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Arsenic is a risk factor for several noncommunicable diseases, even at low doses. Urinary arsenic (UAs) concentration is a good biomarker for internal dose, and demographic, dietary, and lifestyle factors are proposed predictors in nonoccupationally exposed populations. However, most predictor studies are limited in terms of size and number of predictors. We investigated demographic, dietary, and lifestyle determinants of UAs concentrations in 744 postmenopausal Danish women who had UAs measurements and questionnaire data on potential predictors. UAs concentrations were determined using mass spectrometry (ICP-MS), and determinants of the concentration were investigated using univariate and multivariate regression models. We used a forward selection procedure for model optimization. In all models, fish, alcohol, and poultry intake were associated with higher UAs concentration, and tap water, fruit, potato, and dairy intake with lower concentration. A forward regression model explained 35% ( R ²) of the variation in concentrations. Age, smoking, education, and area of residence did not predict concentration. The results were relatively robust across sensitivity analyses. The study suggested that UAs concentration in postmenopausal women was primarily determined by dietary factors, with fish consumption showing the strongest direct association. However, the majority of variation in UAs concentration in this study population is still unexplained.

Background: In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation., Methods: Global, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race., Results: Significant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed., Conclusion: Q analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of Oakland and Ingham counties, and to the City of Jackson.

Background: Chronic diseases, including coronary heart disease (CHD), have been associated with ingestion of drinking water with high levels of inorganic arsenic (> 1,000 μg/L). However, associations have been inconclusive in populations with lower levels (< 100 μg/L) of inorganic arsenic exposure., Objectives: We conducted a case-cohort study based on individual estimates of lifetime arsenic exposure to examine the relationship between chronic low-level arsenic exposure and risk of CHD., Methods: This study included 555 participants with 96 CHD events diagnosed between 1984 and 1998 for which individual lifetime arsenic exposure estimates were determined using data from structured interviews and secondary data sources to determine lifetime residence, which was linked to a geospatial model of arsenic concentrations in drinking water. These lifetime arsenic exposure estimates were correlated with historically collected urinary arsenic concentrations. A Cox proportional-hazards model with time-dependent CHD risk factors was used to assess the association between time-weighted average (TWA) lifetime exposure to low-level inorganic arsenic in drinking water and incident CHD., Results: We estimated a positive association between low-level inorganic arsenic exposure and CHD risk [hazard ratio (HR): = 1.38, 95% CI: 1.09, 1.78] per 15 μg/L while adjusting for age, sex, first-degree family history of CHD, and serum low-density lipoprotein levels. The risk of CHD increased monotonically with increasing TWAs for inorganic arsenic exposure in water relative to < 20 μg/L (HR = 1.2, 95% CI: 0.6, 2.2 for 20-30 μg/L; HR = 2.2; 95% CI: 1.2, 4.0 for 30-45 μg/L; and HR = 3, 95% CI: 1.1, 9.1 for 45-88 μg/L)., Conclusions: Lifetime exposure to low-level inorganic arsenic in drinking water was associated with increased risk for CHD in this population.

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Research groups have estimated historic exposure using databases and models of arsenic in drinking water supplies, along with participant residential histories. Urinary arsenic species are an established biomarker of recent exposure; we compare arsenic concentrations in historically collected urine samples with predicted estimates of arsenic exposure. Using a cohort of 462 subjects with at least one urine sample collected from 1984-1992 and an arsenic exposure estimate through drinking water at the time of the urine sample, individual exposure estimates were compared with speciated urine arsenic (UAs) concentrations using correlation and multiple regression analyses. Urine inorganic arsenic (UIAs) concentrations (trivalent arsenic, pentavalent arsenic, monomethylarsonic acid, dimethylarsonic acid) were best predicted by residential water arsenic concentrations (R(2)=0.3688), compared with metrics including water consumption (R(2)=0.2038) or water concentrations at employment locations (R(2)=0.2331). UIAs concentrations showed similar correlation when stratified by whether the arsenic concentration was predicted or measured. Residential water arsenic concentrations, independent of water intake or water concentrations at places of employment, best explain the variability in UIAs concentrations, suggesting historical reconstruction of arsenic exposure that accounts for space-time variability and water concentrations may serve as a proxy for exposure.

Background: Consumption of drinking water with high levels of inorganic arsenic (over 500 μg/L) has been associated with type II diabetes mellitus (DM), but previous studies have been inconclusive about risks at lower levels (<100 μg/L). We present a case-cohort study based on individual estimates of lifetime arsenic exposure to examine the relationship between chronic low-level arsenic exposure and risk of DM., Methods: This case-cohort study included 141 cases of DM diagnosed between 1984 and 1998 as part of the prospective San Luis Valley Diabetes Study. A comparison sub-cohort of 488 participants was randomly sampled from 936 eligible participants who were disease free at baseline. Individual lifetime arsenic exposure estimates were determined using a methodology that incorporates the use of a structured interview to determine lifetime residence and employment history, geospatial modeling of arsenic concentrations in drinking water, and urine arsenic concentrations. A Cox proportional hazards model with known DM risk factors as time-dependent covariates was used to assess the association between lifetime exposure to inorganic arsenic in drinking water and incident DM., Results: Our findings show a significant association between inorganic arsenic exposure and DM risk (hazard ratio [HR]=1.27, 95%=1.01, 1.59 per 15 μg/L) while adjusting for ethnicity and time varying covariates age, body mass index and physical activity level., Conclusions: Exposure to low-level inorganic arsenic in drinking water is associated with increased risk for type II DM in this population based on a comprehensive lifetime exposure assessment., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: Ingestion of groundwater with high concentrations of inorganic arsenic has been linked to adverse health outcomes, including bladder cancer, however studies have not consistently observed any elevation in risk at lower concentrations. Genetic variability in the metabolism and clearance of arsenic is an important consideration in any investigation of its potential health risks. Therefore, we examined the association between genes thought to play a role in the metabolism of arsenic and bladder cancer., Methods: Single nucleotide polymorphisms (SNPs) in GSTO-1, As3MT and MTHFR were genotyped using DNA from 219 bladder cancer cases and 273 controls participating in a case-control study in Southeastern Michigan and exposed to low to moderate (<50 μg/L) levels of arsenic in their drinking water. A time-weighted measure of arsenic exposure was constructed using measures from household water samples combined with past residential history, geocoded and merged with archived arsenic data predicted from multiple resources., Results: While no single SNP in As3MT was significantly associated with bladder cancer overall, several SNPs were associated with bladder cancer among those exposed to higher arsenic levels. Individuals with one or more copies of the C allele in rs11191439 (the Met287Thr polymorphism) had an elevated risk of bladder cancer (OR = 1.17; 95% CI = 1.04-1.32 per 1 μg/L increase in average exposure). However, no association was observed between average arsenic exposure and bladder cancer among TT homozygotes in the same SNP. Bladder cancer cases were also 60% less likely to be homozygotes for the A allele in rs1476413 in MTHFR compared to controls (OR = 0.40; 95% CI = 0.18-0.88)., Conclusions: Variation in As3MT and MTHFR is associated with bladder cancer among those exposed to relatively low concentrations of inorganic arsenic. Further investigation is warranted to confirm these findings.

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. Log(10)-transformed drinking water arsenic concentration at home was a significant (P<0.0001) predictor of SumAs (R(2)=0.18). Associations improved (R(2)=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 (R(2)=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.

Background and Purpose: Mechanistic and human studies suggest a role for arsenic in ischemic stroke; however, risks from chronic, low-level exposures are uncertain and US studies are lacking. The objective was to investigate the association between low-level arsenic exposure in drinking water and ischemic stroke hospital admissions in Michigan., Methods: Ischemic stroke hospital admissions among those aged ≥ 45 years were identified (1994 to 2006). Population-weighted average arsenic concentrations were estimated for each Michigan county (n = 83) and for zip codes in Genesee County (n=27) where there is greater variation in arsenic concentrations. US Census data provided age- and sex-specific population counts and other county- and zip code-level variables (race, income), which were adjusted for in multilevel negative binomial regression models of arsenic and stroke admissions. Hospital admissions for duodenal ulcer and hernia, not hypothesized to be associated with arsenic, were also evaluated., Results: Adjusted county-level analyses suggested a relationship between arsenic and ischemic stroke hospital admissions, although similar associations were observed for duodenal ulcer and hernia. In zip code-level analysis, arsenic was associated with an increased risk of stroke admission (relative risk, 1.03; 95% CI, 1.01 to 1.05 per μg/L increase in arsenic) after adjustment for confounders, and null or negative associations were found between arsenic and nonvascular outcomes., Conclusions: Findings from this study suggest that exposure to even low levels of arsenic in drinking water may be associated with a higher risk of incident stroke. Given the ecological nature of the analysis, further epidemiological study with individual-level data on arsenic exposure and incident stroke is warranted.

Urinary arsenic concentration is often used as a biomarker of arsenic exposure. First morning void (FMV) and spot urine samples from 131 participants in southeastern Michigan were analyzed using an HPLC-IC-PMS system for six different arsenic species: arsenobetaine (AsB), arsenite (As[III]), arsenate (As[V]), methylarsonous acid MMA[III], methylarsenic acid MMA[V], and dimethylarsenic DMA[V]. Bland-Altman plots, intraclass correlation coefficients (ICCs), and Pearson correlation procedures were used to evaluate the relationship between the arsenic species in FMV and spot urine collections after normalizing the samples by specific gravity. DMA[III] and MMA[III] were not detected in any of the samples. The sum of As[III], As[V], MMA[V], and DMA[V] was designated SumAs. The ICC between SumAs in FMV and SumAs in spot samples was 0.90. The ICC showed that 90% of variation comes from between individuals and not within individuals. A significant correlation (r=0.80 p<0.001) was observed between FMV and spot samples for SumAs. The spot sample were a good predictor of the MMA[V] (r=0.83 p<0.0001), and DMA[V] (r=0.77 p<0.0001) in the FMV sample. These associations suggest that either FMV or spot samples can be used as an adequate bioindicator of arsenic metabolites in human urine. The benefit of using spot urine samples, instead of 24-h or FMV urine samples, is the potential reduction in budgetary and logistic requirements in epidemiological studies., (Copyright 2010 Elsevier GmbH. All rights reserved.)

Objective: Arsenic in drinking water has been linked with the risk of urinary bladder cancer, but the dose-response relationships for arsenic exposures below 100 microg/L remain equivocal. We conducted a population-based case-control study in southeastern Michigan, USA, where approximately 230,000 people were exposed to arsenic concentrations between 10 and 100 microg/L., Methods: This study included 411 bladder cancer cases diagnosed between 2000 and 2004, and 566 controls recruited during the same period. Individual lifetime exposure profiles were reconstructed, and residential water source histories, water consumption practices, and water arsenic measurements or modeled estimates were determined at all residences. Arsenic exposure was estimated for 99% of participants' person-years., Results: Overall, an increase in bladder cancer risk was not found for time-weighted average lifetime arsenic exposure >10 microg/L when compared with a reference group exposed to <1 microg/L (odds ratio (OR) = 1.10; 95% confidence interval (CI): 0.65, 1.86). Among ever-smokers, risks from arsenic exposure >10 microg/L were similarly not elevated when compared to the reference group (OR = 0.94; 95% CI: 0.50, 1.78)., Conclusions: We did not find persuasive evidence of an association between low-level arsenic exposure and bladder cancer. Selecting the appropriate exposure metric needs to be thoughtfully considered when investigating risk from low-level arsenic exposure.

Arsenic concentrations exceeding 10 microg/l, the United States maximum contaminant level and the World Health Organization guideline value, are frequently reported in groundwater from bedrock and unconsolidated aquifers of southeastern Michigan. Although arsenic-bearing minerals (including arsenian pyrite and oxide/hydroxide phases) have been identified in Marshall Sandstone bedrock of the Mississippian aquifer system and in tills of the unconsolidated aquifer system, mechanisms responsible for arsenic mobilization and subsequent transport in groundwater are equivocal. Recent evidence has begun to suggest that groundwater recharge and characteristics of well construction may affect arsenic mobilization and transport. Therefore, we investigated the relationship between dissolved arsenic concentrations, reported groundwater recharge rates, well construction characteristics, and geology in unconsolidated and bedrock aquifers. Results of multiple linear regression analyses indicate that arsenic contamination is more prevalent in bedrock wells that are cased in proximity to the bedrock-unconsolidated interface; no other factors were associated with arsenic contamination in water drawn from bedrock or unconsolidated aquifers. Conditions appropriate for arsenic mobilization may be found along the bedrock-unconsolidated interface, including changes in reduction/oxidation potential and enhanced biogeochemical activity because of differences between geologic strata. These results are valuable for understanding arsenic mobilization and guiding well construction practices in southeastern Michigan, and may also provide insights for other regions faced with groundwater arsenic contamination.

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.

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 microg/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.

Objective: Arsenic is a pervasive contaminant in underground aquifers worldwide, yet documentation of health effects associated with low-to-moderate concentrations (<100microg/L) has been stymied by uncertainties in assessing long-term exposure. A critical component of assessing exposure to arsenic in drinking water is the development of models for predicting arsenic concentrations in private well water in the past; however, these models are seldom validated. The objective of this paper is to validate alternative spatial models of arsenic concentrations in private well water in southeastern Michigan., Methods: From 1993 to 2002, the Michigan Department of Environmental Quality analyzed arsenic concentrations in water from 6050 private wells. This dataset was used to develop several spatial models of arsenic concentrations in well water: proxy wells based on nearest-neighbor relationships, averages across geographic regions, and geostatistically derived estimates based on spatial correlation and geologic factors. Output from these models was validated using arsenic concentrations measured in 371 private wells from 2003 to 2006., Results: The geostatisical model and nearest-neighbor approach outperformed the models based on geographic averages. The geostatistical model produced the highest degree of correlation using continuous data (Pearson's r=0.61; Spearman's rank rho=0.46) while the nearest-neighbor approach produced the strongest correlation (kappa(weighted)=0.58) using an a priori categorization of arsenic concentrations (<5, 5-9.99, 10-19.99, > or = 20microg/L). When the maximum contaminant level was used as a cut-off in a two-category classification (<10, > or =10microg/L), the nearest-neighbor approach and geostatistical model had similar values for sensitivity (0.62-0.63), specificity (0.80), negative predictive value (0.85), positive predictive value (0.53), and percent agreement (75%)., Discussion: This validation study reveals that geostatistical modeling and nearest-neighbor approaches are effective spatial models for predicting arsenic concentrations in private well water. Further validation analyses in other regions are necessary to indicate how widely these findings may be generalized.

Background: Exposure to arsenic concentrations in drinking water in excess of 300 microg/L is associated with diseases of the circulatory and respiratory system, several types of cancer, and diabetes; however, little is known about the health consequences of exposure to low-to-moderate levels of arsenic (10-100 microg/L)., Methods: A standardized mortality ratio (SMR) analysis was conducted in a contiguous six county study area of southeastern Michigan to investigate the relationship between moderate arsenic levels and twenty-three selected disease outcomes. Disease outcomes included several types of cancer, diseases of the circulatory and respiratory system, diabetes mellitus, and kidney and liver diseases. Arsenic data were compiled from 9251 well water samples tested by the Michigan Department of Environmental Quality from 1983 through 2002. Michigan Resident Death Files data were amassed for 1979 through 1997 and sex-specific SMR analyses were conducted with indirect adjustment for age and race; 99% confidence intervals (CI) were reported., Results: The six county study area had a population-weighted mean arsenic concentration of 11.00 microg/L and a population-weighted median of 7.58 microg/L. SMR analyses were conducted for the entire six county study area, for only Genesee County (the most populous and urban county), and for the five counties besides Genesee. Concordance of results across analyses is used to interpret the findings. Elevated mortality rates were observed for both males (M) and females (F) for all diseases of the circulatory system (M SMR, 1.11; CI, 1.09-1.13; F SMR, 1.15; CI, 1.13,-1.17), cerebrovascular diseases (M SMR, 1.19; CI, 1.14-1.25; F SMR, 1.19; CI, 1.15-1.23), diabetes mellitus (M SMR, 1.28; CI, 1.18-1.37; F SMR, 1.27; CI, 1.19-1.35), and kidney diseases (M SMR, 1.28; CI, 1.15-1.42; F SMR, 1.38; CI, 1.25-1.52)., Conclusion: This is some of the first evidence to suggest that exposure to low-to-moderate levels of arsenic in drinking water may be associated with several of the leading causes of mortality, although further epidemiologic studies are required to confirm the results suggested by this ecologic SMR analysis.

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 (R2 = .32). When arsenic intake from consumption of tap water and beverages made from tap water (microg/L arsenic x L/d = microg/d) was used as a predictor variable, the correlation was markedly increased for individuals with >1 microg/L arsenic (R2 = .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.

Objectives: A space-time information system (STIS) based method is introduced for calculating individual-level estimates of inorganic arsenic exposure over the adult life-course. STIS enables visualization and analysis of space-time data, overcoming some of the constraints inherent to spatial-only Geographic Information System software. The power of this new methodology is demonstrated using data from southeastern Michigan where 8% of the population is exposed to arsenic >10 microg/l (the World Health Organization guideline) in home drinking water., Methods: Participants (N=440) are members of a control group in a population-based bladder cancer case-control study in southeastern Michigan and were recruited by phone using random digit dialing. Water samples were collected and analyzed for arsenic at current residence and participants were required to answer questions concerning lifetime mobility history and dietary habits. Inorganic arsenic concentrations were estimated at past residences and workplaces, and in select foods. Fluid and food consumption data were integrated with mobility histories and arsenic concentrations to calculate continuous estimates of inorganic arsenic intake over the adult life-course., Results: Estimates of continuous arsenic exposure are displayed, making use of both participant age and calendar year as measures of time. Results illustrate considerable temporal variability in individual-level exposure, with 26% of the participants experiencing a change in drinking water arsenic concentration of at least +/-10 microg/l over their adult lives. The average cumulative intake over the adult life-course ranges from 2.53 x 10(4)-1.30 x 10(5) microg, depending on the selected exposure metric., Conclusions: The STIS-based exposure assessment method allows for flexible inclusion of different parameters or alternative formulations of those parameters, thus enabling the calculation of different exposure metrics. This flexibility is particularly useful when additional exposure routes are considered, input datasets are updated, or when a scientific consensus does not exist regarding the proper formulation of the exposure metric. These results demonstrate the potential of STIS as a useful tool for calculating continuous estimates of adult lifetime exposure to arsenic or other environmental contaminants for application in exposure and risk assessment.

Health effects associated with chronic, low-level exposures to arsenic in drinking water (<100 microg/L) remain unclear, in part due to uncertainties in assessing exposure. Drinking water concentrations have been used to assess past exposure to arsenic in epidemiological studies, under the assumption that a single measurement can be used to estimate historical exposure. This study aims to better understand (1) temporal variability in arsenic concentrations in drinking water and (2) the impact of point-of-use (POU) treatment devices on arsenic exposure measurements, and on reliability of the exposure measurement for population-level studies. Multiple drinking water samples were collected at two points in time (an average of fourteen months apart) for 261 individuals enrolled in a case-control study of arsenic exposure and bladder cancer in Michigan. Sources of drinking water included private wells (n = 221), public water supplies (n = 33), and bottled water (n = 7); mean arsenic concentration was highest in private wells (7.28 microg/L) and lowest in bottled water samples (0.28 microg/L). Arsenic concentrations in primary drinking water samples were highly correlated (r = 0.88, p < 0.0001, n = 196), with 3% of the water sources exceeding the United States Environmental Protection Agency's Maximum Contaminant Level (MCL) in one sample but not in the other sample. Measurement reproducibility did not vary by type of POU device (e.g., softener, filter, reverse osmosis system). Arsenic concentrations did differ, however, between samples treated with POU devices and untreated samples taken on the same day. Substantial differences in arsenic concentrations were consistently observed for reverse osmosis systems; other POU devices had variable effects on arsenic concentrations. These results indicate that while a single residential arsenic measurement may be used to represent exposure in this region, researchers must obtain information on changes in water source and POU treatment devices to better characterize population exposures over time.

Accurate estimates of inorganic arsenic intake are critical for evaluating potential health risks. Intake estimates have not been critically examined in regions of the United States where people are at risk from arsenic concentrations in drinking water exceeding the maximum contaminant limit of 10 microg/l. In southeastern Michigan, approximately 8% of the population is exposed to arsenic in drinking water >10 microg/l. Four hundred and forty participants of a control group in this region, frequency matched to cases in a population-based bladder cancer case-control study, answered a questionnaire about water and food consumption and smoking history. Water samples were collected from participants' current residences and analyzed for arsenic. Water arsenic data were combined with questionnaire data and published data of inorganic arsenic concentrations in select foods and cigarettes to examine the influence of arsenic in water at home, at work, and at other places, as well as inorganic arsenic intake from food and cigarettes. Monte Carlo simulations and analyses of individual-level intake estimates were conducted to quantify the variability attributed to different parameters in this primarily elderly white male population of southeastern Michigan. The 95th percentile of total inorganic arsenic intake ranges from 11 to 24 microg/day, depending on the intake metric selected. Results indicate that arsenic in home drinking water is the largest source of inorganic arsenic, accounting for 55.1% of the variance in the intake estimates. Food intake explains 37.3% of the variance, with rice being the largest contributor. In the upper decile of intake, consumption of plain water and beverages made with water at home, and ingestion of arsenic in water at work, also contribute to intake estimates. Water used for cooking and arsenic from smoking, however, only minimally alter the intake estimates. This is due to a relatively small volume of water absorbed into cooked foods and low concentrations of arsenic in cigarettes. Results from this study will assist investigators in better characterizing exposure to inorganic arsenic.

Background: Ingestion of groundwater with high concentrations of inorganic arsenic has been linked to adverse health outcomes, including bladder cancer, however studies have not consistently observed any elevation in risk at lower concentrations. Genetic variability in the metabolism and clearance of arsenic is an important consideration in any investigation of its potential health risks. Therefore, we examined the association between genes thought to play a role in the metabolism of arsenic and bladder cancer. Methods: Single nucleotide polymorphisms (SNPs) in GSTO-1, As3MT and MTHFR were genotyped using DNA from 219 bladder cancer cases and 273 controls participating in a case-control study in Southeastern Michigan and exposed to low to moderate (<50 µg/L) levels of arsenic in their drinking water. A time-weighted measure of arsenic exposure was constructed using measures from household water samples combined with past residential history, geocoded and merged with archived arsenic data predicted from multiple resources. Results: While no single SNP in As3MT was significantly associated with bladder cancer overall, several SNPs were associated with bladder cancer among those exposed to higher arsenic levels. Individuals with one or more copies of the C allele in rs11191439 (the Met287Thr polymorphism) had an elevated risk of bladder cancer (OR = 1.17; 95% CI = 1.04-1.32 per 1 µg/L increase in average exposure). However, no association was observed between average arsenic exposure and bladder cancer among TT homozygotes in the same SNP. Bladder cancer cases were also 60% less likely to be homozygotes for the A allele in rs1476413 in MTHFR compared to controls (OR = 0.40; 95% CI = 0.18-0.88). Conclusions: Variation in As3MT and MTHFR is associated with bladder cancer among those exposed to relatively low concentrations of inorganic arsenic. Further investigation is warranted to confirm these findings. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Association between Lifetime Exposure to Inorganic Arsenic in Drinking Water and Coronary Heart Disease in Colorado Residents" by Katherine A. James, Tim Byers, John E. Hokanson, Jaymie R. Meliker, and Julie A. Marshall in the February 2015 issue, along with a reply from the authors.