ABSTRACT
Background@#Exposure to particulate matter (PM) emitted from vehicle exhaust might disrupt systemic function and elevate the risk of cardiovascular disease. In this study, we examined the changes of cardiometabolic biomarkers among vehicle inspectors exposed daily to PM0.25 and components. @*Methods@#This cross-sectional study was conducted at two vehicle inspection centers, Pulogadung and Ujung Menteng, located in East Jakarta, Indonesia. The exposed respondents were 43 workers from vehicle inspection centers, and the unexposed group consisted of 22 staff officers working in the same locations. Vehicle exhaust particulate matter was measured for eight hours using a Leland Legacy personal pump attached to a Sioutas Cascade Impactor. The used filters were 25 and 37-mm quartz filters. The particulate matter concentration was analyzed using a gravimetric method, whereas trace elements were analyzed using energy dispersive X-ray fluorescence. An EEL Smoke Stain Reflectometer analyzed black carbon. @*Results@#The personal exposure concentrations of PM0.25 were 10.4-fold higher than those in unexposed groups. Calcium and sulfur were the major components in the obtained dust, and their levels were 3.3- and 7.2-fold higher, respectively, in the exposed group. Based on an independent-samples t-test, high-density lipoprotein, triglyceride, HbA1c, total immunoglobulin E, high-sensitivity C-reactive protein, tumor necrosis factor–alpha, and nitric oxide levels were significantly different between the groups. @*Conclusions@#In summary, it was suggested that PM0.25 exposure from vehicle exhaust might affect cardiometabolic biomarkers change.
ABSTRACT
Background@#Exposure to particulate matter (PM) emitted from vehicle exhaust might disrupt systemic function and elevate the risk of cardiovascular disease. In this study, we examined the changes of cardiometabolic biomarkers among vehicle inspectors exposed daily to PM0.25 and components. @*Methods@#This cross-sectional study was conducted at two vehicle inspection centers, Pulogadung and Ujung Menteng, located in East Jakarta, Indonesia. The exposed respondents were 43 workers from vehicle inspection centers, and the unexposed group consisted of 22 staff officers working in the same locations. Vehicle exhaust particulate matter was measured for eight hours using a Leland Legacy personal pump attached to a Sioutas Cascade Impactor. The used filters were 25 and 37-mm quartz filters. The particulate matter concentration was analyzed using a gravimetric method, whereas trace elements were analyzed using energy dispersive X-ray fluorescence. An EEL Smoke Stain Reflectometer analyzed black carbon. @*Results@#The personal exposure concentrations of PM0.25 were 10.4-fold higher than those in unexposed groups. Calcium and sulfur were the major components in the obtained dust, and their levels were 3.3- and 7.2-fold higher, respectively, in the exposed group. Based on an independent-samples t-test, high-density lipoprotein, triglyceride, HbA1c, total immunoglobulin E, high-sensitivity C-reactive protein, tumor necrosis factor–alpha, and nitric oxide levels were significantly different between the groups. @*Conclusions@#In summary, it was suggested that PM0.25 exposure from vehicle exhaust might affect cardiometabolic biomarkers change.
ABSTRACT
Abstract@#Introduction: Occupational stress is a condition in which one or several factors in the workplace interact with workers, therefore it causes disturbance of the equilibrium both physiological and psychological matter. For a driver, occupational stress will impact on the declining performance that may threaten the safety while driving. Consequently, occupational stress becomes one of the most processes which is being related to harmful behavior to drivers that may affect the risk of accidents. This study aims to analyze the correlation between quantity and quality of sleep with occupational stress on truckload drivers. Methods: This study uses a cross-sectional method. Data instruments are utilizing a questionnaire and few additional instruments (e.g. cocoro meter, fitbit, sphygmomanometer, and oximetry) to measure the relationship between quantity and quality of sleep to occupational stress as its supporting data. The data obtained were statistically analyzed using the chi-square test and different mean test. Results: 27 respondents (60%) experiencing occupational stress at a mild level and 18 respondents (40%) experiencing occupational stress at a moderate level. Conclusion: In addition, from the results of the analysis, it was found that there is a correlation between quantity and quality of sleep with occupational stress on truckload drivers.