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Low Dose Linearity: An Introduction

The idea that induction of cancer might be a stochastic process with the incidence proportional to dose dates back at least to the work of Crowther (1924). This was followed in 1928 by the recommendation of the International Commission on Radiological Protection that a proportional relationship between radiation dose and cancer incidence be assumed for a Prudent Public Policy. Following the second world war this recommendation became of great interest and was generally accepted. Cancers had been observed at doses of 30 Rem (0.5 Sievert) and higher and in some cohorts (such as the group of radium dial painters) there were indications of a threshold at about 20 Rems (0.2 Sv). Nonetheless the public perception arose that the linear-no threshold model was experimentally derived and is therefore true in the low dose region. This has in turn led to, or at least fed, a view that radiation at low doses is uniquely dangerous.

The session did not address the public policy consequences of this assumption, which are serious and fascinating in themselves, but focused on the direct information that is available. To this end I asked three experts on the most important cohorts to tell us the latest information that has been derived therefrom. The first speaker was Dr. Ronald Pierce, a statistician from Radiation Effects Research Foundation (RERF) in Hiroshima, funded half by the Japanese government and half by the US government at $200 million a year. These funds come "off the top" of the budget because of the US moral responsibility. A summary of his presentation follows this article. Dr. Elizabeth Cardis, a biologist who is Director of Radiation Programs of the International Agency for Research on Cancer, a UN organization, presented information on the health experience of the nuclear plant workers of the world (or that part which cooperates with her). Her article on the results from the IARC study appear below. Dr. Bernard Cohen has more data on radon measurements in homes than anyone else and an overview of his results are included in this issue. Bernie is well known to the society as a past recipient of the Bonner prize in nuclear physics.

Figure 1 describes the "conventional wisdom" about the effects of radiation on people. Anyone who receives an "acute" dose (received within a day or less) of 150 Rems (1.5 Sv) gets acute radiation sickness. At a dose of 350 Rems (LD50) half of those exposed will die, but the rest will recover. However, there remains a long term chronic effect of an increase in cancer even if the dose is given slowly, and there an increased chance of cancer even below 150 Rems. Most data are at 50 Rem (0.5 Sv) and above. The linear-no threshold line, labeled as the "pessimistic" dose response relationship, is espoused by national and international regulatory committees. A super pessimist believes that the effect at lower doses is greater than given by this curve. An optimist believes in a threshold below which there is no effect, and a super optimist believes that radiation is "good for you" below this threshold. Radiation and molecular biologists have various theories that describe this region but the role of this session is to discuss the direct data.

Before doing so I introduce an important relationship between threshold behavior and natural backgrounds of cancer. In a seminal paper, Crump et al. (1974) pointed out that if a pollutant produces cancer by the same mechanism as the background cancers, there is a linear relationship between the incremental does and the incremental impact almost independently of the biological model relating dose to response (see Figure 2). Since ALL types of cancer induced by radiation also occur naturally, this is an important observation. Does radiation act by the same mechanism as the causes of the natural backgrounds? If so, there is a low dose incremental linearity regardless of the biological dose mechanism. In this we should note that not all cancers are the same. Leukemia, for example, has a short latent period compared with the others, and it may well be that cancer at one site displays low dose linearity but not cancers at another. It is also worth noting that the argument of Crump et al is very general and applies to other pollutants and end points other than cancer (Crawford and Wilson, 1996).

There are several steps in proving a causal relationship between pollutant exposure and an effect:

1. Observation of an effect by a physician and an appeal to other physicians to look for the same effect. This is not proof, but the first step in stimulating a study.
2. An ecological study whereby average effects in a population are compared to doses averaged over the population.
3. A case control study whereby the dose experience of each victim is compared to a control group with otherwise similar characteristics, age, occupation, and gender (I insist here that no one corrects for sex which is a private matter).
4. A cohort study where a group of exposed individuals is followed throughout life and compared with others.
   From a physicist's perspective, we clearly have more information as we proceed from 1 to 4, but we have smaller statistical accuracy. The RERF and IARC studies follow groups 3 and 4. These studies have limited statistical significance at doses below 20 Rem, and even systematic errors may not be fully taken into account in the region where the increases in cancer rates are small.

Dr. Cohen discusses a study he has made in group 2, for the effects of radon gas on lung cancer. He obtains high statistical accuracy by comparing lung cancer rates in large populations with average radon levels in these communities. Epidemiologists dislike studies in group 2 and claim that you can tell nothing because of the "ecological fallacy" (Sidley and Samet 1995) which roughly speaking can be described by the observation that the average of ab is not necessarily the product of the averages of a and b. Dr. Cohen claims that he has avoided this fallacy, partially by the way he poses the question. He does NOT try to derive a dose response relationship but asks whether the prediction based upon the "conventional wisdom" of the linear dose response relationship hold. This was a source of discussion, and the last speaker Dr. Anthony Nero of LBL asserted that Cohen has fallen into the ecological fallacy, and that ecological studies such as these are worthless. We have included the available information here so that you may judge for yourself.

References

1. Crawford, M., and Wilson, R. (1996), "Low dose linearity: the rule or the exception?", Human and Ecological Risk Assessment 2:305-330.
2. Crowther, J. (1924), "Some considerations relative to the action of x-rays on tumor cells", Proc. Roy. Soc. Lond. B. Biol. Sci. 96:207-211.
3. Crump, K.S., Hoel, D. G., Langley, C. H., and Peto, R. (1976), "Fundamental carcinogenic processes and their implications for low dose risk assessment", Cancer Res. 36:2973-2979.
4. Sidley, C. A. and Samet, J.M. (1995), "Assessment of Ecological regression in the study of lung cancer and indoor radon", Amer. Jour. Epidemiology, v139 p312. Richard Wilson Lyman Laboratory, Harvard University, Cambridge, MA 02138

Patterns of excess risk in the RERF Life Span Study

This brief report summarizes the presentation on the major epidemiological findings regarding excess cancer among the atomic- bomb survivors, with some special attention to what can be said about low-dose risks. It is based on a 1950-90 mortality follow-up of about 87,000 survivors having individual radiation dose estimates. Of these about 50,000 had doses greater than 0.005 Sv, and the remainder serve largely as a comparison group. It is estimated that for this cohort there have been about 400 excess cancer deaths among a total of about 7800. Since there are about 37,000 subjects in the dose range .005--.20 Sv, there is substantial low-dose information in this study. The person-year- Seivert for the dose range under .20 Sv is greater than for any one of the 6 study cohorts of U.S., Canadian, and U.K. nuclear workers and is equal to about 60% of the total for the combined cohorts. It is estimated, without linear extrapolation from higher doses, that for the RERF cohort there have been about 100 excess cancer deaths in the dose range under .20 Sv. There is a statistically significant dose response when the data are restricted to those under about .05 Sv, although there are some issues pertaining to this that should be considered and are discussed in the full report.

Both the dose-response and age-time patterns of excess risk are very different for solid cancers and leukemia. One of the most important findings has been that the solid cancer (absolute) excess risk has steadily increased over the entire follow-up to date, similarly to the age-increase of the background risk. About 25% of the excess solid cancer deaths occurred in the last 5 years of the 1950-90 follow-up. On the contrary most of the excess leukemia risk occurred in the first few years following exposure.

The observed dose response for solid cancers is very linear up to about 3 Sv, whereas for leukemia there is statistically significant upward curvature in that range. Very little has been proposed to explain this distinction. Although there is no hint of upward curvature or a threshold for solid cancers, the inherent difficulty of precisely estimating very small risks along with radiobiological observations that many radiation effects are nonlinear in dose, leads to interest in exploring the maximal extent of nonlinearity with which these data would be consistent. Both this issue and possible explanations of the contrast between solid cancers and leukemia were addressed during the discussion.

The original talk was based on an RERF report which has since been published as "Studies of the Mortality of Atomic Bomb Survivors", Report 12, Part 1, Cancer: 1950-1990, Pierce, Shimizu, Preston, Vaeth, and Mabuchi, Radiation Research 146, 1-27 (1996)

Donald A. Pierce

Radiation Effects Research Foundation, Hiroshima

Collaborators in this work include K. Mabuchi, D. Preston, Y. Shimizu, Japan through its Ministry of Health and Welfare, and the Government of the U.S. through the National Academy of Sciences under contract with the Department of Energy.

Effects of Low Dose Protracted Exposures to Ionizing Radiation: Nuclear Worker Studies

Introduction
Current estimates of cancer risk associated with external exposure to low linear energy transfer (LET)1 ionising radiation are derived primarily from studies of the mortality of atomic bomb survivors in Hiroshima and Nagasaki and of patients irradiated for therapeutic purposes (1-4). Both these groups were exposed primarily at high dose rates. Radiation protection recommendations for environmental and occupational exposures have generally been based on the use of these estimates in conjunction with models to extrapolate the effects of such acute (or short-term) high-level exposures to the relatively low-dose, low-dose rate exposures of environmental and occupational concern, and across populations with different baseline cancer risks (4). These models are, inevitably, subject to uncertainties.

A direct assessment of the carcinogenic effects of long-term, low-level radiation exposure in humans can be made from studies of cancer risk among workers in the nuclear industry2 . Many of these workers have received low, above background doses of ionising radiation, predominantly from external g-ray exposures, and their radiation doses have been carefully monitored over time through the use of personal dosimeters. Published studies have covered cohorts of nuclear industry workers in the US, UK, and Canada (5- 30). Estimates of radiation induced risk from individual studies of such workers have been published and combined analyses have also been carried out in the US and the UK (31-33). The risk estimates for all cancers and for leukemia from individual studies have varied from negative to several times those derived from linear extrapolation from high dose studies. Because of the large degree of uncertainty, many of these estimates were consistent with an even wider range of possibilities, from negative effects to risks an order of magnitude greater than those on which the current radiation protection recommendations have been based.

Recognizing that these studies collectively provided most of the available information for direct quantification of the carcinogenic effect of protracted low-dose exposure to ionizing radiation, a decision was made by the principal investigators in 1988 to carry out combined analyses of the original data at IARC with the objective of providing more precise risk estimates for comparison with estimates derived through extrapolation from studies of atomic bomb survivors and other high dose populations. The detailed results of the analyses summarized here have been published (34-36).

Materials and Methods
Seven cohorts of nuclear industry workers in three countries were included in the combined analyses. They were selected on the basis of availability of adequate dosimetric, demographic, follow-up and mortality data. In all cohorts, the majority of workers had potential for external occupational exposure to ionizing radiation and were monitored through the use of personal dosimeters.

Although radiation exposure in the nuclear industry has been measured more accurately than exposure to most other occupational carcinogens, the exposure measurements were made to monitor adherence to radiation protection guidelines and not for epidemiological purposes. Dosimetry experts reviewed historical dosimetric practices in and across the various facilities and concluded that for the majority of workers in the analyses most of the dose was external, from higher energy (100 keV to 2.5 MeV) X- and g-rays, and that these (as well as dose from tritium) had been measured reasonably comparably in different facilities and at different times (35-36).
Analyses were based on a constant linear relative risk model, in which the relative risk was assumed to be of the form 1 + 'Z, where Z is the cumulative dose in Sv, and ' is the excess relative risk (ERR) per Sv. This model has been used in recent analyses of atomic bomb survivors (37) data and for the derivation of current radiation risk estimates by various international and national committees (1-4). It was chosen since there is not sufficient power in studies of nuclear workers to distinguish between different models of dose response and since the aim of our study was to test whether, using the same risk model, the slope of the dose-response estimated in the range of doses received - in a protracted fashion - by nuclear workers was similar to that obtained over a much wider range of doses received - acutely - by atomic bomb survivors.

To permit comparison between the ERRs estimated for the nuclear industry workers and from the atomic bomb survivors cohort, follow-up data to 1985 from the latter cohort were analysed at IARC in a similar way. The study population for these analyses was restricted to men exposed between the ages of 20 and 60 years, the subgroup most comparable to the population of nuclear workers.

The risk estimates for nuclear workers were also compared to the constant linear excess relative risk estimates for men exposed at the age of 20 or above derived from atomic bomb survivors data by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) (2). These estimates, reduced by a dose and dose-rate effectiveness factor of two, form one of the bases for the current recommendations of the International Commission for Radiological Protection (ICRP) (4).

Results
In the total study population there were 15825 deaths, of which 3830 were from cancers other than leukemia and 119 were from leukemia excluding CLL. The majority (85.4%) of the study subjects were men and they had received 98% of the total collective dose.
The estimates of ERR per Sv for leukemia excluding CLL and for all cancers excluding leukemia are shown in Table 1, together with the corresponding values from our estimation of the atomic bomb survivors data. The ERR for leukemia excluding CLL fell between the value for atomic bomb survivors estimated from a linear extrapolation to low doses and that estimated from a linear-quadratic extrapolation . The ERR for all cancers excluding leukemia was less than the linear estimate derived from atomic bomb survivors. In both cases, the 90% CIs about the ERR estimates for nuclear workers included values of the order of twice the linear estimates obtained from the atomic bomb survivors. The UNSCEAR estimates of the ERR were close to those we obtained from the atomic bomb survivors data and therefore bore a similar relationship to the estimates obtained from the nuclear workers.

Discussion
By combining studies of nuclear industry workers, we have estimated the excess risk of cancer associated with increasing cumulative doses of ionizing radiation. The estimates are the most precise yet to have been obtained directly from populations with protracted exposures to low levels of X and g-radiation. They suggest that the risk estimates obtained by extrapolation from the studies of atomic bomb survivors are unlikely to be substantially in error.

A major issue in radiation risk assessment is whether the cancer risk per unit cumulative dose is different for low-dose protracted exposures than for high-dose acute exposures. The risk estimates derived in this study were generally somewhat lower, but consistent with, estimates derived using constant linear models fitted to the results of high dose studies.

Experimental studies have provided evidence that linear extrapolation may overestimate such risks and, for this reason, the ICRP recommended reducing linear risks by a dose and dose-rate effectiveness factor (DDREF) of two (4). BEIR V used a linear-quadratic model for estimating leukemia risk and also made a recommendation that risks should be reduced to account for lower dose-rate exposures (1). If we assume that the difference in the risk estimates derived from the nuclear workers and the atomic bomb survivors studies is entirely attributable to the effect of dose and dose-rate, we could infer that the DDREF for leukemia excluding CLL is of the order of 1.7 with a lower limit of 0.6 and an upper limit of 37. There may be other differences, however, and at the present time the need for a DDREF cannot be assessed with certainty.

The upper confidence bounds presented in this paper are of particular interest because it has been said that the extrapolation process used to assess cancer risk following low dose protracted exposure may seriously underestimate this risk, possibly by an order of magnitude or more (38). These analyses indicate that if there has been underestimation, it is unlikely to have been by more than a factor of about two.

In conclusion, our estimates are the most precise direct estimates made so far of carcinogenic mortality risk following protracted exposure to low levels of radiation. They provide little evidence that the estimates which form the basis for current radiation protection recommendations are appreciably in error. Many of the workers in the study cohorts are still relatively young; 84.5% are still alive. Additional follow-up of these cohorts and studies of additional cohorts of workers are needed to further increase the precision of the estimates of radiation-related risk of cancer and thus to further strengthen the scientific basis for setting radiation protection standards.

This work was supported by a grant from the UKCCCR and a contract (No. ES-88-15) from the US NIEHS. Data on atomic bomb survivors were provided by the Radiation Effects Research Foundation (RERF) in Hiroshima, Japan. The conclusions in this paper are those of the author and do not necessarily reflect the scientific judgement or opinions of their sponsoring agencies nor of RERF or its funding agencies.

References

1. US NAS, Health Effects on Populations of Exposure to Low Levels of Ionizing Radiation. BEIR V Reports, US National Academy of Sciences, Washington DC (1990).
2. UNSCEAR, Sources and Effects of Ionizing Radiation. UNSCEAR 1988 Report, United Nations, New York (1988).
3. NIH (National Institutes of Health), Report of the National Institutes of Health Ad Hoc Working Group to Develop Radioepidemiological Tables. NIH Publications 95-2748, US Department of Health and Human Services, Washington DC (1985).
4. ICRP (International Commission on Radiological Protection), Recommendations of the International Commission on Radiological Protection. ICRP Report 60, Pergamon Press, Oxford (1991).
5. A.P. Polednak and E.L. Frome, Mortality among men employed between 1943 and 1947 at a uranium-processing plant. J. Occup. Med. 23, 169-178 (1981).
6. R.A. Rinsky, R.D. Zumwalde, R.J. Waxweiler et al., Cancer mortality at a Naval Nuclear Shipyard. Lancet 1, 231-235 (1981).
7. O.C. Hadjimichael, A.M. Ostfeld, D.A. D'Atri et al., Mortality and cancer incidence experience of employees in a nuclear fuels fabrication plant. J. Occup. Med. 25, 48-61 (1983).
8. J.F. Acquavella, L.D. Wiggs, R.J. Waxweiler et al., Mortality among workers at the Pantex weapons facility. Health Phys. 48, 735-746 (1985).
9. V. Beral, H. Inskip, P. Fraser et al., Mortality of employees of the United Kingdom Atomic Energy Authority, 1946- 1979. Br. Med. J. 291, 440-447 (1985).
10. H. Checkoway, R.M. Mathew, C.M. Shy et al., Radiation, work experience, and cause specific mortality among workers at an energy research laboratory. Br. J. Ind. Med. 42, 525-533 (1985).
11. P.G. Smith and A.J. Douglas, Mortality of workers at the Sellafield plant of British Nuclear Fuels. Br. Med. J. 293, 845- 854 (1986).
12. F.B. Stern, R.A. Waxweiler, J.J. Beaumont et al., A case- control study of leukemia at a naval nuclear shipyard. Am. J. Epidemiol. 123, 980-992 (1986).
13. E.A. Dupree, D.L. Cragle, R.W. McLain et al., Mortality among workers at a uranium processing facility, the Linde Air Products Company Ceramics Plant, 1943-1949. Scand. J. Work. Environ. Health 13, 100-107 (1987).
14. G.R. Howe, J.L. Weeks, A.B. Miller, A.M. Chiarelli and J. Etezadi-Amoli, A study of the health of the employees of Atomic Energy of Canada Limited. IV. Analysis of mortality during the period 1950-1981. Open literature report AECL-9442, Atomic Energy of Canada Ltd. Chalk River (1987).
15. G.S. Wilkinson, G.L. Tietjen, L.D. Wiggs et al., Mortality among plutonium and other radiation workers at a plutonium weapons facility. Am. J. Epidemiol. 125, 231-250 (1987).
16. V. Beral, P. Fraser, L. Carpenter et al., Mortality of employees of the Atomic Weapons Establishment, 1951-82. Br. Med. J. 297, 757-770 (1988).
17. H. Checkoway, N. Pearce, D.J. Crawford-Brown et al., Radiation doses and cause-specific mortality among workers at a nuclear materials fabrication plant. Am. J. Epidemiol. 127, 255- 266 (1988).
18.  D.L. Cragle, R.W. McLain, J.R. Qualters et al., Mortality among workers at a nuclear fuels production facility. Am. J. Ind. Med. 14, 379-401 (1988).
19. R.A. Rinsky, J.M. Melius, R.W. Hornung et al., Case-control study of lung cancer in civilian employees at the Portsmouth Naval Shipyard, Kittery, Maine. Am. J. Epidemiol. 127, 55-64 (1988).
20. K. Binks, D.I. Thomas and D. McElvenny, Mortality of Workers at Chapelcross Plant of British Nuclear Fuels. In: Radiation Protection - Theory and Practice. Proceedings 4th International Symposium, Malvern, June 1989. Radiation Protection 49-52 (1989).
21. E.S. Gilbert, G.R. Petersen and J.A. Buchanan, Mortality of workers at the Hanford site: 1945-1981. Health Phys. 56, 11-25 (1989).
22. G.M. Matanoski, Health Effects of Low-Level Radiation in Shipyard Workers. Report to US DOE, (1991).
23.  L.D. Wiggs, C.A. Cox-de-Vore and G.L. Voelz, Mortality among a cohort of workers monitored for 210Po: 1944-1972. Health Phys. 61, 71-76 (1991).
24. L.D. Wiggs, C.A. Cox-de-Vore, G.L. Voelz et al., Mortality among workers exposed to external ionizing radiation at a nuclear facility in Ohio. J. Occup. Med. 33, 632-637 (1991).
25. S. Wing, C.M. Shy, J.L. Wood et al., Mortality among workers of Oak Ridge National Laboratories - evidence of radiation effects in follow-up through 1984. J. Am. Med. Assoc. 265, 1397-1402 (1991).
26. G.M. Kendall, C.R. Muirhead, B.H. MacGibbon et al., Mortality and occupational exposure to radiation: first analysis of the National Registry for Radiation Workers. Br. Med. J. 304, 220-225 (1992).
27. P. Fraser, L. Carpenter, N. Maconochie et al., Cancer mortality and morbidity in employees of the United Kingdom Atomic Energy Authority, 1946-86. Br. J. Cancer 67, 615-624 (1993).
28. E.S. Gilbert, E. Omohundro, J.A. Buchanan et al., Mortality of workers at the Hanford site: 1945-1986. Health Phys. 64, 577- 590 (1993).
29. M.A. Gribbin, J.L. Weeks and G.R. Howe, Cancer mortality (1956-1985) among male employees of Atomic Energy of Canada Limited with respect to occupational exposure to external low- linear-energy-transfer ionizing radiation. Radiat. Res. 133, 375- 380 (1993).
30. A.J. Douglas, R.Z. Omar and P.G. Smith, Cancer mortality and morbidity among workers at the Sellafield plant of British Nuclear. Br. J. Cancer 70, 1232-1243 (1994).
31. E.S. Gilbert, S.A. Fry, L.D. Wiggs et al., Analysis of combined mortality data on workers at the Hanford Site, Oak Ridge National Laboratory and Rocky Flats Nuclear Weapons Plant. Radiat. Res. 120, 19-35 (1989).
32. E.S. Gilbert, D.L. Cragle and L.D. Wiggs, Updated analyses of combined mortality data for workers at the Hanford Site, Oak Ridge National Laboratory, and Rocky Flats Weapons Plant. Radiat. Res. 136, 408-421 (1993).
33. L. Carpenter, C. Higgins, A.J. Douglas et al., Combined analysis of mortality in three United Kingdom nuclear industry workforces, 1946-1988. Radiat. Res. 138, 224-238 (1994).
34. IARC Study Group on cancer risk among nuclear industry workers, Direct estimates of cancer mortality due to low doses of ionizing radiation: an international study. Lancet 344, 1039-1043 (1994).
35. E. Cardis, E.S. Gilbert, L. Carpenter, G.R. Howe, I. Kato, J.J. Fix, L. Salmon, G. Cowper, B.K. Armstrong, V. Beral, A.J. Douglas, S.A. Fry, J. Kaldor, C. Lav, P.G. Smith, G.L. Voelz and L.D. Wiggs, Combined analyses of cancer mortality among nuclear industry workers in Canada, the United Kingdom and the United States of America. IARC Technical Report 25, International Agency for Research on Cancer, Lyon (1995).
36. E. Cardis, E.S. Gilbert, L. Carpenter et al., Effects of low doses and low dose-rates of external ionizing radiation: Cancer mortality among nuclear industry workers in three countries.. Radiat. Res. 142, 117-132 (1995).
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38.  Stewart, A.M. and Kneale, G.M. (1990) A-bomb radiation and evidence of late effects other than cancer. Health Phys., 58, 729-735

Table 1
Comparison of excess relative risk (ERR) estimates per Sv (and 90% confidence intervals) between nuclear workers, atomic bomb survivors and other published estimates of risk from high dose studies (men only) (8)

Estimates of organ dose and recorded whole body dose were used, respectively in analyses of data from atomic bomb survivors and nuclear industry workers. The estimates are adjusted for age, sex, calendar period, facility and, with the exception of AECL, for socioeconomic status.

Footnotes

1. gamma and X-rays in the range 100 to 2500 keV

2. "Nuclear industry" is used to refer to facilities engaged in the production of nuclear power, the manufacture of nuclear weapons, the enrichment and processing of nuclear fuel or reactor or weapons research.  Uranium mining is not included.

3. Adjusted for age, SES, facility, and calendar time.

4. Simulated confidence interval.

5. Adjusted for age, city and calendar time.

6. Based on the linear term of a linear-quadratic (L-Q) dose-response model.. Elisabeth CardisInternational Agency for Research on Cancer (IARC), Lyon, France

Elisabeth Cardis
International Agency for Research on Cancer (IARC), Lyon, France

Test of the Linear-No Threshold Theory of Radiation Carcinogenesis

Test of the Linear-No Threshold Theory of Radiation CarcinogenesisThe cancer risk from low level radiation is normally estimated by use of a linear-no threshold (LNT) theory (with or without added terms that apply at higher doses) which is, prima facia, a logical consequence of the fact that a single particle of radiation interacting with a single cell nucleus can initiate a cancer. The number of initiating events is then proportional to the number of particles of radiation, and hence to the dose. However, this does not consider the role of biological defense mechanisms (BDM) that prevent the billions of potential initiating events we all experience from each developing into a fatal cancer. If exposure to low level radiation were to stimulate BDM, that effect would be added to the effect of LNT, causing a radical deviation from the predictions of LNT alone in the low dose region.

There is now abundant evidence that low level radiation (LLR) does indeed stimulate BDM. It has been shown that various types of cells previously exposed to LLR suffer fewer chromosome aberrations when later exposed to large radiation doses. This effect is ascribed to stimulated production of repair enzymes by the LLR. Pre-exposure to LLR reduces induction of mutations and increases survival rates of cells later exposed to high level radiation. LLR has been found to stimulate immune systems in mice as measured by various indicators, and it is generally believed that the immune system is an important contributor to BDM. These types of evidence raise serious questions about the application of LNT to LLR,which has cost the US public hundreds of billions of dollars, in spite of the fact that LNT has never been tested in the relevant dose region. The purpose of this paper is to provide such a test.

We developed a compilation of radon measurements from available sources which includes the average radon level, r, in homes for 1729 U.S. counties, well over half of all U.S. counties and comprising about 90% of the total U.S. population. Plots of age- adjusted lung cancer mortality rates, m, vs. r are shown in Figures 1a and 1c. We have grouped the counties into intervals of r (shown on the base-line along with the number of counties in each group) and displayed the mean value of m for each group, its standard deviation, and the first and third quartiles of the distribution. We see a clear tendency for m to decrease with increasing r, in sharp contrast to the increase expected from the fact that radon can cause lung cancer, shown by the line labelled "theory".

One obvious problem is migration: people do not spend their whole lives and receive all of their radon exposure in their county of residence at time of death where their cause of death is recorded. However, it is easy to correct the theoretical prediction for this, and the "theory" lines in Fig. 1 have been so corrected. As part of this correction, data for Florida, California, and Arizona, where many people move after retirement, have been deleted, reducing the number of counties to 1601. This deletion does not affect results.

A more serious problem is that this is an "ecological study", relating the average risk of groups (county populations) to their average exposure dose. In general, the average dose does not determine the average risk, and to assume otherwise is what epidemiologists call "the ecological fallacy". However, it is easily shown that the ecological fallacy does not apply in testing a LNT theory. All other problems with ecological studies that have been discussed in the epidemiology literature have also been investigated and found not to be applicable here.

Epidemiologists normally study the mortality risk to individuals, m', from their exposure dose, r', so we start from that premise using the BEIR-IV version of LNT, which in its simplified form is (see the paper listed below for the full treatment):

Summing these over all people in the county and dividing by the population gives:

m = [ S as + (1 - S) an ] ( 1 + b r )

(1) where m and r have the county average definitions given above, and S is the smoking prevalence--the fraction of the adult population that smokes. Equation (1) is the LNT theory we are testing here (in the full paper it is shown that our test also applies to all other LNT theories). It is derived by rigorous mathematics from the risk to individuals, with no problem from the ecological fallacy.

The bracketed term in (1) which we call m0, may be thought of as the correction for smoking. Figures 1b and 1d show m/m0 vs r. We fit the data (1601 points) to

m/m0 = A + B r

deriving values of B . The theory lines are from (1) with slight renormalization. We see that there is a huge discrepancy between measurements and theory of about 20 standard deviations. The theory predicts B = +7.3% per pCi/L, whereas the data are fit by B = -7.3 (+/- 0.6) and -8.3 (+/- 0.8) % per pCi/L for males and females respectively.

All explanations for the discrepancy that we could develop or that have been suggested by others have been tested and found to be grossly inadequate. Three independent sources of radon data have been used, but all give the same result. Three different sources of data on smoking prevalence similarly fail, including one based on lung cancer rates. In fact, it is found that if our best estimate of the width of the distribution of S-values for U.S. counties is correct, even a perfect negative correlation between radon and smoking prevalence eliminates only half of the discrepancy. If the width of the S-value distribution were as wide as the distribution of lung cancer rates, which is the largest credible width since other factors surely contribute to lung cancer rates, an essentially perfect negative correlation between radon levels and smoking prevalence in U.S. Counties would be required to explain the discrepancy. Such a strong correlation would be incredible.

The strong correlation between radon exposure and lung cancer mortality, albeit negative rather than positive, is unique to lung cancer; no remotely comparable correlation was found for any of the other 32 cancer sites. We conclude that the observed behavior is not something that can easily occur by chance.

To investigate effects of a potential confounding variable, data are stratified into quintiles on the values of that variable, and a regression analysis is done separately for each stratum. Since the potential confounder has essentially the same value for all counties in a given stratum, its confounding effect is greatly reduced in these analyses. An average of the slopes, B, of the regression lines for the five quintiles gives a value which is largely free of the confounding under investigation.

This test was carried out for 54 socioeconomic variables and none was found to be a significant confounder. In all 540 regression analyses (54 variables x 5 quintiles x 2 sexes), the slopes, B, were negative and the average B value for the five quintiles was always close to the value for the entire data set. This means that the negative correlation between lung cancer rates and radon exposure is found if we consider only the very urban counties or only the very rural, only the richest counties or only the poorest, only the counties with the best medical care or only those with the poorest medical care, and so forth for all 54 socioeconomic variables. It is also found for all strata in between, such as counties of average urbanicity, wealth, medical care, etc. The possibility of confounding by combinations of socioeconomic variables was also studied by multiple regression analyses and found not to be an important potential explanation for the discrepancy.

The stratification method was also used to investigate the possibility of confounding by geography, and physical features such as altitude, temperature, precipitation, wind, and cloudiness, but these factors were of little help in explaining the discrepancy. The negative slope and gross discrepancy with LNT theory is found if we consider the wettest areas or the dryest, the warmest areas or the coolest areas, etc.

The effects of the two principal recognized factors that correlate with both radon and smoking were calculated in detail: (1) urban people smoke 20% more but average 25% lower radon exposures than rural people; (2) houses of smokers have 10% lower average radon levels than houses of non-smokers. These were found to explain only 3% of the discrepancy. Since they are typical of the largest confounding effects one can plausibly expect, it is extremely difficult to imagine a confounding effect that can explain the discrepancy. Requirements on such an unrecognized confounder were listed, and they make its existence seem extremely implausible.

By far, the most plausible explanation I can find for this discrepancy is that the linear-no threshold theory fails, grossly over-estimating the cancer risk in the low dose, low dose rate region. There are no other data capable of testing the theory in that region.

This paper is a condensation of B.L. Cohen, "Test of the Linear-No Threshold Theory of Radiation Carcinogenesis for Inhaled Radon Decay Products", Health Physics 68: 157-174; 1995. References and more detailed treatments are given therein.

Bernard L. Cohen

University of Pittsburgh

ABM, START, and STARS program in Hawaii

Continuation of the Strategic Target System (STARS) program has serious implications for three major arms control agreements--the ABM treaty and the START I and START II treaties. A March 1995 General Accounting Office report [1] indicates that the Ballistic Missile Defense Organization (BMDO) was considering twelve STARS launches for FY 1995-2000 (see Table 1). Ten of these are said to support Theater Missile Defense (TMD). However, the GAO report notes that using STARS which was designed to simulate multiple- warhead ICBM's, for TMD tests raises ABM treaty compliance question. Only one of the twelve launches is currently funded. BMDO had intended to decide by the end of 1995 but is now evaluating other systems (HERA Piledriver and an air-launched target concept).

Table I. STARS Future Launch Schedule by Fiscal Year (F represents firm launch, P represents a potential launch)

The GAO report also indicates that the STARS project officials are promoting STARS for tests that are restricted by the START treaties. The 29th Agreed Statement of the START I treaty declares that the STARS rocket shall be considered as a booster for research and development purposes subject to the Intermediate Range Nuclear Forces (INF) treaty . The US position is that STARS is exempt from the START I restrictions on missile tests which encrypt telemetry data and from the START II ban of tests using land-based, multiple-warhead missiles. Therefore, using STARS for such tests technically would not violate the START treaties but would circumvent them.

The STARS program, managed by the US Army Space and Strategic Defense Command, originated in 1985 when SDI enthusiasts envisioned dozens of tests. The supply of Minuteman I boosters was insufficient for all of these tests, so it was decided to refurbish 20-year-old Polaris A-3 missiles and add a new third stage for STARS. Because the STARS booster did not have sufficient range to launch test objects from Vandenberg in California to the US ABM test range at Kwajalein (USAKA) in the Marshall Islands, the Kauai Test Facility (KTF) at the Pacific Missile Range Facility (PMRF) on the Hawaiian island of Kauai was chosen as the launch site. KTF was set up in 1963 as part of the Safeguard C program to maintain US readiness to resume atmospheric nuclear testing and is operated by Sandia National Lab. STARS is the largest missile ever launched from PMRF and required a new launch pad and related facilities.

Initially, forty STARS launches were envisioned over a ten-year period. Many of these launches were to use the Operations and Deployment Experiments Simulator (ODES) which could dispense multiple test objects and thus simulate an ICBM bus dispensing warheads and decoys. Several of the tests were to involve space- based sensors as well. The STARS Environmental Assessment [2] contains the following statement about the need for and purpose of STARS:

The USASSDC, in supporting the SDI research and development effort, requires sufficient quantities of boosters with the necessary thrust and maneuvering capability to deliver non- nuclear, experimental payload vehicles to USAKA to simulate intercontinental ballistic missile (ICBM) re-entry conditions. These experiments are required to evaluate research data on candidate operational systems to determine the feasibility of developing an effective ballistic missile defense.

By Firing two stages upward and the third stage downward during the descent, the payload simulates ICBM re-entry conditions in the vicinity of USAKA, 3763 kilometers (2,338 miles) from the existing facilities at KTF.
Opposition to STARS in Hawaii came from Kauai residents, environmental groups, and native Hawaiians. Contentious issues included the reliability of the STARS booster, impacts of hydrogen chloride and other emissions, impacts on Kauai's image and tourism, and the SDI program in general. A coalition of native Hawaiian groups opposed the launches because the STARS launch pad is adjacent to Nohili dune, an ancient Hawaiian burial site.

The first STARS launch was delayed until 26 February 1993 by legal challenges to various STARS environmental studies, Congressional action which required an Environmental Impact Statement, and Hurricane Iniki, which devastated much of Kauai in September of 1992 [3]. The second STARS launch on 25 August 1993 included a British experiment called Zodiac Beauchamp, which apparently involved a new reentry vehicle. Attempts to get detailed information about this test were unsuccessful. BMDO was willing to state that it was "not a warhead". The third STARS launch was the first test of ODES and took place on 22 July 1994, the last day of the launch window, as Hurricane Emilia was south of Kauai.

After the second STARS launch, BMDO was planning eleven more STARS launches in support of National Missile Defense (NMD). At least four of these launches (missions 3-6) would have encrypted telemetry data. The October 1993 Defense Department "Bottom-Up Review" led to cancellation of all but two of these--the first ODES test and another ODES test, launched on 31 August 1996, that dispensed 26 different objects to test sensors on the Midcourse Space Experiment (MSX) spacecraft, which was launched from Vandenberg on 24 April 1996. An article in the 6 September Honolulu Advertiser reported that no additional STARS launches are scheduled but that STARS is being considered for a 1998 launch associated with the Kinetic Energy Anti-Satellite Program.

From the limited information available on the newly proposed STARS launches, it appears that tests relevant to NMD have been given the more palatable TMD label. The shift in emphasis to TMD by STARS proponents raises further doubts about their credibility. A September 1993 GAO report [4] noted that there were viable alternatives for NMD tests planned for STARS launches. In a letter to Defense Secretary Les Aspin which accompanied the release of this GAO report, Representative John Conyers concluded, "Star Wars officials apparently misled the public and the Congress on the existence of acceptable alternatives to launching these test missiles from Hawaii." He also questioned the annual expenditure of $14.1 million for 55 Sandia employees assigned to STARS and recommended canceling STARS to save $160 million.

In response to my request for information about the status of STARS compliance with the ABM treaty, I received an Information Paper dated 14 March 1996 from USASSDC. This paper states that the Defense Dept. Compliance Review Group determined "that STARS could be used as a target booster for testing either theater missile defense (TMD) or national missile defense (NMD) programs" in June of 1995. However, it also notes that "STARS can be used to boost targets for either NMD or TMD as long as the target parameters satisfy the demarcation between ABM and TMD components and systems" and that "clarification of the precise ABM/TMD demarcation is presently under negotiation with Russia." A possible demarcation from the FY-1996 Defense Authorization Bill is that tests against target boosters with range exceeding 3,500 km would qualify as ABM tests. It seems likely that the STARS booster could be used at ranges beyond 3,500 km, since the previous launches had ranges near 3,500 km even with the 3rd stage fired downward. Thus, using STARS for TMD tests would raise questions about compliance with the ABM/TMD limits and with Article VI of the ABM treaty, which bans tests of the TMD systems in an ABM mode.

What is the future of STARS? The FY-1996 Defense Appropriations Bill provided $10 million for STARS and directs BMDO to "take no action to terminate or place the STARS program in a caretaker status." Presumably STARS faces competition for TMD funds from programs that will actually use short-range missiles at White Sands and at Kwajalein. If BMDO operates as in the past, it is unlikely that there will be any discussion of these alternative outside BMDO. What I believe is needed before BMDO decides the future of the STARS is public discussion, at least in the US Senate, about the implications for the ABM and START treaties. This discussion should be part of the broader debate about the goals of the US BMD program and US policy on the ABM treaty.
The author has followed the STARS program closely since its inception but has not worked in it and does not speak for it. The Views expressed are those of the author and do not necessarily represent those of the University of Hawaii.

References

1. Ballistic Missile Defense: Current Status of  Strategic Target System, U.S. General Accounting Office  GAO/NSIAD-95-78 (March 1995)
2. STARS Environmental Assessment, U. S. Army Strategic  Defense Command (July 1990)
3. "STARS no star on Kauai," Bulletin of the Atomic  Scientists (April 1993), pp. 11-13
4. Ballistic Missile Defense: Strategic Target System Launches from Kauai, U.S. General Accounting Office  GAO/NSIAD-93-270 (Sept. 1993)

Michael Jones

University of Hawaii, Honolulu, Hawaii 96822