Background: Musculoskeletal disorders are a major problem in all jobs. Several methods are available for assessing the exposure to risk factors associated with musculoskeletal disorders. This study is aimed at comparing three different ergonomic risk assessment methods—rapid upper limb assessment (RULA), loading on the upper body assessment (LUBA), and new ergonomic posture assessment (NERPA) method—to predict upper extremity musculoskeletal disorders. Materials and Methods: The study was conducted on 210 workers from three different industries including pharmaceutical, automotive, and assembly in the Isfahan province. A Nordic questionnaire was used for determining the levels of musculoskeletal disorders. Then, selected postures were evaluated with RULA, LUBA, and NERPA methods. Finally, data were analyzed with Kolmogorov–Smirnov test to check the normality distribution of data, Spearman's correlation test to investigate the correlation between the assessed levels with musculoskeletal disorders, and Wilcoxon test to identify significant differences between the values with SPSS version 16. Results: Wilcoxon test revealed a significant difference between the values related to NERPA and RULA (P < 0.001), whereas no significant relation between LUBA and RULA was shown by this test (P = 0.914). The correlation coefficients of the musculoskeletal disorders' level with RULA level, NERPA level, and LUBA level were 0.74, 0.73, and 0.69, respectively. Conclusion: Low-risk levels in NERPA, medium-risk levels in LUBA, and high-risk levels in RULA are evaluated better. The results showed that RULA was the best method for assessing musculoskeletal disorders among the three methods.

Respirable crystalline silica (RCS) overexposure can lead to the development of silicosis which is a chronic, irreversible, potentially fatal respiratory disease. The most significant prerequisite for any silica exposure control plan is an accurate occupational exposure assessment. The results of crystalline silica analysis are often affected by other mineral interferences and are influenced by an analyst’s knowledge of mineralogy to accurately interpret infrared spectra and correct matrix interferences. Partial least squares (PLS) and artificial neural networks (ANNs) are two multivariate calibration methods to overcome the problem of spectral interferences without the need for an analyst intervention. The performance of these two methods in quantitative analysis of quartz in the presence of mineral interferences was evaluated and compared in this study. Fifty mixtures with different crystalline silica content ratios were prepared by mixing quartz with four common mineral interferences including kaolinite, albite, muscovite, and amorphous silica. Fourier-transform infrared spectra of the mixtures were split into training and test datasets. The optimal architecture of the ANN model was achieved using a two-level full factorial design experiment and data were modeled using ANN and PLS regression analysis. Root mean squared error of prediction values of 1.69 and 6.12 µg quartz for ANN and PLS models, respectively, revealed the fact that the both models performed very well in quantitative analysis of quartz in the presence of mineral interferences, with a better relative performance of the ANN model which can be related to the inherent nonlinear predictive ability of ANNs. Given the excellent predictive ability of the ANN model which can deal with a completely overlapped peak without any need of user’s intervention, it is recommended that the ANN model be optimized in future studies and utilized for reliable and rapid on-field assessment of RCS exposure.

Restaurant sector is one of the most rapidly developing sectors in the world and there is evidence that restaurant industry has high levels of work-related diseases and injuries. This study examined the prevalence of self-reported work-related injuries and illness (WRIIs) and their association with demographic variables among restaurant workers in Shiraz, the capital of Fars Province, Iran. In this cross-sectional study, 300 randomly selected restaurant workers completed a self-statement, research-made questionnaire regarding the prevalence of self-reported WRIIs, in Shiraz, Iran. Statistical analyses were performed using SPSS version 20. A high prevalence of work-related injuries (84%) and musculoskeletal disorders (70%) was reported among restaurant workers. Cuts and lacerations, arising from accidents with knives, were the most common injuries seen, followed by burns, falls, slips and trips. Moreover, the prevalence of occupational accidents had a significant association with work experience (p = 0.012), cooking (p < 0.001), as well as preparation and washing (p = 0.011). Age (p < 0.001) and work experience (p < 0.001) had a significance association with the prevalence of musculoskeletal disorders. Preventive measures and polices, through providing occupational health and safety services including trainings, personal protective equipment and health examinations, should be taken as to restaurants and catering industry in Iran.

Lighting is one of the environmental factors affecting the performance of the control room operators. Therefore, the aim of this study was to compare the control room operators’ visual performance in two different illumination conditions at a combined cycle power plant through field-work. Sixteen operators in day shift were evaluated with the Freiburg Visual Acuity test (FrACT) software at two lighting systems with different intensities. It includes the first phase with fluorescent illumination system (Power: 40 W, Color Temperature: 4000 Kelvin, Luminous Flux: 2780 Lumen and Model: Pars Shahab) and the second phase with a combined illumination system includes fluorescent and LED (Power: 48 W, Color Temperature: 4000 Kelvin, Luminous Flux: 5400 Lumen and Model: Mazinoor). Based on the results, visual performance index and visual acuity significantly increased after the intervention (p < 0.001). As to contrast, more lighting significantly reduced the percentage of recognized contrast (p < 0.001) and increased the contrast performance index (p < 0.001). The results of this study showed that increasing the intensity of light from the values below the allowable limit to the values above the allowable limit would increase the visual indicators in individuals.

Healthcare workers often have unnoticed minor abrasions on their hands, putting them at risk of contracting infectious diseases from patients, if the integrity of the medical gloves is compromised. This study aimed to compare the rate and location of glove perforation between well-fitted and ill-fitted gloves. The participants of this cross-sectional study were 45 midwives in the maternity ward of a hospital in Shiraz city, Iran. A total of nine pairs of medical gloves including three pairs of fit size, three pairs of gloves with one size smaller (tight), and three pairs of gloves with one size larger (loose) were given to subjects, and asked them to use the gloves during episiotomy repair operations. After completing the task, all gloves were collected safely and gloves perforation was investigated based on water test (NF EN 455-1). The perforation rate of the fit, tight, and loose medical gloves was 20, 37.78, and 34.81%, respectively. The results showed a significant difference between glove perforation of different glove sizes (P < 0.05). In general, there was a significant difference between the perforation rate of the fit glove and ill-fitted gloves (P = 0.013). Wearing the wrong size gloves may increase the glove perforation rate. Providing a wide range of glove sizes by the hospital management, and choosing the best glove size can be very effective in reducing the glove perforation and increasing safety for healthcare workers and patients.