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The association between noise exposure and increased risk of cancer has received little attention in the field of research. Therefore, the goal of this study was to conduct a systematic review on the relationship between noise exposure and the incidence of cancer in humans. In this study, four electronic bibliographic databases including Scopus, PubMed, Web of Science, and Embase were systematically searched up to 21 April 2022. All types of noise exposure were considered, including environmental noise, occupational noise, and leisure or recreational noise. Furthermore, all types of cancers were studied, regardless of the organs involved. In total, 1836 articles were excluded on the basis of containing exclusion criteria or lacking inclusion criteria, leaving 19 articles retained for this study. Five of nine case-control studies showed a significant relationship between occupational or leisure noise exposure and acoustic neuroma. Moreover, four of five case-control and cohort studies indicated statistically significant relationships between environmental noise exposure and breast cancer. Of other cancer types, two case-control studies highlighted the risk of Hodgkin and non-Hodgkin lymphoma and two cohort studies identified an increased risk of colon cancer associated with environmental noise exposure. No relationship between road traffic and railway noise and the risk of prostate cancer was observed. In total, results showed that noise exposure, particularly prolonged and continuous exposure to loud noise, can lead to the incidence of some cancers. However, confirmation of this requires further epidemiological studies and exploration of the exact biological mechanism and pathway for these effects. [ABSTRACT FROM AUTHOR]

Byline: Saeid. Yazdanirad, Farideh. Golbabaei, Mohammad. Monazzam, Habibollah. Dehghan, Abbas. Foroushani Background: Various factors can affect thermal strain at workplaces. To prevent heat illnesses due to the heat strain, one [...]

The need for a biological disease risk assessment method to prevent the contagion of these diseases, particularly among healthcare personnel, is crucial. Therefore, this study aimed to develop and validate a biological risk assessment tool for biological agents among hospital personnel under COVID-19 conditions. This cross-sectional study was performed on 301 employees in two hospitals. Firstly, we identified the items affecting the contagion of biological agents. Then, we computed the weight of the items using the Fuzzy Analytical Hierarchy Process (FAHP) method. We used the identified items and the estimated weights in the next step to develop a predictive equation. The outcome of this tool was the risk score of biological disease contagion. After that, we used the developed method to evaluate the biological risk of the participants. The ROC curve was also used to reveal accuracy of developed method. In this study, 29 items were identified and categorized into five dimensions, including environmental items, ventilation items, job items, equipment-related items, and organizational items. The weights of these dimensions were estimated at 0.172, 0.196, 0.255, 0.233, and 0.144, respectively. The final weight of items was used to develop a predictive equation. The area under ROC curves (AUC) was also calculated as 0.762 (95% CI: 0.704, 0.820) (p<0.001). The tools developed using these items had acceptable diagnostic accuracy for predicting the risk of biological diseases in health care. Therefore, one can apply it in identifying persons exposed to dangerous conditions. [ABSTRACT FROM AUTHOR]

This study aimed to develop and validate a tool for the comprehensive risk assessment of musculoskeletal disorders (CRAMUD). In this cross-sectional study, 300 male workers participated. Data related to personal, psychosocial and physical items and musculoskeletal symptoms were gathered by a designed questionnaire and Cornell musculoskeletal discomfort questionnaire (CMDQ), respectively. Then, the effect coefficients of the items were computed for developing the CRAMUD equation. The total score of the CRAMUD tool was classified by receiver operator curves (ROCs), and it was validated by linear regression analysis. The values of the content validity ratio (CVR), content validity index (CVI) and Cronbach's coefficient alpha (α) of the CRAMUD questionnaire with 38 items were calculated as 0.773, 0.934 and 0.940, respectively. The personal, psychosocial and physical items with the coefficients of 0.265, 0.175 and 0.478 had significant effects on the occurrence of musculoskeletal symptoms, respectively. The equation of the novel tool was written by these coefficients. The CRAMUD score was grouped into four levels by optimal cut-off points of 8.51, 11.03 and 15.31. This tool could predict 75% of variations of musculoskeletal symptoms. This tool can be exploited to accurately estimate the risk level of musculoskeletal symptoms in various jobs. [ABSTRACT FROM AUTHOR]