Use of GIS and Exposure Modeling as Tools in a Study of Cancer Incidence in a Population Exposed to Airborne Dioxin

In environmental health research there is a recognized need to develop improved epidemiologic and statistical methods for rapid assessment of relationships between environment and health. Exposure assessment is identified as a major challenge needing attention. In this study an exposure simulation model was used to delimit almost exactly in space and time an urban population exposed to airborne dioxin. A geographic information system (GIS) was used as the electronic environment in which to link the exposure model with the demographic, migration, and cancer data of the exposed population. This information is available in Denmark on an individual basis. Standardized incidence ratios (SIRs) for both men and women in 10-year age bands were calculated for three different exposure areas. Migration patterns were outlined. SIRs showed no excess of cancer incidences during the time span chosen (13 years; 1986–1998) in the whole exposed area or in the medium or higher polluted areas. The exposure model appeared very useful in selection of the appropriate exposure areas. The integration of the model in a GIS together with individual data on addresses, sex, age, migration, and information from routine health statistics (Danish Cancer Registry) proved its usefulness in demarking the exposed population and identifying the cancers related to that population. Less than one-third of the study population lived at the same address after 13 years of observation, and only half were still residing in the area, indicating migration of people as a major misclassification

Spatial variations in the incidence of breast cancer and potential risks associated with soil dioxin contamination in Midland, Saginaw, and Bay Counties, Michigan, USA

<p>Abstract</p> <p>Background</p> <p>High levels of dioxins in soil and higher-than-average body burdens of dioxins in local residents have been found in the city of Midland and the Tittabawassee River floodplain in Michigan. The objective of this study is threefold: (1) to evaluate dioxin levels in soils; (2) to evaluate the spatial variations in breast cancer incidence in Midland, Saginaw, and Bay Counties in Michigan; (3) to evaluate whether breast cancer rates are spatially associated with the dioxin contamination areas.</p> <p>Methods</p> <p>We acquired 532 published soil dioxin data samples collected from 1995 to 2003 and data pertaining to female breast cancer cases (<it>n </it>= 4,604) at ZIP code level in Midland, Saginaw, and Bay Counties for years 1985 through 2002. Descriptive statistics and self-organizing map algorithm were used to evaluate dioxin levels in soils. Geographic information systems techniques, the Kulldorff's spatial and space-time scan statistics, and genetic algorithms were used to explore the variation in the incidence of breast cancer in space and space-time. Odds ratio and their corresponding 95% confidence intervals, with adjustment for age, were used to investigate a spatial association between breast cancer incidence and soil dioxin contamination.</p> <p>Results</p> <p>High levels of dioxin in soils were observed in the city of Midland and the Tittabawassee River 100-year floodplain. After adjusting for age, we observed high breast cancer incidence rates and detected the presence of spatial clusters in the city of Midland, the confluence area of the Tittabawassee, and Saginaw Rivers. After accounting for spatiotemporal variations, we observed a spatial cluster of breast cancer incidence in Midland between 1985 and 1993. The odds ratio further suggests a statistically significant (<it>α </it>= 0.05) increased breast cancer rate as women get older, and a higher disease burden in Midland and the surrounding areas in close proximity to the dioxin contaminated areas.</p> <p>Conclusion</p> <p>These findings suggest that increased breast cancer incidences are spatially associated with soil dioxin contamination. Aging is a substantial factor in the development of breast cancer. Findings can be used for heightened surveillance and education, as well as formulating new study hypotheses for further research.</p

A European Health and Environment Information System for disease and exposure mapping and risk assessment

The European Health and Environment Information System (EUROHEIS) project aims to improve understanding of the links between environmental exposure, health outcome and risk, by developing integrated information systems for the rapid assessment of relationships between the environment and health at a geographical level.The project is a feasibility study to assess the possibility of implementing systems for point source investigations and disease and exposure mapping in eight European countries (UK, Sweden, Finland, Denmark, Spain, Italy, France and Eire). The partners involved in this project have been at the forefront of developing systems and methodologies for the appraisal and analysis of disease occurrence in small geographical areas as related to point source exposures and disease mapping within their respective countries. A system for point source investigations, including some disease mapping capabilities, has already been developed within the UK. The project aims to use this expertise and experience to extend and apply the systems and methodologies across the participating countries.The project provides a detailed report of the geographically referenced health, environmental, population, socio-economic and geographical datasets available for use in developing the systems within the participating countries. Accessibility, coverage, completeness, quality, and feasibility issues related to their use are addressed.Recommendations, specifications and guidelines on the practical implementation of computerised systems for rapid point source investigation and disease and exposure mapping within each partner country are developed. Sets of core data requirements for various levels of implementation are identified.The possibilities for assessing socio-economic status from the various routinely collected data sources within the participating countries and incorporating these into the systems are explored, together with mechanisms for elucidating inequalities in health and exposure. The impact of data quality and resolution on estimates of disease occurrence are also considered. Previously developed statistical methodologies (including Bayesian statistical models using WinBUGS) are applied within some of the participating countries.The results from the project are to be widely disseminated within the partner countries and the European Community as a whole (including the development of an internet site) and should form the basis for the future practical implementation of the systems and methodologies within the participating countries.<br/