Article Text


0311  Development of a predictive model for estimating gamma radiation exposures among Ontario uranium miners0311  Development of a predictive model for estimating gamma radiation exposures among Ontario uranium miners
  1. Minh Do
  1. Occupational Cancer Research Centre, Toronto, Ontario, Canada


Objectives The objective of this study is to develop and validate a predictive model for estimating gamma radiation exposure for miners working in uranium mines between 1981 and 1985.

Method The dose prediction model was developed and validated using multiple linear regression. To aid in model development, 70% random sample of workers were used in the model development (i.e., Training Sample) while the remainder 30% (i.e., Test Sample) was used to determine model performance. A stepwise approach was used to select variables into the model. Criteria for retaining the variables in the model was based on a p-value of <=0.15. Model fit was assessed using adjusted R-square. Co-linearity was determined by the magnitude of the variance inflation factor (VIF). Variables with VIF greater than 3.0 were removed from the model. In addition, SAS procedure ROBUSTREG was used to minimise the effects of outliers and high leverage in order to provide resistant (stable) results in the presence of outliers and high leverage.

Results Based on 8949 employments records, dosimetric measurements of gamma radiation were significantly correlated with radon exposure (r = 0.499), duration of employment (r = 0.429), year of exposure (r = 0.239), and ore production (r = 0.230). Age was inversely related to gamma dose. Regression analysis showed that individual dosimetric readings can be modestly predicted by individual work history and geological characteristics of Ontario uranium mines (p < 0.001, R2 = 0.374). Additional sources of variation are likely related to individual variability that could not be accounted for in this ecological assessment.

Conclusions Reconstructed gamma dose provides modest agreement with individual dosimetric readings.

Statistics from

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.