Superfund Research Program
New Mapping Method is Developed for Analysis of Environmental Epidemiological Data
Looking at disease patterns on a map provides some of the most provocative clues to environmental causes of disease. Unfortunately, these patterns are not always easy to interpret. A cluster of cases on a map might merely represent the pattern of where people live. Without some information on the underlying population density, maps of disease occurrence are almost impossible to understand. Determining population density can be challenging, however, because we usually only know the population of arbitrary geographic areas such as census tracts, towns or counties. Conversely, trying to find local excesses of disease by using routinely collected vital statistics may fail if the disease straddles boundaries or becomes "diluted" by a much larger area where disease rates are normal. New methods of picturing local excesses of disease are greatly needed.
Researchers at Boston University have developed a new mapping method that is providing a more effective way to identify disease hotspots. This method has been successfully used to produce maps of breast cancer occurrence in a section of Cape Cod, Massachusetts known to have elevated cancer rates. Research and development have been focused in particular on residents of Upper Cape Cod who developed breast cancer between 1983 and 1994.
The locations of all the cancer cases' residences for the last 40 years were coded and entered into a computerized mapping system that allows complex calculations to be performed on the map and its contents. Similar information was obtained from a random sample of controls. The availability of the geographic information from the controls allowed the researchers to make a picture of the background distribution of the population, which, along with the locations of the cancer cases, made it possible to produce the maps of breast cancer occurrence in Upper Cape Cod.
The resulting picture revealed the presence of a hotspot related to an activity at a nearby Superfund site. Although this activity had previously been identified as a possible factor in the excess cancer of this area, the identification was much less specific than what was found through the new mapping method and did not locate the area of excess geographically.
One of the special features of this mapping method is that it gives the researchers the capability to smooth the picture at will to average out random noise. Known as adaptive rate stabilization, this feature indicates the degree to which local rates of disease are increased or decreased. Additional techniques were developed to test whether the localized excesses appearing on the maps were produced by chance. The mapping method is being developed further to take into account other risk factors that might reflect disease risk.
This new method represents a significant advance in visualizing potential relationships between geography, environment and cancer. Since locations are geographically coded by latitude and longitude, questions of arbitrary geographic boundaries are resolved. This capability to "picture" disease rates gives both the researchers and the public a way to readily see where risks are high and low in a region. It can also provide clues to geographically-related environmental factors that might cause cancer.
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