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   ICRP Radiation Model Inadequacies
   Radiation Workers
   Radiation Epidemiology
   Ian Goddard Explains the Linear No-Threshold Model

Radiation Health Effects

ICRP Radiation Model Inadequacies

The officially-sanctioned International Commission of Radiological Protection (ICRP) model masquerades as being scientifically based. It is being used to underestimate cancer and other detrimental health risks of radiation exposure, misrepresent nuclear accident risks, dismiss actual health findings, and excuse inadequate monitoring of the contamination levels.

After millions of dollars spent every year since the 1940s to study radiation health effects, you might have thought there would be no doubt that ionizing radiation, even at low doses, involves risks to health, including increased likelihood of cancers, leukemia and genetic effects. Prominent scientific bodies have concluded, repeatedly, that there is no threshold: even a low dose causes some increased risk, and higher doses cause more risk. A single photon or a single high-speed particle can cause unrepairable damage to our cells, including genetic damage.

The risk of cancer from radiation exposure doses, as presented by the industry, does make the risk of cancer appear relatively small in many cases - the problem is that these predictions are based on biased studies and the risks are higher than the widely accepted International Commission on Radiological Protection (ICRP) model predicts, at least by a factor of 100.

To understand the damage from low radiation doses, begin with Dr. Alice Stewart's 1956 Oxford survey. The exposures in Stewart's study were less than one track per nucleus—and doses don't get lower than that. The Oxford study results showed that x-rays to children in utero increased the likelihood of death by childhood cancer and leukemia.

Stewart's result was controversial for years because neither the nuclear industry nor the medical industry wanted to accept her findings. But several subsequent studies verified her results.

The European Committee on Radiation Risk (ECRR) was formed in 1998 because of criticisms of the ICRP risk models. The ECRR consists of scientists and risk specialists from within Europe but takes evidence from experts worldwide. It presented its findings in 2003 and again in 2010. The ECRR describes important flaws in the ICRP risk model and provides new weighting factors to modify the ICRP model.

Several accessible information resources include:

ECRR - 2010 European Recommendations of the European Committee on Radiation Risk - The Health Effects of Exposure to Low Doses of Ionizing Radiation, Regulators Edition: Brussels 2010.

Gofman, John W., M.D., Ph.D., "Radiation-Induced Cancer from Low-Dose Exposure: An Independent Analysis, 1990, Committee for Nuclear Responsibility, Inc.

Kohnlein,W, PhD., and Nussbaum, R. H., Ph.D., "False Alarm or Public Health Hazard?: Chronic Low-Dose External Radiation Exposure, Medicine and Global Survival, January 1998, Vol. 5, No. 1.

Radiation Workers

The energy worker compensation act, EEOICPA, has paid out billions of dollars to workers with toxin and radiation-related cancers. This should provide some insight about DOE's effectiveness in protecting human health, especially under more lenient radiation protection standards of the past.

The Center for Disease Control (CDC) has under its management the worker dose reconstruction analysis to determine worker claim eligibility and while some claimant favorable assumptions are applied, DOE contractor statements are assumed to be honest while workers statements are doubted. Apparently no effort is made by CDC or its National Institute of Occupational Health to see if DOE contractor claims change over time or to identify facilities with a high number of claims.

The Energy worker compensation act (EEOICPA) points out that "studies indicate than 98 percent of radiation-induced cancers within the nuclear weapons complex have occurred at dose levels below existing maximum safe thresholds." (See 42 USC 7384, The Act-Energy Employees Occupational Illness Compensation Program Act of 2000 (EEOICPA), as Amended.)

See the website for the Center for Disease Control, National Institute of Occupational Safety and Health, Division of Compensation Analysis and Support here.

See testimony at a July 29, 2014 NIOSH meeting in Idaho Falls concerning chemical, drinking water, dose falsification and other issues here.

A NIOSH dose reconstruction document for the EEOICPA law states that at INL even in 1961, radiation was "carefully monitored and well-documented." Estimates of the radiological releases back then have been shown to be underestimates. Many of the health-significant radionuclides were not measured or estimated. Descriptions by DOE management attempting to show they were performing competently do not reflect reality.

NIOSH IREP is used to calculate the Excess Relative Risk and Probability of Causation for radiation workers exposed in the past to radiation who have been diagnosed with cancer. You and use it online at IREP

Inadequate monitoring of chemical vapor hazards has been in the news at Hanford recently, and chemical hazards contribute to health risks for INL workers as well.

It is important to understand that a worker 5 Rem per year permissible limit is not protective of health, despite the fact that it may take a decade for cancer to occur.

Comparisons of doses to the DOE and NRC annual dose limit of 5 rem for workers are misleading. First of all, the 5 rem/yr dose is not protective of workers although in comparisons it is made to appear as a harmless dose. The permissible dose to the public from routine emissions of 100 mrem annually is a health compromising dose and a huge impact for people exposed for multiple years. While comparisons imply that people could safely attain 5 rem doses each year, it is known that such doses would greatly increase cancer and other health risks. Therefore, the industry has applied various limits to radiation workers such as a limit on the cumulative dose in any 10 year period and the lifetime cumulative dose a worker may receive. The lifetime average dose is restricted to 1.5 rem/yr (1993 NCRP) or less than 10 rem (ICRP 1990).

It is important to note that the permissible 5 rem annual whole body dose is not recognized as a safe dose and adverse health effects have been found for nuclear workers receiving doses far below 5 rem annually. It is natural to think that radiation permissible limits are "safe" levels of radiation, but that has never been the case. Post-1960 permissible limits were set with the knowledge that there was no safe dose; they stated that it was hoped that the benefits of the nuclear industry would outweigh the health risks. The permissible limits are set less on biological facts than on what appeared to be reasonable at the time in order to not hamper the nuclear industry.

It is also important to remember just how low the doses are in studies of nuclear workers that have found an increased risk of cancer and leukemia. Epidemiologic studies have found the increased risk of cancer in nuclear workers even though the cumulative doses were less than 2 rem and usually accumulated in less than 40 mrem increments.

Radiation workers may need multiple Complete Blood Counts following a suspected significant radiation exposure from external radiation or from an internal dose due to inhalation, ingestion or wound entry of radionuclides in to the body. Bioassay of urine and fecal samples is conducted to track radionuclide excretion following an intake of radionuclides. Understanding Complete Blood Count Results Following Radiation Exposure, by Tami Thatcher, July 2018.

Radiological and Chemical Exposures at the Idaho National Laboratory That Workers May Not Have Known About - How Health is Harmed by Uranium, Plutonium and Other Radionuclides and Chemicals and Possible Nutritional Support Strategies, by Tami Thatcher, April 2017

Radiation Epidemiology

The National Cancer Institute has made an interactive I-131 fallout map available online. This is only for Nevada Test Site weapons fallout and does not include intentional or accidental releases from the Idaho National Laboratory. I-131 interactive map. Enter the year you were born, county you lived in, and milk drinking habits and the name and date of the weapons tests affecting your area and your estimated dose will be provided.

It is important to know DOE's history of concealing unfavorable epidemiology results in the past. DOE's misbehavior resulted in congressional hearings and a special panel convened by former Energy Secretary Wakins, ending DOE's direct control of epidemiologic studies.

Many past examples of dismissing adverse health effects of radiation exposure in the Department of Energy's weapons and nuclear complex are described in Dead Reckoning, a report by Steven Wing specifically about the investigation of health effects of Plutonium, and by Tim Conner.

The ECRR also summarizes the problems plaguing many epidemiology studies that are so important to the study of radiation worker and public health. Some of the problems that have occurred in epidemiologic studies are highlighted below:

  • The wrong dose conversion factors are used to assess the significance of the doses (this is a key point from the ECRR).
  • The dose estimates are believed to be known, but in reality are not representative of the doses actually received. (This happened in the U.S. regarding the Three Mile Island nuclear accident.)
  • The control group (the group not exposed to radiation) has received elevated radiation levels, because of the distribution of contaminated food from fallout, for example.
  • The control group may not be representative, i.e., the healthy worker effect means that this group needs to be compared to other healthy and economically similar workers. (When the healthy worker effect is accounted for, the ECRR notes that nuclear workers have double the risk of cancer within 5 years of working in the industry.)
  • The sample group (the group exposed to radiation) is diluted with many people who have not received a elevated radiation exposure. (This is what happens when county statistics are used without regard for proximity to the nuclear facility and has been the historical basis for the NRC to state that nuclear plants don't cause cancer.)
  • Inadequate definition of endpoint, such as the focus by death from cancer while excluding the occurrence of cancer, or the exclusion of infant and perinatal mortality.
  • The wrong conclusions are drawn from the data.
  • The data has been tampered with, such as the withholding or falsification of data required by Soviet authorities in forbidding that medical professionals attribute the cause of illness to radiation or the withholding or inaccurate underreporting of the actual doses in dosimetry records by the Department of Energy.

Data tampering? Yes, in the former USSR, but in the United States? In a letter by Ernest Sternglass, PhD to Dr. Steven Chu, the Secretary of Energy:

"Therefore, when it was discovered in the 1960's that small amounts of fission products produced much greater damage than had been expected, and not only leukemia and other forms of cancer but also premature births, low birth-weight and infant mortality, it was kept secret by our government for fear that it would endanger the deterrent value of the nuclear arsenal."

Ian Goddard Explains the Linear No-Threshold Model and Looks at Epidemiology Since the 2006 BEIR VII Report

Ian Goddard put together a video explaining the often debated "linear no-threshold" radiation health risk model. Nuclear proponents often argue that at doses below 10 rem there is no harm; they propose that there is a threshold below which radiation causes no harm. Other proponents argue that hormesis theory shows that radiation at low doses has a protective effect. Ian reviews human epidemiology studies that have been published since the National Academy of Sciences published its radiation health study in 2006. The BEIR VII study had concluded that the linear no-threshold model provided the best fit of the available human epidemiology. Ian's look supports that the BEIR VII study represents or underrepresents radiation health risk and that the linear no-threshold model is still appropropriate.

Epidemiology studies cited by Ian Goddard:

Pooling of dose responses animated

National Academy of Sciences (2006). BEIR VII. http://www.nap.edu/read/11340

Solid-Cancer Dose Responses (adult and mixed age) Post-BEIR VII

Boice JD et al (2006). Mortality among Radiation Workers at Rocketdyne (Atomics International), 1948–1999, Radiat Res. 166(1 Pt 1):98-115. http://pubmed.gov/16808626

Cardis et al (2007). The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: estimates of radiation-related cancer risks. Radiat Res. 167(4):396-416. http://pubmed.gov/17388693

Ronckers et al (2008). Multiple diagnostic X-rays for spine deformities and risk of breast cancer. Cancer Epidemiol Biomarkers Prev. 17(3):605-13. http://pubmed.gov/18349278

Muirhead et al (2009). Mortality and cancer incidence following occupational radiation exposure: third analysis of the National Registry for Radiation Workers. Br J Cancer. 13; 100(1): 206–212. http://pubmed.gov/19127272

Ozasa et al (2012). Studies of the Mortality of Atomic Bomb Survivors, Report 14, 1950–2003: An Overview of Cancer and Noncancer Diseases. Radiat Res. 177(3):229-43. http://pubmed.gov/23289384

Metz-Flemant et al (2013). Mortality associated with chronic external radiation exposure in the French combined cohort of nuclear workers. Occup Environ Med. 70(9):630-8. http://pubmed.gov/23716722

Kashcheev et al (2015). Incidence and mortality of solid cancer among emergency workers of the Chernobyl accident: assessment of radiation risks for the follow-up period of 1992–2009. Radiat Environ Biophys. 54(1):13-23. http://pubmed.gov/25315643

Davis et al (2015). Solid Cancer Incidence in the Techa River Incidence Cohort: 1956–2007. Radiat Res. 184(1):56-65. http://pubmed.gov/26121228

Sokolnikov et al (2015). Radiation Effects on Mortality from Solid Cancers Other than Lung, Liver, and Bone Cancer in the Mayak Worker Cohort: 1948–2008. PLoS One. 26;10(2):e0117784. http://pubmed.gov/25719381

Richardson et al (2015). Risk of cancer from occupational exposure to ionising radiation: retrospective cohort study of workers in France, the United Kingdom, and the United States (INWORKS). BMJ. 351:h5359. http://pubmed.gov/26487649.

Solid-Cancer Dose Responses (children) Post-BEIR VII

Spycher et al (2015). Background ionizing radiation and the risk of childhood cancer: a census-based nationwide cohort study. Environ Health Perspect. 123(6):622-8. Shown @ 6:20 but not included in the pooled graph graph due to x axis being dose rate, not cumulative dose. http://pubmed.gov/25707026

Pearce et al (2012). Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet. 380(9840):499-505. http://pubmed.gov/22681860

Mathews et al (2013). Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians. BMJ. 21;346:f2360. http://pubmed.gov/23694687

Kendall et al (2013). A record-based case–control study of natural background radiation and the incidence of childhood leukaemia and other cancers in Great Britain during 1980–2006. Leukemia. 27(1):3-9. http://pubmed.gov/22766784

Child-only leukemia graphs shown after 6:55 are from Pearce and Kendall above.

Pooled solid-cancer studies animation:

Note: the pooled graphs use the Excess Relative Risk (ERR) standard where baseline risk is valued @ 0. Included graphs using the Relative Risk (RR) standard, where baseline risk is valued @ 1, are fit into the pooled graph by the standard definition: ERR = RR - 1

In the case of Mathews et al (2013) (fitted @ 3:21), the y axis is Incidence Rate Ratio (IRR), which is equivalent to RR. Additionally, the x axis in Mathews is a count of CT scans. As per Table 8, the average scan in the 5-year-lag group whose graph I used (given it is between the 1- and 10-year lag groups) was 4.5 mSv, with the maximum data point representing a sub-group with an average of 3.5 scans, hence 15.75 mSv is the x-axis value for the highest-dose data point (see Mathews Fig 2 for the 1-year lag and Appendix Figures A(a,b) for the 5- and 10-year lag graphs http://bmj.com/content/bmj/suppl/2013... , of which I used the 5-year lag).