Abstract
This study provides background levels for five arsenic species in urine, based on urinary data obtained from 95 nonoccupationally exposed volunteers based in the UK. Using a novel, sensitive, robust and reliable speciation methodology, five species of arsenic (arsenobetaine [AB], arsenite [As(3+)], arsenate [As(5+)], monomethylarsonic acid [MMA(5+)] and dimethylarsinic acid [DMA(5+)]) were determined in urine samples collected from 95 adults. The analytical instrumentation used to analyze the urine samples was a hyphenated micro liquid chromatography (μLC) system coupled to an inductively coupled plasma mass spectrometry (ICP-MS). Separation was achieved using an anion exchange micro-sized column. The results presented give the 95th percentile of concentrations, both uncorrected for creatinine (µg/L) and creatinine corrected (µmol/mol) in urine for the 95 volunteers. Statistical analysis was performed on the dataset using a Bayesian model to determine and quantify effects of gender, smoking and diet. The statistical results show that the consumption of fish, shellfish and red wine has a significant elevating effect on AB, DMA and MMA urinary concentrations; however, no significant effect was observed for smoking. The regression model results indicate that creatinine correction was effective for arsenic species As(3+), MMA, DMA and AB. The background levels established here can be used as reference values to help aid interpretation of arsenic speciation results and better assess exposure.