Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University School of Medicine, Washington, DC 20007, USA.
Center for Epidemiology and Environmental Health (CEOH, LLC), Washington, DC 20016, USA.
Int J Environ Res Public Health. 2020 Feb 4;17(3):960. doi: 10.3390/ijerph17030960.
Although inorganic arsenic in drinking water at high levels (100s-1000s μg/L [ppb]) increases cancer risk (skin, bladder, lung, and possibly prostate), the evidence at lower levels is limited. : We conducted an ecologic analysis of the dose-response relationship between prostate cancer incidence and low arsenic levels in drinking water in a large study of U.S. counties ( = 710). County arsenic levels were <200 ug/L with median <100 ug/L and dependency greater than 10%. Groundwater well usage, water arsenic levels, prostate cancer incidence rates (2009-2013), and co-variate data were obtained from various U.S. governmental agencies. Poisson and negative-binomial regression analyses and stratified analysis were performed. : The best fitting polynomial analysis yielded a J-shaped linear-quadratic model. Linear and quadratic terms were significant ( < 0.001) in the Poisson model, and the quadratic term was significant ( < 0.05) in the negative binomial model. This model indicated a decreasing risk of prostate cancer with increasing arsenic level in the low range and increasing risk above. : This study of prostate cancer incidence in US counties with low levels of arsenic in their well-water arsenic levels finds a j-shaped model with decreasing risk at very low levels and increasing risk at higher levels.
虽然高浓度(100-1000μg/L[ppb])的饮用水无机砷会增加癌症风险(皮肤癌、膀胱癌、肺癌,可能还有前列腺癌),但低浓度下的证据有限。我们在美国的一个大型县(710 个)研究中,对饮用水中低浓度砷与前列腺癌发病率之间的剂量反应关系进行了生态分析。县砷浓度<200μg/L,中位数<100μg/L,依赖性>10%。地下水井的使用情况、水砷水平、前列腺癌发病率(2009-2013 年)和协变量数据均来自美国各政府机构。进行了泊松和负二项式回归分析和分层分析。最佳拟合多项式分析得出了线性二次模型的 J 形。泊松模型中线性和二次项均具有统计学意义(<0.001),负二项式模型中二次项具有统计学意义(<0.05)。该模型表明,在低浓度范围内,砷水平升高与前列腺癌风险降低有关,而在较高浓度范围内,砷水平升高与前列腺癌风险升高有关。本研究对美国县的前列腺癌发病率进行了研究,这些县的井水砷水平较低,发现了一个 J 形模型,表明极低浓度下风险降低,而较高浓度下风险增加。