

    Welders' exposure to welding fumes with multiple metals leads to decreased pulmonary function. Previous studies have focused on single metal exposure, while giving little attention to the impact of metal mixtures.

    Objective

    To assess the association between metal levels in urine and blood of welders and pulmonary function indicators, and to identify key metals for occupational health risk assessment.

    Methods

    Questionnaire surveys, lung function tests, urine and blood sampling were conducted among welders and control workers in a shipyard in Shanghai. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect the concentrations of 12 metals such as vanadium, chromium, and manganese in urine and blood. Spearman correlation was applied to analyze the correlations between the metals in urine and blood. Multiple linear regression, weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) were used to analyze the relationships between mixed metal exposure and pulmonary function parameters, such as forced vital capacity (FVC), forced vital capacity as a percentage of predicted value (FVC%), forced expiratory volume in the first second (FEV1), forced expiratory volume in the first second as a percentage of predicted value (FEV1%), and forced expiratory volume in the first second/forced vital capacity (FEV1/FVC).

    Results

    This study enrolled 445 subjects, including 322 welders (72.36%) and 123 controls (27.64%). The mean age of the 445 participants was (37.64±8.80) years, and 87.19% participants were male. The welders had significantly higher levels of urinary cadmium (0.88 vs 0.58 μg·L−1), blood chromium (5.86 vs 5.06 μg·L−1), and blood manganese (24.24 vs 21.38 μg·L−1) than the controls (P<0.05). The Spearman correlation coefficients between the metals in urine and blood ranged from −0.46 to 0.68. After adjustment for confounders, the multiple linear regression indicted that the urine molybdenum of the welders was negatively correlated with FVC and FEV1. There were also negative correlations between the molybdenum in blood and FVC, FVC%, FEV1, and FEV1%, and between the copper in blood and FEV1/FVC. The WQS model showed that FEV1 and FVC decreased by 0.112 L and 0.353 L with each quartile increase of metal mixture concentrations in urine and blood among the welders respectively, and the leading contributors were copper, zinc, vanadium, and antimony. The BKMR model showed a negative overall effect of metal mixtures in urine and blood among the welders on FVC, FVC%, FEV1, and FEV1%, and the univariate exposure response-relationship between the molybdenum concentration in urine or blood and FVC, FVC%, FEV1, or FEV1% had an approximately linear decreasing trend. Meanwhile, there may be an interaction of cadmium with manganese, nickel, or vanadium, and an interaction of vanadium with iron, molybdenum, zinc, or copper, when different metals in urine among the welders interacted with FEV1%.

    Conclusion

    Exposure to multiple metals in welders leads to a decline in lung function, with molybdenum, antimony, copper, and zinc as the leading contributors.

     

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