This study describes tripper car operators’ exposure to coal tar pitch volatiles at an operation at Coal Distribution Steam Plant that involves the use of coal tar mix to feed as fuel the steam generating boilers. A cross-sectional task-based exposure assessment approached was used. The objectives of this study were to monitor tripper car operators’ exposures to coal tar pitch volatiles as benzene soluble fraction and to then compare the measured concentrations with the occupational exposure limit. The general aim of the study was to accumulate data about employee exposure to coal tar pitch volatiles in South African Petrochemical Refineries. A total of 56 samples was collected and analyzed for coal tar pitch volatiles – benzene soluble fraction. Of the 56 samples, 41 were personal samples collected on the breathing zones of the workers and 15 samples were field blank samples. The method used for the collection of the samples was the United States Department of Labor, Occupational Safety & Health Administration Method 58. In South Africa the available occupational exposure limit for coal tar pitch volatiles is the time weighted average occupational exposure limit – recommended limit for cyclohexane soluble fraction which is 0.14 mg/m3. For the evaluation of personal exposure to compare with the occupational exposure limit, the UK Health & Safety Executive Method for the Determination of Hazardous Substances (MDHS) 68 was adopted in the past to monitor workplace air. This method was since withdrawn by the Health & Safety Executive after research conducted by the Health & Safety Laboratory revealed that unacceptable variability were introduced into the method due to the small mass changes involved and the difficulty in accurately weighing the filters before and after the cyclohexane extraction. Due to the unavailability of a suitable and acceptable method to assess workers’ exposure to coal tar pitch volatiles – cyclohexane soluble fraction to compare to the South African occupational exposure limit, the Occupational Safety & Health Administration Method Number 58 was used during this study for the collection of the samples. This is a validated method. This method follows a similar approach as the MDHS 68 however benzene is used instead of cyclohexane during sample extraction. The Occupational Safety and Health Administration have the permissible exposure limit of 0.2 mg/m3 for coal tar pitch volatiles – benzene soluble fraction to use when assessing worker exposure. This limit was used during this study for assessing tripper car exposure to coal tar pitch volatiles. No coal tar pitch volatiles were detected on the samples collected during the study. The results revealed concentrations below detection limit of the test laboratory analytical method. The detection limit used thereof was 0.1 mg per sample. The tripper car operators were therefore exposed to coal tar pitch volatiles at concentrations that complied with the permissible exposure limit 0.2 mg/m3. The hypothesis of this study was that the tripper car operators at Coal Distribution Steam Plant are over exposed to coal tar pitch volatiles – benzene soluble fraction. This hypothesis is therefore rejected. Based on the results derived from this study it is recommended that further research studies be conducted specifically with focus on different methods of exposure assessment to workers exposed to coal tar pitch volatiles in South African Petrochemical Refinery Plants. - ii - Since the method used was limited to the particulate phase of the contaminant exposure, with the gaseous phase of exposure to coal tar pitch volatiles only looked at when the PEL is exceeded. A method that can measure both the gaseous and particulate phase of the contaminant must be investigated.

Earlier retrospective noise exposure assessments for use in epidemiological research were not adequately characterized because they did not properly account for use of hearing protection devices (HPD) which would result in potential misclassification. Exposure misclassification has been shown to attenuate exposure-outcomes relations. In the case of already subtle relationships such as noise and cardiovascular diseases, this would potentially annihilate any association. We investigated two approaches using Workers’ Compensation Board (WorkSafe BC) audiometric surveillance data to (i) re-assess the noise exposure in a cohort of lumber mill workers in British Columbia using data on the use of HPD and the determinants of their use available through WorkSafe BC, and (ii) test the validity of the new exposure measures by testing their predictions of noise-induced hearing loss, a well-established association. Work history, noise exposure measurements, and audiometric surveillance data were merged together, forming job-exposure-audiometric information for each of 13,147 lumber mill workers. Correction factors specific to each type and class of HPD were determined based on research and standards. HPD-relevant correction factors were created using 1) deterministic methods and self-reported HPD use after filling gaps in the exposure history, or 2) a model of the determinants of use of HPD, then adjusting noise estimates according to the methods’ predictions and attenuation factors. For both methods, the HPD-adjusted and unadjusted noise exposure estimates were cumulated across all jobs each worker held in a cohort-participating lumber mill. Finally, these noise metrics were compared by examining how well each predicted hearing loss. Analyses controlled for gender, age, race as well as medical and non-occupational risk factors. Both methods led to a strengthening of the noise-hearing loss relationships compared to methods using HPD-unadjusted noise estimates. The method based on the modeling of HPD use had the best performance with a four-fold increase in the slope compared to the unadjusted noise-hearing loss slope. Accounting for HPD use in noise exposure assessment is necessary since we have shown that misclassification attenuated the exposure-response relationships. Exposure-response analyses subsequent to exposure reassessment provide predictive validity and gives confidence in the exposure adjustment methods.

Coal workers’ pneumoconiosis (CWP), commonly referred to as black lung, is a chronic lung disease that results from the inhalation and deposition of coal dust in the lungs. While this disease continues to afflict coal miners, its prevalence has steadily declined over three decades since 1970. Based on a voluntary X-ray surveillance program, conducted by the National Institute for Occupational Safety and Health (NIOSH), this downward trend, however, ended in 2000 and has actually begun to rise. The Mine Safety and Health Administration (MSHA) instituted a Comprehensive Initiative to “End Black Lung” to combat the reported upturn in black lung disease. Rulemaking, with the intent of strengthening respirable dust regulations, is a major part of this initiative. This thesis addresses a controversial aspect of the newly proposed rules – single-shift compliance sampling. Establishing new requirements for respirable dust compliance requires an understanding of both the accuracy and variability of measurements. Measurement variability is especially important in underground mining where the workplace is constantly moving and ventilation controls are continually changing. The results of a ventilation study performed in three underground coal mines are presented in this thesis. A total of 600 dust-concentration measurements were obtained in this study using Continuous Personal Dust Monitors (CPDMs). The data was analyzed to determine the variability associated with taking dust measurements in the mining workplace. The Johnson transformation was found to produce the best-fit distribution model for the data. This thesis summarizes the results of this study and presents a statistical procedure for establishing an exposure limit.

Background Hand-arm vibration (HAV) is an occupational hazard which, cumulatively, leads to hand-arm vibration syndrome (HAVS). Detection and reduction of HAV can help prevent the disease or slow down its progress. Unfortunately, assessment of HAV through direct measurement is difficult due to the high cost of measurement equipment, interruption of work performance, and long travel cost to worksites. An alternative assessment method is through development of an exposure prediction model to identify workplace, tool, and task characteristics which significantly predict HAV exposure. Purpose The purpose of this study is twofold: 1) to determine the extent and nature of previously published scientific journal articles on exposure prediction modeling of HAV through performing a systematic review; and 2) to develop a new exposure prediction model using administrative data to find significant HAV predictors. Methods A systematic review of relevant studies involved humans aged 18 or over, applicable to occupational setting, with vibration measured using tri-axial accelerometer and statistical modeling of the effects of occupational characteristics on measure HAV were identified. Five online bibliographic databases (Medline, CINAHL, Web of Science, Scopus, and EMBASE) were searched using a combined word list of terms under three categories: “occupational diseases”; “Hand-arm vibration”; and “Statistical Modelling”. Two multiple linear regression models predicting average hand-arm vibration exposure over 8 hour day, A(8), were built using enforcement data collected by Ministry of Labour Relations and Workplace Safety Saskatchewan using standard model building method. In addition, GEE was used to account for repeated data collection within workers and worksites. Results In the first manuscript, 7 articles found were deemed relevant. Four studies built regression models, while three used ANOVA to find significant HAV predictors. Examples of significant HAV predictors included: tool age, tool weight, participant, and operating power; the proportion of HAV variance explained varied from 46 to 90%. In the second manuscript, the models based on administrative data explained 16% to 27% of A(8) variance. The included variables were tool power source, vibration control, and job type for the parsimonious model; the comprehensive model has the same variables as parsimonious along with accelerometer attachment method and tool brand. Conclusion HAV prediction through exposure prediction modeling is a relatively new method for assessing occupational HAV. It is feasible to find HAV predictors using low-cost administrative data, and variables such as tool power source, job type, and vibration control make promising predictors. However, the variance explained will be lower than using data collected for research purposes. The significant predictors found in the systematic review can be considered when installing protective measures in the future. The significant predictors found and procedures used from the modeling study can be considered for future HAV exposure prediction modeling studies.

Earlier retrospective noise exposure assessments for use in epidemiological research were not adequately characterized because they did not properly account for use of hearing protection devices (HPD) which would result in potential misclassification. Exposure misclassification has been shown to attenuate exposure-outcomes relations. In the case of already subtle relationships such as noise and cardiovascular diseases, this would potentially annihilate any association. We investigated two approaches using Workers’ Compensation Board (WorkSafe BC) audiometric surveillance data to (i) re-assess the noise exposure in a cohort of lumber mill workers in British Columbia using data on the use of HPD and the determinants of their use available through WorkSafe BC, and (ii) test the validity of the new exposure measures by testing their predictions of noise-induced hearing loss, a well-established association. Work history, noise exposure measurements, and audiometric surveillance data were merged together, forming job-exposure-audiometric information for each of 13,147 lumber mill workers. Correction factors specific to each type and class of HPD were determined based on research and standards. HPD-relevant correction factors were created using 1) deterministic methods and self-reported HPD use after filling gaps in the exposure history, or 2) a model of the determinants of use of HPD, then adjusting noise estimates according to the methods’ predictions and attenuation factors. For both methods, the HPD-adjusted and unadjusted noise exposure estimates were cumulated across all jobs each worker held in a cohort-participating lumber mill. Finally, these noise metrics were compared by examining how well each predicted hearing loss. Analyses controlled for gender, age, race as well as medical and non-occupational risk factors. Both methods led to a strengthening of the noise-hearing loss relationships compared to methods using HPD-unadjusted noise estimates. The method based on the modeling of HPD use had the best performance with a four-fold increase in the slope compared to the unadjusted noise-hearing loss slope. Accounting for HPD use in noise exposure assessment is necessary since we have shown that misclassification attenuated the exposure-response relationships. Exposure-response analyses subsequent to exposure reassessment provide predictive validity and gives confidence in the exposure adjustment methods.

Diss. (sammanfattning) Örebro : Örebro universitet, 2006. / Härtill 4 uppsatser.

Earlier retrospective noise exposure assessments for use in epidemiological research were not adequately characterized because they did not properly account for use of hearing protection devices (HPD) which would result in potential misclassification. Exposure misclassification has been shown to attenuate exposure-outcomes relations. In the case of already subtle relationships such as noise and cardiovascular diseases, this would potentially annihilate any association. We investigated two approaches using Workers’ Compensation Board (WorkSafe BC) audiometric surveillance data to (i) re-assess the noise exposure in a cohort of lumber mill workers in British Columbia using data on the use of HPD and the determinants of their use available through WorkSafe BC, and (ii) test the validity of the new exposure measures by testing their predictions of noise-induced hearing loss, a well-established association. Work history, noise exposure measurements, and audiometric surveillance data were merged together, forming job-exposure-audiometric information for each of 13,147 lumber mill workers. Correction factors specific to each type and class of HPD were determined based on research and standards. HPD-relevant correction factors were created using 1) deterministic methods and self-reported HPD use after filling gaps in the exposure history, or 2) a model of the determinants of use of HPD, then adjusting noise estimates according to the methods’ predictions and attenuation factors. For both methods, the HPD-adjusted and unadjusted noise exposure estimates were cumulated across all jobs each worker held in a cohort-participating lumber mill. Finally, these noise metrics were compared by examining how well each predicted hearing loss. Analyses controlled for gender, age, race as well as medical and non-occupational risk factors. Both methods led to a strengthening of the noise-hearing loss relationships compared to methods using HPD-unadjusted noise estimates. The method based on the modeling of HPD use had the best performance with a four-fold increase in the slope compared to the unadjusted noise-hearing loss slope. Accounting for HPD use in noise exposure assessment is necessary since we have shown that misclassification attenuated the exposure-response relationships. Exposure-response analyses subsequent to exposure reassessment provide predictive validity and gives confidence in the exposure adjustment methods. / Medicine, Faculty of / Population and Public Health (SPPH), School of / Graduate

This study sought to explore the existence of a relationship between age and/or military affiliation (active, veteran, or family member) and awareness of local community mental health programs available for the treatment of post-traumatic stress disorder. The study separated age from military affiliation to better distinguish between influences on awareness level. Considerations that remain critical regarding post-traumatic stress disorder were described and used to guide a comprehensive review of the literature to find directions to fulfill the goal of this study. A survey was conducted and 586 active military, veterans, and their family members responded to an instrument that contained 40 items. This study was constrained to three items from the survey; age, military affiliation, self-rated awareness of treatment for PTSD. Multiple analysis techniques found no significant (p < .05) correlation between either age and awareness or military affiliation and awareness. Further analysis found a significant (p = .003) correlation between veterans and awareness, as well as between family members of veterans (p = .017) and awareness. Veterans and their family members indicated a greater awareness of local community mental health programs available for the treatment of post-traumatic stress disorder than did active troops and/or their family members. The significance of this finding presents new opportunities to study and improve both the marketing and the delivery of mental health treatment for PTSD to the active military population. Multiple opportunities for future research are discussed.

No description available.

No description available.