Is the Linear No-Threshold Dose-Response Paradigm Still Necessary for the Assessment of Health Effects of Low Dose Radiation?

Abstract

Inevitable human exposure to ionizing radiation from man-made sources has been increased with the proceeding of human civilization and consequently public concerns focus on the possible risk to human health. Moreover, Fukushima nuclear power plant accidents after the 2011 East-Japan earthquake and tsunami has brought the great fear and anxiety for the exposure of radiation at low levels, even much lower levels similar to natural background. Health effects of low dose radiation less than 100 mSv have been debated whether they are beneficial or detrimental because sample sizes were not large enough to allow epidemiological detection of excess effects and there was lack of consistency among the available experimental data. We have reviewed an extensive literature on the low dose radiation effects in both radiation biology and epidemiology, and highlighted some of the controversies therein. This article could provide a reasonable view of utilizing radiation for human life and responding to the public questions about radiation risk. In addition, it suggests the necessity of integrated studies of radiobiology and epidemiology at the national level in order to collect more systematic and profound information about health effects of low dose radiation.

Keywords: Epidemiology; Health Effects; LNT Model; Low Dose Radiation; Radiobiology.

Fig. 1

Schematic diagram illustrating various dose-response models in risk assessments. Radiation exposed level is represented on the x-axis and overall risk for diseases is represented on the y-axis.

Fig. 2

Recent biological studies on the low dose radiation effects. To increase the consistency and coherence of experimental data on low dose radiation, we should introduce new biological knowledge of emerging area as well as conventional concepts.

Fig. 3

Confounding factors in the analysis of low dose radiation effects. Biological effects of low dose radiation could be determined by several confounding factors as detrimental or beneficial. For example, systemic variables such as hierarchy, maturity, and ageing of irradiated organism, time of irradiation and phenotype emergence, and interaction with other environmental factors.

Fig. 4

Excess relative risk (ERR) for cancer in major cohort studies of radiation workers. (A) all cancer; (B) leukemia. The mean cumulative doses are represented on the x-axis and ERRs for cancer are represented on the y-axis. ^*Solid cancer only; ^†All cancer excluding leukemia; ^‡Leukemia excluding CLL; ^§90% confidence interval.

Fig. 5

Standardized mortality ratio (SMR) (or Standardized incidence ratio [SIR]) for cancer in major cohort studies of radiation workers. (A) all cancer; (B) leukemia. The mean cumulative doses are represented on the x-axis and SMRs (or SIR) for cancer are represented on the y-axis. ^*Solid cancer only; ^†All cancer excluding leukemia; ^‡Leukemia excluding CLL.

Fig. 6

SMR for cancer (all cancer, leukemia excluding chronic lymphocytic leukemia [CLL], melanoma and breast cancer) in major cohort studies of air crews and radiation workers. The names of the studies are represented on the x-axis and SMRs are represented on the y-axis.