Hasan Nishat Tasnim, Xu Xiaohui, Han Daikwon, Sansom Garett, Roh Taehyun
Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX 77843, USA.
Department of Environmental and Occupational Health, Texas A&M School of Public Health, College Station, TX 77843, USA.
J Trace Elem Med Biol. 2024 Dec;86:127559. doi: 10.1016/j.jtemb.2024.127559. Epub 2024 Nov 7.
Chronic arsenic exposure is known to be associated with various diseases by inducing multiple organ dysfunctions. Despite the high prevalence of kidney diseases in the US and globally, population-level research on the link between inorganic arsenic and kidney damage remains limited. In our study, we assessed the association between urinary arsenic levels and kidney damage among US adults using a multi-marker approach.
We analyzed data from the National Health and Nutrition Examination Survey (2007-2018). Multivariable logistic regression models were employed to estimate the odds ratios (ORs) for kidney damage based on total urinary arsenic levels and multiple kidney biomarkers, including albuminuria, low estimated glomerular filtration rate (eGFR), hyperuricemia, and elevated blood urea nitrogen (BUN), while adjusting for demographic, socioeconomic, and other risk factors. Total urinary arsenic levels were calculated by summing the levels of arsenous acid (As3), arsenic acid (As5), and their methylated metabolites, monomethylarsinic acid (MMA), and dimethylarsinic acid (DMA). Dimethylarsinic acid (DMA) was calibrated for arsenobetaine using a residual regression method to minimize the influence of seafood-related exposure.
After adjusting for covariates, we observed 1.29-fold higher odds (95 % CI 1.01, 1.64) of kidney damage in the highest quartile of urinary arsenic compared to the lowest quartile. Specifically, the odds of albuminuria and hyperuricemia were 1.49-fold (95 % CI 1.09, 2.03) and 1.38-fold (95 % CI 1.01, 1.88) higher, respectively, in the highest quartile. Additionally, for every one-unit increase in the natural log of arsenic levels, significant associations were observed for overall kidney damage (OR 1.10, 95 % CI 1.01, 1.20), albuminuria (OR 1.15, 95 % CI 1.03, 1.29), and hyperuricemia (OR 1.12, 95 % CI 1.02, 1.24) when considering arsenic levels in drinking water as a continuous variable.
Our study concludes that higher urinary arsenic levels are positively associated with kidney damage. Further prospective studies are needed to confirm these findings.
已知慢性砷暴露会通过引发多器官功能障碍而与多种疾病相关。尽管在美国和全球范围内肾脏疾病的患病率都很高，但关于无机砷与肾脏损害之间联系的人群水平研究仍然有限。在我们的研究中，我们使用多标记方法评估了美国成年人尿砷水平与肾脏损害之间的关联。
我们分析了来自国家健康与营养检查调查（2007 - 2018年）的数据。采用多变量逻辑回归模型，基于尿总砷水平和多种肾脏生物标志物（包括蛋白尿、低估算肾小球滤过率（eGFR）、高尿酸血症和血尿素氮（BUN）升高）来估计肾脏损害的比值比（OR），同时对人口统计学、社会经济和其他风险因素进行调整。尿总砷水平通过将亚砷酸（As3）、砷酸（As5）及其甲基化代谢产物一甲基胂酸（MMA）和二甲基胂酸（DMA）的水平相加来计算。使用残差回归方法对二甲基胂酸（DMA）进行校准以消除砷甜菜碱的影响，从而将海鲜相关暴露的影响降至最低。
在调整协变量后，我们观察到尿砷最高四分位数组的肾脏损害几率比最低四分位数组高1.29倍（95%可信区间1.01, 1.64）。具体而言，最高四分位数组中蛋白尿和高尿酸血症的几率分别高1.49倍（95%可信区间1.09, 2.03）和1.38倍（95%可信区间1.01, 1.88）。此外，当将饮用水中的砷水平作为连续变量考虑时，砷水平的自然对数每增加一个单位，在总体肾脏损害（OR 1.10, 95%可信区间1.01, 1.20）、蛋白尿（OR 1.15, 95%可信区间1.03, 1.29）和高尿酸血症（OR 1.12, 95%可信区间1.02, 1.24）方面均观察到显著关联。
我们的研究得出结论，较高的尿砷水平与肾脏损害呈正相关。需要进一步的前瞻性研究来证实这些发现。
