Hidden risk factors and the mediating role of sleep in work-related musculoskeletal discomforts.

OBJECTIVE: Musculoskeletal discomforts (MSDs) are prevalent occupational health issues that are associated with a wide range of risk factors. This study aimed to investigate some of the occupational hidden risk factors and the mediating role of sleep in work-related musculoskeletal discomforts. METHODS: In a cross-sectional study, the role of job stress and shift work as two hidden risk factors and sleep problems as the mediator in work-related musculoskeletal discomforts was investigated in 302 healthcare workers using the path analysis models. For this aim, healthcare workers' Occupational Stress and musculoskeletal discomforts were evaluated using the Health and Safety Executive questionnaire and Cornell questionnaire, respectively. Moreover, the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI) were used to examine the sleep characteristics of participants. Shift work and job stress as predictor variables and sleep characteristics as mediating variables were analyzed. RESULTS: The results showed that the path coefficients of job stress on indexes of quality sleep and insomnia severity were significant. Also, the path coefficient of shift work on quality sleep index was significant. In return, the path coefficients of shift work on the insomnia severity index were not significant. Additionally, there was a mutually significant association between indexes of quality sleep and the severity of insomnia and musculoskeletal discomforts. The direct effect coefficient of job stress on MSDs was significant, whereas the direct effect coefficient of shift work on MSDs was insignificant. This means that shift work alone does not significantly impact these disorders. CONCLUSION: It would seem that shift work and job stress as two occupational hidden risk factors can mediate sleep indexes and indirectly play a critical role in the incidence of musculoskeletal discomforts. Moreover, sleep disorders and musculoskeletal discomforts are mutually related and have a bidirectional relationship.

Risk assessment of the work-related musculoskeletal disorders based on individual characteristics using path analysis models.

BACKGROUND: This study aimed to assess the risk of work-related musculoskeletal disorders (WMSDs) using the path analysis models. METHODS: This study was carried out on 350 office employees with good general health. All variables were collected using a questionnaire. Personality traits and mental workload of employees were evaluated using the NEO Personality Inventory and the NASA-task load index software, respectively. The individual and personality traits were used as predictor variables, and mental workload (MWL) and body posture scores as mediating variables of the musculoskeletal discomforts. The role of predictor and mediating variables on discomforts was explained based on the path analysis models. RESULTS: The impact coefficient of MWL and posture on WMSDs was significant. The coefficient of the direct effect of body mass index (BMI) and gender on musculoskeletal disorders was significant and positive and the women have reported a higher rate of discomforts. The strongest positive impact of personality traits on MWL and posture was conscientiousness, followed by neuroticism and agreeableness. In return, the strongest negative impact was extroversion, followed by openness. The strongest positive impact of individual factors on MWL and posture was BMI, followed by work experience. CONCLUSION: Gender, BMI, neuroticism, extraversion, and conscientiousness can be strong predictors for musculoskeletal discomforts which can mediate the impact of body posture and mental workload (mediating factors) on musculoskeletal discomfort. Therefore, personality and individual traits can be strong alarming and indicators for risk identification and preventing musculoskeletal disorders when choosing people for a job or task.

Prediction of occupational exposure limits for noise-induced non-auditory effects.

There is a recent trend to place more emphasis on noise non-auditory effects. Despite its implications on health, there is a lack of recommendations for noise in occupational settings. This study aimed to present occupational exposure limits for noise-induced non-auditory effects in healthy males using empirical exposure-response regression models based on the data of laboratory and field considering the effective variables. To this end, the equivalent noise level was measured and recorded in four working settings including closed offices, open-plan offices, control rooms, and industrial workplaces during a normal working day. They were 65, 68, 73, and 80dB(A), respectively. In the laboratory, 31 healthy males were exposed to five noise conditions (four noisy conditions and one quiet) during 8 h and they were asked to perform the cognitive tests. In the field phase, 124 healthy males were also examined from four working settings in their workstations for 8 h. The psychophysiological parameters of the participants were recorded in both lab and field. The results indicated variations in mental responses at levels above 55dBA, and psychophysiological variations at levels above 70dB(A) in both phases. The findings also showed that the developed regression models could plausibly predict the noise-induced psychophysiological responses during exposure to noise levels; thus, they can be presented the likely exposure limits. Based on the results of the models, the levels <55dB(A) are likelihood of the acoustic comfort limit, and the levels ranged from 55 to 65dB(A) are the acoustic safe limits. The acoustic caution limit is the likelihood of the levels ranged from 65 to 75dB(A). The levels ranged from 75 to 80dB(A) are likely the action levels or control limits, and the occupational exposure limit are the probability of levels> 80dB(A).

Evaluation of bio-aerosols type, density, and modeling of dispersion in inside and outside of different wards of educational hospital.

Exposure to bioaerosols in the air of hospitals is associated with a wide range of adverse health effects due to the presence of airborne microorganisms. Intensity and type of health effects depend on many factors such as the type, density, and diversity of bioaerosols in hospital environments. Therefore, identifying and determining their distribution in hospital environment contribute to reduce their adverse effects and maintain the physical health of patients and staff, as well as find the source of infections and possible allergies due to the presence of bioaerosols. Therefore, the present study was conducted to determine the type and concentration of the bacterial and fungal bioaerosols, and their distribution in the indoor and outdoor air of a teaching hospital to establish a reference for future studies or measures. The air samples were collected with a one-stage Anderson sampler and particle mass counter for a period of four months in the fall and winter of 2019. In total, 262 bacterial and fungal samples were collected from the air of the wards of Tohid Hospital, Sanandaj, Iran. Antibiotic resistance test, bacterial identification by PCR method, and modeling the dispersion of concentrations of bio-aerosols were also conducted. In order to identify bacteria and fungi, some biochemical and molecular tests and microscopic and macroscopic characteristic methods were applied, respectively. The results showed that the highest and lowest densities of the bioaerosols were observed in lung and operating wards (336.67 and 15.25 CFU/m3). Moreover, the highest and least concentrations of particles were seen in the emergency and operating wards, respectively. The most common fungi isolated from the hospital air were Penicillium (24.7%), Cladosporium (23. 4%), Aspergillus niger (13.3%), and Aspergillus Flavus (11.4%). Furthermore, the highest concentration of the isolated bacterium was Staphylococcus hemolyticus (31.84%). Most bacteria showed the highest resistance to gentamicin. The overall average hospital air pollution to bioaerosols was slightly higher than the standards proposed by international organizations. Due to the high concentration of bioaerosols and particles in the studied hospital, providing suitable conditions such as temperature, humidity, proper ventilation, and intelligent air conditioning system using efficient ventilation systems, and restricting the entrance of wards can reduce airborne particles in hospital environment.

Explanation and prediction of accidents using the path analysis approach in industrial units: The effect of safety performance and climate.

BACKGROUND: The safety climate in an organization depends on people's understanding of the safety policies and procedures, as well as the value, importance, and priority of safety in the workplace. OBJECTIVE: This study aimed to describe and predict accidents using the path analysis model (PAM) in industrial units though the analysis of the effect of safety performance and climate. METHODS: This cross-sectional study was conducted on 294 workers in industrial units in Hamadan, a province in the western part of Iran. The data on safety performance and climate was collected using a questionnaire. The first part of the questionnaire was a short version inventory (with 25 items on safety climate) that was used to assess five variables of management commitment, supportive environment, training, personal safety prioritization, and perceived work pressure. Moreover, the safety performance was measured using 10 items on safety rules and participation. The PAM was used to describe the effects of safety climate and performance on accidents. RESULTS: The results showed that the safety climate had the strongest negative impact on work pressure and safety compliance toward accident, followed by safety participation, and quality of training. Moreover, the negative influence of safety climate on accident was mainly mediated by two variables: work pressure and safety participation toward accident. The work pressure had the strongest indirect and total influence on accidents. However, none of the variables had a direct effect on accidents. Training was the most important direct cause of promoting personal safety priority. The safety compliance was more effective than safety participation in reducing accidents rates. CONCLUSIONS: Therefore, it seems that perceived work pressure has an indirect effect on accidents which is mediated by other variables, mainly personal safety priority and safety performance.

Occupational exposure to mercury vapor in a compact fluorescent lamp factory: Evaluation of personal, ambient air, and biological monitoring.

Compact fluorescent lamps (CFLs) have become a popular lighting choice in recent years despite the good performance of light-emitting diode (LED) lamps. The CFLs that have been produced recently contain 1.5-3.5 mg Hg/lamp. There is evidence that even low doses of mercury are toxic. This study aimed to assess occupational exposure to mercury vapor in workers of a CFLs factory by determining mercury levels in personal and ambient air samples and urine of workers. This cross-sectional study was conducted on 59 workers in a CFLs factory in Iran. Personal and ambient air sampling of mercury vapor levels (MVLs) was performed during a workday. In total, 10 personal samples and 10 ambient air samples of mercury vapor were collected simultaneously from different units of the factory. Urine samples were collected before the work shift. Samples were analyzed using a cold-vapor atomic absorption spectrophotometer (CVAAS). The mean of the MVLs in the personal and ambient air samples was 14.78 ± 5.76 and 67.10 ± 59.37 µg.m-3, respectively. The highest MVL was measured for the production line supervisor (25 µg.m-3). There was a significant correlation between the MVLs in the ambient air and personal samples ( r = 0.84, p = 0.005). The mean urinary mercury level (UML) was 13.85 ± 13.14 µg/g creatinine. The UML of 86.4% workers was below the 20 µg/g creatinine recommended by the Centre of Environmental and Occupational Health in Iran. There were significant differences between the UMLs in different areas of the factory ( p = 0.041). Lamp breakage was an important determinant of exposure to mercury vapor; hence, effective programs to control mercury vapor are essential in the CFLs industry.

The combined effects of occupational exposure to noise and other risk factors - a systematic review.

PURPOSE: Noise-induced health effects exacerbate by many other risk factors. This systematic review aims at shedding light on the combined effects of co-exposure to occupational noise and other factors. MATERIAL AND METHODS: A literature search in Web of Science, Scopus, PubMed, Science Direct, and Google Scholar, with appropriate keywords on combined effects of occupational noise, and co-exposure to noise and other factors, revealed 7928 articles which were screened by two researchers. A total of 775 articles were reviewed in full text. We found 149 articles that were relevant and had sufficient quality for analysis. RESULTS: We identified 16 risk factors that exacerbate occupational noise-induced health effects. These factors were classified into four groups: chemical (carbon monoxide (CO), solvents, heavy metals, and other chemicals), physical (lighting, heat, vibration, and cold), personal (age, gender, genetics, smoking, medication, contextual diseases) and occupational (workload and shift work). Hearing loss, hypertension, reduced performance, and cardiovascular strains, are the most important risk factors combined effects due to concurrent exposure to noise and other risk factors. CONCLUSION: Evidences of combined effects of solvents, vibration, heavy metals, CO, smoking, chemicals, aging, heat, and shiftwork were respectively stronger than for other factors. Most of the studies have investigated only the combined effects of risk factors on hearing, and the evidence for non-auditory effects is still limited, and more studies are warranted. Therefore, in the Hearing Conservation Programs, besides noise, aggravating factors of noise effects should also be taken into account.

Upper trapezius fatigue in carpet weaving: the impact of a repetitive task cycle.

INTRODUCTION: Shoulder disorders are one of the most prevalent musculoskeletal disorders among carpet weavers. The most important cause of these disorders is muscle fatigue. The aim of the present study is to investigate the effect of carpet weaving characteristics on upper trapezius (UTr) muscle fatigue during a task cycle. METHOD: In this cross-sectional study, 9 women and 3 men participated. During an 80-min cycle of carpet weaving, a times-series model was applied to assess electromyography amplitude and frequency changes. RESULT: According to the joint analysis of electromyogram spectrum and amplitude method, the participants experienced 0% force decrease, 0.9% recovery, 18% force increase and 72% fatigue in the left UTr. Furthermore, the rates of force decrease, recovery, force increase and fatigue in the right UTr were 18%, 18%, 18% and 45%, respectively. Fatigue in the right and the left UTr was reported to be the dominant state during one carpet weaving task cycle. CONCLUSION: Task cycle appears to have a significant impact on UTr fatigue in participants, and UTr fatigue can be considered a serious risk factor in shoulder musculoskeletal disorders. Hence, further studies should focus on better workstations and work-rest periods during various subtasks.

Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers.

OBJECTIVES: This study aimed to provide an empirical model of predicting low back pain (LBP) by considering the occupational, personal, and psychological risk factor interactions in workers population employed in industrial units using an artificial neural networks approach. METHODS: A total of 92 workers with LBP as the case group and 68 healthy workers as a control group were selected in various industrial units with similar occupational conditions. The demographic information and personal, occupational, and psychosocial factors of the participants were collected via interview, related questionnaires, consultation with occupational medicine, and also the Rapid Entire Body Assessment worksheet and National Aeronautics and Space Administration Task Load Index software. Then, 16 risk factors for LBP were used as input variables to develop the prediction model. Networks with various multilayered structures were developed using MATLAB. RESULTS: The developed neural networks with 1 hidden layer and 26 neurons had the least error of classification in both training and testing phases. The mean of classification accuracy of the developed neural networks for the testing and training phase data were about 88% and 96%, respectively. In addition, the mean of classification accuracy of both training and testing data was 92%, indicating much better results compared with other methods. CONCLUSION: It appears that the prediction model using the neural network approach is more accurate compared with other applied methods. Because occupational LBP is usually untreatable, the results of prediction may be suitable for developing preventive strategies and corrective interventions.

Density assessment and mapping of microorganisms around a biocomposting plant in Sanandaj, Iran.

Exposure to microorganisms can cause various diseases or exacerbate the excitatory responses, inflammation, dry cough and shortness of breath, reduced lung function, chronic obstructive pulmonary disease, and allergic response or allergic immune. The aim of the present study was to investigate the density of microorganisms around the air of processing facilities of a biocomposting plant. Each experiment was carried out according to ASTM E884-82 (2001) method. The samples were collected from inhaled air in four locations of the plant, which had a high traffic of workers and employees, including screen, conveyor belt, aerated compost pile, and static compost pile. The sampling was repeated five times for each location selected. The wind speed and its direction were measured using an anemometer. Temperature and humidity were also recorded at the time of sampling. The multistage impactor used for sampling was equipped with a solidified medium (agar) and a pump (with a flow rate of 28.3 l/m) for passing air through the media. It was found that the mean density of total bacteria was >1.7 × 103 cfu/m3 in the study area. Moreover, the mean densities of fungi, intestinal bacteria (Klebsiella), and Staphylococcus aureus were 5.9 × 103, 3.3 × 103, and 4.1 × 103 cfu/m3, respectively. In conclusion, according to the findings, the density of bacteria and fungi per cubic meter of air in the samples collected around the processing facilities of the biocomposting plant in Sanandaj City was higher than the microbial standard for inhaled air.

Subjective Mental Workload and Its Correlation With Musculoskeletal Disorders in Bank Staff.

OBJECTIVE: The purpose of this study was to evaluate the rate of subjective mental workload (SMWL) and its correlation with musculoskeletal disorders among bank staff members in Kurdistan Province located in western Iran. METHODS: This cross-sectional study was conducted among 200 bank staff members in Kurdistan Province, Iran. The mental workload was assessed using the National Aeronautics and Space Administration-Task Load Index (NASA-TLX) computerized version. NASA-TLX is a multidimensional rating procedure that derives an overall workload score based on a weighted average of ratings on 6 subscales. These subscales include Mental Demands, Physical Demands, Temporal Demands, Performance, Effort, Effectiveness, and Frustration. The musculoskeletal disorders (MSDs) were documented with the Nordic Musculoskeletal Questionnaire and generic body diagram. RESULTS: Of the staff members, 78.5% experienced pain at least once during the past year in 1 of their 9 musculoskeletal body regions. The highest frequencies of pain were in the neck and lower back. The NASA-TLX estimated the Effort and Performance scales with mean ± SD of 72.8 ± 25.2 and 36 ± 22.6, respectively, as the maximal and minimal scores among the 6 subscales of SMWL. The statistical analysis of the data revealed that there was a significant correlation between the overall mental workload score and also among the 6 subscales of SMWL separately with MSDs (P < .05). CONCLUSION: SMWL appears to be a risk factor in the incidence of MSDs, so that the odds of MSDs increased by 11% with each additional 1-point increase in SMWL score.

Empirical estimation of the grades of hearing impairment among industrial workers based on new artificial neural networks and classical regression methods.

BACKGROUND: Prediction models are used in a variety of medical domains, and they are frequently built from experience which constitutes data acquired from actual cases. This study aimed to analyze the potential of artificial neural networks and logistic regression techniques for estimation of hearing impairment among industrial workers. MATERIALS AND METHODS: A total of 210 workers employed in a steel factory (in West of Iran) were selected, and their occupational exposure histories were analyzed. The hearing loss thresholds of the studied workers were determined using a calibrated audiometer. The personal noise exposures were also measured using a noise dosimeter in the workstations. Data obtained from five variables, which can influence the hearing loss, were used as input features, and the hearing loss thresholds were considered as target feature of the prediction methods. Multilayer feedforward neural networks and logistic regression were developed using MATLAB R2011a software. RESULTS: Based on the World Health Organization classification for the grades of hearing loss, 74.2% of the studied workers have normal hearing thresholds, 23.4% have slight hearing loss, and 2.4% have moderate hearing loss. The accuracy and kappa coefficient of the best developed neural networks for prediction of the grades of hearing loss were 88.6 and 66.30, respectively. The accuracy and kappa coefficient of the logistic regression were also 84.28 and 51.30, respectively. CONCLUSION: Neural networks could provide more accurate predictions of the hearing loss than logistic regression. The prediction method can provide reliable and comprehensible information for occupational health and medicine experts.

The efficacy of radiant heat controls on workers' heat stress around the blast furnace of a steel industry.

BACKGROUND: Workers' exposure to excessive heat in molten industries is mainly due to radiant heat from hot sources. OBJECTIVE: The aim of this study was to evaluate the efficacy of radiant heat controls on workers heat stress around a typical blast furnace. METHODS: Two main interventions were applied for reducing radiant heat around the blast furnace of a steel industry located in western Iran. These included using a heat absorbing system in the furnace body and installing reflective aluminum barrier in the main workstation. Heat stress indexes were measured before and after each intervention using the digital WBGT-meter. RESULTS: The results showed MRT and WBGT indexes decreased by 20 °C and 3.9 °C, respectively after using heat absorbing system and also decreased by 18.6 °C and 2.5 °C, respectively after installing a reflective barrier. These indexes decrease by 26.5 °C and 5.2 °C, respectively due to the simultaneous application of the two interventions which were statistically significant (p < 0.001). The core body temperature of workers decreased by 2.6 °C after the application of interventions which was also significant (p < 0.05). CONCLUSIONS: The results confirmed heat control at source can be considered as a first solution for reducing radiant heat of blast furnaces. However, the simultaneous application of interventions could noticeably reduce worker heat stress. The results provide reliable information in order to implement the effective heat controls in typical hot steel industries.

Effect of STOP technique on safety climate in a construction company.

BACKGROUND: Safety programs are a core part of safety management in workplaces that can reduce incidents and injuries. The aim of this study was to investigate the influence of Safety Training Observation Program (STOP) technique as a behavior modification program on safety climate in a construction company. METHODS: This cross-sectional study was carried out on workers of the Petrochemical Construction Company, western Iran. In order to improve safety climate, an unsafe behavior modification program entitled STOP was launched among workers of project during 12 months from April 2013 and April 2014. The STOP technique effectiveness in creating a positive safety climate was evaluated using the Safety Climate Assessment Toolkit. RESULTS: 76.78% of total behaviors were unsafe. 54.76% of total unsafe acts/ at-risk behaviors were related to the fall hazard. The most cause of unsafe behaviors was associated with habit and unavailability of safety equipment. After 12 month of continuous implementation the STOP technique, 55.8% of unsafe behaviors reduced among workers. The average score of safety climate evaluated using of the Toolkit, before and after the implementation of the STOP technique was 5.77 and 7.24, respectively. CONCLUSIONS: The STOP technique can be considered as effective approach for eliminating at-risk behavior, reinforcing safe work practices, and creating a positive safety climate in order to reduction incidents/injuries.

Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.

PURPOSE: Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using artificial neural networks, this study aims to present an empirical model for the prediction of the hearing loss threshold among noise-exposed workers. METHODS: Two hundred and ten workers employed in a steel factory were chosen, and their occupational exposure histories were collected. To determine the hearing loss threshold, the audiometric test was carried out using a calibrated audiometer. The personal noise exposure was also measured using a noise dosimeter in the workstations of workers. Finally, data obtained five variables, which can influence the hearing loss, were used for the development of the prediction model. Multilayer feed-forward neural networks with different structures were developed using MATLAB software. Neural network structures had one hidden layer with the number of neurons being approximately between 5 and 15 neurons. RESULTS: The best developed neural networks with one hidden layer and ten neurons could accurately predict the hearing loss threshold with RMSE = 2.6 dB and R(2) = 0.89. The results also confirmed that neural networks could provide more accurate predictions than multiple regressions. CONCLUSIONS: Since occupational hearing loss is frequently non-curable, results of accurate prediction can be used by occupational health experts to modify and improve noise exposure conditions.

An intervention for noise control of blast furnace in steel industry.

BACKGROUND: Noise pollution is currently a major health risk factor for workers in industries. The aim of this study was to investigate noise pollution and implement a control intervention plan for blast furnace in a steel industry. METHODS: The measurement of sound pressure level (SPL) along with frequency analysis was done with the sound-level-meter Cell-450. Personal noise exposure was performed using dosimeter TES-1345 calibrated with CEL-282. Before planning noise controls, acoustic insulation properties of the furnace control unit and workers' rest room were assessed. Control room and workers' rest room were redesigned in order to improve acoustical condition. RESULTS: The SPL before intervention around the Blast Furnace was 90.3 dB (L) and its dominant frequency was 4000 Hz. Besides, noise transmission loss of the control and rest rooms were 10.3 dB and 4.2 dB, respectively. After intervention, noise reduction rates in the control and rest rooms were 27.4 dB and 27.7 dB, respectively. The workers' noise dose before and after the intervention was 240% and less than 100%, respectively. CONCLUSIONS: Improvement the workroom acoustic conditions through noise insulation can be considered effective method for preventing workers exposure to harmful noise.