Melissa J. Slotnick

Geostatistical modeling of the spatial variability of arsenic in groundwater of southeast Michigan

During the last decade one has witnessed an increasing interest in assessing healthrisks caused by exposure to contaminants present in the soil, air, and water. A keycomponent of any exposure study is a reliable model for the space-time distribution ofpollutants. This paper compares the performances of multi-Gaussian and indicator krigingfor modeling probabilistically the spatial distribution of arsenic concentrations ingroundwater of southeast Michigan, accounting for arsenic data collected at privateresidential wells and the hydrogeochemistry of the area. The arsenic data set, which wasprovided by the Michigan Department of Environmental Quality (MDEQ), includesmeasurements collected between 1993 and 2002 at 8212 different wells. Factorial krigingwas used to filter the short-range spatial variability in arsenic concentration, leading to asignificant increase (17–65%) in the proportion of variance explained by secondaryinformation, such as type of unconsolidated deposits and proximity to Marshall Sandstonesubcrop. Cross validation of well data shows that accounting for this regional backgrounddoes not improve the local prediction of arsenic, which reveals the presence ofunexplained sources of variability and the importance of modeling the uncertaintyattached to these predictions. Slightly more precise models of uncertainty were obtainedusing indicator kriging. Well data collected in 2004 were compared to the predictionmodelandbestresultswerefoundforsoftindicatorkrigingwhichhasameanabsoluteerrorof 5.6 mg/L. Although this error is large with respect to the USEPA standard of 10 mg/L,it is smaller than the average difference (12.53 mg/L) between data collected at the samewell and day, as reported in the MDEQ data set. Thus the uncertainty attached to thesampled values themselves, which arises from laboratory errors and lack of informationregarding the sample origin, contributes to the poor accuracy of the geostatisticalpredictions in southeast Michigan.

Toenails as a Biomarker of Inorganic Arsenic Intake From Drinking Water and Foods

Toenails were used recently in epidemiological and environmental health studies as a means of assessing exposure to arsenic from drinking water. While positive correlations between toenail and drinking-water arsenic concentrations were reported in the literature, a significant percentage of the variation in toenail arsenic concentration remains unexplained by drinking-water concentration alone. Here, the influence of water consumption at home and work, food intake, and drinking-water concentration on toenail arsenic concentration was investigated using data from a case-control study being conducted in 11 counties of Michigan. The results from 440 controls are presented. Log-transformed drinking-water arsenic concentration at home was a significant predictor (p < .05) of toenail arsenic concentration (R 2 = .32). When arsenic intake from consumption of tap water and beverages made from tap water (μg/L arsenic × L/d = μg/d) was used as a predictor variable, the correlation was markedly increased for individuals with >1 μg/L arsenic (R 2 = .48). Increased intake of seafood and intake of arsenic from water at work were independently and significantly associated with increased toenail arsenic concentration. However, when added to intake at home, work drinking-water exposure and food intake had little influence on the overall correlation. These results suggest that arsenic exposure from drinking-water consumption is an important determinant of toenail arsenic concentration, and therefore should be considered when validating and applying toenails as a biomarker of arsenic exposure.

Improving exposure assessment in environmental epidemiology: Application of spatio-temporal visualization tools

Abstract.A thorough assessment of human exposure to environmental agents should incorporate mobility patterns and temporal changes in human behaviors and concentrations of contaminants; yet the temporal dimension is often under-emphasized in exposure assessment endeavors, due in part to insufficient tools for visualizing and examining temporal datasets. Spatio-temporal visualization tools are valuable for integrating a temporal component, thus allowing for examination of continuous exposure histories in environmental epidemiologic investigations. An application of these tools to a bladder cancer case-control study in Michigan illustrates continuous exposure life-lines and maps that display smooth, continuous changes over time. Preliminary results suggest increased risk of bladder cancer from combined exposure to arsenic in drinking water (>25 μg/day) and heavy smoking (>30 cigarettes/day) in the 1970s and 1980s, and a possible cancer cluster around automotive, paint, and organic chemical industries in the early 1970s. These tools have broad application for examining spatially- and temporally-specific relationships between exposures to environmental risk factors and disease.

Urinary arsenic species, toenail arsenic, and arsenic intake estimates in a Michigan population with low levels of arsenic in drinking water.

The large disparity between arsenic concentrations in drinking water and urine remains unexplained. This study aims to evaluate predictors of urinary arsenic in a population exposed to low concentrations (≤50 μg/l) of arsenic in drinking water. Urine and drinking water samples were collected from a subsample (n=343) of a population enrolled in a bladder cancer case–control study in southeastern Michigan. Total arsenic in water and arsenic species in urine were determined using ICP-MS: arsenobetaine (AsB), arsenite (As[III]), arsenate (As[V]), methylarsenic acid (MMA[V]), and dimethylarsenic acid (DMA[V]). The sum of As[III], As[V], MMA[V], and DMA[V] was denoted as SumAs. Dietary information was obtained through a self-reported food intake questionnaire. Log10-transformed drinking water arsenic concentration at home was a significant (P<0.0001) predictor of SumAs (R2=0.18). Associations improved (R2=0.29, P<0.0001) when individuals with less than 1 μg/l of arsenic in drinking water were removed and further improved when analyses were applied to individuals who consumed amounts of home drinking water above the median volume (R2=0.40, P<0.0001). A separate analysis indicated that AsB and DMA[V] were significantly correlated with fish and shellfish consumption, which may suggest that seafood intake influences DMA[V] excretion. The Spearman correlation between arsenic concentration in toenails and SumAs was 0.36 and between arsenic concentration in toenails and arsenic concentration in water was 0.42. Results show that arsenic exposure from drinking water consumption is an important determinant of urinary arsenic concentrations, even in a population exposed to relatively low levels of arsenic in drinking water, and suggest that seafood intake may influence urinary DMA[V] concentrations.

Profiles of trace elements in toenails of Arab-Americans in the Detroit area, Michigan.

Exposure to environmental contaminants is complicated by factors related to socioeconomic status, diet, and other culturally conditioned risk behaviors. Determination of a trace element profile in toenails can be used as a tool in biomonitoring the exposure history or assessing the deficiency of a particular element in a study population, which can lead to a better understanding of environmental and disease risks. Toenail clippings from 259 Arab Americans (163 adults, 96 children) residing in a highly industrialized area were analyzed for Al, V, Cr, Mn, Co, Ni, Cu, As, Se, Mo, Cd, Ba, Tl, and Pb using an inductively coupled plasma-mass spectrometer. Mean concentrations were compared with published values, and the influence of age, gender, and other demographic factors were explored. Elevated levels of Ni in this population warrant further investigation. Significant differences in the mean concentration of Al, V, Cr, Mn, Cd, Pb, and Se exist between toenails of adults and children. Pearson correlation coefficients reveal strong significant associations among Cd, Cr, and Tl (p<0.05), in addition to other elements. These investigations provide insight into exposures and factors influencing exposures in this population while adding to the growing fund of knowledge surrounding use of toenails as a marker of exposure.

Intra-individual variability in toenail arsenic concentrations in a Michigan population, USA

Arsenic concentration in toenail clippings is used as a biomarker of exposure in epidemiological studies, often under the assumption that a single measurement represents long-term exposure. For this assumption to hold, the measured arsenic concentrations must be stable over time, yet temporal variability has not been adequately assessed. This study aims to evaluate temporal variability in multiple toenail samples collected from a population exposed to drinking water arsenic levels <100 μg/l. Our objectives are to investigate factors responsible for biomarker variability and to assess the suitability of single versus multiple measurements for determining exposure in epidemiological studies. Multiple toenail and drinking water samples were collected from 254 participants enrolled in a case–control study of arsenic exposure and bladder cancer in Michigan, USA; participants also answered questions on water consumption. Toenail samples collected an average of 14 months apart were positively correlated, although a substantial amount of variability was detected (r=0.43, P<0.0001, n=236). Arsenic concentration in drinking water was stable and small changes in drinking water arsenic concentration did not explain variability in toenail arsenic concentration. Change in drinking water consumption, however, was significant in predicting differences in toenail arsenic concentration. Stronger correlations between drinking water arsenic concentration and intake and toenail arsenic concentration were observed when two toenail samples were averaged, suggesting that multiple measurements may more accurately reflect exposure. When exposure was categorized into tertiles and other pre-determined categories, 25–40% of exposures were differentially classified. Only a small percentage (<4%), however, were classified as having low exposure using a single measurement and high exposure when an average of two measurements was used. These results suggest that the use of multiple measurements is unlikely to affect exposure classification of individuals into high- or low-exposure groups; however, collection of multiple samples may be advantageous for more refined exposure classification.

Effects of nutritional measures on toenail arsenic concentration as a biomarker of arsenic exposure

Abstract Correlations between drinking water and toenail arsenic concentrations have been demonstrated in previous studies, yet factors that may modify the exposure–biomarker association have not been adequately assessed. Using data from 500 controls enrolled in a bladder cancer study underway in Michigan, USA, the effects of demographic characteristics and nutritional measures on the biomarker response were evaluated. Drinking water and toenail samples were collected during a home visit and analyzed for arsenic and other elements. Participants reported dietary supplement intake habits and provided demographic data. Arsenic concentrations of drinking water and toenail samples were positively correlated. Of the nutritional measures evaluated, toenail iron concentration was a significant modifier of the exposure–biomarker association. No demographic characteristics or general measures of dietary intake affected the biomarker response. The results presented herein are critical for biomarker validation and prove promising for sound application of the arsenic toenail biomarker to future epidemiological investigations.

Toenails for Biomonitoring of Environmental Exposures

Human nails are composed of keratins, proteins that incorporate different elements and lipophilic chemicals as they grow. Given this characteristic, coupled with the ease of collection and storage and the potential to reflect multiple exposures occurring approximately 1 year ago, toenail concentrations are promising biomarkers of environmental exposures. In particular, research has focused on elemental concentration in toenail clippings. Although reporting baseline elemental concentrations in nails is useful for understanding how this biological material may reflect exposure, steps must be taken to validate the biomarker before widespread application. In particular, efforts should focus on relating the biomarker to estimated intake of the contaminant, exploring temporal stability of the biomarker concentration, and understanding the association with other known biological markers for the contaminant. A majority of work related to toenail biomarker validity has focused on arsenic and selenium; these studies suggest that toenails may be useful in measuring exposure to these elements. Further work should focus on validation of this potentially valuable biomarker for other contaminants of interest, while continuing to refine the exposure–biomarker association for arsenic and selenium.

Exposure Assessment in Environmental Epidemiology

A key component of environmental epidemiologic research is the assessment of historic exposure to environmental contaminants. The continual expansion of space-time databases, coupled with the recognized need to incorporate mobility histories in environmental epidemiology, has highlighted the deficiencies of current software to visualize and process space-time information for exposure assessment (Mather et al. 2004; Pickle et al. 2005). This need is most pressing in retrospective studies or large studies where collection of individual biomarkers is unattainable or prohibitively expensive, and models and software tools are required for exposure reconstruction. In diseases of long latency such as cancer, exposure may need to be reconstructed over the entire life-course, taking into consideration residential mobility, occupational mobility, changes in risk behaviors, and time-changing maps generated from models of environmental contaminants. Even for outcomes of short latency such as asthma attacks, exposure reconstruction may involve daily mobility/activity patterns and temporally-varying maps of contaminants. These types of datasets, for example, mobility histories and timechanging maps of environmental contaminants, are almost always characterized by spatial, temporal, and, spatio-temporal variability. While current state-of-theart methods can integrate datasets that contain either spatial or temporal variability, datasets exhibiting both spatial and temporal variability have proven largely unmanageable until now, and researchers have been forced to simplify the dynamic nature of their datasets by reducing or eliminating the spatial or temporal dimension.