Iranian Journal of Health Sciences
Volume:6 Issue: 1, Winter 2018

Background and It is likely that industrial workplaces increase the chance of developing obesity and cardiovascular disease risk factors in the employees. The aim of this study was to compare obesity and some health markers between male employees of gas refinery (first exposure group) and petrochemical staff (second exposure group) compared to non-industrial male employees of general population (non-exposure group).
Seventy five male employees of a petrochemical plant in Assaluyeh, eighty eight male employee of a gas refinery, and eighty six non-industrial male employees of the general population participated in this study. Weight, height, waist circumference, fasting blood glucose, blood pressure, and serum total cholesterol and triglyceride were measured in all the participants. Statistical analyses were performed using the SPSS Software, version 16 (SPSS Inc., Chicago, IL, USA).
The mean body mass index, waist circumference, fasting blood glucose, and serum triglyceride level were significantly higher in gas refinery staff compared to petrochemical employees, and non-industrial employees (P-values The results of this study showed that obesity, high fasting blood glucose and hypertriglyceridemia were significantly higher in gas refinery staff. It is recommended to develop a health promotion program for weight management and prevention of obesity in the industrial work place staff.

Background and Quick removal of dye from water and waste water is very important in the research related to eliminating pollutions; this is because of the spread of damaging effects of dyes in water on the human beings and the environment. Four different carbon nanostructures, namely graphene oxide, oxidized multiwalled carbon nanotubes, activated carbon, and multiwalled carbon nanotubes were applied as adsorbents for the removal of Indigo Carmin (IC) dye from aqueous solution.
These carbon nanostructures were determined by X-ray diffractometer and scanning electron microscope. Batch adsorption experiments were then performed to investigate the effect of solution pH, concentration, contact time, and temperature on IC removal. To study the characteristics of IC adsorption process, adsorption constants were calculated by first-order and pseudo second-order models.
Adsorption equilibrium was indicated with Freundlich and Langmuir isotherm models. This study was the first research conducted on the removal of dye which uses four carbon nanostructures adsorbents.
The results indicated better efficiency for GO in IC removal than other carbon adsorbents. The isotherm parameters for the Freundlich and Langmuir models were calculated. The kinetics research also revealed that the experimental data was well fitted by pseudo second-order equation.

Background and Copper (Cu) is an essential trace element. The toxic level of copper can catalyze the formation of free radicals which cause various diseases including kidney failure. The main aim of this study was to evaluate the effects of purslane on kidney failure due to copper toxicity in rat model.
Twenty-eight male Wistar rats were divided equally and randomly into four groups. Group I was control group, while in group II, copper sulphate was administrated orally in dose of 200 mg/kg body weight every day for one month. In group III, on the other hand, purslane was orally given in a dose of 400 mg/kg body weight per day for one month. Group IV received combined treatment of copper sulphate and pursalne as described in groups II and III. Blood urea nitrogen (BUN) and serum creatinine was then measured. The kidney tissues were subject to histopathological study.
The results showed that serum BUN and creatinine were increased in the copper-treated rat which were 52/20± 4/91 and 0/56± 0/06, respectively. Purslane administration also decreased the elevated level of creatinine and BUN in rats which received toxic levels of copper (0/48± 0/03 and 44/80± 5/7, respectively).
The present study revealed that purslane improved some kidney function parameters due to its antioxidant and anti-inflammatory properties.

Background and Phenol is an aromatic hydrocarbon and one of the banzan derivatives which has a higher dissolution rate in water. Therefore, it must be removed for water pollution prevention. The aim of this study was to investigate the possibility of Pistaciamuticabio mass as an alternative adsorbent for phenol removal from aqueous solution.
The effect of various parameters including contact time (10-102 min), pH(2-8), adsorbent dosage (0.4-1.5g/L), phenol concentration (50-150mg/L) were investigated in this experimental-lab study. Also, the isotherm and kinetic investigations were performed for phenol adsorption process. The adsorption equilibriums were analyzed by Langmuir, Temkin, Freundlich and Harkins Jura isotherm models.
It was found that the data fitted to Langmuir (R2=0.98) better than other isotherm models. Batch kinetic experiments showed that the adsorption followed Pseudo second-order kinetic model with correlation coefficients greater than 0.998.
It was revealed that P. mutica was not only an inexpensive absorbent, but also a quite effective factor in removal of phenol from water and wastewater.

Background and The present study is aimed to investigate the prediction of the experimental data for the removal of agricultural pesticides including three herbicides Trifluralin, Glyphosate, and 2,4-Dichlorophenoxyacetic acid from aqueous solution by carbon nanoparticles synthesized from pomegranate peel using artificial neural network.
Removal studies were conducted under the different experimental conditions in pH = 4-8, contact time of 0-25 minutes, and the initial concentrations in the range of 50-250 mg/L. In the present study, artificial neural network, back propagation algorithm, and Levenberg Marquardt training approach were used.
The results showed that the removal of agricultural pesticides Trifluralin, Glyphosate and 2,4D depended on pH such that the optimal removal efficiency observed for pesticides Trifluralin, Glyphosate, and 2,4D in pH=8 was 92.6, 78, and 92%, respectively. The optimal adsorbent weight was also found to be 0.5 g for pesticides Trifluralin, Glyphosate, and 2,4D so that the removal efficiency was equal to 97, 98.8 and 98.4% within 20 minutes. In the initial concentration of 50 mg/L, the removal efficiency was respectively equal to 88, 94, and 92% for Trifluralin, Glyphosate, and 2,4D. The results also showed that the experimental data followed from both isotherm models.
The artificial neural network successfully predicts the data, and there is a good agreement between experimental and predicted data.

Background and Services quality is an important factor of satisfaction, as well as a remarkable tool for marketing to achieve the competitive differentiation and promotion of customer's loyalty. The present study was aimed to analyze the quality gap using SERVQUAL approach at selected hospitals in Golestan Province at the year 2015.
A cross-sectional survey was conducted on 361 patients of selected hospitals of Golestan Province. To determine sample size, Cochran's sample size formula was utilized. Also, to collect the data, SERVQUAL questionnaire was used. The collected data was analyzed through SPSS Software (version 18), and running statistical tests including paired t-test and Pearson correlation. The level of significance was also considered to be ≤ 0.05.
The most expectation of hospital services quality was related to reliability dimension (31.60 ± 4.00), while the lowest perception was about responsiveness aspect (13.36 ± 5.74). The greatest gap between perceptions and expectances was in the reliability dimension (-4.54), which was significant (P The largest gap between perceptions and expectances was about reliability and tangibles dimensions that can likely be reduced by the staff appearance, physical environment, and utilization of suitable equipment and assurance to patients.