Narges Kaydani; Kourosh Zarea; Ahmad Soltanzadeh
Abstract
Background: Gastrointestinal and cardiovascular diseases are considered to be among the consequences of shiftwork in nursing staff. This study aimed to investigate the prevalence of gastrointestinal and cardiovascular diseases and model their consequences in nurses.Methods: This cross-sectional study ...
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Background: Gastrointestinal and cardiovascular diseases are considered to be among the consequences of shiftwork in nursing staff. This study aimed to investigate the prevalence of gastrointestinal and cardiovascular diseases and model their consequences in nurses.Methods: This cross-sectional study was conducted in seven hospitals in Khuzestan Province in 2020. The participants of the study were 652 nurses. The data were collected through a questionnaire developed by Choobineh et al. The questionnaire included demographic questions and shift work related health effects. The modeling was performed via logistic regression in SPSS 22.Results: The prevalence of gastrointestinal (52.53% vs. 35.19%) and cardiovascular (35.02% vs. 22.22%) disorders were significantly higher in shift working nurses than in day-working ones (P<0.05). In addition to shiftwork, work experience, working hours per week, and hospital wards significantly affected the prevalence of gastrointestinal disorders in nurses (P<0.05). The shiftwork system, age, work experience, and working hours per week had significant positive correlations with the prevalence of cardiovascular diseases in nurses (P<0.05). Furthermore, the chance of having gastrointestinal and cardiovascular diseases was 2.73 and 2.08 times more in shift-working nurses than in day-working ones, respectively.Conclusion: Beside the shift work, the findings of the study indicated the important role of other risk factors, such as age, work experience, working hours per week, and hospital wards for the prevalence of gastrointestinal and cardiovascular diseases in nurses. Therefore, it is recommended that these factors should be taken into account while trying to manage, control, and reduce such negative consequences in nurses.
Reza Moghadam; Seyed Ali Jozi; Rokhshad Hejazi; Mojgan Zaeimdar; Saeed Malmasi
Abstract
Background: Cities, as population centers, face increasingly diverse environmental problems. Hence, there is an urgent need for a healthy environment by eliminating the emission of various life-threatening air pollutants with different origins. The present study aimed to determine the air pollution zones ...
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Background: Cities, as population centers, face increasingly diverse environmental problems. Hence, there is an urgent need for a healthy environment by eliminating the emission of various life-threatening air pollutants with different origins. The present study aimed to determine the air pollution zones using the AERMOD model and provide a strategic management plan to reduce air pollution in District 2 of Tehran, Iran. Methods: In this study, the air pollutant dispersion was evaluated by the AERMOD model exploiting spatial analysis (interpolation) and field measurements. The samples were collected from 32 places in the North, South, Central, East and West of District 2 of Tehran. Air quality indices, including ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide were analyzed in the experiments. Zoning and mapping of dispersion maps and spatial analysis were performed by ArcGIS.10 software using inverse distance weighted interpolation methods in the study area. Results: According to the results, the highest concentrations of sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide pollutants were related to stations 28, 26, 15 and 15 with values of 10.9, 54.6, 32.8, and 31.9 ppb, corresponding to the southern, eastern, southern, and southwestern regions in Sharif, Punak, and Kuy-e Nasr neighborhoods, respectively. Conclusion: Based on the statistical tests of correlation coefficient, normalized mean error, and normalized mean bias, all the calculated results confirmed the accuracy of constructed model and that the modeling would not have sufficient accuracy and performance without the implementation of AERMAP
