مجله بهداشت و ایمنی کار
سال دهم شماره 4 (زمستان 1399)

Styrene (C₆H₅CH=CH₂) is known as one of the volatile organic substances produced or used in petrochemical industries. Exposure to this chemical compound can thus lead to respiratory diseases. Therefore, this study aimed to evaluate occupational exposure to styrene vapor and to determine the risks of its health consequences in petrochemical industry workers through a quantitative method.

In this descriptive cross-sectional study, a total number of 150 samples from 50 employees were studied using the National Institute for Occupational Safety and Health (NIOSH) 1501 method. The samples were then analyzed by the Varian CP-3800 chromatograph. Upon determining exposure to styrene vapor, the risk assessment of the health consequences of styrene in the workers in the given industry was evaluated via the relationships established by the United States Environmental Protection Agency (US/EPA).

According to the results, the polybutadiene latex unit (PBL) was observed with the highest average exposure (0.44 mg.(kg-day)-1). Therefore, the top predictors of carcinogenic and non-carcinogenic risks were valued 0.44 and 0.71, respectively, for the PBL unit. Given the lowest average exposure (0.0012 mg.(kg-day)-1) in the drying unit, the prediction revealed the most moderate carcinogenic (0.1 ×10-5) and non-carcinogenic risks (2×10-3) for the same employees.

Overall, the health risk was higher than the permissible limit in the petrochemical industry studied, especially in the PBL unit. Therefore, it is recommended to make use of artificial ventilation, notably the local type, in addition to the natural ones.

The world is currently facing an all-out crisis over the coronavirus disease 2019 (COVID-19). This review study aimed to determine the applications of the assistive intelligent technologies of the Fourth Industrial Revolution (Industry 4.0) in occupational safety and health (OSH) and response to COVID-19.

The given review was carried out from May to June 2020 and the search strategy was fulfilled in the databases of Google Scholar, PubMed, and Scopus. The keywords were collected from the Medical Subject Headings (MeSH) database and searched individually or in combination. Accordingly, the articles with the term “COVID-19” in their titles or abstracts and some other keywords such as “smart hospital, Industry 4.0, or intelligent technology” were selected and reviewed. Next, the titles, abstracts, and keywords of these studies were examined. To augment the sensitivity of the search, the keywords and the references of the selected articles were also surveyed. Then, the related studies were separated from the irrelevant ones and the duplicates were removed. Finally, the full texts of the selected articles were reviewed.

In this resepct, a total number of 175 studies, published in the databases of Google Scholar, PubMed, and Scopus in 2020 were retrieved. According to the inclusion and exclusion criteria and qualitative screening, 30 articles were included in this review. The assistive intelligent technologies such as artificial intelligence (AI), the internet of things (IoT), big data, virtual reality (VR), holography, cloud computing, autonomous robots (autorobots), three-dimensional (3D) scanning, 3D printing, and biosensors were established as useful ones to respond to COVID-19. In addition, AI and autorobots could be the most significant technologies of Industry 4.0 in the incoming articles.

These technologies can thus help governments to identify, track, monitor, and treat patients and increase resilience in society and workplace environments during the COVID-19 pandemic.

The main purpose of this study was to identify and evaluate environmental problems and their ranking and to determine the conceptual model of environmental impact assessment (EIA) in industrial parks. Accordingly.

In this study, environmental infrastructure issues were classified into five sections. The decision-making trial and evaluation laboratory (DEMATEL) technique was also employed to establish the relationships between the criteria. Moreover, the analytic network process (ANP) was utilized to determine their weight.

Examining the internal relationships between the variables correspondingly revealed that cultural and economic criteria were the most influential. On the other hand, the biological criterion was very effective. The ANP results also showed that the “low share of environmental investment” as an indicator was an economic criterion with a normal weight of 0.80, which was of utmost importance among the other defined cases.

It was concluded that the definition of conceptual models in EIA processes can make it possible to examine and analyze the criteria and indicators affecting evaluation processes.

The development of residential and industrial areas has led to increasing gas consumption and overcrowding in gas supply networks. Accordingly, hazards and risks caused by human errors, processing and mechanical failures in pipelines, and gas leaks are on a rise. Several techniques have been so far proposed for identifying and controlling human errors. The main purpose of this study was to compare two human error evaluation techniques, namely, Human Error Template (HET) and Systematic Human Error Reduction and Prediction Approach (SHERPA) in gas supply operations using the analytic hierarchy process (AHP) to select a suitable method.

This cross-sectional descriptive study was to identify the human error modes in one of the gas supply projects operating by Kurdistan Gas Company, Kurdistan, Iran. Different tasks in gas supply operations were accordingly determined by the health, safety, and environment (HSE) unit, then the ones susceptible to human errors were selected and analyzed through task analysis technique. The next step was to weight and rank the human errors by evaluating indexes based on many variables including accuracy, sensitivity, and quantity of the errors as well as usability, time, and education analysis using the Expert Choice software (ver. 11).

According to the findings of this research, the criteria were ranked based on accuracy (0.339), sensitivity (0.322), quantity of errors (0.118), usability (0.116), time (0.056), education (0.050), and analysis. The inconsistency ratio was also equal to 0.1, which meant that the subjective judgments were accepted.

The results also showed that the analysis of human errors, using the HET, required less training and time, while the number of the detected errors and applicability in the SHERPA was greater. Considering the weight of the criteria, their importance in determining the superior technique and the weight of each one in relation to the criteria, the contribution of that method in the relevant criterion was expressed. Calculating the final weight of the techniques revealed that SHERPA with a weight of 0.53 was more practical compared with HET with a weight of 0.46.

 Errors are a byproduct of human information processing or cognitive functioning. Although everyone is disposed to an error while performing various activities, individual differences in cognitive abilities can lead to various types and rates of errors committed in similar situations. Human errors are one of the most important challenges in work environments, including health care systems, wherein such errors are abundantly occurring. Errors in the delivery of correct medications due to the resemblance in appearance and name are thus one of the cognitive errors that come about in health care systems. The main purpose of this systematic review was to evaluate evidence and approaches recently practiced to reduce medication errors caused by the use of look-alike-sound-alike (LASA) medications.

 The study was conducted on August 30, 2018, through searches in the databases of PubMed and Embase, all available years, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) instructions. The searches were done in the titles or abstracts of the articles using the intended terms and the Medical Subject Headings (MeSH) index in combination. These studies were selected based on the inclusion and exclusion criteria and then categorized based on the type of interventions and outputs. Finally, the data were analyzed descriptively.

 The research designs and methods varied widely among the studies. There were also discrepancies in the number of participants, number of tests, type of medications, and test conditions. The approaches examined in these studies were tall-man lettering, color-coding, label background variations, and use of signs and symbols. Accordingly, 11 studies had utilized tall-man lettering and the most important reported in all articles were “error rate” and “response times”. As well, a wide range of medication names had been tested. It should be noted that medication

 errors have different dimensions, but the errors caused by the look-alike-sound-alike (LASA) medications and the effect of tall-man lettering of medication name were only investigated in the present study. Laboratory studies in this respect have shown that tall-man lettering contributes to mitigating the rate of errors, which might be due to the better legibility of labels, but evaluations in real work environments are needed to reinforce this conclusion. There is also insufficient evidence to support color-coding, as well as several other approaches such as use of signs and symbols. Because of the novelty of the studies in this field, no uniform mechanism has been so far introduced.

 As a metropolitan area in Iran, Tehran is exposed to damage from air pollution due to its large population and pollutants from various sources. Accordingly, research on damage induced by air pollution in this city seems necessary. The main purpose of this study was to forecast ozone in the city of Tehran. Considering the hazards of ozone (O3) gas on human health and the environment and its ascending trend over the past decades, it is also essential to study and predict its quantities in the air. Forecasting ozone in the air can be further used to prevent and control pollution by authorities.

 Using an analytical-applied research method, this study was to predict ozone gas in this metropolitan area via daily ozone data of air quality measurement stations, traffic variables, green space, as well as time factors such as one-day time delay. In this regard, an artificial neural network (ANN) model was employed to forecast ozone concentration using the MATLAB software.

 The results of the ANN model were compared with a linear regression one. Correlation coefficient and root-mean-square error (RMSE) of the ANN model were subsequently compared with R2=0.734 and RMSE=0.56 as well as R2=0.608 and RMSE=11.69 regression equations.

 It was concluded that the error in the ANN model was smaller than that in the regression one. According to the results of the sensitivity analysis of the season parameters, the length of sunshine hours had the most significant effect on the amount of ozone gas in Tehran air.

Even with the rising number of diseases and their severity as well as occupational-environmental accidents occurring within organizations, most managers do not still care about the profitability of implementing the health, safety, and environment (HSE) management system requirements.

Accordingly, the integration of the HSE costs calculated through engineering-economics relations was investigated to evaluate the given profitability using a different approach. For this purpose, costs of diseases and occupational-environmental accidents were computed (n=2207), and then lack of their spending was considered as system income. By determining the correlation and calculating the P-value as well as the associated costs, the regression model was subsequently fitted. Investment in the HSE management system was further examined, and return on investment (ROI) and net present value (NPV) were calculated. Afterwards, the relationship between ROI and disease recurrence rates together with occupational-environmental accidents was explored.

health costs with a P-value=0.03 had a significant effect on disease recurrence rates, so that the incidence rate was equal to 1.432 e-15 as it increased by one unit. The costs of accidents with a P-value=0.048 also had a substantial impact on the occurrence of occupational accidents and a growth by one unit, wherein the accident recurrence rates were 9.183 e. However, no significant association was found between environmental accidents and disease incidence rates.

The results implied that investment in HSE management systems is not just in accordance with implementing profitability requirements, but it should be targeted and based on priorities, influenced by the results of examining root causes of diseases and accidents as well as assessing risks facing organizations.

Occupational stress is known today as one of the biggest challenges to higher education policy-makers. Students with high levels of stress find themselves lacking in self-confidence, vulnerable in controlling academic processes, and unable to compensate for clinical weaknesses. The main purpose of this study was to assess the levels of occupational stress among clinical dental students of Alborz University of Medical Sciences, Alborz, Iran.

This study was a descriptive-analytic research with a cross-sectional design. The statistical population included all dental clinical students enrolled in the 7th, 9th, and 11th semesters in 2018 (n=84). According to the Krejcie and Morgan’s table, the sample size was 70. The data were also collected through the Osipow Occupational Stress Questionnaire, and then analyzed using the SPSS Statistics software (ver. 22). Besides, t-test was employed to investigate the relationship between variables and stress.

The results revealed that the mean score of the students was 150.8. The mean total stress in the age group above 26 years was also 158 and that was 147 for those under the age of 26 (P-value=0.027). Besides, the mean score of overall occupational stress was equal in women and men. Comparisons also demonstrated that students in the 9th and 11th semesters (mean=161) were undergoing more stress than the ones enrolled in the 7th semester (mean=147) (P-value=0.014).

It was concluded that these clinical dental students were suffering from moderate-to-severe occupational stress. Likewise, older students had more stress than younger counterparts did. As well, male and female students’ levels of occupational stress were the same. Resolving this issue accordingly required special attention by higher education policy-makers to provide support and counseling in this respect.

Road traffic accidents (RTAs) have always a major concern and human factor has been recognized as their leading cause. Since taxi drivers play a significant role in accidents, the main purpose of this study was to provide a valid and reliable version of the Dula Dangerous Driving Index (3DI) for taxi drivers working in the city of Zanjan, Iran.

Based on the convenience sampling method, 316 taxi (including taxi, internet taxi, etc.) drivers were recruited in this descriptive study. The 3DI contained 28 items within three factors related to dangerous driving behavior. After linguistic validation, qualitative and quantitative face validity was determined for the given questionnaire. Consequently, content validity index (CVI) and content validity ratio (CVR) were assessed by a panel of 10 experts. Internal reliability was further calculated based on Cronbach’s alpha coefficient and test-retest method.

The results revealed that face validity (1.60-3.82.), CVR (0.8-1), and CVI (0.891-1) were acceptable. Cronbach’s alpha coefficient was also 0.896 for the total reliability of the instrument and 0.95, 0.89, and 0.94 for each factor, respectively. In addition, Spearman’s rank correlation coefficient was 0.871 (P-value<0.001).

The results ultimately demonstrated that the Persian version of the 3DI had adequate reliability, as well as, face and content validity. However, construct validity remains.

Assessing health, safety, and environment (HSE) performance based on up-to-date analytical models like resilience engineering, especially in automobile manufacturing companies, affected by the trilogy of HSE factors and functions, is of crucial importance. Therefore, this study was to review the factors effectively involved in HSE management performance assessment based on resilience engineering in automobile manufacturing industries.

To collect and classify the data, many relevant articles and procedures published in journals or presented at seminars were researched and cited. In this study, reliable online databases, including Google Scholar, Web of Science, Scopus, and PubMed were searched to meet this purpose. Other databases in Farsi such as Magiran, CIVILICA, and Scientific Information Database (SID) were also employed. Accordingly, a total number of 211 articles were extracted and filtered in terms of content and topic by a team of four HSE senior experts, whereby irrelevant studies were deleted, the full text of each relevant article was more closely considered, and finally 18 studies were selected and thoroughly examined.

The findings from these 18 articles revealed that the HSE would be influenced in various industries by factors such as organizational culture, learning and training, political-economic variables, workforce qualifications and skills, strategic and large-scale programs of organization plus its assets and financial resources. In automobile manufacturing industries as well, circumstances might emerge because of some extra-organizational threats and intra-organizational weaknesses, whereby the appearance of deficiencies in various processes and even the functions of the HSE as a whole would be impaired. Of the many external factors, one could mention economic sanctions, large-scale socioeconomic problems, and lack of materials and production equipment. The internal problems would also range from production reduction and cuts in budgets earmarked for different management departments to a rise in the number of accidents and diseases, soaring medical treatment costs, as well as growing expectations in employees, which together impact the HSE management performance.

Regarding the studies conducted on various models presented so far in the area of resilience, it was concluded that the HSE performance of organizations intended to prevent and control risk factors were by no means distinct from other management factors and strategic decision-making in an organization. Rather, the HSE indicators could be impacted by many extra- and intra-organizational factors. Based on the models surveyed, it would be essential to consider the concept of resilience in HSE management. The reason for this is that the idea of the HSE would appear to be an issue of less virtue and importance in various stages and situations in the lifecycle of an organization, which is not consistent with the HSE management system and does not keep pace with the influencing factors.