Cancer Mortality, State Mean Elevations, and Other Selected Predictors

This ecological inquiry compares cancer mortality rates in the U.S. to the predictor of natural background radiation (via land elevation means) along with eight other predictors thought to be associated with cancer mortality. Age-adjusted cancer mortality in 2006 was compared to the predictors of mean land elevation, percent of smokers, educational attainment, percent of population without health insurance, income, obesity, health perception, physical activity, and diet. Among the six predictors considered appropriate for multiple linear regression, three were found to be statistically significant; from strongest to weakest, these three were: smoking, land elevation, and educational attainment. The predictors of smoking and educational attainment have long been considered associated with cancer mortality. The finding that the predictor of land elevation / natural background radiation is inversely related to cancer mortality is another piece of evidence supporting the theory of radiation hormesis. In this study, land elevation / natural background radiation ranked second in predictive strength regarding cancer mortality, behind smoking and ahead of educational attainment. Since this is an ecological inquiry, no causal inferences can be made

Radiation Hormesis: Historical Perspective and Implications for Low-Dose Cancer Risk Assessment

Current guidelines for limiting exposure of humans to ionizing radiation are based on the linear-no-threshold (LNT) hypothesis for radiation carcinogenesis under which cancer risk increases linearly as the radiation dose increases. With the LNT model even a very small dose could cause cancer and the model is used in establishing guidelines for limiting radiation exposure of humans. A slope change at low doses and dose rates is implemented using an empirical dose and dose rate effectiveness factor (DDREF). This imposes usually unacknowledged nonlinearity but not a threshold in the dose-response curve for cancer induction. In contrast, with the hormetic model, low doses of radiation reduce the cancer incidence while it is elevated after high doses. Based on a review of epidemiological and other data for exposure to low radiation doses and dose rates, it was found that the LNT model fails badly. Cancer risk after ordinarily encountered radiation exposure (medical X-rays, natural background radiation, etc.) is much lower than projections based on the LNT model and is often less than the risk for spontaneous cancer (a hormetic response). Understanding the mechanistic basis for hormetic responses will provide new insights about both risks and benefits from low-dose radiation exposure