Characteristics and Assessing Biological Risks of Airborne Bacteria in Waste Sorting Plant

Examining the concentration and types of airborne bacteria in waste paper and cardboard sorting plants (WPCSP) is an urgent matter to inform policy makers about the health impacts on exposed workers. Herein, we collected 20 samples at 9 points of a WPCSP every 6 winter days, and found that the most abundant airborne bacteria were positively and negatively correlated to relative humidity and temperature, respectively. The most abundant airborne bacteria (in units of CFU m−3) were: Staphylococcus sp. (72.4) \u3e Micrococcus sp. (52.2) \u3e Bacillus sp. (30.3) \u3e Enterococcus sp. (24.0) \u3e Serratia marcescens (20.1) \u3e E. coli (19.1) \u3e Pseudomonas sp. (16.0) \u3e Nocardia sp. (1.9). The lifetime average daily dose (LADD) for the inhalation and dermal routes for the intake of airborne bacteria ranged from 3.7 × 10−3 ≤ LADDInhalation ≤ 2.07 × 101 CFU (kg d)−1 and 4.75 × 10−6 ≤ LADDDermal ≤ 1.64 × 10−5 CFU (kg d)−1, respectively. Based on a sensitivity analysis (SA), the concentration of airborne bacteria (C) and the exposure duration (ED) had the most effect on the LADDInhalation and LADDDermal for all sampling locations. Although the Hazard Quotient of airborne bacteria was HQ \u3c 1, an acceptable level, the indoor/outdoor ratio (1.5 ≤ I/O ≤ 6.6) of airborne bacteria typically exceeded the threshold value (I/O \u3e 2), indicating worker’s exposure to an infected environment. Therefore, in the absence of sufficient natural ventilation the indoor ambient conditions of the WPCSP studied should be controlled by supplying mechanical ventilation

Prediction of Metabolic Syndrome based on Sleep and Work-related Risk Factors using an Artificial Neural Network.

Background Metabolic syndrome (MetS) is a major public health concern due to its high prevalence and association with heart disease and diabetes. Artificial neural networks (ANN) are emerging as a reliable means of modelling relationships towards understanding complex illness situations such as MetS. Using ANN, this research sought to clarify predictors of metabolic syndrome (MetS) in a working age population. Methods 468 employees of an oil refinery in Iran consented to providing anthropometric and biochemical measurements, and survey data pertaining to lifestyle, work-related stressors and sleep variables. National Cholesterol Education Programme Adult Treatment Panel ІІI criteria was used for determining MetS status. The Management Standards Indicator Tool and STOP-BANG questionnaire were used to measure work-related stress and obstructive sleep apnoea respectively. With 17 input variables, multilayer perceptron was used to develop ANNs in 16 rounds of learning. ANNs were compared to logistic regression models using the mean squared error criterion for validation. Results Sex, age, exercise habit, smoking, high risk of obstructive sleep apnoea, and work-related stressors, particularly Role, all significantly affected the odds of MetS, but shiftworking did not. Prediction accuracy for an ANN using two hidden layers and all available input variables was 89%, compared to 72% for the logistic regression model. Sensitivity was 82.5% for ANN compared to 67.5% for the logistic regression, while specificities were 92.2% and 74% respectively. Conclusions Our analyses indicate that ANN models which include psychosocial stressors and sleep variables as well as biomedical and clinical variables perform well in predicting MetS. The findings can be helpful in designing preventative strategies to reduce the cost of healthcare associated with MetS in the workplace

Utjecaj izloženosti 1,6-heksametilen diizocijanatu (HDI) na vršni ekspiratorni protok u autolakirera u Iranu

The aim of this study was to investigate the effects of occupational exposure to 1,6-hexamethylene diisocyanate (HDI) on peak flowmetry in automobile body paint shop workers in Iran. We studied a population of 43 car painters exposed to HDI at their workplaces. Peak expiratory fl ow was tested for one working week, from the start to the end of each shift. Air was sampled and HDI analysed in parallel, according to the OSHA 42 method. Daily and weekly HDI exposure averages were (0.42±0.1) mg m-3 and (0.13±0.05) mg m-3, respectively. On painting days, 72 % of workers showed more than a 10 % variation in peak expiratory fl ow. Inhalation exposure exceeded the threshold limit value (TLV) ten times over. This strongly suggests that HDI affected the peak fl owmetry in the studied workers.Cilj je ovog ispitivanja bio utvrditi vršni protok u 43 iranska autolakirera profesionalno izložena 1,6-heksametilen diizocijanatu (HDI). Vršni ekspiratorni protok testiran je tjedan dana na početku i kraju svake smjene. Uzorkovanje i mjerenje HDI-ja u zraku radilo se istodobno s testiranjem vršnoga protoka, prema metodi OSHA 42. Prosječna dnevna izloženost radnika HDI-ju iznosila je (0.42±0.1) mg m-3, a tjedna (0.13±0.05) mg m-3. U 72 % radnika vršni ekspiratorni protok tijekom dana varirao je više od 10 %. Radnici su udisali deset puta više razine HDI-ja od graničnih te je moguće da je HDI utjecao na mjerenja plućne funkcije

Investigation the prevalence of COVID-19 in different occupations in Shahroud city

Introduction: Covid-19 was first reported as a viral disease in China in 2019, and it soon became a global pandemic. In addition, the types of occupations people have and the environments in which they work may increase the likelihood of being exposed to the virus. Thus, this study was conducted to investigate the prevalence of Covid-19 disease in various occupations and its relationship with some effective parameters in Shahroud city. Methods: This research is a cross-sectional, descriptive-analytical study that was conducted in 2021. The required information was extracted from the database provided by Shahroud University of Medical Sciences. These files contain the results of the comprehensive study of COVID-19 in Shahroud. All the jobs that were asked of the person were classified based on International Standard Classification of Occupations and suspicious and definite cases were examined in different occupation. The information analyzed using SPSS software version 22. Results: According to the results, the highest percentage of cases (45%) was in healthcare workers, such as doctors, nurses, and operating room staffs—in other words, all employees working in the healthcare system. The next highest percentages were in household and home nursing workers (44.5%), retirees (43.2%), and construction workers (43%). The relationship between variables such as age, smoking status, presence of comorbidities, and presence of a high body mass index (BMI) associated with Covid-19 disease was examined by the regression test. It was found that the relationship was significant, that these variables affected the prevalence of the disease. Based on the odds ratio in the age variable, with each year of age, the chance of getting infected increased by 1%. A current smoker had a reduced chance of getting the disease by 57.2%. Having a comorbidity increased the chance of getting the disease by 14%, and with each increase in BMI, the chance of getting the disease increased by 3.8%. Conclusion: The study found that in some occupations, such as healthcare worker, the prevalence of the disease was higher because workers were in direct contact with patients and people infected with the virus. In general, it can be said that the prevalence of the disease was low in workers who could telework and remain at home rather than go to a job or in the community. Factors such as age, the presence of comorbidities, status as a current smoker, and having a high BMI had an effect on contracting Covid-19 disease

Job Stress and related factors in Nurses in Ilam

Background: Nowadays, in most countries of the world, especially in industrial societies and the societies in which the social and economical chaos have disrupted the normal life, social sources of stress have got common more than ever, in a way that stress is considered as the black plague in the current era. The aim of this study is to assess Job stress and related factors in nurses in Ilam. Methods: This study is of the descriptive-analytical kind, which was performed in a temporary way. The sample was consisted of all nurses working in governmental hospitals of Ilam city. Sampling was performed through consensus, and the Cooper’s job stress questionnaire was used for collecting data. SPSS software and one-way Analysis Of Variance (ANOVA) test were used to analyze the data. Results: 56 percents of research units have experienced severe stress. Using the ANOVA test, a significant relationship was observed between the average years of employment and the kind of the hospital and the average level of stress (p<0.05). Conclusion: Our results show that in the begging years of employment and in nurses with low record of employment stress is severe, and after ten years of employment stress level declines. Conflict with other nurses and physicians, and also lacking enough skill for performing nursing services, are the main causes of prevalence of stress among nurses in governmental hospitals in Ilam