Superfund basic research program: a model for contemporary research programs.
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Biomedical subjects
Publications and source records attributed to David Ozonoff.
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In 1998 we published the results of a study suggesting an association between breast cancer and perchloroethylene (PCE; also called tetrachloroethylene) exposure from public drinking water. The present case-control study was undertaken to evaluate this association further. The cases were composed of female residents of eight towns in the Cape Cod region of Massachusetts who had been diagnosed with breast cancer from 1987 through 1993 (n = 672). Controls were composed of demographically similar women from the same towns (n = 616). Women were exposed to PCE when it leached from the vinyl lining of water distribution pipes from the late 1960s through the early 1980s. A relative delivered dose of PCE that entered a home was estimated using an algorithm that took into account residential history, water flow, and pipe characteristics. Small to moderate elevations in risk were seen among women whose exposure levels were above the 75th and 90th percentiles when 0-15 years of latency were considered (adjusted odds ratios, 1.5-1.9 for > 75th percentile, 1.3-2.8 for > 90th percentile). When data from the present and prior studies were combined, small to moderate increases in risk were also seen among women whose exposure levels were above the 75th and 90th percentiles when 0-15 years of latency were considered (adjusted odds ratios, 1.6-1.9 for > 75th percentile, 1.3-1.9 for > 90th percentile). The results of the present study confirm those of the previous one and suggest that women with the highest PCE exposure levels have a small to moderate increased risk of breast cancer.
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Spatial distributions of disease occurrence and risk have traditionally served as a tool for identifying exposures of public health concern. Current software for manipulating geographic data (GIS) now allows many kinds of analyses not feasible before. This paper presents a method for producing a "picture" of disease risks based on residential history data from a population based case-control study. We illustrate the method using geographically coded data on individual-level risk factors, such as age and smoking, from a cancer study of the Upper Cape Cod region of Massachusetts for 1983-1986. Our results show the association between lung cancer and residential location as an indicator of exposure. Crude and adjusted odds ratios were estimated by adaptive rate stabilization and mapped using kriging as an interpolation method to examine the risk of lung cancer in the region. The crude and adjusted surfaces for various smoothing parameters were compared to identify areas of increased lung cancer not explained by standard risk factors. Such spatial patterns of disease risk may provide clues to exposures of importance or confirm associations with previously suspected exposures.
Locating geographic hot spots of cancer may lead to new causal hypotheses and ultimately to new knowledge of cancer-causing factors. The Cape Cod region of Massachusetts has experienced elevated incidence of breast cancer compared with statewide averages. The origins of the excess remain largely unexplained, even after the Upper Cape Cod Cancer Incidence Study investigated numerous potential environmental exposures. Using case-control data from this study (258 cases and 686 controls), we developed an exploratory approach for measuring associations between residential location and breast cancer incidence, adjusting for individual-level risk factors. We measured crude and adjusted odds ratios over the study region using fixed-scale grids and a smoothing algorithm of overlapping circular units. Polycircular hot spot regions, derived from the peak values of the smoothed odds ratios, delineated geographic areas wherein residence was associated with 60% [odds ratio (OR), 1.6; 95% confidence interval (CI), 0.8-3.2] to 210% (OR, 3.1; 95% CI, 1.3-7.2) increased incidence relative to the remainder of the study population. The findings suggest several directions for further research, including the identification of potential environmental exposures that may be assessed in forthcoming case-control studies.
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