Biomedical subjects

Jaymie R Meliker

Publications and source records attributed to Jaymie R Meliker.

6 recordsLinked to original sources

PubMed2006

Individual lifetime exposure to inorganic arsenic using a space-time information system.

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.

Adult↗

PubMed2006

Case-control geographic clustering for residential histories accounting for risk factors and covariates.

BACKGROUND: Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn - we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. RESULTS: Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. CONCLUSION: These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case-control study design.

Age Factors↗

PubMed2006

Effects of time and point-of-use devices on arsenic levels in Southeastern Michigan drinking water, USA.

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.

Arsenic↗

PubMed2006

Major contributors to inorganic arsenic intake in southeastern Michigan.

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.

Adult↗

PubMed2004

Visualization and exploratory analysis of epidemiologic data using a novel space time information system.

BACKGROUND: Recent years have seen an expansion in the use of Geographic Information Systems (GIS) in environmental health research. In this field GIS can be used to detect disease clustering, to analyze access to hospital emergency care, to predict environmental outbreaks, and to estimate exposure to toxic compounds. Despite these advances the inability of GIS to properly handle temporal information is increasingly recognised as a significant constraint. The effective representation and visualization of both spatial and temporal dimensions therefore is expected to significantly enhance our ability to undertake environmental health research using time-referenced geospatial data. Especially for diseases with long latency periods (such as cancer) the ability to represent, quantify and model individual exposure through time is a critical component of risk estimation. In response to this need a STIS - a Space Time Information System has been developed to visualize and analyze objects simultaneously through space and time. RESULTS: In this paper we present a "first use" of a STIS in a case-control study of the relationship between arsenic exposure and bladder cancer in south eastern Michigan. Individual arsenic exposure is reconstructed by incorporating spatiotemporal data including residential mobility and drinking water habits. The unique contribution of the STIS is its ability to visualize and analyze residential histories over different temporal scales. Participant information is viewed and statistically analyzed using dynamic views in which values of an attribute change through time. These views include tables, graphs (such as histograms and scatterplots), and maps. In addition, these views can be linked and synchronized for complex data exploration using cartographic brushing, statistical brushing, and animation. CONCLUSION: The STIS provides new and powerful ways to visualize and analyze how individual exposure and associated environmental variables change through time. We expect to see innovative space-time methods being utilized in future environmental health research now that the successful "first use" of a STIS in exposure reconstruction has been accomplished.

Journal Article↗

PubMed2004

Spatial analysis of alcohol-related motor vehicle crash injuries in southeastern Michigan.

Temporal, behavioral and social risk factors that affect injuries resulting from alcohol-related motor vehicle crashes have been characterized in previous research. Much less is known about spatial patterns and environmental associations of alcohol-related motor vehicle crashes. The aim of this study was to evaluate geographic patterns of alcohol-related motor vehicle crashes and to determine if locations of alcohol outlets are associated with those crashes. In addition, we sought to demonstrate the value of integrating spatial and traditional statistical techniques in the analysis of this preventable public health risk. The study design was a cross-sectional analysis of individual-level blood alcohol content, traffic report information, census block group data, and alcohol distribution outlets. Besag and Newell's spatial analysis and traditional logistic regression both indicated that areas of low population density had more alcohol-related motor vehicle crashes than expected (P < 0.05). There was no significant association between alcohol outlets and alcohol-related motor vehicle crashes using distance analyses, logistic regression, and Chi-square. Differences in environmental or behavioral factors characteristic of areas of low population density may be responsible for the higher proportion of alcohol-related crashes occurring in these areas.

Accidents, Traffic↗