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GEE Models for the Longitudinal Analysis of the Effects of Occupational Radiation Exposure on Lymphocyte Counts in Russian Nuclear Workers

Soaita, Adina Iulia (2007) GEE Models for the Longitudinal Analysis of the Effects of Occupational Radiation Exposure on Lymphocyte Counts in Russian Nuclear Workers. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

The health effects of occupational radiation exposure have long been a source of scientific and administrative debates related to setting exposure standards. Relevant to this field are the effects of occupational long term radiation exposure on the lymphocyte counts which are especially sensitive to radiation. The trend of lymphocyte counts in radiation workers is of major importance since decreases in lymphocyte counts may be precursors of immunity disorders, cancer susceptibility or other chronic conditions. Another important question is whether the occupational radiation affects the lymphocyte counts similarly in males and females, given the relative lack of information on the effects and health implications of long term occupational radiation exposure on female subjects. This dissertation presents a comprehensive statistical analysis of the relationship between dosimetric (yearly gamma exposure) and hematological (lymphocyte counts) data collected from a historical cohort (1948-1956) of highly exposed radiation workers at Mayak Plant Association located in Russia. The analysis controls for important covariates, such as the baseline lymphocyte counts, sex, work location related to Plutonium exposure lifestyle variables and the number of years from the first exposure. The analysis contrasts the most relevant radiation dose-response models by using marginal models and the GEE technique. STATA programming tools have been developed to check the assumptions required by the GEE technique, with special attention to the missing data mechanisms and patterns in the framework of a longitudinal study with repeated measurements and unbalanced number of observations. The issue of non-linearity between the outcome variable and the explanatory covariates is addressed by the implementation of linear splines within GEE models. Statistical analyses indicate: (a) that a linear radiation dose-response model is appropriate for the data, (b) a statistically significant negative relationship between the log-transformed lymphocyte counts and the log-transformed external gamma dose, (c) no statistically significant differences between males and females regarding the effect of occupational radiation exposure on the lymphocyte counts. Public health significance of this research is:a) The linear radiation dose-response model is reasonable for regulatory purposes, andb) Males and females do not require differential regulatory standards for low dose occupational radiation exposure.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Soaita, Adina Iuliaais8@pitt.edu, asoaita_ro@yahoo.comAIS8
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairRedmond, Carol Kckr3@pitt.eduCKR3
Committee CoChair Day, Richard Dday@nsabp.pitt.edu
Committee MemberYouk, Ada Oayouk@pitt.eduAYOUK
Committee MemberSlaughter, David Mslaughter@eng.utah.edu
Committee MemberWald, Nielwald@pitt.eduWALD
Date: 20 February 2007
Date Type: Completion
Defense Date: 17 November 2006
Approval Date: 20 February 2007
Submission Date: 28 November 2006
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Biostatistics
Degree: DrPH - Doctor of Public Health
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: lymphocyte counts; Mayak; missing data; occupational radiation exposure; GEE models; goodness of fit
Other ID: http://etd.library.pitt.edu/ETD/available/etd-11282006-163122/, etd-11282006-163122
Date Deposited: 10 Nov 2011 20:06
Last Modified: 15 Nov 2016 13:52
URI: http://d-scholarship.pitt.edu/id/eprint/9831

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