Biomedical subjects

Gillian A Avruskin

Publications and source records attributed to Gillian A Avruskin.

3 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↗

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↗