Originally Posted By: Bill Field
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Residential radon studies do not require linear no threshold extrapolations, so this is not an issue. Regarding Dr. Cohen?s data, even the National Council on Radiation Protection has invalidated his findings. In fact, Dr. Cohen has stated many times that his data can not be used to assess the risk posed by radon. Nonetheless, as the National Council on Radiation Protection points out, ?The clearest data for estimating lung cancer risk from low levels of radon exposure continue to rest with higher-dose studies of miner populations in which projections to zero dose are consistent with estimates arising from most case-control studies regarding residential exposure.?
RESIDENTIAL RADON EXPOSURE AND LUNG CANCER RISK: COMMENTARY ON COHEN'S COUNTY-BASED STUDY.
Health Physics. 87(6):647-655, December 2004.
Heath, C W. Jr *; Bond, P D. +; Hoel, D G. ++; Meinhold, C B. +[S]
National Council on Radiation Protection Summary report - http://www.ncrponline.org/
The large United States county-based study ( Cohen 1995, 2001) in which an inverse relationship has been suggested between residential low-dose radon levels and lung cancer mortality has been reviewed. While this study has been used to evaluate the validity of the linear nonthreshold theory, the grouped nature of its data limits the usefulness of this application. Our assessment of the study's approach, including a reanalysis of its data, also indicates that the likelihood of strong, undetected confounding effects by cigarette smoking, coupled with approximations of data values and uncertainties in accuracy of data sources regarding levels of radon exposure and intensity of smoking, compromises the study's analytic power. The clearest data for estimating lung cancer risk from low levels of radon exposure continue to rest with higher-dose studies of miner populations in which projections to zero dose are consistent with estimates arising from most case-control studies regarding residential exposure.
Health Phys. 2003 Apr;84(4):526-32.
Smoking as a confounder in ecologic correlations of cancer mortality rates with average county radon levels.
Office of Radiation and Indoor Air, U.S. EPA, Washington, DC 20460, USA. firstname.lastname@example.org
Cohen has reported a negative correlation between lung cancer mortality and average radon levels by county. In this paper, the correlation of U.S. county mortality rates for various types of cancers during the period 1970-1994 with Cohen's radon measurements is examined. In general, quantitatively similar, strongly negative correlations are found for cancers strongly linked to cigarette smoking, weaker negative correlations are found for cancers moderately increased by smoking, whereas no such correlation is found for cancers not linked to smoking. The results indicate that the negative trend previously reported for lung cancer can be largely accounted for by a negative correlation between smoking and radon levels across counties. Hence, the observed ecological correlation provides no substantial evidence for a protective effect of low level radon exposure.
J Radiol Prot. 2002 Jun;22(2):141-8.
The potential for bias in Cohen's ecological analysis of lung cancer and residential radon.
Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20892-7244, USA. email@example.com
Cohen's ecological analysis of US lung cancer mortality rates and mean county radon concentration shows decreasing mortality rates with increasing radon concentration (Cohen 1995 Health Phys. 68 157-74). The results prompted his rejection of the linear-no-threshold (LNT) model for radon and lung cancer. Although several authors have demonstrated that risk patterns in ecological analyses provide no inferential value for assessment of risk to individuals, Cohen advances two arguments in a recent response to Darby and Doll (2000 J. Radiol. Prot. 20 221-2) who suggest Cohen's results are and will always be burdened by the ecological fallacy. Cohen asserts that the ecological fallacy does not apply when testing the LNT model, for which average exposure determines average risk, and that the influence of confounding factors is obviated by the use of large numbers of stratification variables. These assertions are erroneous. Average dose determines average risk only for models which are linear in all covariates, in which case ecological analyses are valid. However, lung cancer risk and radon exposure, while linear in the relative risk, are not linearly related to the scale of absolute risk, and thus Cohen's rejection of the LNT model is based on a false premise of linearity. In addition, it is demonstrated that the deleterious association for radon and lung cancer observed in residential and miner studies is consistent with negative trends from ecological studies, of the type described by Cohen.
Health Phys. 1998 Jul;75(1):11-7.
Residential 222Rn exposure and lung cancer: testing the linear no-threshold theory with ecologic data.
Smith BJ, Field RW, Lynch CF.
College of Medicine, Department of Preventive Medicine and Environmental Health, University of Iowa, Iowa City 52242, USA.
In most rigorous epidemiologic studies, such as case-control and cohort studies, the basic unit of analysis is the individual. Each individual is classified in terms of exposure and disease status. However, in ecologic epidemiologic studies, the unit of analysis is some aggregate group of individuals. Summary measures of exposure and disease frequency are obtained for each aggregate, and the analyses focus on determining whether or not the aggregates with high levels of exposure also display high disease rates. The ecologic study design has major limitations, including ecologic confounding and cross level bias. Cohen has attempted to circumvent these limitations by invoking the linear no-threshold theory of radiation carcinogenesis to derive aggregate "exposures" from individual-level associations. He asserts that, "while an ecologic study cannot determine whether radon causes lung cancer, it can test the validity of a linear-no threshold relationship between them." Cohen compares his testing of the linear no-threshold relationship between radon exposure and lung cancer to the practice of estimating the number of deaths from the person-rem collective dose, dividing the person-rem by the number of individuals in the population to derive the individual average dose, and then determining individual average risk by dividing the number of deaths by the number of individuals in the population. We show that Cohen's erroneous assumptions concerning occupancy rates and smoking effects result in the use of the wrong model to test the linear no-threshold theory. Because of these assumptions, the ecologic confounding and cross level bias associated with Cohen's model invalidate his findings. Furthermore, when more recent Iowa county lung cancer incidence rates are regressed on Cohen's mean radon levels, the reported large negative associations between radon exposure and lung cancer are no longer obtained.
Health Phys. 1998 Jul;75(1):4-10
On the discrepancy between epidemiologic studies in individuals of lung cancer and residential radon and Cohen's ecologic regression.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
There is still substantial confusion in the radiation effects community about the inherent limitations of ecologic analysis. As a result, inordinate attention has been given to the discrepant results of Cohen, in which a negative estimate is observed for the regression of county mortality rates for lung cancer on estimated county radon levels. This paper demonstrates that Cohen's ecologic analysis cannot produce valid inference on the exposure-response relationship for individuals unless lung cancer risk factors (smoking, age, occupation, etc.) for individuals are statistically uncorrelated with indoor radon level within counties or unless risk effects for radon and other factors are additive. Both of these assumptions are contradicted in the literature. Thus, contrary to common assumption, when a linear no-threshold model is the true model for radon risk for individuals, higher average radon concentration for a county does not necessarily imply a higher lung cancer rate for the county. In addition, valid inference from county-level ecologic analysis and the elimination of the ecologic bias cannot be achieved with the addition of county-wide summary variables (including "stratification" variables) to the regression equation. Using hypothetical data for smoking and radon and assuming a true positive association for radon and lung cancer for individuals, the analysis demonstrates that a negative county-level ecologic regression can be induced when correlation coefficients for smoking and radon within county are in the range -0.05 to 0.05. Since adverse effects for radon at low exposures are supported by analysis of miner data (all data and data restricted only to low cumulative exposures), a meta-analysis of indoor radon studies, and molecular and cellular studies, and since ecologic regressions are burdened by severe limitations, the negative results from Cohen's analysis are most likely due to bias and should be rejected.