Showing 3 results for Shoaei
Neda Nazari, Hossein Fakhrzadeh, Farshad Sharifi, Seyed Masoud Arzaghi, Mahtab Alizadeh, Neda Mehrdad, Shervan Shoaei, Baharak Najafi, Mostafa Qorbani,
Volume 13, Issue 1 (1-2014)
Abstract
Introduction: The height measurements in the elderly are associated with several problems. In this study
we used a model to predict of the Iranian people aged height from age, shin length and forearm length.
Methods: A total 165 aged people ≥60 years were randomly selected based on medical record number of
about 800 eligible older people who lived in Kahrizak Charity Foundation. Standing height, shin length
and forearm length were measured. Data from 99 participants were used to creat a predicting multivariate
linear regression model for estimation of standing height of older men and women. The data of the rest
66 participants were used for models testing.
Result: The following equations were created:
Men height = 78.928+ (1.430× shin length) + (0.817×forearm length)-(0.176×age)
The height of women = 71.694+ (1.414×shin length) + (1.084× forearm length)-(0.277× age)
R2
were calculated as 0.63 for men and 0.52 for women. Error of estimation was +0.44 cm and it was -
0.16cm and +1.09cm for men and women respectively. Estimated heights were not significantly different
from standing statures.
Conclusion: height was predictable from shin length and for forearm lengths and also age with a
relatively small error in the estimation among Iranian older people. The error of model is more in women
than men.
Baharak Najafi, Seyed Masoud Arzaghi, Hossein Fakhrzadeh, Farshad Sharifi, Shervan Shoaei, Mahtab Alizadeh, Mohsen Asadi Lari, Reza Fadayevatan, Neda Mehrdad,
Volume 13, Issue 1 (1-2014)
Abstract
Introduction: Mental disorders are common in the elderly.The purpose of this study was to assess the
general health status and its related factors among people ≥ 65 years in different districts of Tehran.
Methods: This study has used data of the participants ≥ 65 years old in urban health equity and response
tool (Urban-HEART) study. Finally the data of 1313 elderly were considered for this study. Variables
included demographic characteristics (gender, age, education level, family size, marital status and
employment status) and mental health using the Persian GHQ -28 questionnaire (domains: somatic,
depression, insomnia and anxiety) and quality of life using the SF12.
Results: The mean age of participants was 73.68 (5.91) (women=627 and men=686). GHQ-28 median of
scores the participants were 24.00 (22.00)[20.00 (27.00) in women and 19.00 (19.00) in men
(P<0.01)].Based on GHQ-28 cut-point 23, 50.2%of the participants had mental health problems, [61.2%
women and 40.1% men (P<0.01)].The residents of third municipality districts had the best mental health
(26.3% of men and 38.5% of women had mental health problems) and the aged of 20th municipality
district had the worst health status (65.7% of males and 84.2% of women had mental health problems).In
multivariable logistic regression model, for each year of increment age, 2.9% chance of mental health
problems increased (P<0.01). With increasing level of education, mental health status was improved (P
trend < 0.01). The relationship between family size and mental health was not significant (P =0.06).
Conclusion: Mental health status of the elderly in Tehran was worse than the many other countries. The
elderly lived in 20th
municipal district, had the worst and the dwellers in the 3th
district had the best mental
health status.
Aboozar Ramezani, Leila Shahmoradi, Fereydoon Azadeh, Fatemeh Sheikhshoaei, Rasha Atlasi, Nazli Namazi, Bagher Larijani,
Volume 20, Issue 1 (25th Anniversary of the Foundation, Special Issue 2021)
Abstract
Background: A key aspect of Scientific collaboration increases scientific productivity. This study aimed to draw up a scientific collaboration network of the Endocrinology and Metabolism Research Institute (EMRI) at Tehran University of Medical Sciences.
Methods: A Descriptive Cross-Sectional Study was conducted by the Scientometrics method. Data collection from the Scopus and Web of Science Core collection databases between 2002 until 30 October 2020. MS-Excel, HistCite, VOSviewer, and ScientoPy were used for descriptive statistics and data analysis.
Results: A total of 4190 records with the affiliation of the EMRI are indexed in two international databases. All of the records received a sum of 89480 citations. The EMRI Researchers were published in 1118 journals. The annual growth rate of publication and citation of the scientific output of the EMRI was 20.3% and 22.7%, respectively. A total of 17662 authors from 186 countries participated in the publication. The co-authorship pattern shows. The next section of the Study was classified and visualized based on authorship (institutes and country of affiliation), keywords (co-occurrence and trend).
Conclusion: Overall, these results indicate that the pattern of collaborations in the authorships' articles increases the flow of knowledge among the institute's researchers as a result of international collaborations, interaction with leading countries, and interdisciplinary collaborations. To develop a full picture of co-authorship, additional studies will need a comprehensive picture of network cooperation to analyze the situation with other social network analysis indicators.
