Jaymie R. Meliker

Arsenic in drinking water and cerebrovascular disease, diabetes mellitus, and kidney disease in Michigan: a standardized mortality ratio analysis

BackgroundExposure to arsenic concentrations in drinking water in excess of 300 μg/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 μg/L).MethodsA 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.ResultsThe six county study area had a population-weighted mean arsenic concentration of 11.00 μg/L and a population-weighted median of 7.58 μg/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).ConclusionThis 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.

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.

Dietary cadmium exposure and risk of breast, endometrial, and ovarian cancer in the Women's Health Initiative.

Background: In vitro and animal data suggest that cadmium, a heavy metal that contaminates some foods and tobacco plants, is an estrogenic endocrine disruptor. Elevated estrogen exposure is associated with breast, endometrial, and ovarian cancer risk. Objectives: We examined the association between dietary cadmium intake and risk of these cancers in the large, well-characterized Women’s Health Initiative (WHI). Methods: A total of 155,069 postmenopausal women, 50–79 years of age, who were enrolled in the WHI clinical trials or observational study, participated in this study. We estimated dietary cadmium consumption by combining baseline food frequency questionnaire responses with U.S. Food and Drug Administration data on food cadmium content. Participants reported incident invasive breast, endometrial, or ovarian cancer, and WHI centrally adjudicated all cases through August 2009. We applied Cox regression to estimate adjusted hazard ratios (HRs) and 95% CIs for each cancer, comparing quintiles of energy-adjusted dietary cadmium intake. Results: Over an average of 10.5 years, 6,658 invasive breast cancers, 1,198 endometrial cancers, and 735 ovarian cancers were reported. We observed no statistically significant associations between dietary cadmium and risk of any of these cancers after adjustment for potential confounders including total dietary energy intake. Results did not differ in any subgroup of women examined. Conclusions: We found little evidence that dietary cadmium is a risk factor for breast, endometrial, or ovarian cancers in postmenopausal women. Misclassification in dietary cadmium assessment may have attenuated observed associations. Citation: Adams SV, Quraishi SM, Shafer MM, Passarelli MN, Freney EP, Chlebowski RT, Luo J, Meliker JR, Mu L, Neuhouser ML, Newcomb PA. 2014. Dietary cadmium exposure and risk of breast, endometrial, and ovarian cancer in the Women’s Health Initiative. Environ Health Perspect 122:594–600; http://dx.doi.org/10.1289/ehp.1307054

Association between Lifetime Exposure to Inorganic Arsenic in Drinking Water and Coronary Heart Disease in Colorado Residents

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. Citation: James KA, Byers T, Hokanson JE, Meliker JR, Zerbe GO, Marshall JA. 2015. Association between lifetime exposure to inorganic arsenic in drinking water and coronary heart disease in Colorado residents. Environ Health Perspect 123:128–134; http://dx.doi.org/10.1289/ehp.1307839

Global, local and focused geographic clustering for case-control data with residential histories

BackgroundThis paper introduces a new approach for evaluating clustering in case-control data that accounts for residential histories. Although many statistics have been proposed for assessing local, focused and global clustering in health outcomes, few, if any, exist for evaluating clusters when individuals are mobile.MethodsLocal, global and focused tests for residential histories are developed based on sets of matrices of nearest neighbor relationships that reflect the changing topology of cases and controls. Exposure traces are defined that account for the latency between exposure and disease manifestation, and that use exposure windows whose duration may vary. Several of the methods so derived are applied to evaluate clustering of residential histories in a case-control study of bladder cancer in south eastern Michigan. These data are still being collected and the analysis is conducted for demonstration purposes only.ResultsStatistically significant clustering of residential histories of cases was found but is likely due to delayed reporting of cases by one of the hospitals participating in the study.ConclusionData with residential histories are preferable when causative exposures and disease latencies occur on a long enough time span that human mobility matters. To analyze such data, methods are needed that take residential histories into account.

A case-cohort study examining lifetime exposure to inorganic arsenic in drinking water and diabetes mellitus.

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.

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.

Spatial cluster analysis of early stage breast cancer: a method for public health practice using cancer registry data.

ObjectivesCancer 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.MethodsSpatial patterns of early stage breast cancer throughout Michigan were analyzed comparing several scales of spatial support, and different clustering algorithms.ResultsAnalyses 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.ConclusionsIn 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.

Genetic variation in Glutathione S-Transferase Omega-1, Arsenic Methyltransferase and Methylene-tetrahydrofolate Reductase, arsenic exposure and bladder cancer: A case-control study

BackgroundIngestion 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.MethodsSingle 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.ResultsWhile 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).ConclusionsVariation 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.