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. (23rd June 2014)
- Record Type:
- Journal Article
- Title:
- 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. (23rd June 2014)
- Main Title:
- 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
- Authors:
- Do, Minh
- Abstract:
- Abstract : 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 (pAbstract : 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. … (more)
- Is Part Of:
- Occupational and environmental medicine. Volume 71(2014)Supplement 1
- Journal:
- Occupational and environmental medicine
- Issue:
- Volume 71(2014)Supplement 1
- Issue Display:
- Volume 71, Issue 1 (2014)
- Year:
- 2014
- Volume:
- 71
- Issue:
- 1
- Issue Sort Value:
- 2014-0071-0001-0000
- Page Start:
- A37
- Page End:
- A38
- Publication Date:
- 2014-06-23
- Subjects:
- Medicine, Industrial -- Periodicals
Environmental health -- Periodicals
616.980305 - Journal URLs:
- http://oem.bmj.com/ ↗
http://www.jstor.org/journals/13510711.html ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=172&action=archive ↗
http://www.bmj.com/archive ↗ - DOI:
- 10.1136/oemed-2014-102362.116 ↗
- Languages:
- English
- ISSNs:
- 1351-0711
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19229.xml