Showing 4 results for Gohari
A Kassani, M Gohari, M Mousavi, M Asadi Lari, M Rohani, M Shoja,
Volume 8, Issue 2 (20 2012)
Abstract
Background and Objectives: Social capital consists of
individuals' communicational networks, social norms such as mutual trust and
cooperation in social networks. The aim of this study was to develop a model to
assess the implication of different determinants such as age, gender,
occupational status, mental and physical health on social capital components to
draw a correlation network for social capital determinants.
Methods: For the purpose of this study, data
was used from ‘social capital' section of Urban HEART-1 survey, which included
22,500 households from all 22 districts of Tehran, who were approached in a
randomized multistage cluster sampling method. Path analysis is a statistical
method to test hypothetical causal models, which requires various causal (path)
diagrams. To demonstrate the causal models of social capital, the hypothetical
paths of various components were developed and the final model of social
capital was drawn using multiple regression analyses.
Results: Path analysis indicated that social
capital components are influenced by various variables: A) Individual trust, by
occupational status, marital status, and physical component of health-related
quality of life B) Cohesion and social support, by education, age, and marital
status C) Collective trust and associative relation, by family size, age and
physical health. Direct effect of these variables on social capital components
was more than their indirect effects (through mental health and physical
health).
Conclusion: Social capital components
are directly affected by occupational, marital, educational status, family
size, physical health and duration of local residency. Planning to improve
educational and occupational status, strengthening family bonds and provision
of local facilities, may improve social capital.
Mr Gohari, F Zayeri, Z Moghadami Fard, N Kholdi,
Volume 10, Issue 4 (Vol 10, No 4 2015)
Abstract
Background and Objectives : Failure to gain weight (FTG) is one of the predominant health issues in children. The aim of this study is application of longitudinal transition model in determining the prognostic factors for failure to gain weight in children under two years.
Methods: In this study, 363 children under 2 years that were visited at the health centers in the east of Tehran were studied. Samples were selected using the two stage clustering method. The study variables were measured repeatedly in 18 consecutive times. Since the data was longitudinal and are dependent, first order transition model was used to determine the risk factors of failure to gain weight. All analyses conducted in R.
Results : The mean (±sd) birth weight was 3057gr(± 838) and 6.9% of the children weighed less than 2500gr at birth. Moreover, 231 children (63.6 %) had no FTW until 2 years of age while 23 ( 6.3 %) had three or more episodes of FTW. Diarrhea (P<0.001), weaning (P<0.001), catching cold (<0.001), and teething (P<.001) were significant risk factors of failure to gain weight. To measure the association between weight loss and the weight in the previous visit, the logarithm of odds ratios was used that was significant (P=0.039).
Conclusion: The association between two consecutive measurements showed that any failure in weight would affect weight gain in the next period of time and the effect of weight deficiency remains for at least one month.
E Abdalmaleki, Zh Abdi, M Goharimehr, R Alvandi, S Riazi Esfahani , E Ahmadnezhad,
Volume 15, Issue 3 (Vol.15, No.3 2019)
Abstract
Background and Objectives: Iran has carried out a series of surveys based on the Global school-based student health survey (GSHS) referred to as the CASPIAN. The aim of this paper was to compare the methodology and tools of CASPIAN surveys and to propose recommendations and suggestions for future implementations.
Methods: The data of this systematic review study were gathered from the World Health Organization (WHO) documentations, international databases including Pubmed, EMBASE, Scopus, GoogleScholar, and ScienceDirect, and national databases including Magiran, SID, and Irandoc. The search was conducted in both English and Persian (for the time period from 2003 to 2018). The time and place of the study, target population, questionnaire(s), sample size, and sampling method were compared between the surveys.
Results: Five rounds of CASPIAN survey were conducted in Iran from 2003 to 2015. The surveys had two sets of questionnaires for students and parents. In all five rounds, sampling methods and questionnaires were similar in the core and differed in some details that were added selectively in each round. The questionnaires were designed based on the GSHS and the WHO stepwise approach to non-communicable disease risk factor surveillance (STEPS) programs.
Conclusion: Considering the small variation in each series and compliance with the global model, it is suggested that the next CASPIAN survey be conducted according to the previous series in accordance with the standards presented in the global model in recent years in a reasonable interval from the 2015 survey.
M Safari, M Abbasi, F Gohari Ensaf , Z Berangi, Gh Roshanaei,
Volume 15, Issue 4 (Vol.15, No.4 2020)
Abstract
Background and Objectives: In survival analysis, using the Cox model to determine the effective factors requires the assumptions whose failure of leads to biased results. The aim of this paper was to determine the factors affecting the survival of metastatic gastric cancer patients using the non-parametric method of Randomized Survival Forest (RSF) model and to compare its result with the Cox model.
Methods: In this retrospective cohort study, 201 patients with metastatic gastric cancer were evaluated in Hamadan Province. Patient survival was calculated from diagnosis to death or end of study. Demographic characteristics (such as gender and age) and clinical variables (including stage, tumor size, etc.) were extracted from the patient records. Factors affecting survival were determined using the Cox model and RSF. Data analysis was performed using the R3.4.3 software and RandomForestSRC and survival packages.
Results: The mean (SD) age of patients was 61.5 (12.9) years old. The Cox model showed that chemotherapy (p=0.033) was effective in survival, and the results of fitting the RSF model showed that the most important variables affecting survival were type of surgery, location of metastasis, chemotherapy, age, tumor grade, surgery, number of involved lymph nodes, sex and radiotherapy. Based on the model appropriateness, the RSF model with log-rank split rule had a better performance compared to the Cox model.
Conclusion: If the number of variables is high and there is a relationship between the variables, the RSF method identifies the important and effective variables on survival with high accuracy without requiring restrictive assumptions compared to the Cox model.
