Adjusted Urinary Metal Concentrations and Regional Air Pollution Data from the Swiss Plateau (2016–2019)

This dataset contains covariate-adjusted urinary metal concentrations from 276 patients who underwent standardized provoked metal excretion testing between January 2016 and November 2019 in central Switzerland, along with time-lagged regional air pollution data. All patients lived within a 60 km radius of our clinic in the Swiss Plateau (Mittelland), a densely populated region between the Jura and the Alps. The study was initiated following a noticeable spike in urinary uranium concentrations in spring 2017, coinciding with elevated fine dust levels and increased heating activity. Air pollution data — including PM₁₀, PM₂.₅, indirectly calculated PM₁₀–₂.₅, elemental carbon (EC), NO₂, SO₂, and CO — were retrieved from the NABEL station Zurich-Kaserne, located approximately 27 km (17 miles) from the clinic. This site was selected as the primary exposure reference due to its comprehensive and uninterrupted dataset. Given the strong synchrony of pollutant levels across official Swiss Plateau NABEL stations, confirmed by heatmap correlations (see sheet "PM10 NABEL Swiss Plateau Correl"), Zurich-Kaserne is considered representative of regional air quality for the entire patient cohort. <br><br><br>README <br>File: AP–Metals–Adjusted–DDI–PM2.5–Imputed.xlsx This Excel file contains fully processed data for environmental toxicology research, including covariate-adjusted urinary metal concentrations, lagged air pollution exposure (Lag 0 to -26), and inter-site PM₁₀ correlations. <br><br>Sheet Overview: <br><br>PM10 NABEL Swiss Plateau Correl: Spearman correlation matrix showing inter-site PM₁₀ synchrony across the Swiss Plateau. <br><br>Main pollutant sheets (e.g., PM10, PM2.5, EC, etc.): Exam date 27 lagged pollutant values (14-day means) <br><br>Patient metadata (age, sex, CRN) Fully adjusted metal values (log-transformed, age/CRN-corrected, sex-specific residuals, Yeo-Johnson transformed) <br><br>Preprocessing Summary: Creatinine values adjusted to age 50 (CRN50) using sex-specific formulas from &gt;1600 provoked urine samples. <br><br>Exclusion criteria: CRN50 &lt; 0.15 or &gt; 3.5 g/L; Aluminum/CRN &gt; 140 µg/g (to minimize dilution bias and iatrogenic contamination). <br><br>Imputation: Uranium, Bismuth: Uniform imputation in [DL/3, DL] Other metals: MICE with age, CRN, and other metal concentrations (if Al/CRN &lt; 140). Log-transformation of metals, covariate adjustment via linear regression (logCRN50, age), and sex-specific Yeo-Johnson transformation.<br>PM₂.₅ imputed using ridge regression (predictors: PM₁₀, EC, NO₂, SO₂, CO for the same lag). PM₁₀–₂.₅ calculated as PM₁₀ minus imputed PM₂.₅; not imputed separately.本数据集包含2016年1月至2019年11月期间，在瑞士中部接受标准化金属排泄激发试验的276名患者的协变量校正后尿液金属浓度数据，以及时滞区域空气污染数据。所有患者均居住于瑞士高原（Mittelland，汝拉山脉与阿尔卑斯山脉之间的人口稠密区域）内距离本诊所60公里半径范围内。本研究启动于2017年春季，当时患者尿液铀浓度出现显著升高，同时伴随细颗粒物浓度上升与采暖活动增加。 空气污染数据涵盖PM₁₀、PM₂.₅、间接计算得到的PM₁₀–₂.₅、元素碳(EC)、NO₂、SO₂及CO，均从距离诊所约27公里（17英里）的苏黎世军营(NABEL)监测站获取。该站点因拥有完整且无间断的数据集而被选为主要暴露参考位点。鉴于瑞士高原官方NABEL监测站之间的污染物浓度具有高度同步性，该结论已通过热图相关性分析验证（详见工作表"PM10 NABEL Swiss Plateau Correl"），因此苏黎世军营监测站可代表整个患者队列的区域空气质量。 README 文件：AP–Metals–Adjusted–DDI–PM2.5–Imputed.xlsx 本Excel文件包含用于环境毒理学研究的全流程处理数据，涵盖协变量校正后的尿液金属浓度、时滞空气污染暴露数据（滞后阶数0至-26）以及站点间PM₁₀相关性数据。 工作表说明： PM10 NABEL Swiss Plateau Correl：斯皮尔曼相关系数矩阵，展示瑞士高原各监测站PM₁₀浓度的同步性。 主要污染物工作表（如PM10、PM2.5、EC等）：包含检查日期对应的27组时滞污染物值（14日均值）。 患者元数据（年龄、性别、肌酐(Creatinine, CRN)）；经全面校正的金属浓度值：经对数转换、年龄/肌酐校正、性别特异性残差处理及Yeo-Johnson变换。 预处理总结：基于超过1600份激发尿液样本的性别特异性公式，将肌酐值校正至50岁标准值（CRN50）。 排除标准：CRN50小于0.15或大于3.5 g/L；尿铝/肌酐比值大于140 µg/g，以最小化稀释偏差与医源性污染。 插补方案：铀、铋：采用[检测限(Detection Limit, DL)/3, 检测限(Detection Limit, DL)]区间内的均匀分布插补；其余金属：采用多重链式方程插补(Multiple Imputation by Chained Equations, MICE)，以年龄、CRN及其他金属浓度为预测变量（仅当铝/肌酐比值小于140时）。对金属浓度进行对数转换，通过线性回归（以logCRN50、年龄为协变量）完成协变量校正，并进行性别特异性Yeo-Johnson变换。 PM₂.₅采用岭回归进行插补，预测变量为同一滞后阶数下的PM₁₀、EC、NO₂、SO₂及CO浓度。PM₁₀–₂.₅通过PM₁₀减去插补后的PM₂.₅计算得到，未单独进行插补。