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BACKGROUND:It seems qualitative measurements of subjective reactions are not appropriate indicators to assess the effect of noise on cognitive performance.AIM:In this study, quantitative and combined indicators were applied to study the effect of noise on cognitive performance.MATERIAL AND METHODS:A total of 54 young subjects were included in this experimental study. The participants’ mental workload and attention were evaluated under different levels of noise exposure including, background noise, 75, 85 and 95 dBA noise levels. The study subject’s EEG signals were recorded for 10 minutes while they were performing the IVA test. The EEG signals were used to estimate the relative power of their brain frequency bands.RESULTS:Results revealed that mental workload and visual/auditory attention is significantly reduced when the participants are exposed to noise at 95 dBA level (P < 0.05). Results also showed that with the rise in noise levels, the relative power of the Alpha band increases while the relative power of the Beta band decreases as compared to background noise. The most prominent change in the relative power of the Alpha and Beta bands occurs in the occipital and frontal regions of the brain respectively.CONCLUSION:The application of new indicators, including brain signal analysis and power spectral density analysis, is strongly recommended in the assessment of cognitive performance during noise exposure. Further studies are suggested regarding the effects of other psychoacoustic parameters such as tonality, noise pitch (treble or bass) at extended exposure levels.

Background: Exposure to crystalline silica has long been identified to be associated with lung diseases. Therefore, the present study aimed to assess the risk of silicosis and lung cancer associated with occupational exposure to crystalline silica in Iran. Study Design: It is a systematic review study. Methods: Different databases were searched, and the Cochrane method was used for the systematic review. Thereafter, cumulative exposure to crystalline silica (mg/m3 -y) was calculated in every industry. The relative risk of death from silicosis was performed using Mannetje’s method. Based on the geometric mean of exposure, the lung cancer risk of exposure to crystalline silica was also calculated. Results: As evidenced by the results, worker’s exposure to silica ranged from a geometric mean of 0.0212- 0.2689 mg/m3 (Recommended standard by the American Conference of Governmental Industrial Hygienists (ACGIH) was 0.025 mg/m3 ), which is generally higher than the occupational exposure limit recommended by National Institute for Occupational Safety and Health (NIOSH), ACGIH, and occupational exposure limits. The relative risk of silicosis was in the range of 1 to 14 per 1000 people, and the risk of lung cancer in workers ranged from 13-137 per 1000 people. Conclusion: Since workers are at considerable risk of cancer due to exposure to silica in Iran, exposure control programs need to be implemented in workplaces to decrease the concentration of silica.

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Background and Objective: Many indices are used to assess occupational heat stress at the work environments. The aim of this study was to evaluate heat stress using Wet Bulb Globe Temperature (WBGT) index and Discomfort Index (DI), and by measuring physiological responses in the workers of the rolling industry and comparing the appropriateness of these indices for measuring heat stress. Methods: This cross-sectional study was carried out on 90 healthy workers of a rolling industry in eastern Tehran in 2017. Physiological parameters of core body temperature (Tcr) and Heart Rate (HR) were measured during the working shift according to ISO9886 standard. At the same time, environmental variables such as the natural wet temperature (Tnw), dry temperature (Td) and globe temperature (Tg) were measured and recorded at the workstations. Then, the DI and the WBGT indices were calculated using the related formulae. Data were analyzed using SPSS v. 21, t-test and Pearson correlation coefficient. Results: The mean heat stress indices were significantly higher in working conditions than resting conditions, and there was a significant difference between the physiological parameters of Tcr and HR in resting and working conditions (P<0.001). According to the screening criteria of DI, 43.3% of the workers were exposed to the moderate level and 56.7% to the severe level of heat stress. There was a significant difference between the mean WBGT and the Threshold limit values (t= 4.903, P<0.001). Pearson correlation test showed that there was a significant and direct linear relationship between the WBGT and the physiological parameters of Tcr and HR (r=0.317, P=0.002; r=0.434, P<0.001, respectively). The DI index had a significant and direct linear relationship with HR; (r=0.229, P=0.03). Conclusion: The results showed that WBGT is a more appropriate index for evaluating the heat stress of workers in the rolling industry. High heat stress levels at the workstations along with heavy physical activity are health risks for workers in this industry; therefore, interventions must be undertaken to reduce exposure.