Bakhtyar Tartibian; Mehdi Kushkestani; Shiva Ebrahimpour Nosrani; Mohsen Parvani
Abstract
Purpose: On the other hand, fatigue is one of the most important indicators of aging syndrome. This study aimed to investigate the relationship between the level of physical activity and fatigue in elderly residents of rest homes in Tehran. Method: This was a descriptive correlational study in which ...
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Purpose: On the other hand, fatigue is one of the most important indicators of aging syndrome. This study aimed to investigate the relationship between the level of physical activity and fatigue in elderly residents of rest homes in Tehran. Method: This was a descriptive correlational study in which 20 rest homes located in Tehran province constituted the study population. By visiting rest homes, the eligible subjects were chosen. Physical activity was measured by the Physical Activity Scale for the Elderly (PASE). The FACIT Fatigue Scale is a short, 13-item, easy to administer tool that measures an individual’s level of fatigue during their usual daily activities over the past week. Nutritional status was evaluated by mini nutritional assessment (MNA). Results: The results of statistical analysis indicated a significant and positive correlation between PASE and FACIT scores (r=0.48, p<0.01) while, there was a significant negative correlation between FACIT score and age (r=-0.23, p<0.01). Also, there was a significant positive correlation between MNA and FACIT (r=0.40, p<0.01). In addition, a significant positive correlation was found between MNA and PASE score (r=0.31, p<0.01). Conclusions: The findings of this study indicate that holding sports classes under the supervision of exercise physiologists is an essential matter to increase health and prevent age-related complications in elderly residents of Tehran rest homes.
Bakhtyar Tartibian; Leila Fasihi; Rasul Eslami
Abstract
Purpose: A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed Data mining algorithm with the aim of more accurately identifying the risk of in postmenopausal women compared to ...
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Purpose: A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed Data mining algorithm with the aim of more accurately identifying the risk of in postmenopausal women compared to the ability of conventional clinical decision tools. Materials and Methods: The present study was a cross-sectional development study conducted in the second half of 2018. In the present study, first, by identifying the influential variables, a survey questionnaire was prepared to select the most important clinical factors. Bone mineral density information of women referred to the bone density measurement unit of Khatam Al-Anbia Hospital in Tehran was used to teach the K-Nearest Ne neighbors (K-NN) algorithm (based on simple studies). Evaluation was based on accuracy. We also reviewed the results of several scientific articles and suggested the best sports activities according to the bone density of individuals. Results: The K-NN algorithm with sub-curve surface (AUC) showed significant performance. The algorithm predicted the risk of osteoporosis with an accuracy of 61.7% in the femoral neck for women participating in the experiment. Also, regular resistance and endurance training exercises repeated for 2-3 times a week for a year can have significant effects on maintaining or increasing hip BMD in postmenopausal women. Conclusion: Considering various predictors associated with low bone density, the K-NN algorithm may be an effective tool for identifying women at high risk for osteoporosis. This method widely recommends and predicts regular resistance and endurance training exercises for women with a high risk of osteoporosis.
