期刊
RADIATION RESEARCH
卷 179, 期 3, 页码 332-342出版社
RADIATION RESEARCH SOC
DOI: 10.1667/RR3054.1
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资金
- U.S. Department of Energy (DOE) under the JCCRER
- Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health
- Japanese Ministry of Health, Labour and Welfare (MHLW)
- U.S. Department of Energy through the National Academy of Sciences
Workers at the Mayak nuclear facility in the Russian Federation offer a unique opportunity to evaluate health risks from exposure to inhaled plutonium. Risks of mortality from lung cancer, the most serious carcinogenic effect of plutonium, were evaluated in 14,621 Mayak workers who were hired in the period from 1948-1982, followed for at least 5 years, and either monitored for plutonium or never worked with plutonium. Over the follow-up period from 1953-2008, there were 486 deaths from lung cancer, 446 of them in men. In analyses that were adjusted for external radiation dose and smoking, the plutonium excess relative risk (ERR) per Gy declined with attained age and was higher for females than for males. The ERR per Gy for males at age 60 was 7.4 (95% CI: 5.0-11) while that for females was 24 (95% CI: 11-56). When analyses were restricted to plutonium doses <0.2 Gy, the ERR per Gy for males at age 60 was similar: 7.0 (95% CI: 2.5-13). Of the 486 lung cancer deaths, 105 (22%) were attributed to plutonium exposure and 29 (6%) to external exposure. Analyses of the 12,708 workers with information on smoking indicated that the relationship of plutonium exposure and smoking was likely sub-multiplicative (P = 0.011) and strongly indicated that it was super-additive (P < 0.001). Although extensive efforts have been made to improve plutonium dose estimates in this cohort, they are nevertheless subject to large uncertainties. Large bioassay measurement errors alone are likely to have resulted in serious underestimation of risks, whereas other sources of uncertainty may have biased results in ways that are difficult to predict. (C) 2013 by Radiation Research Society
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