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Ionizing radiation at diagnostic and therapeutic doses is a known contributor to the development of brain and spinal cord (CNS) cancer. However, little is known about risk from exposure to radon, a natural radiation source which the general population is exposed to residentially and environmentally. This study investigated correlations between mean county radon levels and CNS cancer incidence in five highly populated and radon-enriched US states (Minnesota, mean radon level 4.6 pCi/L; Wisconsin, 5.7 pCi/L; Pennsylvania, 8.6 pCi/L; Iowa, 6.1 pCi/L; and New Jersey, 4.4 pCi/L). Mean radon levels per county were accessed through AirChek, which provides publicly available radon data measured in residences and workplaces. CNS cancer incidence data were accessed through the states' health department websites and span differing amounts of time due to the publicly accessible nature of the data, though all time spans were over 10 years. Negative binomial regressions were run to assess correlations between mean radon and CNS cancer incidence per county. Quantile maps were constructed and Moran's I was calculated to assess spatial autocorrelation in residuals; no spatial autocorrelation was evident. Iowa was the only state with a significant positive association between radon and CNS incidence; no associations were detected in other states, and a negative association was observed in the 5 states combined. This study does not provide evidence that radon is a risk factor for CNS cancer; however, the possibility of an association cannot be ruled out due to limitations of the study, principally its ecologic nature and lack of individual-level exposure data. [ABSTRACT FROM AUTHOR]

The decision whether to fluoridate drinking water continues to be controversial in some communities. Dental and skeletal fluorosis in response to chronic fluoride overexposure are cited as reasons to avoid community water fluoridation in spite of evidence of the oral and skeletal health benefits fluoridation confers. Community fluoridation of ~ 1 mg/L fluoride has not been found to be associated with primary bone cancer but is associated with improved bone strength. No studies have examined fluoride exposure and secondary bone cancer, a common metastasis with significant morbidity. We hypothesize that fluoridation could diminish the likelihood of secondary bone cancer due to its role in bone fortification. We examined the association between community water fluoridation category and prevalence of secondary bone cancer from 2008 to 2010 among cancer patients of 18 years of age or older in counties in New York State. Relative to counties with less than 25% of the water supply fluoridated, we report no association between secondary bone cancer among cancer patients in counties with 25–75% of the water supply fluoridated (β = 0.02, p = 0.96) and among those in counties with > 75% fluoridated (β = 0.02, p = 0.97). We found no evidence of an association between community water fluoridation category and secondary bone cancer from 2008 to 2010 at the county level in New York State. [ABSTRACT FROM AUTHOR]

Exposure to lead (Pb) is implicated in a plethora of health threats in both adults and children. Increased exposure levels are associated with oxidative stress in the blood of workers exposed at occupational levels. However, it is not known whether lower Pb exposure levels are related to a shift toward a more oxidized state. To assess the association between blood lead level (BLL) and glutathione (GSH) redox biomarkers in a population of healthy adults, BLL and four GSH markers (GSH, GSSG, GSH/GSSG ratio and redox potential Eh) were measured in the blood of a cross-sectional cohort of 282 avid seafood-eating healthy adults living on Long Island (NY). Additionally, blood levels of two other metals known to affect GSH redox status, selenium (Se) and mercury (Hg), and omega-3 index were tested for effect modification. Regression models were further adjusted for demographic and smoking status. Increasing exposure to Pb, measured in blood, was not associated with GSSG, but was associated with lower levels of GSH/GSSG ratio and more positive GSH redox potential Eh, driven by its association with GSH. No effect modification was observed in analyses stratified by Hg, Se, omega-3 index, sex, age, or smoking. Blood Pb is associated with lower levels of GSH and the GSH/GSSG ratio in this cross-sectional study of healthy adults. [ABSTRACT FROM AUTHOR]

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 (R2=0.3688), compared with metrics including water consumption (R2=0.2038) or water concentrations at employment locations (R2=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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps. [ABSTRACT FROM AUTHOR]

Objectives: Cancer registries are increasingly mapping residences of patients at time of diagnosis, however, an accepted protocol for spatial analysis of these data is lacking. We undertook a public health practice-research partnership to develop a strategy for detecting spatial clusters of early stage breast cancer using registry data.Methods: Spatial patterns of early stage breast cancer throughout Michigan were analyzed comparing several scales of spatial support, and different clustering algorithms.Results: Analyses relying on point data identified spatial clusters not detected using data aggregated into census block groups, census tracts, or legislative districts. Further, using point data, Cuzick-Edwards' nearest neighbor test identified clusters not detected by the SaTScan spatial scan statistic. Regression and simulation analyses lent credibility to these findings.Conclusions: In these cluster analyses of early stage breast cancer in Michigan, spatial analyses of point data are more sensitive than analyses relying on data aggregated into polygons, and the Cuzick-Edwards' test is more sensitive than the SaTScan spatial scan statistic, with acceptable Type I error. Cuzick-Edwards' test also enables presentation of results in a manner easily communicated to public health practitioners. The approach outlined here should help cancer registries conduct and communicate results of geographic analyses. [ABSTRACT FROM AUTHOR]

Exposure misclassification is a major concern in epidemiologic studies. The potential for misclassification becomes even more problematic when participants are asked to recall historical information. Yet, historical information is important in cancer studies, where latency is long and causative exposures may have occurred years or even decades prior to diagnosis. Even though self-reported proximity to farmland is a commonly used exposure measure, the accuracy of recall is seldom, if ever validated. Geographic Information Systems (GISs) and land cover information derived from satellite imagery can allow researchers to assess the accuracy of this exposure measure, and to quantify the extent and importance of exposure misclassification. As part of a bladder cancer case–control study in Michigan, participants were asked whether they lived on a farm, or within a distance of 1/4, 1/4–1, 1–5, or >5 miles from farmland for each residence over their lifespan. Responses from 531 participants over two time periods — 1978 and 2001 — were investigated. Self reported proximity to farmland was compared to a “gold standard” derived from Michigan land cover files for the same time periods. Logistic regression and other statistical measures including sensitivity, specificity, and percentage matching were evaluated. In comparing self-reported and land cover-derived proximity to farmland, cases exhibited better agreement than controls in 2001 (adjusted OR=1.74; 95% CI=1.01, 2.99) and worse agreement in 1978, although not significantly (adjusted OR=0.74; 95% CI=0.47, 1.16). When comparing 2001 with 1978, both cases and controls showed better agreement in 2001, but only cases showed a significant difference (adjusted OR=2.36; 95% CI=1.33, 4.18). These differences in agreement may be influenced by differences in educational attainment between cases and controls, although adjustment for education did not diminish the association. Gender, age, number of years at residence, and geocoding accuracy did not influence agreement between the proximity approaches. This study suggests that proximity measures taken from satellite-derived land cover imagery may be useful for assessing proximity to farmland, and it raises some concerns about the use of self-reported proximity to farmland in exposure assessments.Journal of Exposure Science and Environmental Epidemiology (2008) 18, 381–391; doi:10.1038/sj.jes.7500610; published online 5 September 2007 [ABSTRACT FROM AUTHOR]

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.Journal of Exposure Science and Environmental Epidemiology (2008) 18, 149–157; doi:10.1038/sj.jes.7500569; published online 11 April 2007 [ABSTRACT FROM AUTHOR]

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 (>25µg/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. [ABSTRACT FROM AUTHOR]