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What follows is the continuation, in serial form, of a central chapter from my book A Primer in the Art of Deception: The Cult of Nuclearists, Uranium Weapons and Fraudulent Science.
SCAM NUMBER SEVENTEEN: Disembowel the profession of health physics to such an extent that its members will turn a blind eye to the misdeeds of Government.
Of what use is the profession of health physics in protecting humanity from the hazards of radiation if none of its practitioners has the courage to speak out against Government abuse of science as exemplified by any of the previously mentioned scams?
Up to this point in Exhibit E, we have scrutinized that pesky and dodgy character dose, and witnessed some of the antics it is called upon to perform in the highly politicized extravaganza of downplaying the hazards of exposure to ionizing radiation. The time has come to turn attention to the other prankster in the carnival: risk. Determining the risks to health that accompany exposure is a central objective of the science of radiation protection. No sane community of human beings is going to allow the dispersal of a toxin within its midst unless it is confident that it has correctly assessed that toxin’s risk to health and found that risk to be acceptable. Analyzing ionizing radiation’s impact on health is a labyrinthine exercise, and conventionally, the issue has been the province of experts in the field. Due to the complexity of the subject matter, laymen have been forced to surrender their well-being to the radiation protection community and government decision makers. In a world operating on the principle that truth is the fundamental priority, this delegation of authority to the experts and those in power would be adequate to guarantee public health and communal well-being. Unfortunately, those who control the assessment of risk simultaneously control the perception of risk, and too much evidence has accumulated bearing witness to the fact that the integrity of the radiation protection community has been compromised by proponents of nuclear/radiological weaponry and commercial nuclear power. When the experts and those who sponsor them have their own priorities that take precedence over truth, the public is vulnerable to abuse. The fabric of a free and democratic society is rent asunder when its guardian institutions traffic in mischief in matters of basic science and replace truth with falsehood for the benefit of vested interests.
To estimate the potential threat to an individual or a population following a radiation release, the first requirement is a determination of the probable dosages involved. The scams revealed up to this point amply illustrate that the seemingly straightforward process of establishing objective dose measurements is an opportunity for great rascality and devilment. In addition to dosages, a body of epidemiological studies must be available that demonstrate from previous instances of exposure the relationship that exists between the size of a radiation dose and the incidence of disease. Exhibit C reviewed some of the currently relied upon studies and demonstrated their limitations. In particular, it highlighted the prominent place awarded the corrupted Hiroshima study and detailed how this study has been purposely designed to skew risk assessment in favor of the nuclear industry for generations to come. A third essential element for evaluating the risks following a radiation event is a reliable model of dose-response into which new data can be plugged in to derive estimates of collective health detriment in an emergency. For scenarios of low-dose exposure, the favored method of extrapolation from high-dose effects is the fundamental determinant of what risks are thought to exist. This explains the fierceness of the battle over the shape of the dose-response curve. The reigning model controls the perception of risk. From this point, a disturbing conclusion emerges: the objectivity of science is a myth. Those in power control the science, and they use their corrupted science to justify whatever programs they elect to sponsor.
When the human organism is exposed to ionizing radiation, deterministic effects and/or stochastic effects may be induced. A deterministic (nonstochastic) effect occurs when exposure exceeds some threshold dose and results directly from the effects of the killing of cells. It’s a predictable outcome observed in most or all of those receiving the threshold level of exposure, and its severity is dose-related. Deterministic effects have yet to be identified as occurring at low dosages. In contrast, stochastic effects are those that depend upon chance or probability. In whole-body doses of less than one sievert (100 rems), stochastic effects are the predominant concern. In doses above one sievert, stochastic effects can be produced in addition to deterministic effects. Cancer and inheritable genetic damage are examples of stochastic effects. These effects arise from cells that are altered by radiation and that manage to survive. The probability of their occurrence increases as the dose increases, but their severity is independent of dosage. At present, the majority of radiation scientists operate on the assumption that there is no minimum threshold dose required to induce stochastic effects. Even a single track through a cell, the lowest possible dose, is thought capable of producing stochastic effects, though the probability of this occurring is extremely low. This point is a major source of contention due to the many uncertainties of effect in the low-dose range. When stochastic effects are produced, they are initiated at the moment of exposure, but years or decades might elapse before the whole-organism response to these changes manifest as altered functioning and ill health.
In harmony with the computational system for determining dosages, mathematical models have been developed to assess the risk of cancer in both individuals and whole populations following radiation exposure. A number of organizations involved in radiation protection, such as UNSCEAR, BEIR, ICRP, and the Environmental Protection Agency (EPA), have published estimates of risk. Although differing in minor ways, they all are in substantial agreement. These estimates are based on the study of survivors from the bombings of Hiroshima and Nagasaki, on groups who received radiation for diagnostic or therapeutic purposes, and workers who received occupational exposure. Successful modeling of the risk of cancer incidence demands consideration on a wide range of variables. According to BEIR V:
"The risk depends on the particular kind of cancer; on the age and sex of the person exposed; on the magnitude of the dose to a particular organ; on the quality of the radiation; on the nature of the exposure, whether brief or chronic; on the presence of factors such as exposure to other carcinogens and promoters that may interact with the radiation; and on individual characteristics that cannot be specified but which may help to explain why some persons do and others do not develop cancers when similarly exposed."
For the sake of simplicity, the mathematical model to assess risk can be reduced to its bare essentials. Only three numbers are required to estimate the increased risk of cancer to a population resulting from radiation exposure: the dose to the average individual, the number of people receiving that dose, and the risk factor applicable to the type of cancer under consideration. To give an example, if the average dose to a population of 10 people is 100 rems, the collective dose is 1000 person-rems (10 x 100). Similarly, if the average dose received by a population of 10,000 people is 0.1 rem, the collective dose works out to be the same: 1000 person-rems. In order to calculate the number of fatal cancers expected in the two populations, the collective dose is multiplied by the appropriate risk factor. The risk factors per sievert (per 100 rems) have been developed by the international radiation protection agencies to cover different scenarios of whole-body exposure and/or exposure to individual tissues and organs. Note that when the identical collective dose in the two examples mentioned above are multiplied by the same risk factor, the number of cancers anticipated in each population is the same. This conclusion is a consequence of the Linear No-Threshold Hypothesis. Cancer yield is proportional to the collective dose. The same numbers of cancers will be produced whether 1,000,000 people each receive a thousandth of a rem or 1,000 people each receive one rem. In the low-dose range, this assumption of linearity is under increasing fire for either under- or overestimating the cancer yield or for being woefully simplistic.
To appreciate the function played by risk factors in estimating cancer incidence, a simple example will suffice. The 1990 ICRP absolute risk value for fatal cancer probability in the high dose and high dose region was 8 x 10-2 (0.08) per sievert. To calculate the number of fatal cancers in an exposed population, this risk factor is multiplied by the average dose to each member of the population which in turn is multiplied by the number of people receiving that dose. Thus, if 10,000 people each receive a dose of 1 sievert, the probable number of fatal cancers will be 800. (0.08 x 1.0 x 10,000 = 800). The utilitarian value of this methodology is obvious. In the aftermath of a radiation release, an estimate can be quickly generated satisfying the intellectual desire to come to terms with the health consequences of what has taken place long before the actual pain and suffering becomes apparent within the population, if they ever become apparent at all. (Of course, the stricken victim will be aware of his own pain and suffering, but he may be handicapped by the long latency period of radiation-induced cancer of ever knowing if the origin of his illness is radiation-related.)
Because it is difficult to observe low-dose effects in populations, attempts at estimation have extrapolated from relatively reliable high-dose effects. The data from Japan clearly shows an adverse health effect among adults who received a dose above 200 milliSieverts (20 rems) and children who received a dose about 100 milliSieverts (10 rems). The key question that draws daggers out from underneath lab coats is, what is the risk to health at levels of exposure below these dosages?
To gain an appreciation of the difficulties of determining cancer incidence at low doses, let’s suppose that in a population of 10,000 people, each member received a dose of only 10 millisieverts (1 rem, i.e., one hundredth of the previous example.) The expected number of fatal cancers in this instance would be 8 (0.08 x 0.01 x 10,000 = 8). Normally, approximately 20% of the population dies of cancer. So rather than 2,000 cancer deaths, the expected number of cancer deaths in the exposed population would be 2,008. Due to statistical fluctuations and normal levels of uncertainty, there is no way to be sure that radiation caused excess cancers in this population. As Caufield observes:
"With such a large base of cancers, it may be statistically impossible to detect a relatively small number of extra cancer deaths. Some scientists argue that in order to get statistically reliable data on the effects of doses on the order of one rem, it would be necessary to study 10 million exposed people, and a matching group of ten million people who have not been exposed to radiation. Matters are further complicated by the need to continue a study from the first exposure until death" [1].
Given these uncertainties, the radiation protection agencies rely on their risk factors for interpreting the health consequences of radiation accidents and planned radiation releases. These risk factors are the eyes for all human beings who wish to evaluate radiation effects, for they enable us to see what is invisible and unmeasurable. They inform us of the level of human suffering produced by nuclear weapons, nuclear reactors, radioactive waste, and now, non-nuclear weapons containing radioactive material.
At this juncture, the reader might reflect on a number of questions: What if the risk factors are wrong? What if they produce calculations that misrepresent, by underestimating, the actual health consequences of human exposure to radiation? Given that in the absence of direct observation, the risk factors are the central window through which we perceive the hazards of a radiation release, are they not the likely focal point for intentional malfeasance by the Cult of Nuclearists so as to keep the world ignorant of the breadth of their misdeeds? And finally, isn’t the raison d'être of the corrupted Hiroshima study now perfectly clear, since by it, the current risk factors are justified?
If the risk factors are wrong, humanity has been hoodwinked and rendered blind by artful lies. Crimes against humanity and crimes against life can be committed before our very eyes, and we will fail to see them for what they are. Could there be a more perfect crime than one committed before a world of blindfolded witnesses?
Exhibit F will testify to the falsehood of the current risk factors. But before we walk down that road, we must first explore the vagaries of that shifty character called “risk,” and observe some of the many tricks its handlers can make it perform to alter the perception of hazard of ionizing radiation.
Bibliography
[1] Caufield C. Multiple Exposures: Chronicles of the Radiation Age. Toronto: Stoddart; 1988.
