Radioimmunity Center, Shaanxi Provincial People's Hospital, Xi'an, 710069, Shaanxi, P.R. China.
School of Public Health, Ningxia Medical University, Yinchuan, 750004, Ningxia, P.R. China; Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan, 750004, Ningxia, P.R. China.
Ecotoxicol Environ Saf. 2024 Jan 15;270:115828. doi: 10.1016/j.ecoenv.2023.115828. Epub 2023 Dec 20.
Anemia seriously affects the health and quality of life of the older adult population and may be influenced by various types of environmental metal exposure. Current studies on metals and anemia are mainly limited to single metals, and the association between polymetals and their mixtures and anemia remains unclear.
We determined 11 urinary metal concentrations and hemoglobin levels in 3781 participants. Binary logistic regression and restricted cubic spline (RCS) model were used to estimate the association of individual metals with anemia. We used Bayesian kernel machine regression (BKMR) and Quantile g-computation (Q-g) regression to assess the overall association between metal mixtures and anemia and identify the major contributing elements. Stratified analyses were used to explore the association of different metals with anemia in different populations.
In a single-metal model, nine urinary metals significantly associated with anemia. RCS analysis further showed that the association of arsenic (As) and copper (Cu) with anemia was linear, while cobalt, molybdenum, thallium, and zinc were non-linear. The BKMR model revealed a significant positive association between the concentration of metal mixtures and anemia. Combined Q-g regression analysis suggested that metals such as Cu, As, and tellurium (Te) were positively associated with anemia, with Te as the most significant contributor. Stratified analyses showed that the association of different metals with anemia varied among people of different sexes, obesity levels, lifestyle habits, and blood pressure levels.
Multiple metals are associated with anemia in the older adult population. A significant positive association was observed between metal mixture concentrations and anemia, with Te being the most important factor. The association between urinary metal concentrations and anemia is more sensitive in the non-hypertensive populations.
贫血严重影响老年人的健康和生活质量，可能受到各种类型环境金属暴露的影响。目前关于金属和贫血的研究主要局限于单一金属，多金属及其混合物与贫血之间的关系尚不清楚。
我们在 3781 名参与者中测定了 11 种尿金属浓度和血红蛋白水平。采用二项逻辑回归和限制立方样条（RCS）模型来估计个体金属与贫血的关联。我们采用贝叶斯核机器回归（BKMR）和分位数 g 计算（Q-g）回归来评估金属混合物与贫血的整体关联，并确定主要贡献元素。分层分析用于探讨不同人群中不同金属与贫血的关联。
在单金属模型中，有 9 种尿金属与贫血显著相关。RCS 分析进一步表明，砷（As）和铜（Cu）与贫血的关联呈线性，而钴、钼、铊和锌呈非线性。BKMR 模型显示金属混合物浓度与贫血之间存在显著正相关。结合 Q-g 回归分析表明，Cu、As 和碲（Te）等金属与贫血呈正相关，其中 Te 的贡献最大。分层分析表明，不同金属与贫血的关联在不同性别、肥胖水平、生活方式习惯和血压水平的人群中存在差异。
多种金属与老年人群贫血相关。金属混合物浓度与贫血之间存在显著正相关，Te 是最重要的因素。在非高血压人群中，尿金属浓度与贫血的关联更为敏感。
