ABSTRACT
The primary healthcare [PHC] services in the Islamic Republic of Iran have succeeded in addressing high levels of communicable diseases; however, they seem less able to deal with maternal and paediatric oral diseases. The aim of this study was to examine problems in integrating oral health services into PHC. This was a qualitative research study comprising focus group discussions and interviews. Five focus-group discussions were held with midwives, family healthcare practitioners, rural PHC workers, duty-service dentists, and public health dentists. Also, individual interviews were organized with experts of faculty members in related fields, informant managers and policy makers, and in-depth interviews were done with pregnant women in four PHC centres. Audiotapes were transcribed following each session, and then a qualitative thematic analysis was carried out on gathered data. Data analysis resulted in 4 main themes relating to the challenges: environmental, educational, organizational and school-based programme factors. This study provides a clearer understanding of the challenges of integrating oral health services into PHC
ABSTRACT
The Tehran province was subject to the second highest incidence of fatalities due to traffic accidents in 1390. Most studies in this field examine rural traffic accidents, but this study is based on the use of logit models and artificial neural networks to evaluate the factors that affect the severity of accidents within the city of Tehran. Among the various types of crashes, head-on collisions are specified as the most serious type, which is investigated in this study with the use of Tehran's accident data. In the modeling process, the severity of the accident is the dependent variable and defined as a binary covariate, which are non-injury accidents and injury accidents. The independent variables are parameters such as the characteristics of the driver, time of the accident, traffic and environmental characteristics. In addition to the prediction accuracy comparison of the two models, the elasticity of the logit model is compared with a sensitivity analysis of the neural network. The results show that the proposed model provides a good estimate of an accident's severity. The explanatory variables that have been determined to be significant in the final models are the driver's gender, age and education, along with negligence of the traffic rules, inappropriate acceleration, deviation to the left, type of vehicle, pavement conditions, time of the crash and street width. An artificial neural network model can be useful as a statistical model in the analysis of factors that affect the severity of accidents. According to the results, human errors and illiteracy of drivers increase the severity of crashes, and therefore, educating drivers is the main strategy that will reduce accident severity in Iran. Special attention should be given to a driver's age group, with particular care taken when they are very young.
ABSTRACT
Atherosclerosis is the most important cause of death in hemodialysis and renal transplanted patients while hyperlipidemia and lipid peroxidation are considered major risk factors of it. For this reason, the most important goals of therapy are elimination of risk factors of atherosclerosis among these patients. Since peroxidation of lipids are a multifactorial process and all factors have not been investigated in one study, we decided to investigate, serum concentrations of total cholesterol, triglycerides, cholesterol contained of high density lipoprotein [HDL-c], concentration of albumin, total magnesium [Mg], malondialdehyde [MDA] and total antioxidant of these patients and compare the results with corresponding data obtained for age and sex matched control group. In this cross-sectional study, 30 patients who were on hemodialysis and 30 renal transplanted patients were participated. Parameters mentioned above were measured using sera separated from the fasting blood collected from the patients. Evaluation of these parameters were done by following protocols provided by the manufactures of the kits, The results obtained were compared with the corresponding data of 30 healthy persons who served as control group. In addition, the cholesterol contained of low density lipoprotein [LDL-c] was calculated and plasma level of cyclosporine was measured for renal transplanted patients. Evaluated data showed elevation in the serum levels of triglycerides [p<0.05], MDA [p<0.001] and decrease in the serum levels of total antioxidant among hemodialysis and renal transplanted patients [p<0.001]. In addition, the serum levels of magnesium in hemodialysis patients were higher than control group [p<0.01], while it was lower in renal transplant patients [p<0.01]. Finally, Serum albumin levels were significantly lower in the patient groups, when compared with control group [p<0.01]. Pearson regression analysis showed a positive and significant correlation between triglycerides level and MDA [r= -0.47, p<0.001] and negative correlation with total antioxidant [r=-0.42, p<0.001]. In addition, there was a negative and significant correlation between Mg and cyclosporine level [r=-0.44, p<0.01] among renal transplanted patients. In conclusion, present results demonstrated that cyclosporine is the most important cause of hypomagnesaemia in renal transplanted patients. Therefore, oral magnesium supplement should be used for these patients, when cyclosporine recommended. In addition, low levels of antioxidant detected among the patient groups suggest that prescription of oral antioxidant such as vitamin C and E could reduce the risk of atherosclerosis in these patients